| 谭家儒.重症颅脑损伤患者术后并发迟发性颅内出血的风险预测模型的建立与验证[J].内科急危重症杂志,2026,32(4):359-362 |
| 重症颅脑损伤患者术后并发迟发性颅内出血的风险预测模型的建立与验证 |
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| DOI：10.11768/nkjwzzzz.202401240073 |
| 中文关键词: 重症颅脑损伤 迟发性颅内出血 影响因素 列线图模型 |
| 英文关键词: Severe head injury Delayed intracranial hemorrhage Influencing factors Column chart model |
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| 中文摘要: |
| 摘要 目的：建立重症颅脑损伤患者术后并发迟发性颅内出血相关风险预测模型。方法：选取重症颅脑损伤患者168例为建模组，另选取72例为验证组，根据术后是否出现迟发性颅内出血分为颅内出血组和非颅内出血组。采用多因素Logistic回归分析并筛选患者术后并发迟发性颅内出血的危险因素；基于危险因素通过R 3.6.3软件建立并验证预测患者术后并发迟发性颅内出血的列线图模型。结果：颅内出血组手术时机、高血压史比例、凝血酶时间、脑挫裂伤比例、颅骨骨折比例长于或高于非颅内出血组（P均<0.05）。较长的手术时机和凝血酶时间、有脑挫裂伤和颅骨骨折是重症颅脑损伤患者术后并发迟发性颅内出血的危险因素（P均<0.05）。建模组应用模型的受试者工作特征曲线的曲线下面积为（0.933，95%CI：0.895-0.970），验证组为（0.950，95%CI：0.898-0.983），Hosmer-Lemeshow拟合优度检验显示模型拟合度较好（建模组：χ2=5.645，P=0.687，验证组：χ2=4.788，P=20.780）。结论：建立的预测重症颅脑损伤患者术后并发迟发性颅内出血列线图模型的区分度和一致性良好。 |
| 英文摘要: |
| Abstract Objective: To analyze the factors that may affect delayed intracranial hemorrhage in patients with severe head injury after surgery, and establish a relevant column chart model. Methods: A total of 168 patients with severe craniocerebral injury were selected as the modeling group, and 72 patients were selected as the validation group. Patients were divided into an intracranial hemorrhage group and a non-intracranial hemorrhage group based on whether delayed intracranial hemorrhage occurred postoperatively. Multivariate logistic regression analysis was used to identify risk factors for postoperative delayed intracranial hemorrhage. Based on the identified risk factors, a nomogram prediction model was established and validated using R 3.6.3 software. Results: The surgical timing, proportion of hypertension history, thrombin time, proportion of brain contusions and lacerations, and proportion of skull fractures in the intracranial hemorrhage group were longer or higher than those in the non intracranial hemorrhage group (P< 0.05). Long surgical timing and thrombin time, brain contusions and lacerations, and skull fractures were risk factors for postoperative delayed intracranial hemorrhage in patients with severe head injury (P< 0.05). The area under the model curve and 95% CI of the modeling group were (0.933, 0.895-0.970), while those in the validation group were (0.950, 0.898-0.983). Hosmer-Lemeshow goodness-of-fit test results indicated that the modeling group had χ2=5.645, P= 20.687, and the validation group had χ2=4.788, P= 20.780. Conclusion: The established column chart model for predicting postoperative delayed intracranial hemorrhage in patients with severe head injury has good discrimination and consistency. |
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