Key result
Novel CPET-based risk model predicts long-term mortality and readmission in HF with ~0.69 C-index.
Why the study?
Existing international risk prediction models have limitations when applied to the Chinese population, creating a need for a heart failure prognosis model tailored to this group.
Can a multiple Cox regression model accurately predict long-term mortality and readmission risk in Chinese patients with chronic heart failure?
Cohort (n=547)
Open-label
No
Can a multiple Cox regression model accurately predict long-term mortality and readmission risk in Chinese patients with chronic heart failure?
Effect estimate: C-index 0.69 (95% CI 0.65-0.72)
A newly developed nomogram scoring model using 8 clinical variables demonstrated moderate predictive ability for long-term mortality and readmission in Chinese patients with chronic heart failure.
Should not yet change HF risk stratification; leaves open external validation of this CPET model.
Background: Although many risk prediction models have been released internationally, the application of these models in the Chinese population still has some limitations. Aims: The purpose of the study was to establish a heart failure (HF) prognosis model suitable for the Chinese population. Methods: According to the inclusion criteria, we included patients with chronic heart failure (CHF) who were admitted to the Department of Cardiac Rehabilitation of Tongji Hospital from March 2007 to December 2018, recorded each patient's condition and followed up on the patient's re-admission and death. All data sets were randomly divided into derivation and validation cohorts in a ratio of 7/3. Least absolute shrinkage and selection operator regression and Cox regression were used to screen independent predictors; a nomogram chart scoring model was constructed and validated. Results: A total of 547 patients were recruited in this cohort, and the median follow-up time was 519 days. The independent predictors screened out by the derivation cohort included age, atrial fibrillation (AF), percutaneous coronary intervention (PCI), diabetes mellitus (DM), peak oxygen uptake (peak VO 2 ), heart rate at the 8th minute after the cardiopulmonary exercise peaked (HR8min), C-reaction protein(CRP), and uric acid (UA). The C indexes values of the derivation and the validation cohorts were 0.69 and 0.62, respectively, and the calibration curves indicate that the model's predictions were in good agreement with the actual observations. Conclusions: We have developed and validated a multiple Cox regression model to predict long-term mortality and readmission risk of Chinese patients with CHF. Registration Number: ChicTR-TRC-00000235.
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Zhuang et al. (2021) conducted a cohort in Chronic heart failure (CHF) (n=547). A novel risk prediction model incorporating cardiopulmonary exercise testing predicted long-term mortality and readmission in Chinese heart failure patients with a C-index of 0.69.
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