Zhuang Bo, Shen Ting, Li Dejie, Jiang Yumei, Li Guanghe, Luo Qian, Jin Yishan, Shan Ziwei, Che Lin, Wang Lemin, Zheng Liang, Shen Yuqin
Department of Rehabilitation, Tongji Hospital Affiliated to Tongji University, Tongji University School of Medicine, Shanghai, China.
Department of Cardiology, Tongji Hospital Affiliated to Tongji University, Tongji University School of Medicine, Shanghai, China.
Front Cardiovasc Med. 2021 Nov 18;8:761605. doi: 10.3389/fcvm.2021.761605. eCollection 2021.
Although many risk prediction models have been released internationally, the application of these models in the Chinese population still has some limitations. The purpose of the study was to establish a heart failure (HF) prognosis model suitable for the Chinese population. 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. 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), 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. We have developed and validated a multiple Cox regression model to predict long-term mortality and readmission risk of Chinese patients with CHF. ChicTR-TRC-00000235.
尽管国际上已发布了许多风险预测模型，但这些模型在中国人群中的应用仍存在一些局限性。本研究的目的是建立一个适用于中国人群的心力衰竭（HF）预后模型。根据纳入标准，我们纳入了2007年3月至2018年12月在同济医院心脏康复科住院的慢性心力衰竭（CHF）患者，记录每位患者的病情，并对患者的再次入院和死亡情况进行随访。所有数据集按7/3的比例随机分为推导队列和验证队列。使用最小绝对收缩和选择算子回归以及Cox回归筛选独立预测因素；构建并验证了列线图评分模型。该队列共纳入547例患者，中位随访时间为519天。推导队列筛选出的独立预测因素包括年龄、心房颤动（AF）、经皮冠状动脉介入治疗（PCI）、糖尿病（DM）、峰值摄氧量（peak VO）、心肺运动峰值后第8分钟心率（HR8min）、C反应蛋白（CRP）和尿酸（UA）。推导队列和验证队列的C指数值分别为0.69和0.62，校准曲线表明模型预测与实际观察结果吻合良好。我们开发并验证了一个多重Cox回归模型，以预测中国CHF患者的长期死亡率和再次入院风险。ChicTR-TRC-00000235。
