Objective. We compared single-and multi-item measures of general self-rated health (GSRH) to predict mortality and clinical events a large population of veteran patients. Data Source/Study Setting. We analyzed prospective cohort data collected from 21,732 patients as part of the Veterans Affairs Ambulatory Care Quality Improvement Project (ACQUIP), a randomized controlled trial investigating quality-of-care interventions. Study Design. We created an age-adjusted, logistic regression model for each predictor and outcome combination, and estimated the odds of events by response category of the GSRH question and compared the discriminative ability of the predictors by developing receiver operator characteristic curves and comparing the associated area under the curve (AUC)/c-statistic for the single-and multi-item measures. Data Collection/Extraction Methods. All patients were sent a baseline assessment that included a multi-item measure of general health, the 36-item Medical Outcomes Study Short Form (SF-36), and an inventory of comorbid conditions. We compared the predictive and discriminative ability of the GSRH to the SF-36 physical component score (PCS), the mental component score (MCS), and the Seattle index of comorbidity (SIC). The GSRH is an item included in the SF-36, with the wording: ''In general, would you say your health is: Excellent, Very Good, Good, Fair, Poor?'' Principal Findings. The GSRH, PCS, and SIC had comparable AUC for predicting mortality (AUC 0.74, 0.73, and 0.73, respectively); hospitalization (AUC 0.63, 0.64, and 0.60, respectively); and high outpatient use (AUC 0.61, 0.61, and 0.60, respectively). The MCS had statistically poorer discriminatory performance for mortality and hospitalization than any other other predictors ( po.001). Conclusions. The GSRH response categories can be used to stratify patients with varying risks for adverse outcomes. Patients reporting ''poor'' health are at significantly greater odds of dying or requiring health care resources compared with their peers. The GSRH, collectable at the point of care, is comparable with longer instruments.

Key Points Question What are the risk factors associated with hospitalization, mechanical ventilation, and death among patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection? Findings In this national cohort study of 88 747 veterans tested for SARS-CoV-2, hospitalization, mechanical ventilation, and mortality were significantly higher in patients with positive SARS-CoV-2 test results than among those with negative test results. Significant risk factors for mortality included older age, high regional coronavirus disease 2019 burden, higher Charlson Comorbidity Index score, fever, dyspnea, and abnormal results in many routine laboratory tests; however, obesity, Black race, Hispanic ethnicity, chronic obstructive pulmonary disease, hypertension, and smoking were not associated with mortality. Meaning In this study, most deaths from SARS-CoV-2 occurred in patients with age of 50 years or older, male sex, and greater comorbidity burden.

Background — Although patient-reported health status measures have been used as end points in clinical trials, they are rarely used in other settings. Demonstrating that they independently predict mortality and hospitalizations among outpatients with coronary disease could emphasize their clinical value. Methods and Results — This study evaluated the prognostic utility of the Seattle Angina Questionnaire (SAQ), a disease-specific health status measure for patients with coronary artery disease. Patients were enrolled in a prospective cohort study from 6 Veterans Affairs General Internal Medicine Clinics. All patients reporting coronary artery disease who completed a SAQ and had 1 year of follow-up were analyzed (n=5558). SAQ predictor variables were the physical limitation, angina stability, angina frequency, and quality-of-life scores. The primary outcome was 1-year all-cause mortality, and a secondary outcome was hospitalization for acute coronary syndrome (ACS). Lower SAQ scores were associated with increased risks of mortality and ACS admissions. Prognostic models controlling for demographic and clinical characteristics demonstrated significant independent mortality risk with lower SAQ physical limitation scores; odds ratios for mild, moderate, and severe limitation were 1.5, 2.0, and 4.0 versus minimal limitation ( P <0.001). Odds ratios for mild, moderate, and severe angina frequency were 0.8, 1.2, and 1.6 ( P =0.078). The odds ratios for ACS admission among those with mild, moderate, and severe angina frequency were 1.4, 2.0, and 2.2, respectively ( P =0.016). Conclusions — SAQ scores are independently associated with 1-year mortality and ACS among outpatients with coronary disease and may serve a valuable role in the risk stratification of such patients.