• 基于临床特征可构建急性心肌梗死患者室壁瘤形成的预测模型
  • 王莹莹.基于临床特征可构建急性心肌梗死患者室壁瘤形成的预测模型[J].内科急危重症杂志,2022,28(6):492-495
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    DOI:10.11768/nkjwzzzz20220613
    中文关键词:  急性心肌梗死  室壁瘤  影响因素  预测模型
    英文关键词:
    基金项目:河北省医学课题项目(No:202004A028)
    作者单位E-mail
    王莹莹 秦皇岛市第一医院 dhn01269@21cn.com 
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    中文摘要:
          摘要 目的:分析急性心肌梗死(AMI)患者室壁瘤形成的影响因素,建立预测模型。方法:收集312例AMI患者,统计室壁瘤发生情况,分为室壁瘤组(78例)与非室壁瘤组(234例),采用单、多因素方式分析AMI患者室壁瘤形成的影响因素,并建立预测模型,采用似然比卡方、Wald卡方、拟合优度检验、受试者工作特征(ROC)曲线及曲线下面积(AUC)评价模型及其预测价值。结果:312例AMI患者室壁瘤发生率为25%。Logistic回归方程显示,年龄≥60岁、吸烟史、前壁心肌梗死、前降支(LAD)近中段病变、≥4个相邻导联ST段抬高、胸痛时间≥24h为AMI患者室壁瘤形成的独立危险因素(OR=60.289、73.931、52.227、61.674、64.166、60.134,P均<0.05)。Logistic回归模型评价显示,模型建立具有统计学意义,模型构建有效,模型拟合效果较好。采用Logistic回归模型统计分析数据集,预测AMI患者室壁瘤形成的AUC为0.902,敏感度为83.33%,特异性为92.91%。结论:AMI患者室壁瘤发生率为25%,主要与吸烟史、年龄、ST段抬高、LAD近中段病变、胸痛时间、前壁心肌梗死有关,据此建立Logistic回归预测模型预测室壁瘤形成价值高。
    英文摘要:
          Abstract Objective: To analyze the factors influencing ventricular wall tumor formation in AMI patients with acute myocardial infarction and to establish a prediction model. Methods: A total of 312 patients with AMI were collected, and the occurrence of ventricular wall tumors was counted and divided into ventricular wall tumor rent (78 cases) and non-ventricular wall tumor (234 cases) groups . The factors influencing the formation of ventricular wall tumors in AMI patients were analyzed in a single- and multifactorial manner, and prediction models were developed, and the likelihood ratio chi-square, Wald chi-square, goodness-of-fit test, subject operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the models and their predictive value. Results: The incidence of ventricular wall tumors was 25% in 312 patients with AMI. Logistic regression equation showed that age ≥60 years, history of smoking, anterior wall myocardial infarction, proximal to mid-lateral lesions of the anterior descending branch (LAD), ST-segment elevation in ≥4 adjacent leads, and duration of chest pain ≥24h were independent risk factors for ventricular wall tumor formation in patients with AMI (OR=60.289, 73.931, 52.227, 61.674, 64.166, 60.134, all P< 0.05). Logistic regression model evaluation showed that model building was statistically significant, model construction was valid, and model fit was good. The statistical analysis of the data set using the logistic regression model predicted an AUC of 0.902, a sensitivity of 83.33%, and a specificity of 92.91% for the formation of ventricular wall tumors in patients with AMI. Conclusion: The incidence of ventricular wall tumor in AMI patients was 25.00%, which was mainly associated with smoking history, age, ST-segment elevation, proximal to mid-LAD lesion, duration of chest pain, and anterior wall myocardial infarction, and a logistic regression prediction model was established to predict ventricular wall tumor formation with high value.