Post-Traumatic Amputations Epidemiology and Outcomes Within The National Trauma Data Bank: Improved Survival Over Time Results in Increased Population in Need of Rehabilitation Support.

OBJECTIVE: Acute trauma care has significantly reduced mortality over the last two decades. The last study to examine the epidemiology of traumatic amputees predates these gains. The majority of those who sustain traumatic amputation are male; therefore, limited data exist on female amputees. This study aimed to (1) provide a current epidemiological analysis of traumatic amputees, and (2) compare male and female amputees. DESIGN: All patients sustaining a major limb amputation in the National Trauma Data Bank (NTDB) from 2013 to 2017 were identified. First, descriptive analyses of patient demographics and injury characteristics were performed and compared with a prior 2000-2004 NTDB study. Second, female and male traumatic amputees were compared in this study. RESULTS: From 2013 to 2017 we identified 7,016 patients who underwent major limb amputation. Compared to prior years, the current amputees were older and more severely injured. Mortality was 6.3% in the current years compared to 13.4% in the prior years (odds ratio [OR] 0.44, 95% CI = 0.37 to 0.51, p < 0.001). After multivariable analysis, mortality remained significantly decreased, with no difference in hospital length of stay. CONCLUSIONS: Contemporary NTDB analysis demonstrated that patients with traumatic amputations, regardless of sex, often survive until hospital discharge, despite more severe injuries.

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes.

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

White Matter Integrity and Chronic Poststroke Upper Limb Function: An ENIGMA Stroke Recovery Analysis.

BACKGROUND: Integrity of the corticospinal tract (CST) is an important biomarker for upper limb motor function following stroke. However, when structurally compromised, other tracts may become relevant for compensation or recovery of function. METHODS: We used the ENIGMA Stroke Recovery data set, a multicenter, retrospective, and cross-sectional collection of patients with upper limb impairment during the chronic phase of stroke to test the relevance of tracts in individuals with less and more severe (laterality index of CST fractional anisotropy ≥0.25) CST damage in an observational study design. White matter integrity was quantified using fractional anisotropy for the CST, the superior longitudinal fascicle, and the callosal fibers interconnecting the primary motor cortices between hemispheres. Optic radiations served as a control tract as they have no a priori relevance for the motor system. Pearson correlation was used for testing correlation with upper limb motor function (Fugl-Meyer upper extremity). RESULTS: From 1235 available data sets, 166 were selected (by imaging, Fugl-Meyer upper extremity, covariates, stroke location, and stage) for analyses. Only individuals with severe CST damage showed a positive association of fractional anisotropy in both callosal fibers interconnecting the primary motor cortices (r[21]=0.49; P=0.025) and superior longitudinal fascicle (r[21]=0.51; P=0.018) with Fugl-Meyer upper extremity. CONCLUSIONS: Our data support the notion that individuals with more severe damage of the CST depend on residual pathways for achieving better upper limb outcome than those with less affected CST.