Predicting Heart Failure Outcomes Using Patient-Reported Health Status: Real-World Validation of the KCCQ-12.

Area of Science:

• Cardiology
• Clinical Outcomes Research
• Health Services Research

Background:

• The Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) is a patient-reported outcome measure for heart failure.
• Its predictive utility in real-world clinical practice for hospitalizations and mortality is not well-established, unlike in clinical trials.

Purpose of the Study:

• To evaluate the predictive value of the KCCQ-12 for hospitalizations and mortality in patients receiving outpatient heart failure care.
• To assess the KCCQ-12 Overall Summary (KCCQ-OS) score's performance as a prognostic indicator.

Main Methods:

• A cohort study involving 4,406 patients in heart failure clinics from July 2019 to March 2024.
• Primary exposure: KCCQ-OS score. Primary outcomes: 90-day hospitalization and cumulative mortality.
• Statistical analysis included logistic regression, Cox proportional hazards models, and machine learning (XGBoost, random survival forest).

Main Results:

• Among 2,888 (66%) patients who completed the KCCQ-12, a median KCCQ-OS score of 59.4 was observed.
• Scores <25 were associated with significantly higher adjusted risks of 90-day hospitalization (OR: 3.49) and cumulative mortality (HR: 3.09).
• KCCQ-OS was the most important predictor in machine learning models for both outcomes. Noncompletion also predicted worse outcomes.

Conclusions:

• Lower KCCQ-OS scores in outpatient heart failure care strongly correlate with increased hospitalizations and mortality.
• The KCCQ-12, including its noncompletion status, serves as a valuable prognostic tool in routine clinical practice.
• The KCCQ-OS score demonstrated dominant predictive power in machine learning analyses for key adverse events.