Feasibility of combining serial smartphone single-lead electrocardiograms for the diagnosis of ST-elevation myocardial infarction.

BACKGROUND: The rate-limiting step in STEMI diagnosis often is the availability of a 12-lead electrocardiogram (ECG) and its interpretation. The potential may exist to speed the availability of 12-lead ECG information by using commonly available mobile technologies. We sought to test whether combining serial smartphone single-lead ECGs to create a virtual 12-lead ECG can accurately diagnose STEMI. METHODS: Consenting patients presenting with symptoms consistent with a possible STEMI had contemporaneous standard 12-lead and smartphone '12-lead equivalent' ECG (produced by electronically combining serial single-lead ECGs) recordings obtained. Matched ECGs were evaluated qualitatively and quantitatively by a panel of blinded readers and classified as STEMI/STEMI equivalent (LBBB), Not-STEMI, or uninterpretable. Interpretable ECG pairs were graded as showing good, fair, or poor correlation. RESULTS: Two hundred four subjects (age = 60 years, males = 57%, STEMI activation = 45%) were enrolled from 5 international sites. Smartphone ECG quality was graded as good in 151 (74.0%), fair in 32 (15.7%), poor in 8 (3.9%), and uninterpretable in 13 (6.4%). A STEMI/STEMI equivalent diagnosis was identified by standard 12-lead ECG in 57/204 (27.9%) recordings. For all interpretable pairs of smartphone ECGs compared with standard ECGs (n = 190), the sensitivity, specificity, and positive and negative predictive values for STEMI/STEMI equivalent by smartphone were 0.89, 0.84, 0.70 and 0.95, respectively. CONCLUSIONS: A '12-lead equivalent' ECG obtained from multiple serial single-lead ECGs from a smartphone can identify STEMI with good correlation to a standard 12-lead ECG. This technology holds promise to improve outcomes in STEMI by enhancing the reach and speed of diagnosis and thereby early treatment.

Smartphone ECG for evaluation of ST-segment elevation myocardial infarction (STEMI): Design of the ST LEUIS International Multicenter Study.

In patients experiencing an ST-elevation myocardial infarction (STEMI), rapid diagnosis and immediate access to reperfusion therapy leads to optimal clinical outcomes. The rate-limiting step in STEMI diagnosis is the availability and performance of a 12-lead ECG. Recent technology has provided access to a reliable means of obtaining an ECG reading through a smartphone application (app) that works with an attachment providing all 12-leads of a standard ECG system. The ST LEUIS study was designed to validate the smartphone ECG app and its ability to accurately assess the presence or absence of STEMI in patients presenting with chest pain compared with the gold standard 12-lead ECG. We aimed to support the diagnostic utility of smartphone technology to provide a timely diagnosis and treatment of STEMI. The study will take place over 12months at five institutions. Approximately 60 patients will be enrolled per institution, for a total recruitment of 300 patients.

HerediGene Population Study IT infrastructure: A model to support genomic research recruitment and precision public health.

The HerediGene Population Study is a large research study focused on identifying new genetic biomarkers for disease prevention, diagnosis, prognosis, and development of new therapeutics. A substantial IT infrastructure evolved to reach enrollment targets and return results to participants. More than 170,000 participants have been enrolled in the study to date, with 5.87% of those whole genome sequenced and 0.46% of those genotyped harboring pathogenic variants. Among other purposes, this infrastructure supports: (1) identifying candidates from clinical criteria, (2) monitoring for qualifying clinical events (e.g., blood draw), (3) contacting candidates, (4) obtaining consent electronically, (5) initiating lab orders, (6) integrating consent and lab orders into clinical workflow, (7) de-identifying samples and clinical data, (8) shipping/transmitting samples and clinical data, (9) genotyping/sequencing samples, (10) and re-identifying and returning results for participants where applicable. This study may serve as a model for similar genomic research and precision public health initiatives.

Observational study of caloric and nutrient intake, bone density, and body composition in infants and children with spinal muscular atrophy type I.

Clinical experience supports a critical role for nutrition in patients with spinal muscular atrophy (SMA). Three-day dietary intake records were analyzed for 156 visits in 47 SMA type I patients, 25 males and 22 females, ages 1month to 13years (median 9.8months) and compared to dietary reference intakes for gender and age along with anthropometric measures and dual-energy X-ray absorptiometry (DEXA) data. Using standardized growth curves, twelve patients met criteria for failure to thrive (FTT) with weight for age <3rd percentile; eight met criteria based on weight for height. Percentage of body fat mass was not correlated with weight for height and weight for age across percentile categories. DEXA analysis further demonstrated that SMA type I children have higher fat mass and lower fat free mass than healthy peers (p<0.001). DEXA and dietary analysis indicates a strong correlation with magnesium intake and bone mineral density (r=0.65, p<0.001). Average caloric intake for 1-3years old was 68.8±15.8kcal/kg - 67% of peers' recommended intake. Children with SMA type I may have lower caloric requirements than healthy age-matched peers, increasing risk for over and undernourished states and deficiencies of critical nutrients. Standardized growth charts may overestimate FTT status in SMA type I.