Priya Prahalad, MD, PhD

All Publications

• A Machine Learning Model for Week-Ahead Hypoglycemia Prediction From Continuous Glucose Monitoring Data. Journal of diabetes science and technology Giammarino, F., Senanayake, R., Prahalad, P., Maahs, D. M., Scheinker, D. 2024: 19322968241236208

  Abstract

  BACKGROUND: Remote patient monitoring (RPM) programs augment type 1 diabetes (T1D) care based on retrospective continuous glucose monitoring (CGM) data. Few methods are available to estimate the likelihood of a patient experiencing clinically significant hypoglycemia within one week.METHODS: We developed a machine learning model to estimate the probability that a patient will experience a clinically significant hypoglycemic event, defined as CGM readings below 54 mg/dL for at least 15 consecutive minutes, within one week. The model takes as input the patient's CGM time series over a given week, and outputs the predicted probability of a clinically significant hypoglycemic event the following week. We used 10-fold cross-validation and external validation (testing on cohorts different from the training cohort) to evaluate performance. We used CGM data from three different cohorts of patients with T1D: REPLACE-BG (226 patients), Juvenile Diabetes Research Foundation (JDRF; 355 patients) and Tidepool (120 patients).RESULTS: In 10-fold cross-validation, the average area under the receiver operating characteristic curve (ROC-AUC) was 0.77 (standard deviation [SD]: 0.0233) on the REPLACE-BG cohort, 0.74 (SD: 0.0188) on the JDRF cohort, and 0.76 (SD: 0.02) on the Tidepool cohort. In external validation, the average ROC-AUC across the three cohorts was 0.74 (SD: 0.0262).CONCLUSIONS: We developed a machine learning algorithm to estimate the probability of a clinically significant hypoglycemic event within one week. Predictive algorithms may provide diabetes care providers using RPM with additional context when prioritizing T1D patients for review.

  View details for DOI 10.1177/19322968241236208

  View details for PubMedID 38445628

• Diabetes Technology and Therapy in the Pediatric Age Group. Diabetes technology & therapeutics Maahs, D. M., Prahalad, P., Schweiger, D. S., Shalitin, S. 2024; 26 (S1): S117-S140

  View details for DOI 10.1089/dia.2024.2508

  View details for PubMedID 38441448

• Demographic, Clinical, Management, and Outcome Characteristics of 8,004 Young Children With Type 1 Diabetes. Diabetes care Sandy, J. L., Tittel, S. R., Rompicherla, S., Karges, B., James, S., Rioles, N., Zimmerman, A. G., Frohlich-Reiterer, E., Maahs, D. M., Lanzinger, S., Craig, M. E., Ebekozien, O., Australasian Diabetes Data Network (ADDN), T1D Exchanged Quality Improvement Collaborative (T1DX-QI), Prospective Diabetes Follow-Up Registry Initiative (DPV), Craig, M., Colman, P., Glastras, S., Jones, T., Johnson, S., Sinnott, R., Zimmerman, A., Anderson, K., Andrikopoulos, S., Ambler, G., Batch, J., Bergman, P., Brown, J., Cameron, F., Conwell, L., Cotterill, A., Couper, J., Davis, E., de Bock, M., Donaghue, K., Fairchild, J., Fegan, G., Fourlanos, S., Goss, P., Gray, L., Hamblin, S., Hofman, P., Holmes-Walker, D. J., Huynh, T., James, S., Jefferies, C., Kao, J., King, B. R., Lafferty, A., Martin, M., McCrossin, R., Neville, K., Pascoe, M., Paul, R., Pena, A., Phillips, L., Price, D., Rodda, C., Simmons, D., Smart, C., Stone, M., Stranks, S., Tham, E., Ward, G., Wheeler, B., Woodhead, H., Alonso, G. T., DeSalvo, D., Miyazaki, B., Choudhary, A., Clements, M., Majidi, S., Corathers, S., Mucci, A., Hsieh, S., Cossen, K., Gallagher, M. P., Hannon, T., Wolf, R., Bazan, G., Fogel, N., Wilkes, M., Kamboj, M., Sarhis, J., Mekhoubad, A., Accacha, S., Guttmann-Bauman, I., Demeterco-Berggren, C., Malik, F., Roberts, A., Eng, D., Prahalad, P., Izquierdo, R., Crossen, S., Schulmeister, C., Wong, J., Scott, M. L., Jacobsen, L., Sanchez, J., Lee, J., Guarneri, A., Raman, V., Mann, L., Antal, Z., Akturk, H., Steenkamp, D., Rao, P., Vouyiouklis, M., Agarwal, S., Davis, G., Mathioudakis, N., Levy, C., Aleppo, G., Golden, L., Ahmann, A., Lorincz, I., Basina, M., Weinstock, R., Surampudi, P., Kulasa, K., Masharani, U., Vendrame, F., Ng, J., Zupa, M., Herrick, C., Seyoum, B., Fantasia, K., DiGiovanna, M., Haw, S., Ziemer, D., Garg, R., Haft, H., Tsai, S., Gangupantula, G. 2024

  Abstract

  OBJECTIVE: To compare demographic, clinical, and therapeutic characteristics of children with type 1 diabetes age <6 years across three international registries: Diabetes Prospective Follow-Up Registry (DPV; Europe), T1D Exchange Quality Improvement Network (T1DX-QI; U.S.), and Australasian Diabetes Data Network (ADDN; Australasia).RESEARCH DESIGN AND METHODS: An analysis was conducted comparing 2019-2021 prospective registry data from 8,004 children.RESULTS: Mean ± SD ages at diabetes diagnosis were 3.2 ± 1.4 (DPV and ADDN) and 3.7 ± 1.8 years (T1DX-QI). Mean ± SD diabetes durations were 1.4 ± 1.3 (DPV), 1.4 ± 1.6 (T1DX-QI), and 1.5 ± 1.3 years (ADDN). BMI z scores were in the overweight range in 36.2% (DPV), 41.8% (T1DX-QI), and 50.0% (ADDN) of participants. Mean ± SD HbA1c varied among registries: DPV 7.3 ± 0.9% (56 ± 10 mmol/mol), T1DX-QI 8.0 ± 1.4% (64 ± 16 mmol/mol), and ADDN 7.7 ± 1.2% (61 ± 13 mmol/mol). Overall, 37.5% of children achieved the target HbA1c of <7.0% (53 mmol/mol): 43.6% in DPV, 25.5% in T1DX-QI, and 27.5% in ADDN. Use of diabetes technologies such as insulin pump (DPV 86.6%, T1DX 46.6%, and ADDN 39.2%) and continuous glucose monitoring (CGM; DPV 85.1%, T1DX-QI 57.6%, and ADDN 70.5%) varied among registries. Use of hybrid closed-loop (HCL) systems was uncommon (from 0.5% [ADDN] to 6.9% [DPV]).CONCLUSIONS: Across three major registries, more than half of children age <6 years did not achieve the target HbA1c of <7.0% (53 mmol/mol). CGM was used by most participants, whereas insulin pump use varied across registries, and HCL system use was rare. The differences seen in glycemia and use of diabetes technologies among registries require further investigation to determine potential contributing factors and areas to target to improve the care of this vulnerable group.

  View details for DOI 10.2337/dc23-1317

  View details for PubMedID 38305782

• Smart Start - Designing Powerful Clinical Trials Using Pilot Study Data. NEJM evidence Ferstad, J. O., Prahalad, P., Maahs, D. M., Zaharieva, D. P., Fox, E., Desai, M., Johari, R., Scheinker, D. 2024; 3 (2): EVIDoa2300164

  Abstract

  Using Pilot Study Data to Design Clinical TrialsDigital health interventions are often studied in a pilot trial before full evaluation in a randomized controlled trial. The authors introduce Smart Start, a framework for using pilot study data to optimize the intervention and design the subsequent randomized controlled trial to maximize the chance of success.

  View details for DOI 10.1056/EVIDoa2300164

  View details for PubMedID 38320487

• Benchmarking Diabetes Technology Use Among 21 U.S. Pediatric Diabetes Centers. Clinical diabetes : a publication of the American Diabetes Association Prahalad, P., Hardison, H., Odugbesan, O., Lyons, S., Alwazeer, M., Neyman, A., Miyazaki, B., Cossen, K., Hsieh, S., Eng, D., Roberts, A., Clements, M. A., Ebekozien, O., T1D Exchange Quality Improvement Collaborative 2024; 42 (1): 27-33

  Abstract

  The American Diabetes Association's Standards of Care in Diabetes recommends the use of diabetes technology such as continuous glucose monitoring systems and insulin pumps for people living with type 1 diabetes. Unfortunately, there are multiple barriers to uptake of these devices, including local diabetes center practices. This study aimed to examine overall change and center-to-center variation in uptake of diabetes technology across 21 pediatric centers in the T1D Exchange Quality Improvement Collaborative. It found an overall increase in diabetes technology use for most centers from 2021 to 2022 with significant variation.

  View details for DOI 10.2337/cd23-0052

  View details for PubMedID 38230344

• Roadmap to Continuous Glucose Monitoring Adoption and Improved Outcomes in Endocrinology: The 4T (Teamwork, Targets, Technology, and Tight Control) Program. Diabetes spectrum : a publication of the American Diabetes Association Prahalad, P., Maahs, D. M. 2023; 36 (4): 299-305

  Abstract

  Glucose monitoring is essential for the management of type 1 diabetes and has evolved from urine glucose monitoring in the early 1900s to home blood glucose monitoring in the 1980s to continuous glucose monitoring (CGM) today. Youth with type 1 diabetes struggle to meet A1C goals; however, CGM is associated with improved A1C in these youth and is recommended as a standard of care by diabetes professional organizations. Despite their utility, expanding uptake of CGM systems has been challenging, especially in minoritized communities. The 4T (Teamwork, Targets, Technology, and Tight Control) program was developed using a team-based approach to set consistent glycemic targets and equitably initiate CGM and remote patient monitoring in all youth with new-onset type 1 diabetes. In the pilot 4T study, youth in the 4T cohort had a 0.5% improvement in A1C 12 months after diabetes diagnosis compared with those in the historical cohort. The 4T program can serve as a roadmap for other multidisciplinary pediatric type 1 diabetes clinics to increase CGM adoption and improve glycemic outcomes.

  View details for DOI 10.2337/dsi23-0003

  View details for PubMedID 37982062

  View details for PubMedCentralID PMC10654131

• Diabetic ketoacidosis (DKA) at diagnosis in youth with type 1 diabetes (T1D) is associated with a higher hemoglobin A1c even with intensive insulin management. Diabetes technology & therapeutics Zaharieva, D. P., Ding, V., Addala, A., Prahalad, P., Bishop, F., Hood, K., Desai, M., Wilson, D. M., Buckingham, B. A., Maahs, D. M. 2023

  Abstract

  Diabetic ketoacidosis (DKA) at diagnosis is associated with short- and long-term complications. We assessed the relationship between DKA status and hemoglobin A1c (A1c) levels in the first year following type 1 diabetes (T1D) diagnosis.The Pilot 4T study offered continuous glucose monitoring to youth with T1D within 1 month of diagnosis. A1c levels were compared between historical (n=271) and Pilot 4T (n=135) cohorts stratified by DKA status at diagnosis (DKA: historical=94, 4T=67 vs without DKA historical=177, 4T=68). A1c was evaluated using locally estimated scatter plot smoothing. Change in A1c from 4- to 12-months post-diagnosis was evaluated using a linear mixed model.Median age was 9.7 [IQR: 6.6, 12.7] vs 9.7 [IQR: 6.8, 12.7] years, 49% vs 47% female, 44% vs 39% Non-Hispanic White in historical vs Pilot 4T. In historical and 4T cohorts, DKA at diagnosis demonstrated higher A1c at 6 (0.5% [95%CI: 0.21, 0.79; p<0.01] and 0.38% [95% CI: 0.02, 0.74; p=0.04], respectively) and 12 months (0.62% [95% CI: -0.06, 1.29; p=0.07] and 0.39% [95% CI: -0.32, 1.10; p=0.29], respectively). The highest % time in range (TIR; 70-180 mg/dL) was seen between weeks 15-20 (69%) vs 25-30 (75%) post-diagnosis for youth with vs without DKA in Pilot 4T, respectively.Pilot 4T improved A1c outcomes vs the historical cohort, but those with DKA at diagnosis had persistently elevated A1c throughout the study and intensive diabetes management did not mitigate this difference. DKA prevention at diagnosis may translate into better glycemic outcomes in the first year post-diagnosis.

  View details for DOI 10.1089/dia.2023.0405

  View details for PubMedID 37955644

• Continuous Glucose Monitoring Provides Durable Glycemic Benefit in Adolescents and Young Adults with Type 1 Diabetes: 12-Month Follow-Up Results PEDIATRIC DIABETES Miller, K. M., Bauza, C., Kanapka, L. G., Clements, M. A., Desalvo, D. J., Hood, K., Messer, L. H., Sherr, J., Bergamo, K., Criego, A., Freiner, E., Lyons, S. K., Monzavi, R., Moore, W., Prahalad, P., Simmons, J. H., Sulik, M., Wadwa, R., Weinstock, R. S., Willi, S. M., Williams, K., Laffel, L. M., CITY Study Grp 2023; 2023

  View details for DOI 10.1155/2023/6718115

  View details for Web of Science ID 001097195800001

• Management of Neonatal Diabetes due to a KCNJ11 Mutation with Automated Insulin Delivery System and Remote Patient Monitoring. Case reports in endocrinology Lee, M. Y., Gloyn, A. L., Maahs, D. M., Prahalad, P. 2023; 2023: 8825724

  Abstract

  Neonatal diabetes mellitus (NDM) is a monogenic form of diabetes. Management of hyperglycemia in neonates with subcutaneous insulin is challenging because of frequent feeding, variable quantity of milk intake with each feed, low insulin dose requirements, and high risk for hypoglycemia and associated complications in this population. We present a case of NDM in a proband initially presenting with focal seizures and diabetic ketoacidosis due to a pathologic mutation in the beta cell potassium ATP channel gene KCNJ11 c.679G > A (p.E227K). We describe the use of continuous glucose monitoring (CGM), insulin pump, automated insulin delivery system, and remote patient monitoring technologies to facilitate rapid and safe outpatient cross-titration from insulin to oral sulfonylurea. Our case highlights the safety and efficacy of these technologies for infants with diabetes, including improvements in glycemia, quality of life, and cost-effectiveness by shortening hospital stay.

