PDF(Pubmed)
Abstract：
BACKGROUND: The mortality rate of patients with traumatic brain injury (TBI) is still high even while undergoing decompressive craniectomy (DC), and the expensive treatment costs bring huge economic burden to the families of patients.
OBJECTIVE: The aim of this study was to identify preoperative indicators that influence patient outcomes and to develop a risk model for predicting patient mortality by a retrospective analysis of TBI patients undergoing DC.
METHODS: A total of 288 TBI patients treated with DC, admitted to the First Affiliated Hospital of Shantou University Medical School from August 2015 to April 2021, were used for univariate and multivariate logistic regression analysis to determine the risk factors for death after DC in TBI patients. We also built a risk model for the identified risk factors and conducted internal verification and model evaluation.
RESULTS: Univariate and multivariate logistic regression analysis identified four risk factors: Glasgow Coma Scale, age, activated partial thrombin time, and mean CT value of the superior sagittal sinus. These risk factors can be obtained before DC. In addition, we also developed a 3-month mortality risk model and conducted a bootstrap 1000 resampling internal validation, with C-indices of 0.852 and 0.845, respectively.
CONCLUSIONS: We developed a risk model that has clinical significance for the early identification of patients who will still die after DC. Interestingly, we also identified a new early risk factor for TBI patients after DC, that is, preoperative mean CT value of the superior sagittal sinus (p < .05).
OBJECTIVE: The aim of this study was to identify preoperative indicators that influence patient outcomes and to develop a risk model for predicting patient mortality by a retrospective analysis of TBI patients undergoing DC.
METHODS: A total of 288 TBI patients treated with DC, admitted to the First Affiliated Hospital of Shantou University Medical School from August 2015 to April 2021, were used for univariate and multivariate logistic regression analysis to determine the risk factors for death after DC in TBI patients. We also built a risk model for the identified risk factors and conducted internal verification and model evaluation.
RESULTS: Univariate and multivariate logistic regression analysis identified four risk factors: Glasgow Coma Scale, age, activated partial thrombin time, and mean CT value of the superior sagittal sinus. These risk factors can be obtained before DC. In addition, we also developed a 3-month mortality risk model and conducted a bootstrap 1000 resampling internal validation, with C-indices of 0.852 and 0.845, respectively.
CONCLUSIONS: We developed a risk model that has clinical significance for the early identification of patients who will still die after DC. Interestingly, we also identified a new early risk factor for TBI patients after DC, that is, preoperative mean CT value of the superior sagittal sinus (p < .05).
摘要：
背景：即使接受去骨瓣减压术（DC），创伤性脑损伤（TBI）患者的死亡率仍然很高，昂贵的治疗费用给患者家庭带来巨大的经济负担。
目的：本研究的目的是通过对接受DC的TBI患者的回顾性分析，确定影响患者预后的术前指标，并建立预测患者死亡率的风险模型。
方法：共有288例TBI患者接受DC治疗，方法对2015年8月至2021年4月于汕头大学医学院第一附属医院收治的TBI患者DC后死亡的危险因素进行单因素和多因素logistic回归分析。并对识别出的风险因素建立了风险模型，进行了内部验证和模型评价。
结果：单变量和多变量逻辑回归分析确定了四个危险因素：格拉斯哥昏迷量表，年龄,活化部分凝血酶时间,上矢状窦的平均CT值。这些风险因素可以在DC之前获得。此外,我们还开发了一个3个月的死亡风险模型，并进行了一次Bootstrap1000重采样内部验证，C指数分别为0.852和0.845。
结论：我们开发了一种风险模型，对早期识别DC后仍将死亡的患者具有临床意义。有趣的是,我们还确定了TBI患者在DC后的新的早期危险因素，也就是说,上矢状窦的术前平均CT值（p<0.05）。
目的：本研究的目的是通过对接受DC的TBI患者的回顾性分析，确定影响患者预后的术前指标，并建立预测患者死亡率的风险模型。
方法：共有288例TBI患者接受DC治疗，方法对2015年8月至2021年4月于汕头大学医学院第一附属医院收治的TBI患者DC后死亡的危险因素进行单因素和多因素logistic回归分析。并对识别出的风险因素建立了风险模型，进行了内部验证和模型评价。
结果：单变量和多变量逻辑回归分析确定了四个危险因素：格拉斯哥昏迷量表，年龄,活化部分凝血酶时间,上矢状窦的平均CT值。这些风险因素可以在DC之前获得。此外,我们还开发了一个3个月的死亡风险模型，并进行了一次Bootstrap1000重采样内部验证，C指数分别为0.852和0.845。
结论：我们开发了一种风险模型，对早期识别DC后仍将死亡的患者具有临床意义。有趣的是,我们还确定了TBI患者在DC后的新的早期危险因素，也就是说,上矢状窦的术前平均CT值（p<0.05）。
