The impact of hospital safety-net burden on mortality and readmission after CABG surgery.

BACKGROUND AND AIM: Safety-net hospitals (SNHs) serve high proportions of uninsured and Medicaid patients. Data conflict as to the impact of hospital safety-net status on perioperative complications. Our goal was to assess the effect of hospital safety-net burden on mortality and readmission following coronary artery bypass graft (CABG) surgery. METHODS: A retrospective analysis was performed using five State Inpatient Databases (2007-2014) for isolated CABG surgery. High, medium, and low burden hospitals were those with the highest, middle, and lowest tertiles of uninsured and Medicaid admissions, respectively. We compared patient demographics and hospital characteristics by safety-net status. Multivariable logistic regression models assessed adjusted odds of in-hospital mortality and 30- and 90-day readmission. RESULTS: About 304 080 patients were included in our analysis. On univariate analysis, high burden hospitals had higher inpatient mortality (2.06% vs 1.71%; P < .001) and 30 day- (16.3% vs 15.3%; P < .001) and 90-day readmission rates (24.6% vs 23.0%; P < .001). On multivariate analysis, high-burden status was not associated with significantly increased adjusted odds of inpatient mortality (OR, 1.047; 95% CI, 0.878-1.249), or readmission at 30 (OR, 1.035; 95% CI, 0.958-1.118) or 90 days (OR, 1.040; 95% CI, 0.968-1.117). CONCLUSION: SNHs do not have worse mortality and readmission outcomes following CABG, after adjusting for patient and hospital characteristics. These findings are reassuring regarding the quality of cardiac surgery care provided to underinsured patient groups. More research is needed to further elucidate trends in outcomes.

Predictor Biomarkers of Nonelective Hospital Readmission and Mortality in Malnourished Hospitalized Older Adults.

BACKGROUND: 90-day mortality and rehospitalizations are important hospital quality metrics. Biomarkers that predict these outcomes among malnourished hospitalized patients could identify those at risk and help direct care plans. OBJECTIVES: To identify biomarkers that predict 90-day (primary) and 30-day (secondary) mortality or nonelective rehospitalization. DESIGN AND PARTICIPANTS: An analysis of the ability of biomarkers to predict 90- and 30-day mortality and rehospitalization among malnourished hospitalized patients. SETTING: 52 blood biomarkers were measured in 193 participants in NOURISH, a randomized trial that determined the effects of a nutritional supplement on 90-day readmission and death in patients >65 years. Composite outcomes were defined as readmission or death over 90-days or 30-days. Univariate Cox Proportional Hazards models were used to select best predictors of outcomes. Markers with the strongest association were included in multivariate stepwise regression. Final model of hospital readmission or death was derived using stepwise selection. MEASUREMENTS: Nutritional, inflammatory, hormonal and muscle biomarkers. RESULTS: Mean age was 76 years, 51% were men. In univariate models, 10 biomarkers were significantly associated with 90-day outcomes and 4 biomarkers with 30-day outcomes. In multivariate stepwise selection, glutamate, hydroxyproline, tau-methylhistidine levels, and sex were associated with death and readmission within 90-days. In stepwise selection, age-adjusted model that included sex and these 3 amino-acids demonstrated moderate discriminating ability over 90-days (C-statistic 0.68 (95%CI 0.61, 0.75); age-adjusted model that included sex, hydroxyproline and Charlson Comorbidity Index was predictive of 30-day outcomes (C-statistic 0.76 (95%CI 0.68, 0.85). CONCLUSIONS: Baseline glutamate, hydroxyproline, and tau-methylhistidine levels, along with sex and age, predict risk of 90-day mortality and nonelective readmission in malnourished hospitalized older patients. This biomarker set should be further validated in prospective studies and could be useful in prognostication of malnourished hospitalized patients and guiding in-hospital care.