The electrocardiogram (ECG) is a widely used medical test, consisting of voltage versus time traces collected from surface recordings over the heart
. Here we hypothesized that a deep neural network ...(DNN) can predict an important future clinical event, 1-year all-cause mortality, from ECG voltage-time traces. By using ECGs collected over a 34-year period in a large regional health system, we trained a DNN with 1,169,662 12-lead resting ECGs obtained from 253,397 patients, in which 99,371 events occurred. The model achieved an area under the curve (AUC) of 0.88 on a held-out test set of 168,914 patients, in which 14,207 events occurred. Even within the large subset of patients (n = 45,285) with ECGs interpreted as 'normal' by a physician, the performance of the model in predicting 1-year mortality remained high (AUC = 0.85). A blinded survey of cardiologists demonstrated that many of the discriminating features of these normal ECGs were not apparent to expert reviewers. Finally, a Cox proportional-hazard model revealed a hazard ratio of 9.5 (P < 0.005) for the two predicted groups (dead versus alive 1 year after ECG) over a 25-year follow-up period. These results show that deep learning can add substantial prognostic information to the interpretation of 12-lead resting ECGs, even in cases that are interpreted as normal by physicians.
Familial hypercholesterolemia (FH) remains underdiagnosed despite widespread cholesterol screening. Exome sequencing and electronic health record (EHR) data of 50,726 individuals were used to assess ...the prevalence and clinical impact of FH-associated genomic variants in the Geisinger Health System. The estimated FH prevalence was 1:256 in unselected participants and 1:118 in participants ascertained via the cardiac catheterization laboratory. FH variant carriers had significantly increased risk of coronary artery disease. Only 24% of carriers met EHR-based presequencing criteria for probable or definite FH diagnosis. Active statin use was identified in 58% of carriers; 46% of statin-treated carriers had a low-density lipoprotein cholesterol level below 100 mg/dl. Thus, we find that genomic screening can prompt the diagnosis of FH patients, most of whom are receiving inadequate lipid-lowering therapy.
The DiscovEHR collaboration between the Regeneron Genetics Center and Geisinger Health System couples high-throughput sequencing to an integrated health care system using longitudinal electronic ...health records (EHRs). We sequenced the exomes of 50,726 adult participants in the DiscovEHR study to identify ~4.2 million rare single-nucleotide variants and insertion/deletion events, of which ~176,000 are predicted to result in a loss of gene function. Linking these data to EHR-derived clinical phenotypes, we find clinical associations supporting therapeutic targets, including genes encoding drug targets for lipid lowering, and identify previously unidentified rare alleles associated with lipid levels and other blood level traits. About 3.5% of individuals harbor deleterious variants in 76 clinically actionable genes. The DiscovEHR data set provides a blueprint for large-scale precision medicine initiatives and genomics-guided therapeutic discovery.
Three genetic conditions-hereditary breast and ovarian cancer syndrome, Lynch syndrome, and familial hypercholesterolemia-have tier 1 evidence for interventions that reduce morbidity and mortality, ...prompting proposals to screen unselected populations for these conditions. We examined the impact of genomic screening on risk management and early detection in an unselected population.
Observational study of electronic health records (EHR) among individuals in whom a pathogenic/likely pathogenic variant in a tier 1 gene was discovered through Geisinger's MyCode project. EHR of all eligible participants was evaluated for a prior genetic diagnosis and, among participants without such a diagnosis, relevant personal/family history, postdisclosure clinical diagnoses, and postdisclosure risk management.
Eighty-seven percent of participants (305/351) did not have a prior genetic diagnosis of their tier 1 result. Of these, 65% had EHR evidence of relevant personal and/or family history of disease. Of 255 individuals eligible to have risk management, 70% (n = 179) had a recommended risk management procedure after results disclosure. Thirteen percent of participants (41/305) received a relevant clinical diagnosis after results disclosure.
Genomic screening programs can identify previously unrecognized individuals at increased risk of cancer and heart disease and facilitate risk management and early cancer detection.
Geisinger Health System (GHS) provides an ideal platform for Precision Medicine. Key elements are the integrated health system, stable patient population, and electronic health record (EHR) ...infrastructure. In 2007, Geisinger launched MyCode, a system-wide biobanking program to link samples and EHR data for broad research use.
Patient-centered input into MyCode was obtained using participant focus groups. Participation in MyCode is based on opt-in informed consent and allows recontact, which facilitates collection of data not in the EHR and, since 2013, the return of clinically actionable results to participants. MyCode leverages Geisinger's technology and clinical infrastructure for participant tracking and sample collection.
