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作 者:卓健伟 刘国东 曹鑫意 疏龙飞 王玉海 Zhuo Jianwei;Liu Guodong;Cao Xinyi;Shu Longfei;Wang Yuhai(Department of Neurosurgery,The 904st Hospital of the Joint Service Support Force of the PLA,Wuxi 214044,China)
机构地区:[1]解放军联勤保障部队第九〇四医院神经外科,无锡214044
出 处:《中华神经创伤外科电子杂志》2020年第6期332-337,共6页Chinese Journal Of Neurotraumatic Surgery:Electronic Edition
基 金:江苏省卫健委重点科研项目(K2019018);无锡市医学重点学科建设(ZDXK005)。
摘 要:目的基于临床资料建立并验证创伤性颅脑损伤(TBI)去骨瓣减压(DC)术后并发脑积水(PTH)的预测模型。方法选取解放军联勤保障部队第九〇四医院神经外科自2010年1月至2019年12月诊治的符合纳入条件的451例TBI患者,随访6个月后根据PTH诊断标准分为PTH组(127例)和无PTH组(324例),分析与之可能相关的15项因素。采用最小绝对收缩和选择算子(LASSO)回归降低数据维度和筛选预测因子。纳入多因素Logistic回归分析后建立预测模型并制作列线图,受试者工作特征曲线(ROC)和校准曲线用于检测模型的区分度和拟合优度,决策曲线分析(DCA)评价模型的临床适用性。结果LASSO回归筛选出5个预测因子并用于构成模型。经过验证,模型的ROC曲线下面积为0.762。校准曲线显示预测概率与实际概率有很好的一致性。DCA表明模型在一定范围内的临床适用性。结论本研究建立一个PTH的预测模型,具有良好的区分度、拟合优度和临床适用性,有利于高危患者的识别和针对性随访干预。Objective To establish and verify the prediction model of post-traumatic hydrocephalus(PTH)after decompressive craniotomy(DC)of traumatic brain injury(TBI)based on clinical data.Methods Four hundred and fifty-one eligible TBI cases admitted to Neurosurgery Department of the 904st Hospital of the Joint Service Support Force of the PLA from January 2010 to December 2019 were collected.After 6 months follow-up,according to the diagnostic criteria of PTH,the patients were divided into PTH group(n=127)and non-PTH group(n=324),and 15 factors related to PTH were analyzed.The least absolute shrinkage and selection operator(LASSO)regression was used to reduce the data dimension and filter the prediction factors.The multivariate logistic regression was used to establish the prediction model and constructe nomogram.Receiver operating characteristic(ROC)curve and calibration curve are respectively used to detect the discrimination and goodness of fit of the model.Decision curve analysis(DCA)was used to evaluate the clinical applicability of the prediction model.Results Five predictors were screened out by LASSO regression and constituted a model.After verification,the area under the curve of ROC was 0.762.The calibration curve showed that the predicted probability was in good agreement with the actual probability.DCA showed the clinical applicability of the model in a certain range.Conclusion This study established a prediction model of PTH,which has good differentiation,goodness of fit and clinical applicability,and is conducive to the the identification of high-risk patients and targeted follow-up intervention.
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