| 刘素娥,苏敏玲,陈淑玲,等.心肌梗死幸存者发病 2周后抑郁状态的影响因素分析[J].安徽医药,2026,30(11):2194-2199. |
| 心肌梗死幸存者发病 2周后抑郁状态的影响因素分析 |
| Influencing factors for depression in acute myocardial infarction survivors two weeks after onset |
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| DOI：10.3969/j.issn.1009-6469.2026.11.014 |
| 中文关键词: 心肌梗死 幸存者 抑郁状态 影响因素 病人健康问卷 -9 预测模型 |
| 英文关键词: Myocardial Infarction Survivors Depression Influence factor Patient Health Questionnaire-9 Prediction model |
| 基金项目:国家自然科学基金( 82300278) |
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| 中文摘要: |
| 目的探究急性心肌梗死( AMI)幸存者发病 2周后抑郁状态的影响因素。方法前瞻性纳入 2018年 1月至 2024年 12月在南方医科大学附属广东省人民医院住院治疗且存活出院的 1 483例 AMI病人为研究对象，在发病后 2周时进行随访，使用病人健康问卷 -9(PHQ-9)量表评估病人状态并计算得分。 PHQ-9量表得分 ≥10分判断为合并抑郁状态，并以合并抑郁状态作为研究终点。根据是否合并抑郁状态将病人分为抑郁组( 239例)和非抑郁组( 1 244例)。采用逐步向后 logistic回归确定影响因素，并绘制受试者操作特征曲线( ROC曲线)评估预测效能。结果抑郁组病人与非抑郁组病人相比，年龄、性别、身体质量指数( BMI)、受教育程度、合并症疾病史比例(充血性心力衰竭、糖尿病、卒中、失眠、吸烟)均差异有统计学意义。经逐步回归确定的影响因素共计 7个，其中 5个危险因素包括:性别［OR=1.43，95%CI:(1.05，1.94)］、糖尿病［OR=1.63，95%CI:(1.20， 2.20)］、卒中［OR=1.79，95%CI:(1.28，2.50)］、失眠［OR=2.89，95%CI:(2.12，3.92)］、吸烟［OR=1.77，95%CI:(1.27，2.46)］，其余 2个则为保护因素，包括:年龄［OR=0.96，95%CI:(0.95，0.98)］和受教育程度(以高中以下为参照，高中［OR=0.58，95%CI:(0.40，0.85)］；高中以上［OR=0.47，95%CI:(0.33，0.66)］。多因素回归模型的 ROC曲线下面积( AUC)为 0.76，95%CI:(0.73，0.79)。结论女性、糖尿病、卒中、失眠、吸烟是 AMI幸存者发病 2周后抑郁状态的危险因素，而年龄和受教育程度则为保护因素。基于此 7个影响因素的多因素预测模型显示出了良好的预测效能。 |
| 英文摘要: |
| Objective To explore the influencing factors for depressive state in survivors of acute myocardial infarction(AMI) two weeks after the onset.Methods A total of 1483 patients with AMI, who were hospitalized and survived in the Guangdong ProvincialPeople's Hospital from January 2018 to December 2024, were prospectively included as the research subjects. Follow-up was conduct-ed two weeks after the onset, and the Patient Health Questionnaire-9(PHQ-9) scale was used to assess the patients'status and calculate the scores. A PHQ-9 score of ≥10 was considered as having a comorbid depressive state, which served as the endpoint of the study. Thepatients were assignedtoa depression group(n=239) ora non-depression group(n=1 244) based on whether they had a depressive state.Stepwise backward logistic regression was used to identify the influencing factors, and the receiver operating characteristic curve(ROC-curve) was drawn to evaluate the predictive efficacy.Results Significant differences were observed between the depression group and the non-depression group in age, gender, body mass index (BMI), educational level, and the proportion of comorbid disease history(con-gestive heart failure, diabetes, stroke, insomnia, and smoking). A total of 7 influencing factors were identified by stepwise regression, ofwhich 5 were risk factors, including gender [OR=1.43, 95%CI: (1.05, 1.94)], diabetes [OR=1.63, 95%CI: (1.20, 2.20)], stroke [OR=1.79, 95%CI:(1.28,2.50)], insomnia[(OR=2.89, 95%CI:(2.12,3.92)],and smoking [OR=1.77,95%CI:(1.27,2.46)],and the other 2 were protec-tive factors, including age [OR=0.96,95%CI:(0.95,0.98)] and educational level(with below high school as reference: high school [OR= 0.58,95%CI:(0.40,0.85)]; above high school [OR=0.47,95%CI:(0.33,0.66)]). The area under the ROC curve(AUC) of the multivariate re-gression model was [0.76,95%CI:(0.73,0.79)].Conclusions Female gender, diabetes, stroke, insomnia, and smoking are risk factorsfor depressive state in AMI survivors two weeks after the onset, while age and educational level are protective factors. The multivariateprediction model based on these 7 influencing factors showed good predictive efficacy. |
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