system
Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, BACKGROUND, METHODS, RESULTS. Meshes: Adult, Aged, Aged, 80 and over, Female, Hospital Mortality, Humans, Logistic Models, Male, Middle Aged, Risk Factors, Social Class, Surgical Procedures, Operative, United States.
user
Is patient socioeconomic status an independent predictor of operative mortality? Context: To evaluate the impact of patient socioeconomic status (SES) on operative mortality within the context of associated factors. Outcomes disparities among surgical patients are a significant concern. Previous studies have suggested that the correlation between SES and outcomes is attributable to other patient- or hospital-level explanatory factors such as race or hospital wealth. These studies have typically focused on a single explanation for the existence of these inequalities. Analyzing more than 1 million records of the Nationwide Inpatient Sample, we used multimodel inference to evaluate the effects of socioeconomic predictors on surgical mortality. Using univariate and multivariate logistic regression, we find that patient's SES is a strong predictor of operative mortality. Multivariate regressions incorporated many additional hospital- and patient-level covariates. A single-level increase in patient SES results in a mean decrease in operative mortality risk of 7.1%.
assistant
SES at the level of the individual patient has a statistically significant effect on operative mortality. Mortality is greatest among patients in the lowest socioeconomic strata. The effect of patient SES on mortality is not mitigated by other explanatory hospital- or patient-level factors. Final Decision: yes