Petra Mamic

All Publications

• Gut Microbiome-Based Management ofPatients With HeartFailure: JACC Review Topic of the Week. Journal of the American College of Cardiology Mamic, P., Snyder, M., Tang, W. H. 2023; 81 (17): 1729-1739

  Abstract

  Despite therapeutic advances, chronic heart failure (HF) is still associated with significant risk of morbidity and mortality. The course of disease and responses to therapies vary widely among individuals with HF, highlighting the need for precision medicine approaches. Gut microbiome stands to be an important aspect of precision medicine in HF. Exploratory clinical studies have revealed shared patterns of gut microbiome dysregulation in this disease, with mechanistic animal studies providing evidence for active involvement of the gut microbiome in development and pathophysiology of HF. Deeper insights into gut microbiome-host interactions in patients with HF promise to deliver novel disease biomarkers, preventative and therapeutic targets, and improve disease risk stratification. This knowledge may enable a paradigm shift in how we care for patients with HF, and pave the path toward improved clinical outcomes through personalized HF care.

  View details for DOI 10.1016/j.jacc.2023.02.045

  View details for PubMedID 37100490

• Arrhythmias Other Than Atrial Fibrillation in Those With an Irregular Pulse Detected With a Smartwatch: Findings From the Apple Heart Study. Circulation. Arrhythmia and electrophysiology Perino, A. C., Gummidipundi, S. E., Lee, J., Hedlin, H., Garcia, A., Ferris, T., Balasubramanian, V., Gardner, R. M., Cheung, L., Hung, G., Granger, C. B., Kowey, P., Rumsfeld, J. S., Russo, A. M., True Hills, M., Talati, N., Nag, D., Tsay, D., Desai, S., Desai, M., Mahaffey, K. W., Turakhia, M. P., Perez, M. V. 2021: CIRCEP121010063

  Abstract

  The Apple watch irregular pulse detection algorithm was found to have a positive predictive value of 0.84 for identification of atrial fibrillation (AF). We sought to describe the prevalence of arrhythmias other than AF in those with an irregular pulse detected on a smartwatch.The Apple Heart Study investigated a smartwatch-based irregular pulse notification algorithm to identify AF. For this secondary analysis, we analyzed participants who received an ambulatory ECG patch after index irregular pulse notification. We excluded participants with AF identified on ECG patch and described the prevalence of other arrhythmias on the remaining participant ECG patches. We also reported the proportion of participants self-reporting subsequent AF diagnosis.Among 419 297 participants enrolled in the Apple Heart Study, 450 participant ECG patches were analyzed, with no AF on 297 ECG patches (66%). Non-AF arrhythmias (excluding supraventricular tachycardias <30 beats and pauses <3 seconds) were detected in 119 participants (40.1%) with ECG patches without AF. The most common arrhythmias were frequent PACs (burden ≥1% to <5%, 15.8%; ≥5% to <15%, 8.8%), atrial tachycardia (≥30 beats, 5.4%), frequent PVCs (burden ≥1% to <5%, 6.1%; ≥5% to <15%, 2.7%), and nonsustained ventricular tachycardia (4-7 beats, 6.4%; ≥8 beats, 3.7%). Of 249 participants with no AF detected on ECG patch and patient-reported data available, 76 participants (30.5%) reported subsequent AF diagnosis.In participants with an irregular pulse notification on the Apple Watch and no AF observed on ECG patch, atrial and ventricular arrhythmias, mostly PACs and PVCs, were detected in 40% of participants. Defining optimal care for patients with detection of incidental arrhythmias other than AF is important as AF detection is further investigated, implemented, and refined.

  View details for DOI 10.1161/CIRCEP.121.010063

  View details for PubMedID 34565178

• Pre-symptomatic detection of COVID-19 from smartwatch data. Nature biomedical engineering Mishra, T., Wang, M., Metwally, A. A., Bogu, G. K., Brooks, A. W., Bahmani, A., Alavi, A., Celli, A., Higgs, E., Dagan-Rosenfeld, O., Fay, B., Kirkpatrick, S., Kellogg, R., Gibson, M., Wang, T., Hunting, E. M., Mamic, P., Ganz, A. B., Rolnik, B., Li, X., Snyder, M. P. 2020

