| 沈 潇,董 皓,周雨森,晏煜昊,张培哲,俞 臻,汤 涌.急性心肌梗死患者应激性高血糖风险的列线图预测模型构建及评价[J].,2024,(21):4182-4184 |
| 急性心肌梗死患者应激性高血糖风险的列线图预测模型构建及评价 |
| Construction and Evaluation of a Nomogram Prediction Model for the Risk of Stress Hyperglycemia in Patients with Acute Myocardial Infarction |
| 投稿时间：2024-05-24 修订日期：2024-06-18 |
| DOI：10.13241/j.cnki.pmb.2024.21.039 |
| 中文关键词: 急性心肌梗死 应激性高血糖 列线图 预测价值 |
| 英文关键词: Acute myocardial infarction Stress hyperglycemia Nomogram Predictive value |
| 基金项目:国家自然科学基金项目（81670326） |
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| 摘要点击次数: 30 |
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| 中文摘要: |
| 摘要 目的：分析急性心肌梗死（AMI）患者应激性高血糖（SHG）发生风险的影响因素，构建列线图预测模型并进行评价。方法：298例AMI患者根据是否发生SHG分为发生组（n=92）和未发生组（n=206）。多因素Logistic回归模型分析AMI患者发生SHG的影响因素，构建影响因素的列线图预测模型，受试者工作特征（ROC）曲线分析列线图预测模型对AMI患者发生SHG的预测价值。结果：女性、高体质量指数（BMI）、心功能Killip分级≥Ⅱ级、高龄、高hs-CRP、高Cys-C为AMI患者发生SHG的独立危险因素（P<0.05）。ROC曲线分析结果显示，性别、年龄、BMI、心功能Killip分级、hs-CRP、Cys-C水平及列线图预测模型的曲线下面积（AUC）分别为0.609、0.711、0.826、0.618、0.768、0.774、0.953。内部验证结果显示，Bias-corrected预测曲线与Ideal线基本重合，C-index为0.905，表明该模型具有良好的预测能力。决策曲线显示，该模型的阈值概率范围为0.01~0.97，其净收益率>0，高于两条无效线。结论：心功能Killip分级≥Ⅱ级、高龄、女性、高BMI、高hs-CRP、高Cys-C为AMI患者发生SHG的独立危险因素。基于上述因素构建的列线图预测模型的预测效能较单一指标更佳。 |
| 英文摘要: |
| ABSTRACT Objective: To analyzed the influencing factors of the risk of stress hyperglycemia (SHG) risk in patients with acute myocardial infarction (AMI), construction and evaluation of nomogram prediction model. Methods: 298 AMI patients were divided into occurrence group (n=92) and non-occurrence group (n=206) according to whether SHG occurred. The influencing factors of SHG in AMI patients wewe analyzed by multivariate Logistic regression model, and a nomogram prediction model of influencing factors was constructed, the predictive value of the nomogram prediction model for SHG in AMI patients was analyzed by receiver operating characteristic(ROC) curve. Results: Female, high body mass index (BMI), cardiac function Killip classification≥class II, advanced age, high hs-CRP and high Cys-C were independent risk factors for SHG in AMI patients (P<0.05). The results of ROC curve analysis showed that, the area under the curve(AUC) of gender, age, BMI, cardiac function Killip classification, hs-CRP, Cys-C levels and nomogram prediction model were 0.609, 0.711, 0.826, 0.618, 0.768, 0.774 and 0.953 respectively. The internal validation results showed that, the Bias-corrected prediction curve basically coincided with the Ideal line, and the C-index was 0.905, which indicated that the model had good predictive ability. The decision curve shows that, the threshold probability of the model ranges was 0.01~0.97, and its net return was>0, which was higher than the two null lines. Conclusion: Cardiac function Killip grade≥II, advanced age, female, high BMI, high hs-CRP and high Cys-C were independent risk factors for SHG in AMI patients. The prediction ability of the nomogram model based on the above factors is better than that of a single index. |
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