Triage After Hospitalization With Advanced Heart Failure

Objectives Identifying high-risk heart failure (HF) patients at hospital discharge may allow more effective triage to management strategies. Background HF severity at presentation predicts outcomes, but the prognostic importance of clinical status changes due to interventions is less well described. Methods Predictive models using variables obtained during hospitalization were created using data from ESCAPE and internally validated by bootstrapping method. Model coefficients were converted to an additive risk score. Additionally, data from the FIRST (Flolan International Randomized Survival Trial) was used to externally validate this model. Results Patients discharged with complete data (n=423) had 6-month mortality and death or rehospitalization rates of 18.7% and 64%. Discharge risk factors for mortality included BNP, per doubling (Hazard Ration [HR]: 1.42, 95% confidence interval [CI]: 1.15–1.75), cardiopulmonary resuscitation or mechanical ventilation during hospitalization (HR: 2.54, 95% CI: 1.12–5.78), blood urea nitrogen, per 20-U increase) (HR: 1.22, 95% CI: 0.96–1.55), serum sodium, per unit increase (HR: 0.93, 95% CI: 0.87–0.99), age >70 (HR: 1.05, 95% CI: 0.51–2.17), daily loop diuretic, furosemide equivalents >240 mg (HR: 1.49, 95% CI: 0.68–3.26), lack of beta-blocker (HR: 1.28, 95% CI: 0.68–2.41), and 6-minute walk, per 100 feet increase (HR: 0.955, 95% CI: 0.99–1.00; c index 0.76. A simplified discharge score discriminated mortality risk from 5% (score=0) to 94% (score =8). Bootstrap validation demonstrated good internal validation of the model (c index 0.78, 95% CI: 0.68–0.83). Conclusions The ESCAPE discharge risk model and score refine risk assessment after inhospital therapy for advanced decompensated systolic HF, allowing clinicians to focus surveillance and triage for early life-saving interventions in this high-risk population.