  Abstract

  Consumer wearable devices that continuously measure vital signs have been used to monitor the onset of infectious disease. Here, we show that data from consumer smartwatches can be used for the pre-symptomatic detection of coronavirus disease 2019 (COVID-19). We analysed physiological and activity data from 32 individuals infected with COVID-19, identified from a cohort of nearly 5,300 participants, and found that 26 of them (81%) had alterations in their heart rate, number of daily steps or time asleep. Of the 25 cases of COVID-19 with detected physiological alterations for which we had symptom information, 22 were detected before (or at) symptom onset, with four cases detected at least nine days earlier. Using retrospective smartwatch data, we show that 63% of the COVID-19 cases could have been detected before symptom onset in real time via a two-tiered warning system based on the occurrence of extreme elevations in resting heart rate relative to the individual baseline. Our findings suggest that activity tracking and health monitoring via consumer wearable devices may be used for the large-scale, real-time detection of respiratory infections, often pre-symptomatically.

  View details for DOI 10.1038/s41551-020-00640-6

  View details for PubMedID 33208926

• Is Our Diet Turning Our Gut Microbiome Against Us? Journal of the American College of Cardiology Heidenreich, P. A., Mamic, P. 2020; 75 (7): 773–75

  View details for DOI 10.1016/j.jacc.2019.12.023

  View details for PubMedID 32081287

• Gut microbiome - A potential mediator of pathogenesis in heart failure and its comorbidities: State-of-the-art review. Journal of molecular and cellular cardiology Mamic, P. n., Chaikijurajai, T. n., Tang, W. H. 2020

  Abstract

  Gut microbiome (GMB) has been increasingly recognized as a contributor to development and progression of heart failure (HF), immune-mediated subtypes of cardiomyopathy (myocarditis and anthracycline-induced cardiotoxicity), response to certain cardiovascular drugs, and HF-related comorbidities, such as chronic kidney disease, cardiorenal syndrome, insulin resistance, malnutrition, and cardiac cachexia. Gut microbiome is also responsible for the "gut hypothesis" of HF, which explains the adverse effects of gut barrier dysfunction and translocation of GMB on the progression of HF. Furthermore, accumulating evidence has suggested that gut microbial metabolites, including short chain fatty acids, trimethylamine N-oxide (TMAO), amino acid metabolites, and bile acids, are mechanistically linked to pathogenesis of HF, and could, therefore, serve as potential therapeutic targets for HF. Even though there are a variety of proposed therapeutic approaches, such as dietary modifications, prebiotics, probiotics, TMAO synthesis inhibitors, and fecal microbial transplant, targeting GMB in HF is still in its infancy and, indeed, requires further preclinical and clinical evidence. In this review, we aim to highlight the role gut microbiome plays in HF pathophysiology and its potential as a novel therapeutic target in HF.

  View details for DOI 10.1016/j.yjmcc.2020.12.001

  View details for PubMedID 33307092

• Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. The New England journal of medicine Perez, M. V., Mahaffey, K. W., Hedlin, H., Rumsfeld, J. S., Garcia, A., Ferris, T., Balasubramanian, V., Russo, A. M., Rajmane, A., Cheung, L., Hung, G., Lee, J., Kowey, P., Talati, N., Nag, D., Gummidipundi, S. E., Beatty, A., Hills, M. T., Desai, S., Granger, C. B., Desai, M., Turakhia, M. P., Apple Heart Study Investigators, Perez, M. V., Turakhia, M. P., Lhamo, K., Smith, S., Berdichesky, M., Sharma, B., Mahaffey, K., Parizo, J., Olivier, C., Nguyen, M., Tallapalli, S., Kaur, R., Gardner, R., Hung, G., Mitchell, D., Olson, G., Datta, S., Gerenrot, D., Wang, X., McCoy, P., Satpathy, B., Jacobsen, H., Makovey, D., Martin, A., Perino, A., O'Brien, C., Gupta, A., Toruno, C., Waydo, S., Brouse, C., Dorfman, D., Stein, J., Huang, J., Patel, M., Fleischer, S., Doll, E., O'Reilly, M., Dedoshka, K., Chou, M., Daniel, H., Crowley, M., Martin, C., Kirby, T., Brumand, M., McCrystale, K., Haggerty, M., Newberger, J., Keen, D., Antall, P., Holbrook, K., Braly, A., Noone, G., Leathers, B., Montrose, A., Kosowsky, J., Lewis, D., Finkelmeier, J. R., Bemis, K., Mahaffey, K. W., Desai, M., Talati, N., Nag, D., Rajmane, A., Desai, S., Caldbeck, D., Cheung, L., Granger, C., Rumsfeld, J., Kowey, P. R., Hills, M. T., Russo, A., Rockhold, F., Albert, C., Alonso, A., Wruck, L., Friday, K., Wheeler, M., Brodt, C., Park, S., Rogers, A., Jones, R., Ouyang, D., Chang, L., Yen, A., Dong, J., Mamic, P., Cheng, P., Shah, R., Lorvidhaya, P. 2019; 381 (20): 1909–17