MyCode has a consent rate of >85%, with more than 90,000 participants currently and with ongoing enrollment of ~4,000 per month. MyCode samples have been used to generate molecular data, including high-density genotype and exome sequence data. Genotype and EHR-derived phenotype data replicate previously reported genetic associations.
The MyCode project has created resources that enable a new model for translational research that is faster, more flexible, and more cost-effective than traditional clinical research approaches. The new model is scalable and will increase in value as these resources grow and are adopted across multiple research platforms.Genet Med 18 9, 906-913.
Abstract
Aims
We investigated the relationship between clinically assessed left ventricular ejection fraction (LVEF) and survival in a large, heterogeneous clinical cohort.
Methods and results
...Physician-reported LVEF on 403 977 echocardiograms from 203 135 patients were linked to all-cause mortality using electronic health records (1998–2018) from US regional healthcare system. Cox proportional hazards regression was used for analyses while adjusting for many patient characteristics including age, sex, and relevant comorbidities. A dataset including 45 531 echocardiograms and 35 976 patients from New Zealand was used to provide independent validation of analyses. During follow-up of the US cohort, 46 258 (23%) patients who had undergone 108 578 (27%) echocardiograms died. Overall, adjusted hazard ratios (HR) for mortality showed a u-shaped relationship for LVEF with a nadir of risk at an LVEF of 60–65%, a HR of 1.71 95% confidence interval (CI) 1.64–1.77 when ≥70% and a HR of 1.73 (95% CI 1.66–1.80) at LVEF of 35–40%. Similar relationships with a nadir at 60–65% were observed in the validation dataset as well as for each age group and both sexes. The results were similar after further adjustments for conditions associated with an elevated LVEF, including mitral regurgitation, increased wall thickness, and anaemia and when restricted to patients reported to have heart failure at the time of the echocardiogram.
Conclusion
Deviation of LVEF from 60% to 65% is associated with poorer survival regardless of age, sex, or other relevant comorbidities such as heart failure. These results may herald the recognition of a new phenotype characterized by supra-normal LVEF.
Acute kidney injury increases mortality risk among those with established chronic kidney disease. In this study we used a propensity score-matched cohort method to retrospectively evaluate the risks ...of death and de novo chronic kidney disease after reversible, hospital-associated acute kidney injury among patients with normal pre-hospitalization kidney function. Of 30,207 discharged patients alive at 90 days, 1610 with reversible acute kidney injury that resolved within the 90 days were successfully matched across multiple parameters with 3652 control patients who had not experienced acute kidney injury. Median follow-up was 3.3 and 3.4 years (injured and control groups, respectively). In Cox proportional hazard models, the risk of death associated with reversible acute kidney injury was significant (hazard ratio 1.50); however, adjustment for the development of chronic kidney injury during follow-up attenuated this risk (hazard ratio 1.18). Reversible acute kidney injury was associated with a significant risk of de novo chronic kidney disease (hazard ratio 1.91). Thus, a resolved episode of hospital-associated acute kidney injury has important implications for the longitudinal surveillance of patients without preexisting, clinically evident kidney disease.
Atrial fibrillation (AF) is associated with substantial morbidity, especially when it goes undetected. If new-onset AF could be predicted, targeted screening could be used to find it early. We ...hypothesized that a deep neural network could predict new-onset AF from the resting 12-lead ECG and that this prediction may help identify those at risk of AF-related stroke.
We used 1.6 M resting 12-lead digital ECG traces from 430 000 patients collected from 1984 to 2019. Deep neural networks were trained to predict new-onset AF (within 1 year) in patients without a history of AF. Performance was evaluated using areas under the receiver operating characteristic curve and precision-recall curve. We performed an incidence-free survival analysis for a period of 30 years following the ECG stratified by model predictions. To simulate real-world deployment, we trained a separate model using all ECGs before 2010 and evaluated model performance on a test set of ECGs from 2010 through 2014 that were linked to our stroke registry. We identified the patients at risk for AF-related stroke among those predicted to be high risk for AF by the model at different prediction thresholds.
