Mortality Prediction in Severe Traumatic Brain Injury Using Traditional and Machine Learning Algorithms.

Abstract Prognostic prediction of traumatic brain injury (TBI) in patients is crucial in clinical decision and health care policy making. This study aimed to develop and validate prediction models for in-hospital mortality after severe traumatic brain injury (sTBI). We developed and validated logistic regression (LR), LASSO regression, and machine learning (ML) algorithms including support vector machines (SVM) and XGBoost models. Fifty-four candidate predictors were included. Model performance was expressed in terms of discrimination (C-statistic) and calibration (intercept and slope). For model development, 2804 patients with sTBI in the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) China Registry study were included. External validation was performed in 1113 patients with sTBI in the CENTER-TBI European Registry study. XGBoost achieved high discrimination in mortality prediction, and it outperformed logistic and LASSO regression. The XGBoost model established in this study also outperformed prediction models currently available, including the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) core and International Mission for Prognosis and Analysis of Clinical Trials (CRASH) basic models. When including 54 variables, XGBoost and SVM reached C-statistics of 0.87 (95% confidence interval [CI]: 0.81-0.92) and 0.85 (95% CI: 0.79-0.90) at internal validation, and 0.88 (95% CI: 0.87-0.88) and 0.86 (95% CI: 0.85-0.87) at external validation, respectively. A simplified version of XGBoost and SVM using 26 variables selected by recursive feature elimination (RFE) reached C-statistics of 0.87 (95% CI: 0.82-0.92) and 0.86 (95% CI: 0.80-0.91) at internal validation, and 0.87 (95% CI: 0.87-0.88) and 0.87 (95% CI: 0.86-0.87) at external validation, respectively. However, when the number of variables included decreased, the difference between ML and LR diminished. All the prediction models can be accessed via a web-based calculator. Glasgow Coma Scale (GCS) score, age, pupillary light reflex, Injury Severity Score (ISS) for brain region, and the presence of acute subdural hematoma were the five strongest predictors for mortality prediction. The study showed that ML techniques such as XGBoost may capture information hidden in demographic and clinical predictors of patients with sTBI and yield more precise predictions compared with LR approaches.

ALSUntangled #68: ozone therapy.

ALSUntangled reviews alternative and off-label treatments for people living with amyotrophic lateral sclerosis (PALS). Here we review ozone therapy. Ozone therapy has possible mechanisms for slowing ALS progression based on its antioxidant, anti-inflammatory, and mitochondrial effects. A non-peer-reviewed report suggests that ozone treatment may slow progression in a mTDP-43 mouse model of ALS. One verified "ALS reversal" occurred on a cocktail of alternative treatments including ozone. There are no ALS trials using ozone to treat PALS. There can be potentially serious side effects associated with ozone therapy, depending on the dose. Based on the above information, we support an investigation of ozone therapy in ALS cell or animal models but cannot yet recommend it as a treatment in PALS.

Baicalin Alleviates Nitroglycerin-induced Migraine in Rats via the Trigeminovascular System.

Migraine is a common neurological disorder with a serious impact on quality of life. The aim of this study was to explore the effect of baicalin on nitroglycerin-induced migraine rats. We carried out a behavioral research within 2 h post-nitroglycerin injection, and blood samples were drawn for measurements of nitric oxide (NO), calcitonin gene-related peptide, and endothelin (ET) levels. Immunohistochemistry was adopted to detect the activation of C-fos immunoreactive neurons in periaqueductal gray. The number, area size, and integrated optical density of C-fos positive cells were measured using Image-Pro Plus. As a result, baicalin administration (0.22 mm/kg) alleviated pain responses of migraine rats. It profoundly decreased NO and calcitonin gene-related peptide levels, increased ET levels, and rebuilt the NO/ET balance in migraine rats. Besides, baicalin pretreatment significantly reduced the number, the stained area size, and integrated optical density value of C-fos positive cells. In brief, this paper supports the possibility of baicalin as a potential migraine pharmacotherapy. Copyright © 2017 John Wiley & Sons, Ltd.