Academic Appointments


  • Clinical Scholar, Medicine

All Publications


  • Impact of Virtual Interviewing on Cardiovascular Fellowship Applicant Diversity: Insights From 2 Academic Programs. Journal of the American Heart Association Witting, C., Knowles, J. W., DeFaria Yeh, D., Beyene, T. J., Gummipundi, S. E., Heidenreich, P. A., Yong, C. M. 2023: e030255

    View details for DOI 10.1161/JAHA.123.030255

    View details for PubMedID 38156448

  • Predictive Value of Relative Apical Sparing of Longitudinal Strain on Echocardiography for Cardiac Amyloidosis. The American journal of cardiology Bavishi, A., Witting, C., Guo, J., Wu, E., John, J., Jankowski, M., Baldridge, A. S., Meng, D., Maganti, K. 2023; 200: 66-71

    Abstract

    Relative apical longitudinal sparing (RALS) on echocardiography has become an increasingly used tool to evaluate for cardiac amyloidosis (CA), but the predictive value of this finding remains unclear. This is a retrospective analysis at a single tertiary care center across 3years. Patients were included if they had RALS, defined by strain ratio ≥2.0 on echocardiography, and sufficient laboratory, imaging, or histopathologic workup to indicate their likelihood of CA. Patients were stratified by their likelihood of CA, and contributions of other co-morbidities previously shown to be associated with RALS. Of the 220 patients who had adequate workup to determine their likelihood of having CA, 50 (22.7%) had confirmed CA, 35 (15.9%) had suspicious CA, 83 (37.7%) had unlikely CA, and 52 (23.7%) had ruled-out CA. The positive predictive value of RALS for CA was 38.6% for confirmed or suspicious CA. The remaining 61.4% of patients who were unlikely or ruled out for CA had other co-morbidities such as hypertension, chronic kidney disease, malignancy, or aortic stenosis, 17.0% of this group had none of these co-morbidities. In our tertiary care cohort of patients with RALS pattern on echocardiography, we found that fewer than half of patients with RALS were likely to have CA. Given the increasing use of strain technology, further studies are warranted to determine the optimal strategy for assessing CA in a patient with RALS.

    View details for DOI 10.1016/j.amjcard.2023.04.048

    View details for PubMedID 37302282

  • Natural language processing to identify reasons for sex disparity in statin prescriptions. American journal of preventive cardiology Witting, C., Azizi, Z., Gomez, S. E., Zammit, A., Sarraju, A., Ngo, S., Hernandez-Boussard, T., Rodriguez, F. 2023; 14: 100496

    Abstract

    Background: Statins are the cornerstone of treatment of patients with atherosclerotic cardiovascular disease (ASCVD). Despite this, multiple studies have shown that women with ASCVD are less likely to be prescribed statins than men. The objective of this study was to use Natural Language Processing (NLP) to elucidate factors contributing to this disparity.Methods: Our cohort included adult patients with two or more encounters between 2014 and 2021 with an ASCVD diagnosis within a multisite electronic health record (EHR) in Northern California. After reviewing structured EHR prescription data, we used a benchmark deep learning NLP approach, Clinical Bidirectional Encoder Representations from Transformers (BERT), to identify and interpret discussions of statin prescriptions documented in clinical notes. Clinical BERT was evaluated against expert clinician review in 20% test sets.Results: There were 88,913 patients with ASCVD (mean age 67.8±13.1 years) and 35,901 (40.4%) were women. Women with ASCVD were less likely to be prescribed statins compared with men (56.6%vs 67.6%, p <0.001), and, when prescribed, less likely to be prescribed guideline-directed high-intensity dosing (41.4%vs 49.8%, p <0.001). These disparities were more pronounced among younger patients, patients with private insurance, and those for whom English is their preferred language. Among those not prescribed statins, women were less likely than men to have statins mentioned in their clinical notes (16.9%vs 19.1%, p <0.001). Women were less likely than men to have statin use reported in clinical notes despite absence of recorded prescription (32.8%vs 42.6%, p <0.001). Women were slightly more likely than men to have statin intolerance documented in structured data or clinical notes (6.0%vs 5.3%, p=0.003).Conclusions: Women with ASCVD were less likely to be prescribed guideline-directed statins compared with men. NLP identified additional sex-based statin disparities and reasons for statin non-prescription in clinical notes of patients with ASCVD.

