收稿日期: 2024-11-18
网络出版日期: 2025-05-21
基金资助
河南省医学科技攻关计划联合共建项目(LHGJ20220229)
Development and validation of a predictive model for delayed neurological sequelae in acute carbon monoxide poisoning
Received date: 2024-11-18
Online published: 2025-05-21
目的 构建急性一氧化碳中毒（ACMP）迟发性神经后遗症（DNS）的预测模型，并验证其效能。 方法 回顾性分析183例ACMP患者的一般资料，经多因素logistic回归模型分析其发生DNS的影响因素；建立对应的预测模型并验证其效能。 结果 多因素logistic回归模型显示，年龄、吸烟史、重度中毒、血乳酸、中毒至高压氧治疗时间、肺部感染是ACMP发生DNS的独立危险因素（P < 0.05）；该模型预测开发集ACMP发生DNS的曲线下面积（AUC）为0.933，灵敏度为94.12%，特异度为89.77%，预测检验集ACMP发生DNS的AUC为0.906，灵敏度为90.00%，特异度为92.68%；Hosmer-Lemeshow检验显示，该模型预测开发集、检验集ACMP发生DNS的概率与实际概率差异均无统计学意义（P > 0.05）；开发集、检验集中预测模型在分别在风险阈值0.11 ~ 0.98、0.12 ~ 0.92范围内获取临床净收益。 结论 年龄、吸烟史、重度中毒、血乳酸、中毒至高压氧治疗时间、肺部感染是ACMP发生DNS的独立危险因素，对应的预测模型经验证临床效能良好。
李少林 , 马晓红 , 张德河 , 宋鹏 . 急性一氧化碳中毒迟发性神经后遗症预测模型构建与效能验证[J]. 实用医学杂志, 2025 , 41(10) : 1533 -1539 . DOI: 10.3969/j.issn.1006-5725.2025.10.015
Objective To construct a predictive model for delayed neurological sequelae （DNS） following acute carbon monoxide poisoning （ACMP） and to verify its efficacy. Methods A retrospective analysis of the general data of 183 patients with ACMP was conducted. The factors influencing the occurrence of DNS were analyzed using a multivariate Logistic regression model. A corresponding predictive model was then established and its efficacy was verified. Results The multivariate logistic regression model showed that age， smoking history， severe poisoning， blood lactate， time from poisoning to hyperbaric oxygen therapy， and pulmonary infection were independent risk factors for DNS following ACMP （P < 0.05）. The area under the curve （AUC） of the model for predicting DNS in the development set was 0.933， with a sensitivity of 94.12% and specificity of 89.77%. In the validation set， the AUC was 0.906， with a sensitivity of 90.00% and specificity of 92.68%. The Hosmer-Lemeshow test showed that the predicted probabilities of DNS in both the development and validation sets were not significantly different from the actual probabilities （P > 0.05）. The predictive model achieved clinical net benefit within the risk threshold ranges of 0.11 ~ 0.98 for the development set and 0.12 ~ 0.92 for the validation set. Conclusions Age， smoking history， severe poisoning， blood lactate， time from poisoning to hyperbaric oxygen therapy， and pulmonary infection are independent risk factors for DNS following ACMP. The corresponding predictive model has been verified to have good clinical efficacy.
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