{
  "abstract": "Background\n\nTraumatic 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.Methods\n\nThis 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.Results\n\nAmong 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.Conclusion\n\nElevated 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.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Neurocritical Care, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Liwen Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Wenwen Hu"
    },
    {
      "affs": [
        0
      ],
      "name": "Wenjie He"
    },
    {
      "affs": [
        0
      ],
      "name": "Feiyu Huang"
    },
    {
      "affs": [
        0
      ],
      "name": "Jing Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dstg0d76jjtet.bib",
  "cited_by": 0,
  "doi": "10.3389/fneur.2026.1926632",
  "fulltext_url": "https://europepmc.org/articles/PMC13683164",
  "id": "dstg0d76jjtet",
  "issns": [
    "1664-2295"
  ],
  "landing_url": "https://europepmc.org/article/MED/42908636",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2728|Traumatic Brain Injury and Neurovascular Disturbances"
    ]
  ],
  "openalex": "W7220840670",
  "pdf_url": "https://europepmc.org/articles/PMC13683164?pdf=render",
  "pmcid": "PMC13683164",
  "pmid": "42908636",
  "published": "2026-10-07",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/dstg0d76jjtet.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:53Z",
      "native_id": "MED:42908636",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42908636"
    },
    {
      "first_seen": "2026-10-30T12:20:16Z",
      "native_id": "10.3389/fneur.2026.1926632",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fneur.2026.1926632/full"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2728|Traumatic Brain Injury and Neurovascular Disturbances",
      "subfield": "neurology"
    }
  ],
  "title": "Cardiac troponin T and 28-day mortality in traumatic brain injury: a retrospective cohort study and machine learning prediction model.",
  "title_text": "Cardiac troponin T and 28-day mortality in traumatic brain injury: a retrospective cohort study and machine learning prediction model.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:16Z",
  "url": "https://research.draconitic.com/paper/dstg0d76jjtet",
  "venue": "Frontiers in neurology",
  "versions": []
}