    View details for DOI 10.1016/j.ajpc.2023.100496

    View details for PubMedID 37128554

  • Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records. Journal of the American Heart Association Sarraju, A., Zammit, A., Ngo, S., Witting, C., Hernandez-Boussard, T., Rodriguez, F. 2023: e028120

    Abstract

    Background Statins are guideline-recommended medications that reduce cardiovascular events in patients with diabetes. Yet, statin use is concerningly low in this high-risk population. Identifying reasons for statin nonuse, which are typically described in unstructured electronic health record data, can inform targeted system interventions to improve statin use. We aimed to leverage a deep learning approach to identify reasons for statin nonuse in patients with diabetes. Methods and Results Adults with diabetes and no statin prescriptions were identified from a multiethnic, multisite Northern California electronic health record cohort from 2014 to 2020. We used a benchmark deep learning natural language processing approach (Clinical Bidirectional Encoder Representations from Transformers) to identify statin nonuse and reasons for statin nonuse from unstructured electronic health record data. Performance was evaluated against expert clinician review from manual annotation of clinical notes and compared with other natural language processing approaches. Of 33 461 patients with diabetes (mean age 59±15 years, 49% women, 36% White patients, 24% Asian patients, and 15% Hispanic patients), 47% (15 580) had no statin prescriptions. From unstructured data, Clinical Bidirectional Encoder Representations from Transformers accurately identified statin nonuse (area under receiver operating characteristic curve [AUC] 0.99 [0.98-1.0]) and key patient (eg, side effects/contraindications), clinician (eg, guideline-discordant practice), and system reasons (eg, clinical inertia) for statin nonuse (AUC 0.90 [0.86-0.93]) and outperformed other natural language processing approaches. Reasons for nonuse varied by clinical and demographic characteristics, including race and ethnicity. Conclusions A deep learning algorithm identified statin nonuse and actionable reasons for statin nonuse in patients with diabetes. Findings may enable targeted interventions to improve guideline-directed statin use and be scaled to other evidence-based therapies.

    View details for DOI 10.1161/JAHA.122.028120

    View details for PubMedID 36974740

  • Treatment Differences in Medical Therapy for Heart Failure With Reduced Ejection Fraction Between Sociodemographic Groups. JACC. Heart failure Witting, C., Zheng, J., Tisdale, R. L., Shannon, E., Kohsaka, S., Lewis, E. F., Heidenreich, P., Sandhu, A. 2022

    Abstract

    There are sociodemographic disparities in outcomes of heart failure with reduced ejection fraction (HFrEF), but disparities in guideline-directed medical therapy (GDMT) remain poorly characterized.This study aimed to analyze GDMT treatment rates in eligible patients with recently diagnosed HFrEF, and to determine how rates vary by sociodemographic characteristics.This retrospective cohort study included patients diagnosed with HFrEF at Veterans Affairs (VA) hospitals from 2013 to 2019. The authors analyzed GDMT treatment rates and doses, excluding patients with contraindications. Therapies of interest were evidence-based beta-blockers (BBs), renin-angiotensin system inhibitors (RASIs), angiotensin receptor-neprilysin inhibitors (ARNIs), and mineralocorticoid antagonists (MRAs). The authors compared adjusted treatment rates by race and ethnicity, neighborhood social vulnerability, rurality, distance to medical care, and sex.The cohort comprised 126,670 VA patients with recently diagnosed HFrEF. The study found that racial and ethnic minorities had similar or higher treatment rates than White patients. Patients residing in socially vulnerable neighborhoods had 3.4% lower ARNI (95% CI: 1.9%-5.0%) treatment rates. Patients residing farther from specialty care had similar rates of GDMT therapy overall, but were less likely to be taking at least 50% of the target doses of either BBs (4.0% less likely; 95% CI: 3.1%-5.0%) or RASIs (5.0% less likely; 95% CI: 4.1%-6.0%) compared with those closer to care.Among VA patients with recently diagnosed HFrEF, the authors did not find that racial and ethnic minority patients were less likely to receive GDMT. However, appropriate dose up-titration may occur less frequently in more remote patients.

