Janani Rangaswami

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BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763–0.809) in female and 0.757 (0.727–0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81–1.16) and 0.94 (0.81–1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD– and heart failure–specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004–0.005] and 0.005 [0.004–0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84–1.20] versus 1.39 [1.14–1.65]; P =0.01). CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

There is limited information describing the characteristics and clinical outcomes of patients infected with coronavirus disease 2019 (COVID‐19) especially those in underserved urban area with minority population in the United States. This is a retrospective single‐center study for patients who were admitted with COVID‐19 infection. Data collection was from 1 March through 24 April 2020. Demographic, clinical, laboratory, and treatment data were presented using descriptive statistics and frequencies. The χ² test and multivariate logistic regression were used to determine association of risk factors and clinical outcomes. A total of 242 inpatients were included with a mean age of 66 ± 14.75 (±standard deviation). A total of 50% were female and 70% were African American. Comorbidities included hypertension (74%), diabetes mellitus (49%), and 19% had either COPD or asthma. Older age was associated with higher risk of inpatient death odds ratio (OR): 1.056 (95% confidence interval [CI]: 1.023‐1.090; P = .001). Inpatient mortality occurred in 70% who needed mechanical ventilation (OR: 29.51; 95% CI: 13.28‐65.60; P < .0001), 58% who required continuous renal replacement therapy/hemodialysis (CRRT/HD) (OR: 6.63; 95% CI: 2.74‐16.05; P < .0001), and 69% who needed vasopressors (OR: 30.64; 95% CI: 13.56‐69.20; P < .0001). Amongst biomarkers of disease severity, only baseline CRP levels (145 ± 116 mg/L) were associated with mortality OR: 1.008 (95% CI: 1.003‐1.012; P = .002). Majority of hospitalized patients had hypertension and diabetes. Older age was an independent risk factor for inpatient mortality. Requirement of mechanical ventilation, vasopressor use, and CRRT/HD was associated significantly with inpatient mortality. Higher baseline CRP was significantly associated with inpatient death.