  View details for DOI 10.1155/2023/8825724

  View details for PubMedID 37664823

  View details for PubMedCentralID PMC10468271

• Impact of SARS-CoV-2 Infection on Disease Trajectory in Youth with T1D: An EHR-Based Cohort Study from the RECOVER Program PEDIATRIC DIABETES Prahalad, P., Lorman, V., Wu, Q., Razzaghi, H., Chen, Y., Pajor, N., Case, A., Bose-Brill, S., Block, J. B., Patel, P., Rao, S., Mejias, A. B., Forrest, C., Bailey, L., Jhaveri, R., Thacker, D. A., Christakis, D. M., Lee, G., RECOVER Consortium 2023; 2023

  View details for DOI 10.1155/2023/8798997

  View details for Web of Science ID 001051843300001

• A quantitative model to ensure capacity sufficient for timely access to care in a remote patient monitoring program. Endocrinology, diabetes & metabolism Chang, A., Gao, M. Z., Ferstad, J. O., Dupenloup, P., Zaharieva, D. P., Maahs, D. M., Prahalad, P., Johari, R., Scheinker, D. 2023: e435

  Abstract

  Algorithm-enabled remote patient monitoring (RPM) programs pose novel operational challenges. For clinics developing and deploying such programs, no standardized model is available to ensure capacity sufficient for timely access to care. We developed a flexible model and interactive dashboard of capacity planning for whole-population RPM-based care for T1D.Data were gathered from a weekly RPM program for 277 paediatric patients with T1D at a paediatric academic medical centre. Through the analysis of 2 years of observational operational data and iterative interviews with the care team, we identified the primary operational, population, and workforce metrics that drive demand for care providers. Based on these metrics, an interactive model was designed to facilitate capacity planning and deployed as a dashboard.The primary population-level drivers of demand are the number of patients in the program, the rate at which patients enrol and graduate from the program, and the average frequency at which patients require a review of their data. The primary modifiable clinic-level drivers of capacity are the number of care providers, the time required to review patient data and contact a patient, and the number of hours each provider allocates to the program each week. At the institution studied, the model identified a variety of practical operational approaches to better match the demand for patient care.We designed a generalizable, systematic model for capacity planning for a paediatric endocrinology clinic providing RPM for T1D. We deployed this model as an interactive dashboard and used it to facilitate expansion of a novel care program (4 T Study) for newly diagnosed patients with T1D. This model may facilitate the systematic design of RPM-based care programs.

  View details for DOI 10.1002/edm2.435

  View details for PubMedID 37345227

• Disparities in Hemoglobin A1c Levels in the First Year After Diagnosis Among Youths With Type 1 Diabetes Offered Continuous Glucose Monitoring. JAMA network open Addala, A., Ding, V., Zaharieva, D. P., Bishop, F. K., Adams, A. S., King, A. C., Johari, R., Scheinker, D., Hood, K. K., Desai, M., Maahs, D. M., Prahalad, P. 2023; 6 (4): e238881

  Abstract

  Continuous glucose monitoring (CGM) is associated with improvements in hemoglobin A1c (HbA1c) in youths with type 1 diabetes (T1D); however, youths from minoritized racial and ethnic groups and those with public insurance face greater barriers to CGM access. Early initiation of and access to CGM may reduce disparities in CGM uptake and improve diabetes outcomes.To determine whether HbA1c decreases differed by ethnicity and insurance status among a cohort of youths newly diagnosed with T1D and provided CGM.This cohort study used data from the Teamwork, Targets, Technology, and Tight Control (4T) study, a clinical research program that aims to initiate CGM within 1 month of T1D diagnosis. All youths with new-onset T1D diagnosed between July 25, 2018, and June 15, 2020, at Stanford Children's Hospital, a single-site, freestanding children's hospital in California, were approached to enroll in the Pilot-4T study and were followed for 12 months. Data analysis was performed and completed on June 3, 2022.All eligible participants were offered CGM within 1 month of diabetes diagnosis.To assess HbA1c change over the study period, analyses were stratified by ethnicity (Hispanic vs non-Hispanic) or insurance status (public vs private) to compare the Pilot-4T cohort with a historical cohort of 272 youths diagnosed with T1D between June 1, 2014, and December 28, 2016.The Pilot-4T cohort comprised 135 youths, with a median age of 9.7 years (IQR, 6.8-12.7 years) at diagnosis. There were 71 boys (52.6%) and 64 girls (47.4%). Based on self-report, participants' race was categorized as Asian or Pacific Islander (19 [14.1%]), White (62 [45.9%]), or other race (39 [28.9%]); race was missing or not reported for 15 participants (11.1%). Participants also self-reported their ethnicity as Hispanic (29 [21.5%]) or non-Hispanic (92 [68.1%]). A total of 104 participants (77.0%) had private insurance and 31 (23.0%) had public insurance. Compared with the historical cohort, similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were observed for Hispanic individuals (estimated difference, -0.26% [95% CI, -1.05% to 0.43%], -0.60% [-1.46% to 0.21%], and -0.15% [-1.48% to 0.80%]) and non-Hispanic individuals (estimated difference, -0.27% [95% CI, -0.62% to 0.10%], -0.50% [-0.81% to -0.11%], and -0.47% [-0.91% to 0.06%]) in the Pilot-4T cohort. Similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were also observed for publicly insured individuals (estimated difference, -0.52% [95% CI, -1.22% to 0.15%], -0.38% [-1.26% to 0.33%], and -0.57% [-2.08% to 0.74%]) and privately insured individuals (estimated difference, -0.34% [95% CI, -0.67% to 0.03%], -0.57% [-0.85% to -0.26%], and -0.43% [-0.85% to 0.01%]) in the Pilot-4T cohort. Hispanic youths in the Pilot-4T cohort had higher HbA1c at 6, 9, and 12 months postdiagnosis than non-Hispanic youths (estimated difference, 0.28% [95% CI, -0.46% to 0.86%], 0.63% [0.02% to 1.20%], and 1.39% [0.37% to 1.96%]), as did publicly insured youths compared with privately insured youths (estimated difference, 0.39% [95% CI, -0.23% to 0.99%], 0.95% [0.28% to 1.45%], and 1.16% [-0.09% to 2.13%]).The findings of this cohort study suggest that CGM initiation soon after diagnosis is associated with similar improvements in HbA1c for Hispanic and non-Hispanic youths as well as for publicly and privately insured youths. These results further suggest that equitable access to CGM soon after T1D diagnosis may be a first step to improve HbA1c for all youths but is unlikely to eliminate disparities entirely.ClinicalTrials.gov Identifier: NCT04336969.

  View details for DOI 10.1001/jamanetworkopen.2023.8881

  View details for PubMedID 37074715

  View details for PubMedCentralID PMC10116368

• Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program. JAMIA open Lorman, V., Rao, S., Jhaveri, R., Case, A., Mejias, A., Pajor, N. M., Patel, P., Thacker, D., Bose-Brill, S., Block, J., Hanley, P. C., Prahalad, P., Chen, Y., Forrest, C. B., Bailey, L. C., Lee, G. M., Razzaghi, H. 2023; 6 (1): ooad016

  Abstract

  Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC.We used a propensity-matched cohort design comparing children identified using the new PASC ICD10CM diagnosis code (U09.9) (N = 1309) to children with (N = 6545) and without (N = 6545) SARS-CoV-2 infection. We used a tree-based scan statistic to identify potential condition clusters co-occurring more frequently in cases than controls.We found significant enrichment among children with PASC in cardiac, respiratory, neurologic, psychological, endocrine, gastrointestinal, and musculoskeletal systems, the most significant related to circulatory and respiratory such as dyspnea, difficulty breathing, and fatigue and malaise.Our study addresses methodological limitations of prior studies that rely on prespecified clusters of potential PASC-associated diagnoses driven by clinician experience. Future studies are needed to identify patterns of diagnoses and their associations to derive clinical phenotypes.We identified multiple conditions and body systems associated with pediatric PASC. Because we rely on a data-driven approach, several new or under-reported conditions and symptoms were detected that warrant further investigation.

  View details for DOI 10.1093/jamiaopen/ooad016

  View details for PubMedID 36926600

  View details for PubMedCentralID PMC10013630

• Diabetes Technology and Therapy in the Pediatric Age Group. Diabetes technology & therapeutics Maahs, D. M., Prahalad, P., Schweiger, D. Š., Shalitin, S. 2023; 25 (S1): S118-S145

  View details for DOI 10.1089/dia.2023.2508

  View details for PubMedID 36802194

• MULTI-CENTER DIABETES PROVIDER PERSPECTIVE ON BARRIERS TO SMART INSULIN PEN USE IN THE UNITED STATES Odugbesan, O., Mungmode, A., Wright, T., Nelson, G., Aleppo, G., Myers, A., O'Malley, G., Mckee, A., Prahalad, P., Tsai, S., Miyazaki, B., Ebekozien, O. MARY ANN LIEBERT, INC. 2023: A189

  View details for Web of Science ID 001043126000435

• CONTINUOUS GLUCOSE MONITOR (CGM) DERIVED GLYCEMIC OUTCOMES AMONG REAL-TIME CGM VS. FLASH CGM USERS IN A MULTI-CENTER EMR DATABASE FOR PEOPLE WITH T1D Noor, N., Ebekozien, O., Vendrame, F., Jacobsen, L., Weinstock, R., Gallagher, M. P., Corathers, S., Accacha, S., Prahalad, P., Rapaport, R. MARY ANN LIEBERT, INC. 2023: A159

  View details for Web of Science ID 001043126000365

• BRIDGING DISPARITIES IN TYPE 1 CARE IN THE US Maahs, D., Zaharieva, D., Prahalad, P., Scheinker, D., Hood, K., Bishop, F., Addala, A. MARY ANN LIEBERT, INC. 2023: A25

  View details for Web of Science ID 001043126000064

• SEX DIFFERENCES IN THE MANAGEMENT OF EXERCISE IN THE PEDIATRIC AND ADULT POPULATION Zaharieva, D., Ding, V., Ritter, V., Desai, M., Prahalad, P., Scheinker, D., Hood, K., Bishop, F., Addala, A., Tanenbaum, M., Maahs, D. MARY ANN LIEBERT, INC. 2023: A29

  View details for Web of Science ID 001043126000074

• IS TECHNOLOGY USEFUL FOR BREAKING DOWN BARRIERS TO EXERCISE IN DIABETES? Zaharieva, D., Ritter, V., Desai, M., Prahalad, P., Scheinker, D., Hood, K., Bishop, F., Addala, A., Riddell, M., Tanenbaum, M., Maahs, D. MARY ANN LIEBERT, INC. 2023: A4

  View details for Web of Science ID 001043126000012

• Correction: Implementation of Psychosocial Screening into Diabetes Clinics: Experience from the Type 1 Diabetes Exchange Quality Improvement Network. Current diabetes reports Corathers, S., Williford, D. N., Kichler, J., Smith, L., Ospelt, E., Rompicherla, S., Roberts, A., Prahalad, P., Basina, M., Munoz, C., Ebekozien, O. 2023

  View details for DOI 10.1007/s11892-023-01500-8

  View details for PubMedID 36708445

• Diabetes Technology Meeting 2022. Journal of diabetes science and technology Huang, J., Yeung, A. M., DuBord, A. Y., Wolpert, H., Jacobs, P. G., Lee, W. A., Drincic, A., Spanakis, E. K., Sherr, J. L., Prahalad, P., Fleming, A., Hsiao, V. C., Kompala, T., Lal, R. A., Fayfman, M., Ginsberg, B. H., Galindo, R. J., Stuhr, A., Chase, J. G., Najafi, B., Masharani, U., Seley, J. J., Klonoff, D. C. 2023: 19322968221148743

  Abstract

  Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 3 to November 5, 2022. Meeting topics included (1) the measurement of glucose, insulin, and ketones; (2) virtual diabetes care; (3) metrics for managing diabetes and predicting outcomes; (4) integration of continuous glucose monitor data into the electronic health record; (5) regulation of diabetes technology; (6) digital health to nudge behavior; (7) estimating carbohydrates; (8) fully automated insulin delivery systems; (9) hypoglycemia; (10) novel insulins; (11) insulin delivery; (12) on-body sensors; (13) continuous glucose monitoring; (14) diabetic foot ulcers; (15) the environmental impact of diabetes technology; and (16) spinal cord stimulation for painful diabetic neuropathy. A live demonstration of a device that can allow for the recycling of used insulin pens was also presented.

  View details for DOI 10.1177/19322968221148743

  View details for PubMedID 36704821

• Implementation of Psychosocial Screening into Diabetes Clinics: Experience from the Type 1 Diabetes Exchange Quality Improvement Network. Current diabetes reports Corathers, S., Wilford, D., Kichler, J., Smith, L., Ospelt, E., Rompicherla, S., Roberts, A., Prahalad, P., Basina, M., Munoz, C., Ebekozien, O. 2022

  Abstract

  PURPOSE OF REVIEW: Although advances in diabetes technology and pharmacology have significantly and positively impacted diabetes management and health outcomes for some, diabetes care remains burdensome and can be challenging to balance with other life priorities. The purpose of this article is to review the rationale for assessment of psychosocial domains in diabetes care settings and strategies for the implementation of psychosocial screening into routine practice. Survey data from the Type 1 Diabetes Exchange Quality Improvement Network is highlighted.RECENT FINDINGS: Implementation of psychosocial screening requires identifying the population; selecting validated tools to assess target domains; determining frequency of screening and mode of survey delivery; and scoring, interpreting, documenting, and facilitating referrals such that these processes are part of clinical workflows. Recognizing the influence of psychosocial factors for people with diabetes (PWD), professional society guidelines for comprehensive diabetes care recommend the integration of psychosocial screening into routine care.

