The Association of QRS Duration with Risk of Adverse Outcomes in Sex- and Race- Based Subgroups: The Dallas Heart Study.

Introduction: We explored sex and race differences in the prognostic implications of QRS prolongation among healthy adults. Methods: Participants from the Dallas Heart Study (DHS) free of cardiovascular (CV) disease who underwent ECG testing and cMRI evaluation were included. Multivariable linear regression was used to examine the cross-sectional association of QRS duration with left ventricular (LV) mass, LV ejection fraction (LVEF), and LV end diastolic volume (LVEDV). Association of QRS duration with risk of MACE was evaluated using Cox models. Interaction testing was performed between QRS duration and sex/race respectively for each outcome of interest. QRS duration was log transformed. Results: The study included 2,785 participants. Longer QRS duration was associated with higher LV mass, lower LVEF, and higher LVEDV, independent of CV risk factors ([ß: 0.21, P<0.001], [ß: - 0.13, P<0.001], [ß: 0.22, P<0.001] respectively). Men with longer QRS duration were more likely to have higher LV mass and higher LVEDV compared to women (P-int=0.012, P-int=0.01, respectively). Black participants with longer QRS duration were more likely to have higher LV mass as compared to White participants (P-int<0.001). In Cox analysis, QRS prolongation was associated with higher risk of MACE in women (HR = 6.66 [95% CI: 2.32, 19.1]) but not men. This association was attenuated after adjustment for CV risk factors, with a trend toward significance (HR = 2.45 [95% CI: 0.94, 6.39]). Longer QRS duration was not associated with risk of MACE in Black or White participants in the adjusted models. No interaction between sex/race and QRS duration for risk of MACE was observed. Discussion: In healthy adults, QRS duration is differentially associated with abnormalities in LV structure and function. These findings inform the use of QRS duration in identifying subgroups at risk for CV disease, and caution against using QRS duration cut offs uniformly for clinical decision making. What is known?: QRS prolongation in healthy adults is associated with higher risk of death, cardiovascular disease, and left ventricular hypertrophy. What the study adds?: QRS prolongation may reflect a higher degree of underlying LV hypertrophy in Blacks compared to Whites. Longer QRS interval may reflect higher risk of adverse cardiac events, driven by prevalent cardiovascular risk factors. Graphic Abstract: Risk of underlying left ventricular hypertrophy in demographic groups based on QRS prolongation.

New-Onset Atrial Fibrillation in Patients Hospitalized With COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Registry.

BACKGROUND: New-onset atrial fibrillation (AF) in patients hospitalized with COVID-19 has been reported and associated with poor clinical outcomes. We aimed to understand the incidence of and outcomes associated with new-onset AF in a diverse and representative US cohort of patients hospitalized with COVID-19. METHODS: We used data from the American Heart Association COVID-19 Cardiovascular Disease Registry. Patients were stratified by the presence versus absence of new-onset AF. The primary and secondary outcomes were in-hospital mortality and major adverse cardiovascular events (MACE; cardiovascular death, myocardial infarction, stroke, cardiogenic shock, and heart failure). The association of new-onset AF and the primary and secondary outcomes was evaluated using Cox proportional-hazards models for the primary time to event analyses. RESULTS: Of the first 30 999 patients from 120 institutions across the United States hospitalized with COVID-19, 27 851 had no history of AF. One thousand five hundred seventeen (5.4%) developed new-onset AF during their index hospitalization. New-onset AF was associated with higher rates of death (45.2% versus 11.9%) and MACE (23.8% versus 6.5%). The unadjusted hazard ratio for mortality was 1.99 (95% CI, 1.81-2.18) and for MACE was 2.23 (95% CI, 1.98-2.53) for patients with versus without new-onset AF. After adjusting for demographics, clinical comorbidities, and severity of disease, the associations with death (hazard ratio, 1.10 [95% CI, 0.99-1.23]) fully attenuated and MACE (hazard ratio, 1.31 [95% CI, 1.14-1.50]) partially attenuated. CONCLUSIONS: New-onset AF was common (5.4%) among patients hospitalized with COVID-19. Almost half of patients with new-onset AF died during their index hospitalization. After multivariable adjustment for comorbidities and disease severity, new-onset AF was not statistically significantly associated with death, suggesting that new-onset AF in these patients may primarily be a marker of other adverse clinical factors rather than an independent driver of mortality. Causality between the MACE composites and AF needs to be further evaluated.

Association of Kidney Disease With Outcomes in COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Disease Registry.

