Pre-symptomatic detection of COVID-19 from smartwatch data.
Nature biomedical engineering
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 2020; 75 (7): 773–75
Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.
The New England journal of medicine
2019; 381 (20): 1909–17
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
2016; 22 (11): 891-900
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