  View details for DOI 10.1007/s11892-022-01497-6

  View details for PubMedID 36538250

• Impact of diabetes status and related factors on COVID-19-associated hospitalization: A nationwide retrospective cohort study of 116,370 adults with SARS-CoV-2 infection. Diabetes research and clinical practice Tallon, E. M., Ebekozien, O., Sanchez, J., Staggs, V. S., Ferro, D., McDonough, R., Demeterco-Berggren, C., Polsky, S., Gomez, P., Patel, N., Prahalad, P., Odugbesan, O., Mathias, P., Lee, J. M., Smith, C., Shyu, C., Clements, M. A. 2022: 110156

  Abstract

  AIMS: We examined diabetes status (no diabetes; type 1 diabetes [T1D]; type 2 diabetes [T2D]) and other demographic and clinical factors as correlates of coronavirus disease 2019 (COVID-19)-related hospitalization. Further, we evaluated predictors of COVID-19-related hospitalization in T1D and T2D.METHODS: We analyzed electronic health record data from the Cerner Real-World DataTM (CRWD) de-identified COVID-19 database (December 2019 through mid-September 2020; 87 US health systems). Logistic mixed models were used to examine predictors of hospitalization at index encounters associated with confirmed SARS-CoV-2 infection.RESULTS: In 116,370 adults (>=18 years old) with COVID-19 (93,098 no diabetes; 802 T1D; 22,470 T2D), factors that independently increased risk for hospitalization included diabetes, male sex, public health insurance, decreased body mass index (BMI; <25.0-29.9 kg/m2), increased BMI (>25.0-29.9 kg/m2), vitamin D deficiency/insufficiency, and Elixhauser comorbidity score. After further adjustment for concurrent hyperglycemia and acidosis in those with diabetes, hospitalization risk was substantially higher in T1D than T2D and in those with low vitamin D and elevated hemoglobin A1c (HbA1c).CONCLUSIONS: The higher hospitalization risk in T1D versus T2D warrants further investigation. Modifiable risk factors such as vitamin D deficiency/insufficiency, BMI, and elevated HbA1c may serve as prognostic indicators for COVID-19-related hospitalization in adults with diabetes.

  View details for DOI 10.1016/j.diabres.2022.110156

  View details for PubMedID 36400172

• A model to design financially sustainable algorithm-enabled remote patient monitoring for pediatric type 1 diabetes care. Frontiers in endocrinology Dupenloup, P., Pei, R. L., Chang, A., Gao, M. Z., Prahalad, P., Johari, R., Schulman, K., Addala, A., Zaharieva, D. P., Maahs, D. M., Scheinker, D. 2022; 13: 1021982

  Abstract

  Population-level algorithm-enabled remote patient monitoring (RPM) based on continuous glucose monitor (CGM) data review has been shown to improve clinical outcomes in diabetes patients, especially children. However, existing reimbursement models are geared towards the direct provision of clinic care, not population health management. We developed a financial model to assist pediatric type 1 diabetes (T1D) clinics design financially sustainable RPM programs based on algorithm-enabled review of CGM data.Data were gathered from a weekly RPM program for 302 pediatric patients with T1D at Lucile Packard Children's Hospital. We created a customizable financial model to calculate the yearly marginal costs and revenues of providing diabetes education. We consider a baseline or status quo scenario and compare it to two different care delivery scenarios, in which routine appointments are supplemented with algorithm-enabled, flexible, message-based contacts delivered according to patient need. We use the model to estimate the minimum reimbursement rate needed for telemedicine contacts to maintain revenue-neutrality and not suffer an adverse impact to the bottom line.The financial model estimates that in both scenarios, an average reimbursement rate of roughly $10.00 USD per telehealth interaction would be sufficient to maintain revenue-neutrality. Algorithm-enabled RPM could potentially be billed for using existing RPM CPT codes and lead to margin expansion.We designed a model which evaluates the financial impact of adopting algorithm-enabled RPM in a pediatric endocrinology clinic serving T1D patients. This model establishes a clear threshold reimbursement value for maintaining revenue-neutrality, as well as an estimate of potential RPM reimbursement revenue which could be billed for. It may serve as a useful financial-planning tool for a pediatric T1D clinic seeking to leverage algorithm-enabled RPM to provide flexible, more timely interventions to its patients.

  View details for DOI 10.3389/fendo.2022.1021982

  View details for PubMedID 36440201

  View details for PubMedCentralID PMC9691757

• The COVID-19 Pandemic Affects Seasonality, With Increasing Cases of New-Onset Type 1 Diabetes in Children, From the Worldwide SWEET Registry. Diabetes care Reschke, F., Lanzinger, S., Herczeg, V., Prahalad, P., Schiaffini, R., Mul, D., Clapin, H., Zabeen, B., Pelicand, J., Phillip, M., Limbert, C., Danne, T. 2022

  Abstract

  To analyze whether the coronavirus disease 2019 (COVID-19) pandemic increased the number of cases or impacted seasonality of new-onset type 1 diabetes (T1D) in large pediatric diabetes centers globally.We analyzed data on 17,280 cases of T1D diagnosed during 2018-2021 from 92 worldwide centers participating in the SWEET registry using hierarchic linear regression models.The average number of new-onset T1D cases per center adjusted for the total number of patients treated at the center per year and stratified by age-groups increased from 11.2 (95% CI 10.1-12.2) in 2018 to 21.7 (20.6-22.8) in 2021 for the youngest age-group, <6 years; from 13.1 (12.2-14.0) in 2018 to 26.7 (25.7-27.7) in 2021 for children ages 6 to <12 years; and from 12.2 (11.5-12.9) to 24.7 (24.0-25.5) for adolescents ages 12-18 years (all P < 0.001). These increases remained within the expected increase with the 95% CI of the regression line. However, in Europe and North America following the lockdown early in 2020, the typical seasonality of more cases during winter season was delayed, with a peak during the summer and autumn months. While the seasonal pattern in Europe returned to prepandemic times in 2021, this was not the case in North America. Compared with 2018-2019 (HbA1c 7.7%), higher average HbA1c levels (2020, 8.1%; 2021, 8.6%; P < 0.001) were present within the first year of T1D during the pandemic.The slope of the rise in pediatric new-onset T1D in SWEET centers remained unchanged during the COVID-19 pandemic, but a change in the seasonality at onset became apparent.

  View details for DOI 10.2337/dc22-0278

  View details for PubMedID 36166593

• An Evaluation of Point-of-Care HbA1c, HbA1c Home Kits, and Glucose Management Indicator: Potential Solutions for Telehealth Glycemic Assessments. Diabetology Zaharieva, D. P., Addala, A., Prahalad, P., Leverenz, B., Arrizon-Ruiz, N., Ding, V. Y., Desai, M., Karger, A. B., Maahs, D. M. 2022; 3 (3): 494-501

  Abstract

  During the COVID-19 pandemic, fewer in-person clinic visits resulted in fewer point-of-care (POC) HbA1c measurements. In this sub-study, we assessed the performance of alternative glycemic measures that can be obtained remotely, such as HbA1c home kits and Glucose Management Indicator (GMI) values from Dexcom Clarity. Home kit HbA1c (n = 99), GMI, (n = 88), and POC HbA1c (n = 32) were collected from youth with T1D (age 9.7 ± 4.6 years). Bland-Altman analyses and Lin's concordance correlation coefficient (rhoc) were used to characterize the agreement between paired HbA1c measures. Both the HbA1c home kit and GMI showed a slight positive bias (mean difference 0.18% and 0.34%, respectively) and strong concordance with POC HbA1c (rhoc = 0.982 [0.965, 0.991] and 0.823 [0.686, 0.904], respectively). GMI showed a slight positive bias (mean difference 0.28%) and fair concordance (rhoc = 0.750 [0.658, 0.820]) to the HbA1c home kit. In conclusion, the strong concordance of GMI and home kits to POC A1c measures suggest their utility in telehealth visits assessments. Although these are not candidates for replacement, these measures can facilitate telehealth visits, particularly in the context of other POC HbA1c measurements from an individual.

  View details for DOI 10.3390/diabetology3030037

  View details for PubMedID 37163187

• "Much more convenient, just as effective:" Experiences of starting continuous glucose monitoring remotely following Type 1 diabetes diagnosis. Diabetic medicine : a journal of the British Diabetic Association Tanenbaum, M. L., Zaharieva, D. P., Addala, A., Prahalad, P., Hooper, J. A., Leverenz, B., Cortes, A. L., Arrizon-Ruiz, N., Pang, E., Bishop, F., Maahs, D. M. 2022: e14923

  Abstract

  Initiating continuous glucose monitoring (CGM) shortly after Type 1 diabetes diagnosis has glycemic and quality of life benefits for youth with Type 1 diabetes and their families. The SARS-CoV-2 pandemic led to a rapid shift to virtual delivery of CGM initiation visits. We aimed to understand parents' experiences receiving virtual care to initiate CGM within 30 days of diagnosis.We held focus groups and interviews using a semi-structured interview guide with parents of youth who initiated CGM over telehealth within 30 days of diagnosis during the SARS-CoV-2 pandemic. Questions aimed to explore experiences of starting CGM virtually. Groups and interviews were audio-recorded, transcribed, and analyzed using thematic analysis.Participants were 16 English-speaking parents (age 43±6 years; 63% female) of 15 youth (age 9±4 years; 47% female; 47% non-Hispanic White, 20% Hispanic, 13% Asian, 7% Black, 13% other). They described multiple benefits of the virtual visit including convenient access to high-quality care; integrating Type 1 diabetes care into daily life; and being in the comfort of home. A minority experienced challenges with virtual care delivery; most preferred the virtual format. Participants expressed that clinics should offer a choice of virtual or in-person to families initiating CGM in the future.Most parents appreciated receiving CGM initiation education via telehealth and felt it should be an option offered to all families. Further efforts can continue to enhance CGM initiation teaching virtually to address identified barriers.

  View details for DOI 10.1111/dme.14923

  View details for PubMedID 35899591

• Psychosocial Needs for Newly Diagnosed Youth with Type 1 Diabetes and Their Families. Current diabetes reports Patton, S. R., Maahs, D., Prahalad, P., Clements, M. A. 2022

  Abstract

  PURPOSE OF REVIEW: To synthesize findings from studies published within the last 5 to 10years and recruiting families of children with new-onset type 1 diabetes (T1D).RECENT FINDINGS: Children can establish glycated hemoglobin (HbA1c) trajectories in the new-onset period that may persist for up to a decade. Demographic factors, family conflict, and diabetic ketoacidosis at the time of diagnosis may be risk factors for sub-optimal child HbA1c, while new immune modulating therapies and a treatment approach that combines advanced technologies and remote patient monitoring may improve child HbA1c. Nonetheless, recent trials in the new-onset period have largely overlooked how treatments may impact families' psychosocial functioning and longitudinal observational studies have been limited. The new-onset period of T1D is an important time for research and clinical intervention, though gaps exist specific to families' psychosocial needs. Filling these gaps is essential to inform clinical management and standard of care guidelines and improve outcomes.

  View details for DOI 10.1007/s11892-022-01479-8

  View details for PubMedID 35727439

• Algorithm-Enabled, Personalized Glucose Management for Type 1 Diabetes at the Population Scale: Prospective Evaluation in Clinical Practice. JMIR diabetes Scheinker, D., Gu, A., Grossman, J., Ward, A., Ayerdi, O., Miller, D., Leverenz, J., Hood, K., Lee, M. Y., Maahs, D. M., Prahalad, P. 2022; 7 (2): e27284

  Abstract

  BACKGROUND: The use of continuous glucose monitors (CGMs) is recommended as the standard of care by the American Diabetes Association for individuals with type 1 diabetes (T1D). Few hardware-agnostic, open-source, whole-population tools are available to facilitate the use of CGM data by clinicians such as physicians and certified diabetes educators.OBJECTIVE: This study aimed to develop a tool that identifies patients appropriate for contact using an asynchronous message through electronic medical records while minimizing the number of patients reviewed by a certified diabetes educator or physician using the tool.METHODS: We used consensus guidelines to develop timely interventions for diabetes excellence (TIDE), an open-source hardware-agnostic tool to analyze CGM data to identify patients with deteriorating glucose control by generating generic flags (eg, mean glucose [MG] >170 mg/dL) and personalized flags (eg, MG increased by >10 mg/dL). In a prospective 7-week study in a pediatric T1D clinic, we measured the sensitivity of TIDE in identifying patients appropriate for contact and the number of patients reviewed. We simulated measures of the workload generated by TIDE, including the average number of time in range (TIR) flags per patient per review period, on a convenience sample of eight external data sets, 6 from clinical trials and 2 donated by research foundations.RESULTS: Over the 7 weeks of evaluation, the clinical population increased from 56 to 64 patients. The mean sensitivity was 99% (242/245; SD 2.5%), and the mean reduction in the number of patients reviewed was 42.6% (182/427; SD 10.9%). The 8 external data sets contained 1365 patients with 30,017 weeks of data collected by 7 types of CGMs. The rates of generic and personalized TIR flags per patient per review period were, respectively, 0.15 and 0.12 in the data set with the lowest average MG (141 mg/dL) and 0.95 and 0.22 in the data set with the highest average MG (207 mg/dL).CONCLUSIONS: TIDE is an open-source hardware-agnostic tool for personalized analysis of CGM data at the clinical population scale. In a pediatric T1D clinic, TIDE identified 99% of patients appropriate for contact using an asynchronous message through electronic medical records while reducing the number of patients reviewed by certified diabetes care and education specialists by 43%. For each of the 8 external data sets, simulation of the use of TIDE produced fewer than 0.25 personalized TIR flags per patient per review period. The use of TIDE to support telemedicine-based T1D care may facilitate sensitive and efficient guideline-based population health management.

  View details for DOI 10.2196/27284

  View details for PubMedID 35666570

• A New Technology-Enabled Care Model for Pediatric Type 1 Diabetes. NEJM catalyst innovations in care delivery Scheinker, D., Prahalad, P., Johari, R., Maahs, D. M., Majzun, R. 2022; 3 (5)

  Abstract

  In July 2018, pediatric type 1 diabetes (T1D) care at Stanford suffered many of the problems that plague U.S. health care. Patient outcomes lagged behind those of peer European nations, care was delivered primarily on a fixed cadence rather than as needed, continuous glucose monitors (CGMs) were largely unavailable for individuals with public insurance, and providers' primary access to CGM data was through long printouts. Stanford developed a new technology-enabled, telemedicine-based care model for patients with newly diagnosed T1D. They developed and deployed Timely Interventions for Diabetes Excellence (TIDE) to facilitate as-needed patient contact with the partially automated analysis of CGM data and used philanthropic funding to facilitate full access to CGM technology for publicly insured patients, for whom CGM is not readily available in California. A study of the use of CGM for patients with new-onset T1D (pilot Teamwork, Targets, and Technology for Tight Control [4T] study), which incorporated the use of TIDE, was associated with a 0.5%-point reduction in hemoglobin A1c compared with historical controls and an 86% reduction in screen time for providers reviewing patient data. Based on this initial success, Stanford expanded the use of TIDE to a total of 300 patients, including many outside the pilot 4T study, and made TIDE freely available as open-source software. Next steps include expanding the use of TIDE to support the care of approximately 1,000 patients, improving TIDE and the associated workflows to scale their use to more patients, incorporating data from additional sensors, and partnering with other institutions to facilitate their deployment of this care model.

