| Summary: | Guangda He,1 Runqing Ji,1 Xiqian Huo,1 Xiaoming Su,1 Jinzhuo Ge,1 Wei Li,1 Lubi Lei,1 Boxuan Pu,1 Aoxi Tian,1 Jiamin Liu,1 Lihua Zhang,1 Yongjian Wu2 On behalf of the China PEACE Collaborative Group1National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China; 2Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of ChinaCorrespondence: Lihua Zhang, National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, 167 Beilishi Road, Beijing, 100037, People’s Republic of China, Email zhanglihua@fuwai.com Yongjian Wu, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, People’s Republic of China, Email wuyongjian@fuwai.comBackground: Inflammation contributes to the progression of heart failure (HF). However, long-term inflammatory trajectories and their associations with outcomes in patients with acute HF remain unclear.Methods: Data was obtained from the China Patient-Centered Evaluative Assessment of Cardiac Events Prospective Heart Failure Study, and high-sensitivity C-reactive protein (hsCRP) was used to reflect the inflammatory level. Only patients who survived over 12-month and had hsCRP data at admission, 1-, and 12-month after discharge were included. The latent class trajectory modeling was used to characterize hsCRP trajectories. Multivariable Cox regression models were used to explore the association between hsCRP trajectories and following mortality.Results: Totally, 1281 patients with a median 4.77 (interquartile range [IQR]: 4.24– 5.07) years follow-up were included. The median age was 64 years (IQR: 54– 73 years); 453 (35.4%) were female. Four distinct inflammatory trajectories were characterized: persistently low (n = 419, 32.7%), very high-marked decrease (n = 99, 7.7%), persistently high (n = 649, 50.7%), and persistently very high (n = 114, 8.9%). Compared with the persistently low trajectory, the all-cause mortality was increased in a graded pattern in the persistently high (hazard ratio [HR]: 1.59, 95% confidence interval [CI]: 1.23– 2.07) and persistently very high (HR: 2.56, 95% CI: 1.83– 3.70) trajectories; nevertheless, the mortality was not significantly increased in very high-marked decrease trajectory (HR: 0.94, 95% CI: 0.57– 1.54).Conclusion: Four distinct inflammatory trajectories were identified among patients with acute HF who survived over 12-month. Patients with persistently high and very high trajectories had significantly higher mortality than those with the persistently low trajectory.Keywords: heart failure, high-sensitivity C-reactive protein, trajectory, latent class trajectory modeling, mortality
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