The area under the receiver operating characteristic curve and area under the precision-recall curve were 0.85 and 0.22, respectively, for predicting new-onset AF within 1 year of an ECG. The hazard ratio for the predicted high- versus low-risk groups over a 30-year span was 7.2 (95% CI, 6.9-7.6). In a simulated deployment scenario, the model predicted new-onset AF at 1 year with a sensitivity of 69% and specificity of 81%. The number needed to screen to find 1 new case of AF was 9. This model predicted patients at high risk for new-onset AF in 62% of all patients who experienced an AF-related stroke within 3 years of the index ECG.
Deep learning can predict new-onset AF from the 12-lead ECG in patients with no previous history of AF. This prediction may help identify patients at risk for AF-related strokes.
Empirical data on conditions that increase risk of coronavirus disease 2019 (COVID-19) progression are needed to identify high risk individuals. We performed a comprehensive quantitative assessment ...of pre-existing clinical phenotypes associated with COVID-19-related hospitalization.
Phenome-wide association study (PheWAS) of SARS-CoV-2-positive patients from an integrated health system (Geisinger) with system-level outpatient/inpatient COVID-19 testing capacity and retrospective electronic health record (EHR) data to assess pre-COVID-19 pandemic clinical phenotypes associated with hospital admission (hospitalization).
Of 12,971 individuals tested for SARS-CoV-2 with sufficient pre-COVID-19 pandemic EHR data at Geisinger, 1604 were SARS-CoV-2 positive and 354 required hospitalization. We identified 21 clinical phenotypes in 5 disease categories meeting phenome-wide significance (P<1.60x10-4), including: six kidney phenotypes, e.g. end stage renal disease or stage 5 CKD (OR = 11.07, p = 1.96x10-8), six cardiovascular phenotypes, e.g. congestive heart failure (OR = 3.8, p = 3.24x10-5), five respiratory phenotypes, e.g. chronic airway obstruction (OR = 2.54, p = 3.71x10-5), and three metabolic phenotypes, e.g. type 2 diabetes (OR = 1.80, p = 7.51x10-5). Additional analyses defining CKD based on estimated glomerular filtration rate, confirmed high risk of hospitalization associated with pre-existing stage 4 CKD (OR 2.90, 95% CI: 1.47, 5.74), stage 5 CKD/dialysis (OR 8.83, 95% CI: 2.76, 28.27), and kidney transplant (OR 14.98, 95% CI: 2.77, 80.8) but not stage 3 CKD (OR 1.03, 95% CI: 0.71, 1.48).
This study provides quantitative estimates of the contribution of pre-existing clinical phenotypes to COVID-19 hospitalization and highlights kidney disorders as the strongest factors associated with hospitalization in an integrated US healthcare system.
Higher-than-normal levels of circulating triglycerides are a risk factor for ischemic cardiovascular disease. Activation of lipoprotein lipase, an enzyme that is inhibited by angiopoietin-like 4 ...(ANGPTL4), has been shown to reduce levels of circulating triglycerides.
We sequenced the exons of ANGPTL4 in samples obtain from 42,930 participants of predominantly European ancestry in the DiscovEHR human genetics study. We performed tests of association between lipid levels and the missense E40K variant (which has been associated with reduced plasma triglyceride levels) and other inactivating mutations. We then tested for associations between coronary artery disease and the E40K variant and other inactivating mutations in 10,552 participants with coronary artery disease and 29,223 controls. We also tested the effect of a human monoclonal antibody against ANGPTL4 on lipid levels in mice and monkeys.
We identified 1661 heterozygotes and 17 homozygotes for the E40K variant and 75 participants who had 13 other monoallelic inactivating mutations in ANGPTL4. The levels of triglycerides were 13% lower and the levels of high-density lipoprotein (HDL) cholesterol were 7% higher among carriers of the E40K variant than among noncarriers. Carriers of the E40K variant were also significantly less likely than noncarriers to have coronary artery disease (odds ratio, 0.81; 95% confidence interval, 0.70 to 0.92; P=0.002). K40 homozygotes had markedly lower levels of triglycerides and higher levels of HDL cholesterol than did heterozygotes. Carriers of other inactivating mutations also had lower triglyceride levels and higher HDL cholesterol levels and were less likely to have coronary artery disease than were noncarriers. Monoclonal antibody inhibition of Angptl4 in mice and monkeys reduced triglyceride levels.
Carriers of E40K and other inactivating mutations in ANGPTL4 had lower levels of triglycerides and a lower risk of coronary artery disease than did noncarriers. The inhibition of Angptl4 in mice and monkeys also resulted in corresponding reductions in these values. (Funded by Regeneron Pharmaceuticals.).
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