  View details for DOI 10.1056/CAT.21.0438

  View details for PubMedID 36544715

• REDUCING DISPARITIES IN HEMOGLOBIN A1C DURING THE FIRST YEAR OF DIABETES DIAGNOSIS: ACCOMPLISHMENTS AND AREAS FOR IMPROVEMENT IN THE 4T STUDY Addala, A., Ding, V., Bishop, F., Zaharieva, D., Adams, A., King, A., Johari, R., Scheinker, D., Hood, K., Desai, M., Maahs, D., Prahalad, P. MARY ANN LIEBERT, INC. 2022: A60-A61

  View details for Web of Science ID 000791212200153

• YOUTH WITH TYPE 1 DIABETES BENEFIT FROM EARLY CONTINUOUS GLUCOSE MONITORING INITATION IRRESPECTIVE OF DIABETIC KETOACIDOSIS AT DIAGNOSIS: 4T PILOT STUDY RESULTS Zaharieva, D., Addala, A., Prahalad, P., Bishop, F., Hood, K., Maahs, D. MARY ANN LIEBERT, INC. 2022: A48-A49

  View details for Web of Science ID 000791212200128

• A Data-Driven Algorithm to Recommend Initial Clinical Workup for Outpatient Specialty Referral: Algorithm Development and Validation Using Electronic Health Record Data and Expert Surveys. JMIR medical informatics Ip, W., Prahalad, P., Palma, J., Chen, J. H. 2022; 10 (3): e30104

  Abstract

  BACKGROUND: Millions of people have limited access to specialty care. The problem is exacerbated by ineffective specialty visits due to incomplete prereferral workup, leading to delays in diagnosis and treatment. Existing processes to guide prereferral diagnostic workup are labor-intensive (ie, building a consensus guideline between primary care doctors and specialists) and require the availability of the specialists (ie, electronic consultation).OBJECTIVE: Using pediatric endocrinology as an example, we develop a recommender algorithm to anticipate patients' initial workup needs at the time of specialty referral and compare it to a reference benchmark using the most common workup orders. We also evaluate the clinical appropriateness of the algorithm recommendations.METHODS: Electronic health record data were extracted from 3424 pediatric patients with new outpatient endocrinology referrals at an academic institution from 2015 to 2020. Using item co-occurrence statistics, we predicted the initial workup orders that would be entered by specialists and assessed the recommender's performance in a holdout data set based on what the specialists actually ordered. We surveyed endocrinologists to assess the clinical appropriateness of the predicted orders and to understand the initial workup process.RESULTS: Specialists (n=12) indicated that <50% of new patient referrals arrive with complete initial workup for common referral reasons. The algorithm achieved an area under the receiver operating characteristic curve of 0.95 (95% CI 0.95-0.96). Compared to a reference benchmark using the most common orders, precision and recall improved from 37% to 48% (P<.001) and from 27% to 39% (P<.001) for the top 4 recommendations, respectively. The top 4 recommendations generated for common referral conditions (abnormal thyroid studies, obesity, amenorrhea) were considered clinically appropriate the majority of the time by specialists surveyed and practice guidelines reviewed.CONCLUSIONS: An item association-based recommender algorithm can predict appropriate specialists' workup orders with high discriminatory accuracy. This could support future clinical decision support tools to increase effectiveness and access to specialty referrals. Our study demonstrates important first steps toward a data-driven paradigm for outpatient specialty consultation with a tier of automated recommendations that proactively enable initial workup that would otherwise be delayed by awaiting an in-person visit.

  View details for DOI 10.2196/30104

  View details for PubMedID 35238788

• Closing Disparities in Pediatric Diabetes Telehealth Care: Lessons From Telehealth Necessity During the COVID-19 Pandemic. Clinical diabetes : a publication of the American Diabetes Association Prahalad, P., Leverenz, B., Freeman, A., Grover, M., Shah, S., Conrad, B., Morris, C., Stafford, D., Lee, T., Pageler, N., Maahs, D. M. 2022; 40 (2): 153-157

  Abstract

  The coronavirus disease 2019 (COVID-19) pandemic necessitated using telehealth to bridge the clinical gap, but could increase health disparities. This article reports on a chart review of diabetes telehealth visits occurring before COVID-19, during shelter-in-place orders, and during the reopening period. Visits for children with public insurance and for those who were non-English speaking were identified. Telehealth visits for children with public insurance increased from 26.2% before COVID-19 to 37.3% during shelter-in-place orders and 34.3% during reopening. Telehealth visits for children who were non-English speaking increased from 3.5% before COVID-19 to 17.5% during shelter-in-place orders and remained at 15.0% during reopening. Pandemic-related telehealth expansion included optimization of workflows to include patients with public insurance and those who did not speak English. Increased participation by those groups persisted during the reopening phase, indicating that prioritizing inclusive telehealth workflows can reduce disparities in access to care.

  View details for DOI 10.2337/cd20-0123

  View details for PubMedID 35669301

• Disclosures: Standards of Medical Care in Diabetes-2022 DIABETES CARE Draznin, B., Aroda, V. R., Bakris, G., Benson, G., Brown, F. M., Freeman, R., Green, J., Huang, E., Isaacs, D., Kahan, S., Leon, J., Lyons, S. K., Peters, A. L., Prahalad, P., Reusch, J. B., Young-Hyman, D., Das, S., Kosiborod, M., Saraco, M., Hill, M. I., Gabbay, R. A., El Sayed, N. 2022; 45: S256-S258

  View details for DOI 10.2337/dc22-Sdis

  View details for Web of Science ID 000905201100021

  View details for PubMedID 34964863

• Adding glycemic and physical activity metrics to a multimodal algorithm-enabled decision-support tool for type 1 diabetes care: Keys to implementation and opportunities. Frontiers in endocrinology Zaharieva, D. P., Senanayake, R., Brown, C., Watkins, B., Loving, G., Prahalad, P., Ferstad, J. O., Guestrin, C., Fox, E. B., Maahs, D. M., Scheinker, D. 2022; 13: 1096325

  Abstract

  Algorithm-enabled patient prioritization and remote patient monitoring (RPM) have been used to improve clinical workflows at Stanford and have been associated with improved glucose time-in-range in newly diagnosed youth with type 1 diabetes (T1D). This novel algorithm-enabled care model currently integrates continuous glucose monitoring (CGM) data to prioritize patients for weekly reviews by the clinical diabetes team. The use of additional data may help clinical teams make more informed decisions around T1D management. Regular exercise and physical activity are essential to increasing cardiovascular fitness, increasing insulin sensitivity, and improving overall well-being of youth and adults with T1D. However, exercise can lead to fluctuations in glycemia during and after the activity. Future iterations of the care model will integrate physical activity metrics (e.g., heart rate and step count) and physical activity flags to help identify patients whose needs are not fully captured by CGM data. Our aim is to help healthcare professionals improve patient care with a better integration of CGM and physical activity data. We hypothesize that incorporating exercise data into the current CGM-based care model will produce specific, clinically relevant information such as identifying whether patients are meeting exercise guidelines. This work provides an overview of the essential steps of integrating exercise data into an RPM program and the most promising opportunities for the use of these data.

  View details for DOI 10.3389/fendo.2022.1096325

  View details for PubMedID 36714600

• Overcoming Barriers to Diabetes Technology in Youth with Type 1 Diabetes and Public Insurance: Cases and Call to Action. Case reports in endocrinology Lee, M. Y., Tanenbaum, M. L., Maahs, D. M., Prahalad, P. 2022; 2022: 9911736

  Abstract

  Advancements in diabetes technology such as continuous glucose monitoring (CGM), insulin pumps, and automated insulin delivery provide opportunities to improve glycemic control for youth with type 1 diabetes (T1D). However, diabetes technology use is lower in youth on public insurance, and this technology use gap is widening in the US. There is a significant need to develop effective interventions and policies to promote equitable care. The dual purpose of this case series is as follows: (1) describe success stories of the CGM Time in Range Program (CGM TIPs), which removed barriers for initiating CGM and provided asynchronous remote glucose monitoring for youth on public insurance, and (2) advocate for improving CGM coverage by public insurance. We describe a series of six youths with T1D and public insurance who obtained and sustained use of CGM with assistance from the program. Three youths had improved engagement with the care team while on CGM and the remote monitoring protocol, and three youths were able to leverage sustained CGM wear to obtain insurance coverage for automated insulin delivery systems. CGM TIPs helped these youths achieve lower hemoglobin A1c and improved time in range (TIR). Despite the successes, expansion of CGM TIPs is limited by stringent barriers for CGM approval and difficult postapproval patient workflows to receive shipments. These cases highlight the potential for combining diabetes technology and asynchronous remote monitoring to support continued use and provide education to improve glycemic control for youth with T1D on public insurance and the need to reduce barriers for obtaining CGM coverage by public insurance.

  View details for DOI 10.1155/2022/9911736

  View details for PubMedID 35273814

• Novel Pathogenic de novo INS p.T97P Variant Presenting with Severe Neonatal DKA. Endocrinology Lal, R. A., Moeller, H. P., Thomson, E. A., Horton, T. M., Lee, S., Freeman, R., Prahalad, P., Poon, A. S., Annes, J. P. 2021

  Abstract

  Pathogenic INS gene mutations are causative for Mutant INS-gene-induced Diabetes of Youth (MIDY). We characterize a novel de novo heterozygous INS gene mutation (c.289A>C, p.T97P) that presented in an autoantibody-negative 5-month-old male infant with severe diabetic ketoacidosis. In silico pathogenicity prediction tools provided contradictory interpretations, while structural modeling indicated a deleterious effect on proinsulin folding. Transfection of wildtype and INS p.T97P expression and luciferase reporter constructs demonstrated elevated intracellular mutant proinsulin levels and dramatically impaired proinsulin/insulin and luciferase secretion. Notably, proteasome inhibition partially and selectively rescued INS p.T97P-derived luciferase secretion. Additionally, expression of INS p.T97P caused increased intracellular proinsulin aggregate formation and XBP-1s protein levels, consistent with induction of endoplasmic reticulum stress. We conclude that INS p.T97P is a newly identified pathogenic A-chain variant that is causative for MIDY via disruption of proinsulin folding and processing with induction of the endoplasmic reticulum stress response.

  View details for DOI 10.1210/endocr/bqab246

  View details for PubMedID 34888628

• Addressing type 1 diabetes health inequities in the United States: Approaches from the T1D Exchange QI Collaborative. Journal of diabetes Ebekozien, O., Mungmode, A., Odugbesan, O., Majidi, S., Prahalad, P., Noor, N., Rioles, N., Agarwal, S., Weinstock, R. S., Rapaport, R., Kamboj, M., T1DX-QI Collaborative 2021

  View details for DOI 10.1111/1753-0407.13235

  View details for PubMedID 34874109

• T1D exchange quality improvement collaborative: Accelerating change through benchmarking and improvement science for people with type 1 diabetes. Journal of diabetes Prahalad, P., Rioles, N., Noor, N., Rapaport, R., Weinstock, R. S., Ebekozien, O., T1DX-QI Collaborative 2021

  View details for DOI 10.1111/1753-0407.13234

  View details for PubMedID 34854232

• Teamwork, Targets, Technology, and Tight Control in Newly Diagnosed Type 1 Diabetes: Pilot 4T Study. The Journal of clinical endocrinology and metabolism Prahalad, P., Ding, V. Y., Zaharieva, D. P., Addala, A., Johari, R., Scheinker, D., Desai, M., Hood, K., Maahs, D. M. 2021

  Abstract

  CONTEXT: Youth with type 1 diabetes (T1D) do not meet hemoglobin A1c (HbA1c) targets.OBJECTIVE: To assess HbA1c outcomes in children with new onset T1D enrolled in the Teamwork, Targets, Technology and Tight Control (4T) Study.METHOD: HbA1c levels were compared between the 4T and Historical cohorts. HbA1c differences between cohorts were estimated using locally estimated scatter plot smoothing (LOESS). The change from nadir HbA1c (month 4) to 12 months post-diagnosis was estimated by cohort using a piecewise mixed effects regression model accounting for age at diagnosis, sex, ethnicity, and insurance type.SETTING AND PARTICIPANTS: We recruited 135 youth with newly diagnosed T1D at Stanford Children's Health.INTERVENTION: Starting July 2018, all youth within the first month of T1D diagnosis were offered continuous glucose monitoring (CGM) initiation and remote CGM data review was added in March 2019.MAIN OUTCOME MEASURE: HbA1c.RESULTS: HbA1c at 6, 9, and 12 months post-diagnosis was lower in the 4T cohort than in the Historic cohort (-0.54%, -0.52%, and -0.58%, respectively). Within the 4T cohort, HbA1c at 6, 9, and 12 months post-diagnosis was lower in those patients with Remote Monitoring than those without (-0.14%, -0.18%, -0.14%, respectively). Multivariable regression analysis showed that the 4T cohort experienced a significantly lower increase in HbA1c between months 4 and 12 (p < 0.001).CONCLUSIONS: A technology-enabled team-based approach to intensified new onset education involving target setting, CGM initiation, and remote data review significantly decreased HbA1c in youth with T1D 12 months post-diagnosis.

