冠心病患者经皮冠脉介入术后便秘风险列线图预测模型的构建及验证

doi:10.20047/j.issn1673-7210.2022.26.03

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Abstract Objective To construct a nomogram prediction model for the risk of constipation in patients with coronary heart disease after percutaneous coronary intervention, and to conduct internal verification. Methods The clinical data of 398 patients with coronary heart disease who underwent percutaneous coronary intervention in the Department of Cardiology, the Second Affiliated Hospital of Air Force Military Medical University from January 2019 to December 2020 were collected retrospectively. The patients were divided into normal defecation group (262 cases) and constipation group (136 cases) according to whether constipation occurred. The differences of clinical data between the two groups were compared, and the influencing factors of constipation were screened by logistic regression model. R 3.4.3 software was used to construct a nomogram prediction model for the risk of constipation in patients with coronary heart disease after percutaneous coronary intervention, and the Bootstrap method and Hosmer-Lemeshow goodness-of-fit test were used to verify the model internally. Receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of the model. Results In the constipation group, the proportions of age > 60 years, Killip grade Ⅲ-Ⅳ, opioid use after surgery, number of stents implanted > 3, anxiety/depression, diabetes mellitus, and smoking history were higher than those in the normal defecation group, and the proportion of regular exercise was lower than that in the normal defecation group, and the differences were statistically significant (P ＜ 0.05). Logistic regression analysis showed that age > 60 years old, Killip grade Ⅲ-Ⅳ, opioid use after surgery, anxiety/depression, and diabetes mellitus were independent risk factors for constipation after percutaneous coronary intervention (OR = 2.945, 4.859, 3.624, 3.082, 2.770, P ＜ 0.05), regular exercise was a protective factor (OR = 0.447, P ＜ 0.05). The internal validation results of the nomogram prediction model showed that the observed curve was basically consistent with the acceptable curve and the ideal curve (P ＞ 0.05). The area under ROC curve of the nomogram prediction model was 0.788 (95%CI: 0.742-0.833, P < 0.05). Conclusion The nomogram prediction model for the risk of constipation in patients with coronary heart disease after percutaneous coronary intervention has a good degree of calibration and discrimination, which is helpful for medical staff to individualize the risk of constipation in patients.

Key words： Coronary heart disease Percutaneous coronary intervention Constipation Nomograms Prediction

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	WEN Fangfang1 DU Haiwei2 GUO Xiaolan1 XI Xiaoli1 HU Jianqiang1 CHENG Miaomiao1▲

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WEN Fangfang1 DU Haiwei2 GUO Xiaolan1 XI Xiaoli1 HU Jianqiang1 CHENG Miaomiao1▲. Construction and validation of a nomogram prediction model for the risk of constipation in patients with coronary heart disease after percutaneous coronary intervention[J]. 中国医药导报, 2022, 19(26): 15-18,33.

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https://www.yiyaodaobao.com.cn/EN/10.20047/j.issn1673-7210.2022.26.03 OR https://www.yiyaodaobao.com.cn/EN/Y2022/V19/I26/15

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