Patients with KCCQ-OS scores <25 had higher risks of 90-day hospitalization (OR 3.49; 95% CI 2.50-4.90) and cumulative mortality (HR 3.09; 95% CI 2.29-4.17) compared to those with scores ≥75.
Cohort (n=4,406)
Yes
Does the KCCQ-12 Overall Summary score predict 90-day hospitalization and cumulative mortality in outpatient heart failure patients?
Odds Ratio: 3.49 (95% CI 2.5–4.9)
Background: The Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12), a patient-reported outcome measure for adults with heart failure, is associated with hospitalizations and mortality in clinical trials. Curated datasets from controlled trials differ substantially from pragmatic data collected from real-world settings, however, and few data exist on the KCCQ-12’s predictive utility in clinical practice. Objectives: To evaluate the predictive utility of the KCCQ-12 for hospitalizations and mortality when administered during outpatient heart failure care. Methods: We conducted a cohort study of patients assigned the KCCQ-12 in heart failure clinics from July 2019 through March 2024. The primary exposure was KCCQ-12 Overall Summary (KCCQ-OS) score. The primary outcomes were 90-day hospitalization and cumulative mortality. Multivariable-adjusted associations were assessed using logistic regression and Cox proportional hazards models. Gradient boosting (XGBoost) and random survival forest (RSF) machine learning models were used to evaluate KCCQ-OS feature importance in predicting 90-day hospitalizations and cumulative mortality, respectively. Results: Among 4,406 patients assigned the KCCQ-12, 2,888 (66%) completed at least one questionnaire. The median KCCQ-OS score was 59.4 (IQR 35.4–81.8). Patients with KCCQ-OS scores <25 had higher adjusted risks of 90-day hospitalization (OR 3.49, 95% CI 2.50-4.90) and cumulative mortality (HR 3.09, 95% CI 2.29–4.17) compared to those with scores ≥75. The KCCQ-OS score was the most important feature for predicting 90-day hospitalizations in the XGBoost model (AUC 0.760, 95% CI 0.706–0.811) and the most important feature for predicting cumulative mortality in the random survival forest model (C-index 0.783, 95% CI 0.742–0.824) compared to other clinical, demographic, and laboratory variables. KCCQ-12 non-completion was independently associated with increased 90-day hospitalization (OR 1.72, 95% CI 1.46–2.02) and 1-year mortality (HR 1.52, 95% CI 1.25–1.84) after adjusting for all variables in the primary analysis. Conclusions: In outpatient heart failure care, lower KCCQ-OS scores were strongly associated with increased hospitalizations and mortality, with the greatest risk among patients with scores <25. Non-completion of the KCCQ-12 was itself associated with worse outcomes. The KCCQ-OS score was the dominant predictor of 90-day hospitalizations and cumulative mortality in machine learning models, supporting the KCCQ-12 as a prognostic tool in routine clinical practice.
“Vanderbilt has long had a focus on personalized medicine. This is kind of the apex of it, because these surveys focus on outcomes that matter to patients. In patients with heart failure, for example, the survey asks whether they can walk to their mailbox, spend time with friends and other very relevant items to their daily lives.”
El‐Sabawi et al. (Sun,) conducted a cohort in heart failure (n=4,406). KCCQ-OS score <25 vs. KCCQ-OS score ≥75 was evaluated on 90-day hospitalization (OR 3.49, 95% CI 2.50-4.90). Patients with KCCQ-OS scores <25 had higher risks of 90-day hospitalization (OR 3.49; 95% CI 2.50-4.90) and cumulative mortality (HR 3.09; 95% CI 2.29-4.17) compared to those with scores ≥75.