Predictores de rehospitalización en pacientes con insuficiencia cardíaca congestiva / Predictors of readmission in patients with congestive heart failure

ABSTRACT

Repeated hospitalizations among patients (pts) with congestive heart failure (CHF) are common. Purpose: This retrospective study was designed to determine predictors of readmission. Methods: Inclusion criteria admitted to University Hospital with a primary diagnosis of CHF between 10/1/94-9/30/95 lived in Jefferson county. Exclusions cardiac transplant during study period; major comorbidity (e.g. malignancy, advanced renal failure). Predictors of readmission were determined by stepwise logistic regression analysis and predictor of time to readmission with Cox Proportionate Hazards modeling p<0.05 was considered statistically significant. Results: Mean age of the 237 pts was 66.5 yrs; 56 percent women. Mean left ventricular ejection fraction (LVEF) was 29 percent; 96 percent were in NYHA Class III/IV. Mean length of stay was 5 days; 52 pts (22 percent) had >1 admission. CHF etiologies Ischemic (42 percent), hypertensive (37 percent), idiopathic (12 percent). Demographic characteristics and insurance status did not predict readmission risk. Predictors of readmission in the logistic and Cox models were similar. Increased risk of readmission was associated with myocardial ischemia (logistic OR 42.7), past NYHA Class III and IV (OR 32.8), plasmatic creatinine at discharge (OR 1.9) and continued smoking (OR 3.26). History of CABG was associated with a decreased risk of rehospitalization (OR 0.12). Beta-blocker use was associated with decreased risk, but did not achieve statistical significance. ACE-I use (prescribed in 78 percent of pts), did not contribute to the model. Diabetes Mellitus and a lower LVEF were more frequent in the readmitted group, but they did not predict readmission. Conclusion: CHF pts who have evidence of ischemia, advanced symptoms, renal dysfunction, and who continue to smoke are at increased risk for hospital readmission. Pts with these characteristics should be identified prior to hospital discharge and considered for intensive outpatient intervention