Abstract 11680: Comorbidity and Cognitive Function Predict Efficiency of a Disease Management Program in Reducing Short-Term Readmission in Heart Failure

Abstract

Background: Both comorbidity and cognitive impairment are highly prevalent and predictive of outcomes in heart failure (HF). We sought whether these risk factors could identify patients most likely to benefit from a HF disease management program (DMP) to reduce readmission. Methods: 1363 consecutive HF patients were prospectively followed for 1 month after discharge. Of these, 431 (31%) patients received a DMP (1-month duration, including post-discharge home visits, medication reconciliation, exercise guidance and early clinical review). Primary outcome was all-cause readmission/death at 30-day post-discharge. Charlson comorbidity index (CCI) was calculated based on discharge diagnoses and categorised as mild (CCI≤2), moderate (CCI 3-4) and severe (CCI≥5). Cognitive function was assessed on discharge using the Montreal Cognitive Assessment (MoCA) and classified as normal (MoCA 26-30), low-normal (MoCA 23-25), mildly impaired (MoCA 17-22) and moderate/severely impaired (MoCA≤16). Results: 28% (386/1363) of patients died or were readmitted within 30 days after discharge. Both CCI (relative risk RR=1.06 [95% CI: 1.03, 1.10] per point) and MoCA (RR=0.95 [95% CI: 0.94, 0.96] per point) were significantly predictive of outcome, with a statistically significant interaction (p=0.032). Cross-classification of CCI and MoCA identified a group of high-risk patients (≥mild cognitive impairment and/or severe Charlson comorbidity index) who had a 2.02-fold higher risk of 30-day readmission/death (34%, 309/903) than patients with mild/moderate CCI and without cognitive impairment (17%, 72/426). The effect size of DMP was significantly stronger (p=0.034) among the high-risk patients (RR=0.62 [95% CI: 0.49, 0.77]) compared to low-risk patients (RR=0.98 [95% CI: 0.61, 1.58]). Conclusion: Comorbidities and cognitive impairment strongly predict short-term adverse outcomes in HF and can be used to identify patients who are most likely to benefit from a DMP.