  View details for DOI 10.1210/clinem/dgab859

  View details for PubMedID 34850024

• Continuous Ketone Monitoring Consensus Report 2021. Journal of diabetes science and technology Nguyen, K. T., Xu, N. Y., Zhang, J. Y., Shang, T., Basu, A., Bergenstal, R. M., Castorino, K., Chen, K. Y., Kerr, D., Koliwad, S. K., Laffel, L. M., Mathioudakis, N., Midyett, L. K., Miller, J. D., Nichols, J. H., Pasquel, F. J., Prahalad, P., Prausnitz, M. R., Seley, J. J., Sherr, J. L., Spanakis, E. K., Umpierrez, G. E., Wallia, A., Klonoff, D. C. 2021: 19322968211042656

  Abstract

  This article is the work product of the Continuous Ketone Monitoring Consensus Panel, which was organized by Diabetes Technology Society and met virtually on April 20, 2021. The panel consisted of 20 US-based experts in the use of diabetes technology, representing adult endocrinology, pediatric endocrinology, advanced practice nursing, diabetes care and education, clinical chemistry, and bioengineering. The panelists were from universities, hospitals, freestanding research institutes, government, and private practice. Panelists reviewed the medical literature pertaining to ten topics: (1) physiology of ketone production, (2) measurement of ketones, (3) performance of the first continuous ketone monitor (CKM) reported to be used in human trials, (4) demographics and epidemiology of diabetic ketoacidosis (DKA), (5) atypical hyperketonemia, (6) prevention of DKA, (7) non-DKA states of fasting ketonemia and ketonuria, (8) potential integration of CKMs with pumps and automated insulin delivery systems to prevent DKA, (9) clinical trials of CKMs, and (10) the future of CKMs. The panelists summarized the medical literature for each of the ten topics in this report. They also developed 30 conclusions (amounting to three conclusions for each topic) about CKMs and voted unanimously to adopt the 30 conclusions. This report is intended to support the development of safe and effective continuous ketone monitoring and to apply this technology in ways that will benefit people with diabetes.

  View details for DOI 10.1177/19322968211042656

  View details for PubMedID 34605694

• Population-level management of Type 1 diabetes via continuous glucose monitoring and algorithm-enabled patient prioritization: Precision health meets population health. Pediatric diabetes Ferstad, J. O., Vallon, J. J., Jun, D., Gu, A., Vitko, A., Morales, D. P., Leverenz, J., Lee, M. Y., Leverenz, B., Vasilakis, C., Osmanlliu, E., Prahalad, P., Maahs, D. M., Johari, R., Scheinker, D. 2021

  Abstract

  OBJECTIVE: To develop and scale algorithm-enabled patient prioritization to improve population-level management of type 1 diabetes (T1D) in a pediatric clinic with fixed resources, using telemedicine and remote monitoring of patients via continuous glucose monitor (CGM) data review.RESEARCH DESIGN AND METHODS: We adapted consensus glucose targets for T1D patients using CGM to identify interpretable clinical criteria to prioritize patients for weekly provider review. The criteria were constructed to manage the number of patients reviewed weekly and identify patients who most needed provider contact. We developed an interactive dashboard to display CGM data relevant for the patients prioritized for review.RESULTS: The introduction of the new criteria and interactive dashboard was associated with a 60% reduction in the mean time spent by diabetes team members who remotely and asynchronously reviewed patient data and contacted patients, from 3.2±0.20 to 1.3±0.24minutes per patient per week. Given fixed resources for review, this corresponded to an estimated 147% increase in weekly clinic capacity. Patients who qualified for and received remote review (n=58) have associated 8.8 percentage points (pp) (95% CI=0.6-16.9pp) greater time-in-range (70-180mg/dL) glucoses compared to 25 control patients who did not qualify at twelve months after T1D onset.CONCLUSIONS: An algorithm-enabled prioritization of T1D patients with CGM for asynchronous remote review reduced provider time spent per patient and was associated with improved time-in-range. This article is protected by copyright. All rights reserved.

  View details for DOI 10.1111/pedi.13256

  View details for PubMedID 34374183

• T1D Exchange Quality Improvement Collaborative: A Learning Health System to Improve Outcomes for All People With Type 1 Diabetes. Clinical diabetes : a publication of the American Diabetes Association Weinstock, R. S., Prahalad, P., Rioles, N., Ebekozien, O. 2021; 39 (3): 251-255

  View details for DOI 10.2337/cd21-0032

  View details for PubMedID 34421199

• Multi-Clinic Quality Improvement Initiative Increases Continuous Glucose Monitoring Use Among Adolescents and Young Adults With Type 1 Diabetes. Clinical diabetes : a publication of the American Diabetes Association Prahalad, P., Ebekozien, O., Alonso, G. T., Clements, M., Corathers, S., DeSalvo, D., Desimone, M., Lee, J. M., Lorincz, I., McDonough, R., Majidi, S., Odugbesan, O., Obrynba, K., Rioles, N., Kamboj, M., Jones, N. Y., Maahs, D. M. 2021; 39 (3): 264-271

  Abstract

  Continuous glucose monitoring (CGM) use is associated with improved A1C outcomes and quality of life in adolescents and young adults with diabetes; however, CGM uptake is low. This article reports on a quality improvement (QI) initiative of the T1D Exchange Quality Improvement Collaborative to increase CGM use among patients in this age-group. Ten centers participated in developing a key driver diagram and center-specific interventions that resulted in an increase in CGM use from 34 to 55% in adolescents and young adults over 19-22 months. Sites that performed QI tests of change and documented their interventions had the highest increases in CGM uptake, demonstrating that QI methodology and sharing of learnings can increase CGM uptake.

  View details for DOI 10.2337/cd21-0026

  View details for PubMedID 34421201

• INCREASING CAPACITY WITH FIXED RESOURCES THROUGH AUTOMATION AND TASK DELEGATION AT A TERTIARY PEDIATRIC TYPE 1 DIABETES CLINIC Vitko, A., Osmanlliu, E., Johari, R., Prahalad, P., Maahs, D., Scheinker, D. MARY ANN LIEBERT, INC. 2021: A139-A140

  View details for Web of Science ID 000656638700350

• OPTIMIZING WORKFLOWS TO CLOSE DISPARITIES IN TELEHEALTH USE Prahalad, P., Leverenz, B., Freeman, A., Grover, M., Shah, S., Conrad, B., Stafford, D., Maahs, D. MARY ANN LIEBERT, INC. 2021: A43-A44

  View details for Web of Science ID 000656638700121

• Improved individual and population-level HbA1c estimation using CGM data and patient characteristics. Journal of diabetes and its complications Grossman, J., Ward, A., Crandell, J. L., Prahalad, P., Maahs, D. M., Scheinker, D. 2021: 107950

  Abstract

  Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.

  View details for DOI 10.1016/j.jdiacomp.2021.107950

  View details for PubMedID 34127370

• Adoption of Telemedicine for Type 1 Diabetes Care During the COVID-19 Pandemic. Diabetes technology & therapeutics Lee, J., Carlson, E., Albanese-O'Neill, A., Demeterco Berggren, C., Corathers, S., Vendrame, F., Weinstock, R. S., Prahalad, P., Alonso, G. T., Kamboj, M. K., DeSalvo, D. J., Malik, F., Izquierdo, R., Ebekozien, O. 2021

  Abstract

  BACKGROUND: We describe the utilization of telemedicine visits (video or telephone) across the T1D Exchange Quality Improvement Collaborative (T1DX-QI) during the COVID-19 pandemic. Metrics, site-level survey results, and examples of interventions conducted to support telemedicine in type 1 diabetes (T1D) are shown.METHODS: Thirteen clinics (11 pediatric, 2 adult) provided monthly telemedicine metrics between December 2019-August 2020 and 21 clinics completed a survey about their telemedicine practices.RESULTS: The proportion of telemedicine visits in T1DX-QI before the pandemic was less than 1%, rising to an average of 95.2% in April 2020 (range 52.3% to 99.5). Three sites initially used mostly telephone visits before converting to video visits. By August 2020, the proportion of telemedicine visits decreased to an average of 45% across T1DX-QI (range 10% to 86.6%). The majority of clinics (62%) performed both video and telephone visits; Zoom was the most popular video platform used. Over 95% of clinics reported using CareLink, Clarity, Glooko and/or t:connect to view device data, with only one center reporting automated data upload into the electronic medical record. The majority of centers had multidisciplinary teams participating in the video visits. All sites reported reimbursement for video visits, and 95% of sites reported coverage for telephone visits early on in the pandemic.CONCLUSIONS: There was rapid adoption of telemedicine in T1DX-QI during the COVID-19 pandemic. Future insurance reimbursement for telemedicine visits and the ideal ratio of telemedicine to in-person visits in T1D care remain to be determined.

  View details for DOI 10.1089/dia.2021.0080

  View details for PubMedID 33851873

• Lower HbA1c targets are associated with better metabolic control. European journal of pediatrics Van Loocke, M. n., Battelino, T. n., Tittel, S. R., Prahalad, P. n., Goksen, D. n., Davis, E. n., Casteels, K. n. 2021

  Abstract

  Previous studies have suggested that clear HbA1c target setting by the diabetes team is associated with HbA1c outcomes in adolescents. The aim of this study was to evaluate whether this finding is consistent in a larger cohort of children from centers participating in the SWEET international diabetes registry. A questionnaire was sent out to 76 SWEET centers, of which responses from 53 pediatric centers were included (70%). Descriptive outcomes were presented as median with lower and upper quartile. The association between the centers' target HbA1c and mean outcome HbA1c was calculated using linear regression adjusted for age, diabetes duration, sex, and gross domestic product. Median age of the children in the studied centers (n = 35,483) was 13.3 [12.6-14.6] years (49% female). Of the 53 centers, 13.2% reported an HbA1c target between 6.0 and 6.5%, 32.1% had a target between ≥ 6.0 and 7.0%, 18.9% between ≥ 7.0 and 7.5%, and 3.8% between ≥ 7.5 and 8.5%. No specific target value was reported by 32.1% of all centers. Median HbA1c across all centers was 7.9 [7.6-8.3] %. Adjusted regression analysis showed a positive association between HbA1c outcome and target HbA1c (p = 0.005).Conclusions: This international study demonstrated that a lower target for HbA1c was associated with better metabolic control. It is unclear whether low target values result in better metabolic control, or lower HbA1c values actually result in more ambitious target values. This target setting could contribute to the differences in HbA1c values between centers and could be an approach for improving metabolic outcomes. What is Known: • Target setting of HbA1c is important in children and adolescents with type 1 diabetes. • The optimal therapeutic approach of children with type 1 diabetes requires a trained multidisciplinary team. What is New: • Lower HbA1c targets are associated with better metabolic control. • No associations between the composition of the diabetes teams and metabolic control could be demonstrated.

  View details for DOI 10.1007/s00431-020-03891-2

  View details for PubMedID 33415466

• Hemoglobin A1c Trajectories in the First 18 Months After Diabetes Diagnosis in the SWEET Diabetes Registry. Pediatric diabetes Prahalad, P., Schwandt, A., Besancon, S., Mohan, M., Obermannova, B., Kershaw, M., Bonfanti, R., Lyckå, A. P., Hanas, R., Casteels, K. 2021

  Abstract

  A majority of youth with type 1 diabetes do not meet recommended hemoglobin A1c (HbA1c) targets. The SWEET diabetes registry is a multi-national registry of youth with diabetes. We used data from this registry to identify characteristics associated with glycemic control.Patients in the SWEET diabetes registry with at least one HbA1c value within 10 days of diagnosis and 3 follow up measurements in the first 18 months of diagnosis were included (~10% of the SWEET diabetes registry). Locally weighted scatterplot smoothing was used to generate curves of HbA1c. Wilcoxon, Kruskal-Wallis, or χ2-tests were used to calculate differences between groups.The mean HbA1c of youth in the SWEET diabetes registry is highest at diagnosis and lowest between months 4 and 5 post-diabetes diagnosis. HbA1c continues to increase steadily through the first 18 months of diagnosis. There are no differences in HbA1c trajectories based on sex or use of diabetes technology. Youth in North America/Australia/New Zealand had the highest HbA1c throughout the first 18 months of diagnosis. The trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. Youth from countries with the highest gross domestic product (GDP) had the highest HbA1c throughout the first 18 months of diagnosis.In this subset of patients, the trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. High GDP and high use of technology did not seem to protect from a higher trajectory. This article is protected by copyright. All rights reserved.

  View details for DOI 10.1111/pedi.13278

  View details for PubMedID 34779090

• Clinically serious hypoglycemia is rare and not associated with time-in-range in youth with new-onset type 1 diabetes. The Journal of clinical endocrinology and metabolism Addala, A., Zaharieva, D. P., Gu, A. J., Prahalad, P., Scheinker, D., Buckingham, B., Hood, K. K., Maahs, D. M. 2021

  Abstract

  Early initiation of continuous glucose monitoring (CGM) is advocated for youth with type 1 diabetes (T1D). Data to guide CGM use on time-in-range (TIR), hypoglycemia, and the role of partial clinical remission (PCR) are limited. Our aims were to assess whether: 1) an association between increased TIR and hypoglycemia exists, and 2) how time in hypoglycemia varies by PCR status.We analyzed 80 youth who were started on CGM shortly after T1D diagnosis and were followed for up to 1-year post-diagnosis. TIR and hypoglycemia rates were determined by CGM data and retrospectively analyzed. PCR was defined as (visit-HbA1c)+(4*units/kg/day) <9.Youth were started on CGM 8.0 (IQR 6.0-13.0) days post-diagnosis. Time spent <70mg/dL remained low despite changes in TIR (highest TIR 74.6±16.7%, 2.4±2.4% hypoglycemia at 1 month post-diagnosis; lowest TIR 61.3±20.3%, 2.1±2.7% hypoglycemia at 12 months post-diagnosis). No events of severe hypoglycemia occurred. Hypoglycemia was rare and there was minimal difference for PCR versus non-PCR youth (54-70mg/dL: 1.8% vs 1.2%, p=0.04; <54mg/dL: 0.3% vs 0.3%, p=0.55). Approximately 50% of the time spent in hypoglycemia was in the 65-70mg/dL range.As TIR gradually decreased over 12 months post-diagnosis, hypoglycemia was limited with no episodes of severe hypoglycemia. Hypoglycemia rates did not vary in a clinically meaningful manner by PCR status. With CGM being started earlier, consideration needs to be given to modifying CGM hypoglycemia education, including alarm settings. These data support a trial in the year post-diagnosis to determine alarm thresholds for youth who wear CGM.

