The role of coagulopathy and subdural hematoma thickness at admission in predicting the prognoses of patients with severe traumatic brain injury: A multicenter retrospective cohort study from China

Li Chen; Shaohuai Xia; Yinghong Lin; Yuhui Chen; Liang Xian; Yang Yang; Xianshen Qiu; Limei Xu; Zhu Xingshu; Dujuan Chen; Xuewei Xia; Yi Zuo; Shousen Wang

doi:10.1097/JS9.0000000000001650

The role of coagulopathy and subdural hematoma thickness at admission in predicting the prognoses of patients with severe traumatic brain injury: A multicenter retrospective cohort study from China

Int J Surg. 2024 May 16. doi: 10.1097/JS9.0000000000001650. Online ahead of print.

Authors

Li Chen¹, Shaohuai Xia², Yinghong Lin¹, Yuhui Chen¹, Liang Xian¹, Yang Yang¹, Xianshen Qiu³, Limei Xu⁴, Zhu Xingshu⁵, Dujuan Chen¹, Xuewei Xia⁶, Yi Zuo⁷, Shousen Wang¹

Affiliations

¹ Department of Neurosurgery, Fuzong Clinical Medical College of Fujian Medical University, Fuzhou 350001, Fujian, P. R. China.
² Department of Neurotumor, Beijing Xiaotangshan Hospital, Beijing 102211, P. R. China.
³ Department of Neurosurgery, Ganzhou People's Hospital, Ganzhou 341000, Jiangxi, P. R. China.
⁴ Department of Traditional Chinese Medicine, 900th Hospital of Joint Logistics Support Force, Fuzhou 350001, P. R. China.
⁵ College of Integrated Medicine, Fujian University of Traditional Chinese Medicine, Fujian, Fuzhou, P.R. China.
⁶ Department of Neurosurgery, Affiliated Hospital of Guilin Medical University, Guilin 541001, Guangxi, P. R. China.
⁷ Department of Geriatrics, Affiliated Huai'an No.2 People's Hospital of Xuzhou Medical University, Huai'an, Jiangsu, P. R. China.

PMID: 38752515
DOI: 10.1097/JS9.0000000000001650

Abstract

Background: Traumatic brain injury (TBI) is one of the diseases with high disability and mortality worldwide. Recent studies have shown that TBI-related factors may change the complex balance between bleeding and thrombosis, leading to coagulation disorders. The aim of this retrospective study was to investigate the prediction of coagulopathy and subdural hematoma thickness at admission using the Glasgow Outcome Scale (GOS) in patients with severe TBI at 6 months after discharge.

Methods: In this retrospective cohort study, a total of 1,006 patients with severe TBI in large medical centers in three different provinces of China from June 2015 to June 2021 were enrolled after the exclusion criteria, and 800 patients who met the enrollment criteria were included. A receiver operating characteristic (ROC) curve was used to determine the best cut-off values of platelet (PLT), international normalized ratio (INR), activated partial thromboplastin time (APTT), and subdural hematoma (SDH) thickness. The ROC curve, nomogram, calibration curve, and the decision curve were used to evaluate the predictive effect of the coagulopathy and Coagulopathy-SDH(X1) models on the prognoses of patients with severe TBI, and the importance of predictive indicators was ranked by machine learning.

Results: Among the patients with severe TBI on admission, 576/800 (72%) had coagulopathy, 494/800 (61%) had SDH thickness ≥14.05 mm, and 385/800 (48%) had coagulopathy combined with SDH thickness ≥14.05 mm. Multivariate logistic regression analyses showed that age, pupil, brain herniation, WBC, CRP, SDH, coagulopathy, and X1 were independent prognostic factors for GOS after severe TBI. Compared with other single indicators, X1 as a predictor of the prognosis of severe TBI was more accurate. The GOS of patients with coagulopathy and thick SDH (X1, 1 point) at 6 months after discharge was significantly worse than that of patients with coagulopathy and thin SDH (X1, 2 points), patients without coagulopathy and thick SDH (X1, 3 point), and patients without coagulopathy and thin SDH (X1, 4 points). In the training group, the C-index based on the coagulopathy nomogram was 0.900. The C-index of the X1-based nomogram was 0.912. In the validation group, the C-index based on the coagulopathy nomogram was 0.858. The C-index of the X1-based nomogram was 0.877. Decision curve analysis also confirmed that the X1-based model had a higher clinical net benefit of GOS at 6 months after discharge than the coagulopathy-based model in most cases, both in the training and validation groups. In addition, compared with the calibration curve based on the coagulopathy model, the prediction of the X1 model-based calibration curve for the probability of GOS at 6 months after discharge showed better agreement with actual observations. Machine learning compared the importance of each independent influencing factor in the evaluation of GOS prediction after TBI, with results showing that the importance of X1 was better than that of coagulopathy alone.

Conclusion: Coagulopathy combined with SDH thickness could be used as a new, accurate, and objective clinical predictor, and X1, based on combining coagulopathy with SDH thickness could be used to improve the accuracy of GOS prediction in patients with TBI, 6 months after discharge.