  Abstract

  BACKGROUND: Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown.METHODS: Participants without atrial fibrillation (as reported by the participants themselves) used a smartphone (Apple iPhone) app to consent to monitoring. If a smartwatch-based irregular pulse notification algorithm identified possible atrial fibrillation, a telemedicine visit was initiated and an electrocardiography (ECG) patch was mailed to the participant, to be worn for up to 7 days. Surveys were administered 90 days after notification of the irregular pulse and at the end of the study. The main objectives were to estimate the proportion of notified participants with atrial fibrillation shown on an ECG patch and the positive predictive value of irregular pulse intervals with a targeted confidence interval width of 0.10.RESULTS: We recruited 419,297 participants over 8 months. Over a median of 117 days of monitoring, 2161 participants (0.52%) received notifications of irregular pulse. Among the 450 participants who returned ECG patches containing data that could be analyzed - which had been applied, on average, 13 days after notification - atrial fibrillation was present in 34% (97.5% confidence interval [CI], 29 to 39) overall and in 35% (97.5% CI, 27 to 43) of participants 65 years of age or older. Among participants who were notified of an irregular pulse, the positive predictive value was 0.84 (95% CI, 0.76 to 0.92) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular pulse notification and 0.71 (97.5% CI, 0.69 to 0.74) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular tachogram. Of 1376 notified participants who returned a 90-day survey, 57% contacted health care providers outside the study. There were no reports of serious app-related adverse events.CONCLUSIONS: The probability of receiving an irregular pulse notification was low. Among participants who received notification of an irregular pulse, 34% had atrial fibrillation on subsequent ECG patch readings and 84% of notifications were concordant with atrial fibrillation. This siteless (no on-site visits were required for the participants), pragmatic study design provides a foundation for large-scale pragmatic studies in which outcomes or adherence can be reliably assessed with user-owned devices. (Funded by Apple; Apple Heart Study ClinicalTrials.gov number, NCT03335800.).

  View details for DOI 10.1056/NEJMoa1901183

  View details for PubMedID 31722151

• Hospitalized Patients with Heart Failure and Common Bacterial Infections: A Nationwide Analysis of Concomitant Clostridium Difficile Infection Rates and In-Hospital Mortality. Journal of cardiac failure Mamic, P., Heidenreich, P. A., Hedlin, H., Tennakoon, L., Staudenmayer, K. L. 2016; 22 (11): 891-900

  Abstract

  Patients with heart failure (HF) are frequently hospitalized with common bacterial infections. It is unknown whether they experience concomitant Clostridium difficile infection (CDI) more frequently than patients without HF, and whether CDI affects their mortality.We used 2012 National Inpatient Sample data to determine the rate of CDI and associated in-hospital mortality for hospitalized patients with comorbid HF and urinary tract infection (UTI), pneumonia (PNA), or sepsis. Univariate and multivariate analyses were performed. Weighted data are presented.There were an estimated 5,851,582 patient hospitalizations with discharge diagnosis of UTI, PNA, or sepsis in 2012 in the United States. Of these, 23.4% had discharge diagnosis of HF. Patients with HF were on average older and had more comorbidities. CDI rates were higher in hospitalizations with discharge diagnosis of HF compared with those without HF (odds ratio 1.13, 95% confidence interval 1.10-1.16) after controlling for patient demographics and comorbidities and hospital characteristics. Among HF hospitalizations with UTI, PNA, or sepsis, those with concomitant CDI had a higher in-hospital mortality than those without concomitant CDI (odds ratio 1.81, 95% confidence interval 1.71-1.92) after controlling for the covariates outlined previously.HF is associated with higher CDI rates among hospitalized patients with other common bacterial infections, even when adjusting for other known risk factors for CDI. Among these patients with comorbid HF, CDI is associated with markedly higher in-hospital mortality. These findings may suggest an opportunity to improve outcomes for hospitalized patients with HF and common bacterial infections, possibly through improved Clostridium difficile screening and prophylaxis protocols.

  View details for DOI 10.1016/j.cardfail.2016.06.005

  View details for PubMedID 27317844