  View details for DOI 10.1210/clinem/dgab522

  View details for PubMedID 34265059

• Pediatric Subspecialty Adoption of Telemedicine Amidst the COVID-19 Pandemic: An Early Descriptive Analysis. Frontiers in pediatrics Xie, J., Prahalad, P., Lee, T. C., Stevens, L. A., Meister, K. D. 2021; 9: 648631

  Abstract

  Telemedicine has rapidly expanded in many aspects of pediatric care as a result of the COVID-19 pandemic. However, little is known about what factors may make pediatric subspeciality care more apt to long-term adoption of telemedicine. To better delineate the potential patient, provider, and subspecialty factors which may influence subspecialty adoption of telemedicine, we reviewed our institutional experience. The top 36 pediatric subspecialties at Stanford Children's Health were classified into high telemedicine adopters, low telemedicine adopters, and telemedicine reverters. Distance from the patient's home, primary language, insurance type, institutional factors such as wait times, and subspecialty-specific clinical differences correlated with differing patterns of telemedicine adoption. With greater awareness of these factors, institutions and providers can better guide patients in determining which care may be best suited for telemedicine and develop sustainable long-term telemedicine programming.

  View details for DOI 10.3389/fped.2021.648631

  View details for PubMedID 33928058

• "I was ready for it at the beginning": Parent experiences with early introduction of continuous glucose monitoring following their child's Type 1 diabetes diagnosis. Diabetic medicine : a journal of the British Diabetic Association Tanenbaum, M. L., Zaharieva, D. P., Addala, A. n., Ngo, J. n., Prahalad, P. n., Leverenz, B. n., New, C. n., Maahs, D. M., Hood, K. K. 2021: e14567

  Abstract

  To capture the experience of parents of youth with recent onset Type 1 diabetes who initiated use of continuous glucose monitoring (CGM) technology soon after diagnosis, which is a new practice.Focus groups and individual interviews were conducted with parents of youth with Type 1 diabetes who had early initiation of CGM as part of a new clinical protocol. Interviewers used a semi-structured interview guide to elicit feedback and experiences with starting CGM within 30 days of diagnosis, and the benefits and barriers they experienced when adjusting to this technology. Groups and interviews were audio-recorded, transcribed, and analyzed using content analysis.Participants were 16 parents (age 44.13±8.43 years; 75% female; 56.25% non-Hispanic White) of youth (age 12.38±4.15 years; 50% female; 50% non-Hispanic White; diabetes duration 10.35±3.89 months) who initiated CGM 11.31±7.33 days after diabetes diagnosis. Overall, parents reported high levels of satisfaction with starting CGM within a month of diagnosis and described a high level of reliance on the technology to help manage their child's diabetes. All participants recommended early CGM initiation for future families and were committed to continue using the technology for the foreseeable future, provided that insurance covered it.Parents experienced CGM initiation shortly after their child's Type 1 diabetes diagnosis as a highly beneficial and essential part of adjusting to living with diabetes.

  View details for DOI 10.1111/dme.14567

  View details for PubMedID 33772862

• Thiamine-Responsive Megaloblastic Anemia-Related Diabetes: Long-Term Clinical Outcomes in 23 Pediatric Patients From the DPV and SWEET Registries. Canadian journal of diabetes Warncke, K., Prinz, N., Iotova, V., Dunstheimer, D., Datz, N., Karges, B., Jali, M. V., Linsenmeyer, D., Olsen, B. S., Seiwald, M., Prahalad, P., de Sousat, G., Pacaud, D., SWEET and DPV Study Groups 2020

  Abstract

  OBJECTIVES: To describe clinical presentation and long-term outcomes in a large cohort of children diagnosed with thiamine-responsive megaloblastic anemia (TRMA)-related diabetes.METHODS: Data from the Diabetes Patienten Verlaufsdokumentation (DPV) and Better control in Pediatric and Adolescent diabeteS: Working to crEate CEnTers of Reference (SWEET) registries were used to identify cases. Complementary information was collected through a chart review of each case. Descriptive analyses with medians and interquartile ranges and numbers (proportions) were tabulated.RESULTS: We identified 23 cases (52% male) in the 2 registries. Eighteen (78%) had genetic confirmation of TRMA. Median age at diabetes onset was 1.4 (quartiles 0.8 to 3.6) years and median age at initiation of thiamine treatment was 5.9 (2.4 to 12.4) years. At their most recent visit, patients' median age was 14.3 (8.1 to 17.5) years, glycated hemoglobin level was 6.9% (6.1% to 7.9%), insulin dose was 0.9 (0.4 to 1.2) units/kg per day and thiamine dose was 200 (100 to 300) mg/day. Three patients were not treated with insulin or antidiabetic drugs. There was no difference in diabetes outcomes in patients with initiation of thiamine ≤1 year after diabetes onset compared to patients with initiation of thiamine >1 year after diabetes onset.CONCLUSIONS: This is the longest case series of pediatric TRMA-related diabetes reported to date. Diabetes onset often occurs several years before initiation of thiamine supplementation. Early initiation of thiamine (within 1 year of diabetes onset) was not linked to improved diabetes outcome. However, the role of thiamine in pancreatic function needs further assessment. Patients with TRMA-related diabetes maintained good glycemic control even after 9 years (median) of follow up.

  View details for DOI 10.1016/j.jcjd.2020.11.006

  View details for PubMedID 33388275

• Multimethod, multidataset analysis reveals paradoxical relationships between sociodemographic factors, Hispanic ethnicity and diabetes. BMJ open diabetes research & care Knight, G. M., Spencer-Bonilla, G., Maahs, D. M., Blum, M. R., Valencia, A., Zuma, B. Z., Prahalad, P., Sarraju, A., Rodriguez, F., Scheinker, D. 2020; 8 (2)

  Abstract

  INTRODUCTION: Population-level and individual-level analyses have strengths and limitations as do 'blackbox' machine learning (ML) and traditional, interpretable models. Diabetes mellitus (DM) is a leading cause of morbidity and mortality with complex sociodemographic dynamics that have not been analyzed in a way that leverages population-level and individual-level data as well as traditional epidemiological and ML models. We analyzed complementary individual-level and county-level datasets with both regression and ML methods to study the association between sociodemographic factors and DM.RESEARCH DESIGN AND METHODS: County-level DM prevalence, demographics, and socioeconomic status (SES) factors were extracted from the 2018 Robert Wood Johnson Foundation County Health Rankings and merged with US Census data. Analogous individual-level data were extracted from 2007 to 2016 National Health and Nutrition Examination Survey studies and corrected for oversampling with survey weights. We used multivariate linear (logistic) regression and ML regression (classification) models for county (individual) data. Regression and ML models were compared using measures of explained variation (area under the receiver operating characteristic curve (AUC) and R2).RESULTS: Among the 3138 counties assessed, the mean DM prevalence was 11.4% (range: 3.0%-21.1%). Among the 12824 individuals assessed, 1688 met DM criteria (13.2% unweighted; 10.2% weighted). Age, gender, race/ethnicity, income, and education were associated with DM at the county and individual levels. Higher county Hispanic ethnic density was negatively associated with county DM prevalence, while Hispanic ethnicity was positively associated with individual DM. ML outperformed regression in both datasets (mean R2 of 0.679 vs 0.610, respectively (p<0.001) for county-level data; mean AUC of 0.737 vs 0.727 (p<0.0427) for individual-level data).CONCLUSIONS: Hispanic individuals are at higher risk of DM, while counties with larger Hispanic populations have lower DM prevalence. Analyses of population-level and individual-level data with multiple methods may afford more confidence in results and identify areas for further study.

  View details for DOI 10.1136/bmjdrc-2020-001725

  View details for PubMedID 33229378

• Uninterrupted Continuous Glucose Monitoring Access is Associated with a Decrease in HbA1c in Youth with Type 1 Diabetes and Public Insurance. Pediatric diabetes Addala, A., Maahs, D. M., Scheinker, D., Chertow, S., Leverenz, B., Prahalad, P. 2020

  Abstract

  OBJECTIVE: Continuous glucose monitor (CGM) use is associated with improved glucose control. We describe the effect of continued and interrupted CGM use on hemoglobin A1c (HbA1c) in youth with public insurance.METHODS: We reviewed 956 visits from 264 youth with type 1 diabetes (T1D) and public insurance. Demographic data, HbA1c and two-week CGM data were collected. Youth were classified as never user, consistent user, insurance discontinuer, and self-discontinuer. Visits were categorized as never-user visit, visit before CGM start, visit after CGM start, visit with continued CGM use, visit with initial loss of CGM, visit with continued loss of CGM, and visit where CGM is regained after loss. Multivariate regression adjusting for age, sex, race, diabetes duration, initial HbA1c, and BMI were used to calculate adjusted mean and delta HbA1c.RESULTS: Adjusted mean HbA1c was lowest for the consistent user group (HbA1c 8.6%;[95%CI 7.9,9.3]). Delta HbA1c (calculated from visit before CGM start) was lower for visit after CGM start (-0.39%;[95%CI -0.78,-0.02]) and visit with continued CGM use (-0.29%;[95%CI -0.61,0.02]) whereas it was higher for visit with initial loss of CGM (0.40%;[95%CI -0.06,0.86]), visit with continued loss of CGM (0.46%;[95%CI 0.06,0.85]), and visit where CGM is regained after loss (0.57%;[95%CI 0.06,1.10]).CONCLUSIONS: Youth with public insurance using CGM have improved HbA1c, but only when CGM use is uninterrupted. Interruptions in use, primarily due to gaps in insurance coverage of CGM, were associated with increased HbA1c. These data support both initial and ongoing coverage of CGM for youth with T1D and public insurance. This article is protected by copyright. All rights reserved.

  View details for DOI 10.1111/pedi.13082

  View details for PubMedID 32681582

• Effect of Continuous Glucose Monitoring on Glycemic Control in Adolescents and Young Adults With Type 1 Diabetes: A Randomized Clinical Trial. JAMA Laffel, L. M., Kanapka, L. G., Beck, R. W., Bergamo, K., Clements, M. A., Criego, A., DeSalvo, D. J., Goland, R., Hood, K., Liljenquist, D., Messer, L. H., Monzavi, R., Mouse, T. J., Prahalad, P., Sherr, J., Simmons, J. H., Wadwa, R. P., Weinstock, R. S., Willi, S. M., Miller, K. M., CGM Intervention in Teens and Young Adults with T1D (CITY) Study Group, CDE10 2020; 323 (23): 2388–96

  Abstract

  Importance: Adolescents and young adults with type 1 diabetes exhibit the worst glycemic control among individuals with type 1 diabetes across the lifespan. Although continuous glucose monitoring (CGM) has been shown to improve glycemic control in adults, its benefit in adolescents and young adults has not been demonstrated.Objective: To determine the effect of CGM on glycemic control in adolescents and young adults with type 1 diabetes.Design, Setting, and Participants: Randomized clinical trial conducted between January 2018 and May 2019 at 14 endocrinology practices in the US including 153 individuals aged 14 to 24 years with type 1 diabetes and screening hemoglobin A1c (HbA1c) of 7.5% to 10.9%.Interventions: Participants were randomized 1:1 to undergo CGM (CGM group; n=74) or usual care using a blood glucose meter for glucose monitoring (blood glucose monitoring [BGM] group; n=79).Main Outcomes and Measures: The primary outcome was change in HbA1c from baseline to 26 weeks. There were 20 secondary outcomes, including additional HbA1c outcomes, CGM glucose metrics, and patient-reported outcomes with adjustment for multiple comparisons to control for the false discovery rate.Results: Among the 153 participants (mean [SD] age, 17 [3] years; 76 [50%] were female; mean [SD] diabetes duration, 9 [5] years), 142 (93%) completed the study. In the CGM group, 68% of participants used CGM at least 5 days per week in month 6. Mean HbA1c was 8.9% at baseline and 8.5% at 26 weeks in the CGM group and 8.9% at both baseline and 26 weeks in the BGM group (adjusted between-group difference, -0.37% [95% CI, -0.66% to -0.08%]; P=.01). Of 20 prespecified secondary outcomes, there were statistically significant differences in 3 of 7 binary HbA1c outcomes, 8 of 9 CGM metrics, and 1 of 4 patient-reported outcomes. The most commonly reported adverse events in the CGM and BGM groups were severe hypoglycemia (3 participants with an event in the CGM group and 2 in the BGM group), hyperglycemia/ketosis (1 participant with an event in CGM group and 4 in the BGM group), and diabetic ketoacidosis (3 participants with an event in the CGM group and 1 in the BGM group).Conclusions and Relevance: Among adolescents and young adults with type 1 diabetes, continuous glucose monitoring compared with standard blood glucose monitoring resulted in a small but statistically significant improvement in glycemic control over 26 weeks. Further research is needed to understand the clinical importance of the findings.Trial Registration: ClinicalTrials.gov Identifier: NCT03263494.