    View details for DOI 10.1016/j.jchf.2022.08.023

    View details for PubMedID 36647925

  • Sepsis Electronic Decision Support Screen in High-Risk Patients Across Age Groups in a Pediatric Emergency Department PEDIATRIC EMERGENCY CARE Witting, C. S., Simon, N. E., Lorenz, D., Murphy, J. S., Nelson, J., Lehnig, K., Alpern, E. R. 2022; 38 (8): E1479-E1484

    Abstract

    This study aimed to compare the performance of a pediatric decision support algorithm to detect severe sepsis between high-risk pediatric and adult patients in a pediatric emergency department (PED).This is a retrospective cohort study of patients presenting from March 2017 to February 2018 to a tertiary care PED. Patients were identified as high risk for sepsis based on a priori defined criteria and were considered adult if 18 years or older. The 2-step decision support algorithm consists of (1) an electronic health record best-practice alert (BPA) with age-adjusted vital sign ranges, and (2) physician screen. The difference in test characteristics of the intervention for the detection of severe sepsis between pediatric and adult patients was assessed at 0.05 statistical significance.The 2358 enrolled subjects included 2125 children (90.1%) and 233 adults (9.9%). The median ages for children and adults were 3.8 (interquartile range, 1.2-8.6) and 20.1 (interquartile range, 18.2-22.0) years, respectively. In adults, compared with children, the BPA alone had significantly higher sensitivity (0.83 [95% confidence interval {CI}, 0.74-0.89] vs 0.72 [95% CI, 0.69-0.75]; P = 0.02) and lower specificity (0.11 [95% CI, 0.07-0.19] vs 0.48 [95% CI, 0.45-0.51; P < 0.001). With the addition of provider screen, sensitivity and specificity were comparable across age groups, with a lower negative predictive value in adults compared with children (0.66 [95% CI, 0.58-0.74] vs 0.77 [95% CI, 0.75-0.79]; P = 0.005).The BPA was less specific in adults compared with children. With the addition of provider screen, specificity improved; however, the lower negative predictive value suggests that providers may be less likely to suspect sepsis even after automated screen in adult patients. This study invites further research aimed at improving screening algorithms, particularly across the diverse age spectrum presenting to a PED.

    View details for DOI 10.1097/PEC.0000000000002709

    View details for Web of Science ID 000832651100026

    View details for PubMedID 35383693

  • Review of Lipid-Lowering Therapy in Women from Reproductive to Postmenopausal Years. Reviews in cardiovascular medicine Witting, C., Devareddy, A., Rodriguez, F. 2022; 23 (5)

    Abstract

    Although cardiovascular disease is the leading cause of death in women, cardiovascular risk factors remain underrecognized and undertreated. Hyperlipidemia is one of the leading modifiable risk factors for CVD. Statins are the mainstay of lipid lowering therapy (LLT), with additional agents such as ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors as additive or alternative therapies. Clinical trials have demonstrated that these LLTs are equally efficacious in lipid lowering and cardiovascular risk reduction in women as they are in men. Although the data on statin teratogenicity is evolving, in times of pregnancy or attempted pregnancy, most lipid-lowering agents are generally avoided due to lack of high-quality safety data. This leads to limited treatment options in pregnant women with hyperlipidemia or cardiovascular disease. During the perimenopausal period, the mainstay of lipid management remains consistent with guidelines across all ages. Hormone replacement therapy for cardiovascular risk reduction is not recommended. Future research is warranted to target sex-based disparities in LLT initiation and persistence across the life course.

    View details for DOI 10.31083/j.rcm2305183

    View details for PubMedID 38031574

    View details for PubMedCentralID PMC10686310

  • Review of Lipid-Lowering Therapy in Women from Reproductive to Postmenopausal Years REVIEWS IN CARDIOVASCULAR MEDICINE Witting, C., Devareddy, A., Rodriguez, F. 2022; 23 (5)