Basic & Clinical Medicine ›› 2022, Vol. 42 ›› Issue (8): 1169-1175.doi: 10.16352/j.issn.1001-6325.2022.08.1169

• Original Articles •     Next Articles

Construction of a TCM and Western combination model for prognostic evaluation of chronic heart failure based on TCM syndrome elements and machine learning

FAN Jia-sai1,2, DU Yi-fei1,2, XU Jia-ying1,2, CHEN Si-zhen1,2, GAO Yong-hui1,2, REN Jing-yi2*   

  1. 1. School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing 100105;
    2. Heart Failure Center, Department of Cardiology, China-Japan Friendship Hospital, Beijing 100029, China
  • Received:2022-06-03 Revised:2022-06-13 Online:2022-08-05 Published:2022-08-01
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Abstract: Objective To construct a prognostic model of chronic heart failure (CHF) by traditional Chinese medicine (TCM) syndrome elements by machine learning method. Methods Patients with CHF admitted to the Department of Cardiology of China-Japan Friendship Hospital from January 1, 2018 to April 30, 2021 were included, and their demographic data, vital signs, co-morbidities, laboratory tests, echo-cardiographic indicators, TCM syndrome elements and treatment information were collected. The primary end point for this analysis was a model to predict cardiovascular death or hospitalization because of heart failure in one year follow-up. Least absolute shrinkage, selection operator(LASSO) regression and Cox multivariate analysis were used to screen independent risk factors that potentially affect the prognosis of CHF. A nomogram was used to establish a risk prediction model based on TCM syndrome elements. Results Totally 164 patients with an average age of (72.23±14.16) years old and 37.2% male were included in this study. The LASSO screened 9 factors from clinical variables, including coronary heart disease, hypertension, uric acid, N-terminal pro-B type natriuretic peptide (NT-proBNP), left ventricular ejection fraction (LVEF), creatine kinase-myocardial band, myoglobin, Qi deficiency and Yin deficiency. Cox multivariate regression analysis showed that Qi deficiency, hypertension, coronary heart disease, NT-proBNP and LVEF were associated with prognosis in patients with CHF. Conclusions Qi deficiency was an independent predictor of cardiovascular death or heart failure readmission in CHF patients within 1 year. The prognostic model of CHF with integrated Chinese and Western medicine has demonstrated a high accuracy.

Key words: chronic heart failure, syndrome elements, integrated Chinese and Western medicines, machine learning, prognostic model

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