  View details for DOI 10.1001/jama.2020.6940

  View details for PubMedID 32543683

• Novel De Novo INS P.T97P Variant Presenting with Severe Neonatal DKA Lal, R., Moeller, H. P., Freeman, R., Prahalad, P., Annes, J. P. AMER DIABETES ASSOC. 2020

  View details for DOI 10.2337/db20-1801-P

  View details for Web of Science ID 000554509804067

• A Telemedicine-CGM Recommendation System for Personalized Population Health Management Vallon, J., Ward, A. T., Prahalad, P., Hood, K. K., Maahs, D. M., Scheinker, D. AMER DIABETES ASSOC. 2020

  View details for DOI 10.2337/db20-1185-P

  View details for Web of Science ID 000554509802428

• Early Introduction of Continuous Glucose Monitoring Is Well Accepted by Youth and Parents Addala, A., Hanes, S., Zaharieva, D., New, C., Prahalad, P., Maahs, D. M., Hood, K. K., Tanenbaum, M. L. AMER DIABETES ASSOC. 2020

  View details for DOI 10.2337/db20-159-LB

  View details for Web of Science ID 000554509800310

• Newly Diagnosed Pediatric Patients with Type 1 Diabetes Show Steady Decline in Glucose Time-in-Range (TIR) over 1 Year: Pilot Study Zaharieva, D., Prahalad, P., Addala, A., Scheinker, D., Desai, M., Hood, K. K., Leverenz, B., Maahs, D. M. AMER DIABETES ASSOC. 2020

  View details for DOI 10.2337/db20-1295-P

  View details for Web of Science ID 000554509803069

• Clinically Significant Hypoglycemia Is Rare in Youth with T1D during Partial Clinical Remission Addala, A., Gu, A., Zaharieva, D., Prahalad, P., Buckingham, B. A., Scheinker, D., Maahs, D. M. AMER DIABETES ASSOC. 2020

  View details for DOI 10.2337/db20-1294-P

  View details for Web of Science ID 000554509803068

• The Association between Time-in-Range, Mean Glucose, and Incidence of Hypoglycemia in Youth with Newly Diagnosed T1D Gu, A., Prahalad, P., Maahs, D. M., Addala, A., Scheinker, D. AMER DIABETES ASSOC. 2020

  View details for DOI 10.2337/db20-1289-P

  View details for Web of Science ID 000554509803063

• Early CGM Initiation Improves HbA1c in T1D Youth over the First 15 Months Prahalad, P., Ding, V., Addala, A., New, C., Conrad, B. P., Chmielewski, A., Geels, E., Leverenz, J., Martinez-Singh, A., Sagan, P., Senaldi, J., Freeman, A., Scheinker, D., Hood, K. K., Desai, M., Maahs, D. M. AMER DIABETES ASSOC. 2020

  View details for DOI 10.2337/db20-1297-P

  View details for Web of Science ID 000554509803071

• UNMET TECHNOLOGY NEEDS IN MINORITY PEOPLE IN NORTH AND SOUTH AMERICA Prahalad, P. MARY ANN LIEBERT, INC. 2020: A10

  View details for Web of Science ID 000514025300046

• HBA1C TARGET SETTING IS ASSOCIATED WITH METABOLIC CONTROL Van Loocke, M., Battelino, T., Tittel, S., Prahalad, P., Goksen, D., Davis, E., Casteels, K., T Sweet Study Grp MARY ANN LIEBERT, INC. 2020: A237

  View details for Web of Science ID 000514025300602

• Longitudinal Changes in Continuous Glucose Monitoring Use Among Individuals With Type 1 Diabetes: International Comparison in the German and Austrian DPV and U.S. T1D Exchange Registries. Diabetes care Miller, K. M., Hermann, J., Foster, N., Hofer, S. E., Rickels, M. R., Danne, T., Clements, M. A., Lilienthal, E., Maahs, D. M., Holl, R. W., T1D Exchange and DPV Registries, Weinstock, R., Izquierdo, R., Sheikh, U., Conboy, P., Bulger, J., Bzdick, S., Klingensmith, G., Banion, C., Barker, J., Cain, C., Nadeau, K., Rewers, M., Rewers, A., Slover, R., Steck, A., Wadwa, P., Zeitler, P., Alonso, G., Forlenza, G., Gerard-Gonzalez, A., Green, M., Gross, S., Majidi, S., Messer, L., Reznick-Lipina, T., Simmons, E., Thivener, K., Weber, I., Willi, S., Lipman, T., Kucheruk, O., Minnock, P., Carchidi, C., Grant, B., Olivos, D., DiMeglio, L., Hannon, T., Evans-Molina, C., Hansen, D., Pottorff, T., Woerner, S., Hildinger, M., Hufferd, R., Newnum, A., Purtlebaugh, D., Smith, L., Wendholt, K., Goland, R., Gandica, R., Williams, K., Pollack, S., Casciano, E., Hochberg, J., Uche, C., Lee, J., Gregg, B., Tan, M., Ang, L., Pop-Busui, R., Thomas, I., Dhadphale, E., Dominowski, J., Garrity, A., Leone, V., Plunkett, C., Plunkett, B., Monzavi, R., Cheung, C., Fisher, L., Kim, M., Miyazaki, B., Pitukcheewanont, P., Sandstrom, A., Austin, J., Change, N., Raymond, J., Ichihara, B., Lipton, M., Flores Garcia, J., Garg, S., Michels, A., Garcetti, R., Green, M., Gutin, R., Nadeau, K., Polsky, S., Shah, V., Voelmle, M., Myers, L., Coe, G., Demmitt, J., Garcia Reyes, Y., Giordano, D., Joshee, P., Nease, E., Nguyen, N., Wolfsdorf, J., Quinn, M., Fontanet, C., Mukherjee, S., Bethin, K., Quattrin, T., Majumdar, I., Mastrandrea, L., Gorman, E., House, A., Michalovic, S., Musial, W., Shine, B., Ahmann, A., Castle, J., Joarder, F., Aby-Daniel, D., Guttmann-Bauman, I., Klopfenstein, B., Morimoto, V., Cady, N., Fitch, R., DeFrang, D., Jahnke, K., Patoine, C., Raman, V., Foster, C., Murray, M., Brown, T., Davis, C., Slater, H., Langvardt, J., Bode, B., Boyd, J., Johnson, J., Newton, C., Ownby, J., Hosey, R., Rastogi, N., Winslett, B., Hirsch, I., DeSantis, A., Failor, R. A., Greenbaum, C., Trence, D., Trikudanathan, S., Khakpour, D., Thomson, P., Sameshima, L., Tordillos, C., Clements, M., Turpin, A., Babar, G., Broussard, J., Cernich, J., Dileepan, K., Feldt, M., Moore, W., Musick, T., Patton, S., Yan, Y., Tsai, S., Bedard, J., Elrod, A., Hester, L., Beidelschies, M., de la Garza, J., Haith, E., James, J., Ramey, E., Slover, J., Valentine, A., Watkins, D., Whisenhunt, M., Wierson, J., Wilson, D., Buckingham, B., Maahs, D., Prahalad, P., Hsu, L., Kingman, R., Tabatabai, I., Liljenquist, D., Sulik, M., Vance, C., Halford, J., Funke, C., Appiagyei-Dankah, Y., Beltz, E., Moran, K., Starkman, H., Cerame, B., Chin, D., Ebner-Lyon, L., Sabanosh, K., Silverman, L., Wagner, C., Cheruvu, S., Fox, M., Melchionne, F., Bergenstal, R., Madden, M., Martens, T., Criego, A., Powers, M., Carlson, A., Beasley, S., Olson, B., Thomas, L., McCann, K., Dunnigan, S., Ashanti, C., Simmons, J., Russell, W., Jaser, S., Kelley, J., Brendle, F., Williams, L., Savin, K., Flowers, K., Williams, G., Hamburger, E., Davis, A., Hammel, B., Cengiz, E., Tamborlane, W., Weyman, K., Van Name, M., Patel, N., Sherr, J., Tichy, E., Steffen, A., Zgorski, M., Carria, L., Finnegan, J., Duran, E., Mehta, S., Katz, M., Laffel, L., Giani, E., Snelgrove, R., Hanono, A., Commissariat, P., Griffith, J., Atkins, A., Harrington, K., Kim, K., Masclans, L., Naik, N., Ambler-Osborn, L., Schultz, A., Cohen, C., Anderson, B., McGill, J., Granados, A., Clifton, M. J., Hurst, S., Kissel, S., Recklein, C., Kruger, D., Bhan, A., Brown, T., Tassopoulos, A., Hailey, A., Remtema, H., Cushman, T., Wintergerst, K., Watson, S., Kingery, S., Rayborn, L., Rush, H., Foster, M., Deuser, A., Rodriguez-Luna, M., Eubanks, S., Rodriguez, H., Bollepalli, S., Smith, L., Shulman, D., Jorgensen, E. V., Eyth, E., Brownstein, R., Rodriguez, J., O'Bria, J., Aleppo-Kacmarek, G., Hahr, A., Molitch, M., Muayed, E., Toft, D., Fulkerson, C., Adelman, D., Massaro, E., Webb, K., Peters, A., Ruelas, V., Harmel, M., Daniels, M., Forghani, N., Flannery, T., Reh, C., Bhangoo, A., Kashmiri, H., Montgomery, K., Trinh, L., Speer, H., Lane, K., Bergenstal, R., Martens, T., Madden, M., Powers, M., Criego, A., Carlson, A., Olson, B., Beasley, S., McCann, K., Thomas, L., Miller, C., Ashanti, C., Solorzano, C. B., Puskaric, J., Benjamin, R., Adkins, D., Spruill, A., Williams, C., Tsalikian, E., Tansey, M., Bansl, N., Cabbage, J., Coffey, J., Schatz, D., Clare-Salzler, M., Cusi, K., Fudge, B., Haller, M., Meehan, C., Rohrs, H., Silverstein, J., Walker, A., Albanese-O'Niell, A., Foss, S., Adams, J., Cintron, M., Thomas, N., Gottschalk, M., Newfield, R., Hashiguchi, M., Sparling, D., Tryggested, J., Beck, J., Less, J., Weber, L., Adi, S., Gitelman, S., Sanda, S., Wong, J., McDonnell, M., Mueller, M., Izadi, Z., Mistry, S., Nelson, B., Looper, L., Frost, C., Redondo, M., Lyons, S., Klinepeter, S., Fegan-Bohm, K., Bacha, F., DeSalvo, D., Butler, A., Hilliard, M., Khetani, F., Yulatic, R., Hudson, R., Irvine, L., Zubair, S., Pace, C., Pitrello, A., Levy, W., Njoku, C., Zipf, W., Dyer, J., Lozano, R., Seiple, D., Corven, G., Jaycox, M., Wood, J., Macleish, S., Gubitosi-Klug, R., Adams, R., McGuigan, P., Casey, T., Campbell, W., Kittelsrud, J., Gupta, A., Peterson, V., Libman, I., Diaz, A., Jelley, D., Crowder, C., Greer, D., Crawford, J., Goudeau, S., Pihoker, C., Yi-Frazier, J., Kearns, S., Pascual, M., Loots, B., Beauregard, N., Rickels, M., O'Brien, S., Agarwal, S., Peleckis, A., Dalton-Bakes, C., Markmann, E., Umpierrez, G., Muir, A., Ramos, C., Behbahani, K., Dhruv, N., Gartzman, N., Nathan, B., Bellin, M., Sunni, M., Flaherty, N., Leschyshyn, J., Schmid, K., Weingartner, D., Ludwig, M., Nelson, B., Kogler, A., Bartyzal, A., Street, A., Pappenfus, B., Sweet, J., Buse, J., Young, L., Bergamo, K., Goley, A., Kirkman, M., Diner, J., Kass, A., Dezube, M., Arnold, K., Evans, T., Sellers, S., Blackman, S., Abel, K., Rasbach, L., Ali, O., Wolfgram, P., Fiallo-Sharer, R., Kramer, J., Beesley, C., Bingham-Tyson, C., Unteutsh, R., Harlan, D., Lee, M., Soyka, L., Feldman, P., Thompson, M., Gallagher-Dorval, K., Hubacz, L., Hartigan, C., Ciccarelli, C., Edelen, R., Edelen, M., Borgwadt, T., Stauffacher, K., DeGrote, K., Gruetzmacher, C., Shepperd, M., Bhargava, A., Wright, D., Fitzgerald, K., Khoo, T., Young, N., Borg, L., Stifel, K., Rail, C., Casas, L., Eidenshink, E., Huber, C., Rieder, A., Tuchscherer, A., Broadbent, M., Dolan, L., Corathers, S., Kichler, J., Sheanon, N., Baugh, H., Standiford, D., Weis, T., Fox, C., Schultz, C., Ritter, A., Vendrame, F., Blashke, C., Matheson, D., Sanders-Branca, N., Rudolph, J., Biersdorf, D., Fitch-Danielson, J., Eckerle-Mize, D., Brendle, F., Fry, J., Davis, D., Lovell, C., Hammel, B., Williams, L., Hoffman, R., Chaudhari, M., Kamboj, M., Carr, L., Casas, L., Blehm, J., Tello, A., Walter, J. A., Ward, R., Broadbent, M., Blomquist, G., Stewart, M., Cross, P., Racki, S., Sterchi, L., Gouine, D., Kiesow, B., Welch, S., Philis-Tsimikas, A., Daily, G., Chang, A., McCallum, J., Garcia, I., Vela, T., Loupasi, I., Rosal, R., Toschi, E., Middelbeek, R., Munshi, M., Slyne, C., Atakov-Castillo, A., Fox, L., Mauras, N., Wasserman, R., Damaso, L., Englert, K., Sikes, K., Ponthieux, K., Phillipson, L., Cohen, A., Gannon, G., Deeb, L., Shiver, A., Schroeder, L., Schworm, W., Graham, K., Levy, C., Lam, D., Burtman, E., Levister, C., Ogyaadu, S., Gassner, H., Duke, J., Touger, L., Newbern, D., Hoekstra, F., Harwood, K., Prasad, V., Daguanno, J., Pratley, R., Corbin, K., Wright, M., Nagel, S., Water, N., Ghere, M., Whitaker, K., Heptulla, R., Katikaneni, R., Johnson-Newell, D., Crandall, J., Powell, D., Anghel, V., Ghanny, S., Aisenberg, J., Chartoff, A., Sivitz, J., Mathus, S., Cospito, T., Thailkill, K., Fowlkes, J., Kalaitzoglou, E., Morales Pozzo, A., Edwards, K. 2020; 43 (1): e1–e2

  View details for DOI 10.2337/dc19-1214

  View details for PubMedID 31672703

• Improving Clinical Outcomes in Newly Diagnosed Pediatric Type 1 Diabetes: Teamwork, Targets, Technology, and Tight Control-The 4T Study. Frontiers in endocrinology Prahalad, P. n., Zaharieva, D. P., Addala, A. n., New, C. n., Scheinker, D. n., Desai, M. n., Hood, K. K., Maahs, D. M. 2020; 11: 360

  Abstract

  Many youth with type 1 diabetes (T1D) do not achieve hemoglobin A1c (HbA1c) targets. The mean HbA1c of youth in the USA is higher than much of the developed world. Mean HbA1c in other nations has been successfully modified following benchmarking and quality improvement methods. In this review, we describe the novel 4T approach-teamwork, targets, technology, and tight control-to diabetes management in youth with new-onset T1D. In this program, the diabetes care team (physicians, nurse practitioners, certified diabetes educators, dieticians, social workers, psychologists, and exercise physiologists) work closely to deliver diabetes education from diagnosis. Part of the education curriculum involves early integration of technology, specifically continuous glucose monitoring (CGM), and developing a curriculum around using the CGM to maintain tight control and optimize quality of life.