Background Emerging evidence links acute kidney injury (AKI) in patients with COVID-19 with higher mortality and respiratory morbidity, but the relationship of AKI with cardiovascular disease outcomes has not been reported in this population. We sought to evaluate associations between chronic kidney disease (CKD), AKI, and mortality and cardiovascular outcomes in patients hospitalized with COVID-19. Methods and Results In a large multicenter registry including 8574 patients with COVID-19 from 88 US hospitals, data were collected on baseline characteristics and serial laboratory data during index hospitalization. Primary exposure variables were CKD (categorized as no CKD, CKD, and end-stage kidney disease) and AKI (classified into no AKI or stages 1, 2, or 3 using a modification of the Kidney Disease Improving Global Outcomes guideline definition). The primary outcome was all-cause mortality. The key secondary outcome was major adverse cardiac events, defined as cardiovascular death, nonfatal stroke, nonfatal myocardial infarction, new-onset nonfatal heart failure, and nonfatal cardiogenic shock. CKD and end-stage kidney disease were not associated with mortality or major adverse cardiac events after multivariate adjustment. In contrast, AKI was significantly associated with mortality (stage 1 hazard ratio [HR], 1.72 [95% CI, 1.46-2.03]; stage 2 HR, 1.83 [95% CI, 1.52-2.20]; stage 3 HR, 1.69 [95% CI, 1.44-1.98]; versus no AKI) and major adverse cardiac events (stage 1 HR, 2.17 [95% CI, 1.74-2.71]; stage 2 HR, 2.70 [95% CI, 2.07-3.51]; stage 3 HR, 3.06 [95% CI, 2.52-3.72]; versus no AKI). Conclusions This large study demonstrates a significant association between AKI and all-cause mortality and, for the first time, major adverse cardiovascular events in patients hospitalized with COVID-19.

Association of Body Mass Index and Age With Morbidity and Mortality in Patients Hospitalized With COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Disease Registry.

BACKGROUND: Obesity may contribute to adverse outcomes in coronavirus disease 2019 (COVID-19). However, studies of large, broadly generalizable patient populations are lacking, and the effect of body mass index (BMI) on COVID-19 outcomes- particularly in younger adults-remains uncertain. METHODS: We analyzed data from patients hospitalized with COVID-19 at 88 US hospitals enrolled in the American Heart Association's COVID-19 Cardiovascular Disease Registry with data collection through July 22, 2020. BMI was stratified by World Health Organization obesity class, with normal weight prespecified as the reference group. RESULTS: Obesity, and, in particular, class III obesity, was overrepresented in the registry in comparison with the US population, with the largest differences among adults ≤50 years. Among 7606 patients, in-hospital death or mechanical ventilation occurred in 2109 (27.7%), in-hospital death in 1302 (17.1%), and mechanical ventilation in 1602 (21.1%). After multivariable adjustment, classes I to III obesity were associated with higher risks of in-hospital death or mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09-1.51], 1.57 [1.29-1.91], 1.80 [1.47-2.20], respectively), and class III obesity was associated with a higher risk of in-hospital death (hazard ratio, 1.26 [95% CI, 1.00-1.58]). Overweight and class I to III obese individuals were at higher risk for mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09-1.51], 1.54 [1.29-1.84], 1.88 [1.52-2.32], and 2.08 [1.68-2.58], respectively). Significant BMI by age interactions were seen for all primary end points (P-interaction<0.05 for each), such that the association of BMI with death or mechanical ventilation was strongest in adults ≤50 years, intermediate in adults 51 to 70 years, and weakest in adults >70 years. Severe obesity (BMI ≥40 kg/m2) was associated with an increased risk of in-hospital death only in those ≤50 years (hazard ratio, 1.36 [1.01-1.84]). In adjusted analyses, higher BMI was associated with dialysis initiation and with venous thromboembolism but not with major adverse cardiac events. CONCLUSIONS: Obese patients are more likely to be hospitalized with COVID-19, and are at higher risk of in-hospital death or mechanical ventilation, in particular, if young (age ≤50 years). Obese patients are also at higher risk for venous thromboembolism and dialysis. These observations support clear public health messaging and rigorous adherence to COVID-19 prevention strategies in all obese individuals regardless of age.

Development of a Portable Tool to Identify Patients With Atrial Fibrillation Using Clinical Notes From the Electronic Medical Record.

BACKGROUND: The electronic medical record contains a wealth of information buried in free text. We created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone. METHODS AND RESULTS: We created 3 data sets from patients with at least one AF billing code from 2010 to 2017: a training set (n=886), an internal validation set from site no. 1 (n=285), and an external validation set from site no. 2 (n=276). A team of clinicians reviewed and adjudicated patients as AF present or absent, which served as the reference standard. We trained 54 algorithms to classify each patient, varying the model, number of features, number of stop words, and the method used to create the feature set. The algorithm with the highest F-score (the harmonic mean of sensitivity and positive predictive value) in the training set was applied to the validation sets. F-scores and area under the receiver operating characteristic curves were compared between site no. 1 and site no. 2 using bootstrapping. Adjudicated AF prevalence was 75.1% at site no. 1 and 86.2% at site no. 2. Among 54 algorithms, the best performing model was logistic regression, using 1000 features, 100 stop words, and term frequency-inverse document frequency method to create the feature set, with sensitivity 92.8%, specificity 93.9%, and an area under the receiver operating characteristic curve of 0.93 in the training set. The performance at site no. 1 was sensitivity 92.5%, specificity 88.7%, with an area under the receiver operating characteristic curve of 0.91. The performance at site no. 2 was sensitivity 89.5%, specificity 71.1%, with an area under the receiver operating characteristic curve of 0.80. The F-score was lower at site no. 2 compared with site no. 1 (92.5% [SD, 1.1%] versus 94.2% [SD, 1.1%]; P<0.001). CONCLUSIONS: We developed a natural language processing algorithm to identify patients with AF using text alone, with >90% F-score at 2 separate sites. This approach allows better use of the clinical narrative and creates an opportunity for precise, high-throughput cohort identification.