Predicting Vasospasm and Early Mortality in Severe Traumatic Brain Injury: A Model Using Serum Cytokines, Neuronal Proteins, and Clinical Data

医学 血管痉挛 曲线下面积 创伤性脑损伤 内科学 接收机工作特性 Lasso(编程语言) 蛛网膜下腔出血 计算机科学 精神科 万维网
作者
Rima S. Rindler,H. Thomas Robertson,LaShondra De Yampert,Vivek Khatri,Pavlos Texakalidis,Sheila Eshraghi,Scott F. Grey,Seth Schobel,Eric A. Elster,Nicholas M. Boulis,Jonathan A Grossberg
出处
期刊:Neurosurgery [Lippincott Williams & Wilkins]
标识
DOI:10.1227/neu.0000000000003224
摘要

BACKGROUND AND OBJECTIVES: Prediction of patient outcomes after severe traumatic brain injury (sTBI) is limited with current clinical tools. This study aimed to improve such prognostication by combining clinical data and serum inflammatory and neuronal proteins in patients with sTBI to develop predictive models for post-traumatic vasospasm (PTV) and mortality. METHODS: Fifty-three adult civilian patients were prospectively enrolled in the sTBI arm of the Surgical Critical Care Initiative (SC2i). Clinical, serum inflammatory, and neuronal protein data were combined using the parsimonious machine learning methods of least absolute shrinkage and selection operator (LASSO) and classification and regression trees (CART) to construct parsimonious models for predicting development of PTV and mortality. RESULTS: Thirty-six (67.9%) patients developed vasospasm and 10 (18.9%) died. The mean age was 39.2 years; 22.6% were women. CART identified lower IL9, lower presentation pulse rate, and higher eotaxin as predictors of vasospasm development (full data area under curve (AUC) = 0.89, mean cross-validated AUC = 0.47). LASSO identified higher Rotterdam computed tomography score and lower age as risk factors for vasospasm development (full data AUC 0.94, sensitivity 0.86, and specificity 0.94; cross-validation AUC 0.87, sensitivity 0.79, and specificity 0.93). CART identified high levels of eotaxin as most predictive of mortality (AUC 0.74, cross-validation AUC 0.57). LASSO identified higher serum IL6, lower IL12, and higher glucose as predictive of mortality (full data AUC 0.9, sensitivity 1.0, and specificity 0.72; cross-validation AUC 0.8, sensitivity 0.85, and specificity 0.79). CONCLUSION: Inflammatory cytokine levels after sTBI may have predictive value that exceeds conventional clinical variables for certain outcomes. IL-9, pulse rate, and eotaxin as well as Rotterdam score and age predict development of PTV. Eotaxin, IL-6, IL-12, and glucose were predictive of mortality. These results warrant validation in a prospective cohort.
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