  View details for DOI 10.3389/fendo.2020.00360

  View details for PubMedID 32733375

  View details for PubMedCentralID PMC7363838

• ISPAD Annual Conference 2018 Highlights PEDIATRIC DIABETES Prahalad, P., Ray, N., Wong, J. C., Berget, C., Olinder, A., Rangasami, J. J., King, B. R., Deeb, A., Agwu, J. 2019; 20 (4): 375–79

  View details for DOI 10.1111/pedi.12832

  View details for Web of Science ID 000468283100001

• Cinacalcet therapy in an infant with an R185Q calcium-sensing receptor mutation causing hyperparathyroidism: a case report and review of the literature. Journal of pediatric endocrinology & metabolism : JPEM Forman, T. E., Niemi, A., Prahalad, P., Shi, R. Z., Nally, L. M. 2019

  Abstract

  Background Neonatal severe hyperparathyroidism (NSHPT) is commonly treated with either parathyroidectomy or pharmacologic agents with varying efficacy and numerous side effects. Reports of using cinacalcet for NSHPT have increased, however, the effective dose for pediatric patients from the onset of symptoms through infancy has not been established. Case presentation We describe the clinical course of a newborn with a de novo R185Q mutation in the calcium-sensing receptor (CASR) gene, causing NSHPT. The infant received cinacalcet from the first days of life until 1 year of age. Conclusions Cinacalcet therapy effectively controlled the patient's serum calcium, phosphorus, and parathyroid hormone (PTH) levels without side effects.

  View details for PubMedID 30730839

• Hemoglobin A1c Trajectory in Pediatric Patients with Newly Diagnosed Type 1 Diabetes. Diabetes technology & therapeutics Prahalad, P. n., Yang, J. n., Scheinker, D. n., Desai, M. n., Hood, K. n., Maahs, D. M. 2019

  Abstract

  Despite advances in diabetes technology and treatment, a majority of children and adolescents with type 1 diabetes (T1D) fail to meet hemoglobin A1c (HbA1c) targets. Among high-income nations, the United States has one of the highest mean HbA1c values. We tracked the HbA1c values of 261 patients diagnosed with T1D in our practice over a 2.5-year period to identify inflection points in the HbA1c trajectory. The HbA1c declined until 5 months postdiagnosis. There was a rise in the HbA1c between the fifth and sixth month postdiagnosis. The HbA1c continued to steadily rise and by 18 months postdiagnosis, the mean HbA1c was 8.2%, which is also our clinic mean. Understanding the HbA1c trajectory early in the course of diabetes has helped to identify opportunities for intensification of diabetes management to flatten the trajectory of HbA1c and improve clinical outcomes.

  View details for DOI 10.1089/dia.2019.0065

  View details for PubMedID 31180244

• CGM Initiation Soon After Type 1 Diabetes Diagnosis Results in Sustained CGM Use and Wear Time. Diabetes care Prahalad, P. n., Addala, A. n., Scheinker, D. n., Hood, K. K., Maahs, D. M. 2019

  View details for DOI 10.2337/dc19-1205

  View details for PubMedID 31558548

• Diabetes Technology Society Report on the FDA Digital Health Software Precertification Program Meeting. Journal of diabetes science and technology King, F., Klonoff, D. C., Ahn, D., Adi, S., Berg, E. G., Bian, J., Chen, K., Drincic, A., Heyl, M., Magee, M., Mulvaney, S., Pavlovic, Y., Prahalad, P., Ryan, M., Sabharwal, A., Shah, S., Spanakis, E., Thompson, B. M., Thompson, M., Wang, J. 2018: 1932296818810436

  Abstract

  Diabetes Technology Society (DTS) convened a meeting about the US Food and Drug Administration (FDA) Digital Health Software Precertification Program on August 28, 2018. Forty-eight attendees participated from clinical and academic endocrinology (both adult and pediatric), nursing, behavioral health, engineering, and law, as well as representatives of FDA, National Institutes of Health (NIH), National Telecommunications and Information Administration (NTIA), and industry. The meeting was intended to provide ideas to FDA about their plan to launch a Digital Health Software Precertification Program. Attendees discussed the four components of the plan: (1) excellence appraisal and certification, (2) review pathway determination, (3) streamlined premarket review process, and (4) real-world performance. The format included (1) introductory remarks, (2) a program overview presentation from FDA, (3) roundtable working sessions focused on each of the Software Precertification Program's four components, (4) presentations reflecting the discussions, (5) questions to and answers from FDA, and (6) concluding remarks. The meeting provided useful information to the diabetes technology community and thoughtful feedback to FDA.

  View details for PubMedID 30394807

• Sustained Continuous Glucose Monitor Use in Low-Income Youth with Type 1 Diabetes Following Insurance Coverage Supports Expansion of Continuous Glucose Monitor Coverage for All. Diabetes technology & therapeutics Prahalad, P., Addala, A., Buckingham, B., Wilson, D. M., Maahs, D. M. 2018

  View details for PubMedID 30020810

• Sustained Continuous Glucose Monitor Use in Low-Income Youth with Type 1 Diabetes Following Insurance Coverage Supports Expansion of Continuous Glucose Monitor Coverage for All DIABETES TECHNOLOGY & THERAPEUTICS Prahalad, P., Addala, A., Buckingham, B., Wilson, D. M., Maahs, D. M. 2018; 20 (9): 632–34

  View details for DOI 10.1089/dia.2018.0204

  View details for Web of Science ID 000439550100001

• Diabetes technology: improving care, improving patient-reported outcomes and preventing complications in young people with Type 1 diabetes. Diabetic medicine : a journal of the British Diabetic Association Prahalad, P. n., Tanenbaum, M. n., Hood, K. n., Maahs, D. M. 2018

  Abstract

  With the evolution of diabetes technology, those living with Type 1 diabetes are given a wider arsenal of tools with which to achieve glycaemic control and improve patient-reported outcomes. Furthermore, the use of these technologies may help reduce the risk of acute complications, such as severe hypoglycaemia and diabetic ketoacidosis, as well as long-term macro- and microvascular complications. In addition, diabetes technology can have a beneficial impact on psychosocial health by reducing the burden of diabetes. Unfortunately, diabetes goals are often unmet and people with Type 1 diabetes too frequently experience acute and long-term complications of this condition, in addition to often having less than ideal psychosocial outcomes. Increasing realization of the importance of patient-reported outcomes is leading to diabetes care delivery becoming more patient-centred. Diabetes technology in the form of medical devices, digital health and big data analytics have the potential to improve clinical care and psychosocial support, resulting in lower rates of acute and chronic complications, decreased burden of diabetes care, and improved quality of life. This article is protected by copyright. All rights reserved.

  View details for PubMedID 29356074

• Evidence-based Mobile Medical Applications in Diabetes. Endocrinology and metabolism clinics of North America Drincic, A., Prahalad, P., Greenwood, D., Klonoff, D. C. 2016; 45 (4): 943-965

  Abstract

  This article reviews mobile medical applications that are commercially available in the United States or European Union (EU) and are (1) associated with published data of clinical outcomes in the peer-reviewed literature during the past 5 years, (2) cleared by the US Food and Drug Administration (FDA) in the United States, or (3) a recipient of a CE (Conformité Européenne) mark by the EU. Many of these applications have been shown to positively affect outcomes in the short term, but long-term studies are needed. Until more data are available, consumers and professionals can consider guidance based on FDA/CE status.

  View details for DOI 10.1016/j.ecl.2016.06.001

  View details for PubMedID 27823614

• Performance of Cleared Blood Glucose Monitors. Journal of diabetes science and technology Klonoff, D. C., Prahalad, P. 2015; 9 (4): 895-910

  Abstract

  Cleared blood glucose monitor (BGM) systems do not always perform as accurately for users as they did to become cleared. We performed a literature review of recent publications between 2010 and 2014 that present data about the frequency of inaccurate performance using ISO 15197 2003 and ISO 15197 2013 as target standards. We performed an additional literature review of publications that present data about the clinical and economic risks of inaccurate BGMs for making treatment decisions or calibrating continuous glucose monitors (CGMs). We found 11 publications describing performance of 98 unique BGM systems. 53 of these 98 (54%) systems met ISO 15197 2003 and 31 of the 98 (32%) tested systems met ISO 15197 2013 analytical accuracy standards in all studies in which they were evaluated. Of the tested systems, 33 were identified by us as FDA-cleared. Among these FDA-cleared BGM systems, 24 out of 32 (75%) met ISO 15197 2003 and 15 out of 31 (48.3%) met ISO 15197 2013 in all studies in which they were evaluated. Among the non-FDA-cleared BGM systems, 29 of 65 (45%) met ISO 15197 2003 and 15 out of 65 (23%) met ISO 15197 2013 in all studies in which they were evaluated. It is more likely that an FDA-cleared BGM system, compared to a non-FDA-cleared BGM system, will perform according to ISO 15197 2003 (χ(2) = 6.2, df = 3, P = 0.04) and ISO 15197 2013 (χ(2) = 11.4, df = 3, P = 0.003). We identified 7 articles about clinical risks and 3 articles about economic risks of inaccurate BGMs. We conclude that a significant proportion of cleared BGMs do not perform at the level for which they were cleared or according to international standards of accuracy. Such poor performance leads to adverse clinical and economic consequences.

  View details for DOI 10.1177/1932296815584797

  View details for PubMedID 25990294

• Retinoic acid mediates regulation of network formation by COUP-TFII and VE-cadherin expression by TGFbeta receptor kinase in breast cancer cells. PloS one Prahalad, P., Dakshanamurthy, S., Ressom, H., Byers, S. W. 2010; 5 (4)

  Abstract

  Tumor development, growth, and metastasis depend on the provision of an adequate vascular supply. This can be due to regulated angiogenesis, recruitment of circulating endothelial progenitors, and/or vascular transdifferentiation. Our previous studies showed that retinoic acid (RA) treatment converts a subset of breast cancer cells into cells with significant endothelial genotypic and phenotypic elements including marked induction of VE-cadherin, which was responsible for some but not all morphological changes. The present study demonstrates that of the endothelial-related genes induced by RA treatment, only a few were affected by knockdown of VE-cadherin, ruling it out as a regulator of the RA-induced endothelial genotypic switch. In contrast, knockdown of the RA-induced gene COUP-TFII prevented the formation of networks in Matrigel but had no effect on VE-cadherin induction or cell fusion. Two pan-kinase inhibitors markedly blocked RA-induced VE-cadherin expression and cell fusion. However, RA treatment resulted in a marked and broad reduction in tyrosine kinase activity. Several genes in the TGFbeta signaling pathway were induced by RA, and specific inhibition of the TGFbeta type I receptor blocked both RA-induced VE-cadherin expression and cell fusion. Together these data indicate a role for the TGFbeta pathway and COUP-TFII in mediating the endothelial transdifferentiating properties of RA.

  View details for DOI 10.1371/journal.pone.0010023

  View details for PubMedID 20386594

• Role of Sox-9, ER81 and VE-Cadherin in Retinoic Acid-Mediated Trans-Differentiation of Breast Cancer Cells PLOS ONE Endo, Y., Deonauth, K., Prahalad, P., Hoxter, B., Zhu, Y., Byers, S. W. 2008; 3 (7)

  Abstract

  Many aspects of development, tumor growth and metastasis depend upon the provision of an adequate vasculature. This can be a result of regulated angiogenesis, recruitment of circulating endothelial progenitors and/or vascular trans-differentiation. The present study demonstrates that treatment of SKBR-3 breast cancer cells with retinoic acid (RA), an important regulator of embryogenesis, cancer and other diseases, stimulates the formation of networks in Matrigel. RA-treatment of SKBR-3 cells co-cultured with human umbilical vein endothelial cells resulted in the formation of mixed structures. RA induces expression of many endothelial genes including vascular endothelial (VE) cadherin. VE-cadherin was also induced by RA in a number of other breast cancer cells. We show that RA-induced VE-cadherin is responsible for the RA-induced morphological changes. RA rapidly induced the expression of Sox-9 and ER81, which in turn form a complex on the VE-cadherin promoter and are required to mediate the transcriptional regulation of VE-cadherin by RA. These data indicate that RA may promote the expression of endothelial genes resulting in endothelial-like differentiation, or provide a mechanism whereby circulating endothelial progenitor cells could be incorporated into a growing organ or tumor.

  View details for DOI 10.1371/journal.pone.0002714

  View details for Web of Science ID 000264057200057

  View details for PubMedID 18628953

• Regulation of MDCK cell-substratum adhesion by RhoA and myosin light chain kinase after ATP depletion AMERICAN JOURNAL OF PHYSIOLOGY-CELL PHYSIOLOGY Prahalad, P., Calvo, I., Waechter, H., Matthews, J. B., Zuk, A., Matlin, K. S. 2004; 286 (3): C693-C707

  Abstract

  The attachment of epithelial cells to the extracellular matrix substratum is essential for their differentiation and polarization. Despite this, the precise adhesion mechanism and its regulation are poorly understood. In the kidney, an ischemic insult causes renal tubular epithelial cells to detach from the basement membrane, even though they remain viable. To understand this phenomenon, and to probe the regulation of epithelial cell attachment, we used a model system consisting of newly adherent Madin-Darby canine kidney (MDCK) cells subjected to ATP depletion to mimic ischemic injury. We found that MDCK cells detach from collagen I after 60 min of ATP depletion but reattach when resupplied with glucose. Detachment is not caused by degradation or endocytosis of beta(1)-integrins, which mediate attachment to collagen I. Basal actin filaments and paxillin-containing adhesion complexes are disrupted by ATP depletion and quickly reform on glucose repletion. However, partial preservation of basal actin by overexpression of constitutively active RhoA does not significantly affect cell detachment. Furthermore, Y-27632, an inhibitor of the RhoA effector Rho-kinase, does not prevent reattachment of cells on glucose addition, even though reformation of central stress fibers and large adhesion complexes is blocked. In contrast, reattachment of ATP-depleted cells and detachment of cells not previously subjected to ATP depletion are prevented by ML-7, an inhibitor of myosin light chain kinase (MLCK). We conclude that initial adherence of MDCK cells to a collagen I substratum is mediated by peripheral actin filaments and adhesion complexes regulated by MLCK but not by stress fibers and adhesion complexes controlled by RhoA.

  View details for DOI 10.1152/ajpcell.00124.2003

  View details for Web of Science ID 000188707600027

  View details for PubMedID 14644769