Research Article: Cardiac troponin T and 28-day mortality in traumatic brain injury: a retrospective cohort study and machine learning prediction model
Abstract:
Traumatic brain injury (TBI) frequently induces cardiac dysfunction via the brain-heart axis, yet the prognostic value of cardiac troponin T (cTnT) in TBI remains incompletely characterized. This study investigated thye association between cTnT levels and 28-day all-cause mortality in TBI patients and developed a machine learning-based prediction model.
This retrospective cohort study included 837 adult TBI patients from the MIMIC-III/IV databases (development cohort) and 121 patients from a single Chinese center (external validation cohort). The first cTnT measurement within 24?h of ICU admission was analyzed. Restricted cubic spline (RCS) regression was used to explore nonlinear relationships. cTnT was categorized into quartiles (Q1???0.03, Q2 0.03–0.06, Q3 0.06–0.17, Q4?>?0.17?ng/mL). A two-step Boruta plus LASSO feature selection identified 13 robust predictors. Five machine learning algorithms (Random Forest, BART, GBM, CTREE, SVM) were trained. The primary outcome was 28-day all-cause mortality.
Among 837 patients, 217 (25.9%) died within 28?days. RCS revealed a significant nonlinear association (P for nonlinearity < 0.001). In multivariable Cox regression adjusted for the 12 LASSO-selected covariates (excluding cTnT quartile itself), patients in Q3 and Q4 had nearly twofold higher mortality risks compared with Q1 (HR?=?2.01, 95% CI: 1.37–2.95, p <?0.001; and HR?=?1.96, 95% CI: 1.31–2.93, p =?0.001, respectively). Random Forest achieved the best discriminative performance, with an internal AUC of 0.783 and an external validation AUC of 0.706 (95% CI: 0.584–0.828). The model also demonstrated good calibration (Brier score?=?0.155) and favorable clinical utility across clinically relevant threshold probabilities as shown by decision curve analysis.
Elevated cTnT is independently associated with 28-day mortality in TBI patients, with a potential risk threshold of ?0.06?ng/mL. The Random Forest model integrating cTnT with clinical variables provides moderate mortality prediction. cTnT may serve as an integrative marker of systemic stress and multi-organ dysfunction in TBI.
Introduction:
Traumatic brain injury (TBI) frequently induces cardiac dysfunction via the brain-heart axis, yet the prognostic value of cardiac troponin T (cTnT) in TBI remains incompletely characterized. This study investigated thye association between cTnT levels and 28-day all-cause mortality in TBI patients and developed a machine learning-based prediction model.
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