Predictive factors for heart failure after percutaneous coronary intervention
10.3760/cma.j.cn431274-20221225-01350
- VernacularTitle:经皮冠状动脉介入术后心力衰竭的危险因素
- Author:
Lu HUANG
1
;
Chaolun JIN
;
Mengna FU
;
Jinhuan CHEN
Author Information
1. 杭州市第九人民医院心内科，杭州 311225
- Keywords:
Percutaneous coronary intervention;
Heart failure
- From:
Journal of Chinese Physician
2023;25(10):1525-1529
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the factors predictive of heart failure developing during hospital stay after undergoing percutaneous coronary intervention (PCI).Methods:A retrospective analysis was performed on 534 patients with coronary heart disease who underwent PCI treatment at Hangzhou Ninth People′s Hospital from January 2017 to September 2022. The patients were divided into two groups according to whether heart failure occurred after the operation: a heart failure group consisting of 51 patients and a control group consisting of 483 patients. Univariate comparison and multivariate analysis were performed on factors that could lead to heart failure between the two groups, and a prediction model was established.Results:Univariate analysis showed that there were significant differences in age at admission, presence of cerebral infarction, presence of hypertension, New York Heart Association (NYHA) heart function classification, left ventricular ejection fraction (LVEF), serum albumin, neutrophil-to-lymphocyte ratio (dNLR), D-dimer, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels between the PCI postoperative heart failure group and the control group (all P<0.05). Multivariate analysis showed that age ≥60 years, LVEF<40%, presence of cerebral infarction, NYHA heart function classification Ⅱ/Ⅲ, serum albumin<40.15 g/L, and dNLR≥2.30 were independent risk factors for the development of heart failure during hospitalization after PCI (all P<0.05). Conclusions:Age, LVEF, presence of cerebral infarction, NYHA heart function classification, serum albumin, and dNLR can all affect the occurrence of heart failure during hospitalization after PCI for coronary heart disease. Establishing a prediction model based on these indicators can provide guidance for clinical practice.
