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PubMed Case Report / Series Evidence Low

Toxic Shock Syndrome After Orthopaedic Surgery.

Cureus | 2023 | Fernandes SM, Luna A, Hall T, Madden B

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Source
PubMed
Type
Case Report / Series
Evidence
Low

Abstract

Conflict of interest statement: The authors have declared that no competing interests exist. 20. NPJ Digit Med. 2025 Dec 16;9(1):45. doi: 10.1038/s41746-025-02249-y. Prognostic model and U-shaped SBP-risk correlation in unstable pelvic fractures with TBI. Du S(#)(1)(2), Zheng X(#)(1)(3), Zhang Y(1)(2), Xiang Q(4)(5), Zhang C(6)(7). Author information: (1)Department of Emergency Medicine, The First Affiliated Hospital (Southwest Hospital) of Army Medical University, Chongqing, China. (2)Jiangbei Branch of the First Affiliated Hospital, Army Medical University (Army 958th Hospital), Chongqing, China. (3)Department of Orthopedics, The 963rd Hospital of the Joint Service Support Force of the PLA, Jiamusi, China. (4)Department of Emergency Medicine, The First Affiliated Hospital (Southwest Hospital) of Army Medical University, Chongqing, China. xqiang@tmmu.edu.cn. (5)Jiangbei Branch of the First Affiliated Hospital, Army Medical University (Army 958th Hospital), Chongqing, China. xqiang@tmmu.edu.cn. (6)Department of Emergency Medicine, The First Affiliated Hospital (Southwest Hospital) of Army Medical University, Chongqing, China. ChangguiZhang@tmmu.edu.cn. (7)Jiangbei Branch of the First Affiliated Hospital, Army Medical University (Army 958th Hospital), Chongqing, China. ChangguiZhang@tmmu.edu.cn. (#)Contributed equally Patients with unstable pelvic fractures combined with traumatic brain injury (TBI) present complex conditions, with pathophysiological contradictions in clinical treatment between limited fluid resuscitation and maintenance of cerebral perfusion pressure. A retrospective analysis was conducted on 204 patients with unstable pelvic fractures combined with TBI between January 1, 2010, and May 31, 2025. A Nomogram model was constructed via LASSO and multivariate logistic regression, with simultaneous development of an interpretable machine learning prediction model. Results identified shock, abnormal systolic blood pressure (SBP), non-surgical management, and prolonged coagulation time as independent poor prognosis risk factors. The Nomogram constructed using SBP, shock, pelvic fracture surgery, and prothrombin time (PT), showed good performance (AUC = 0.801, C-index = 0.7747). Poor prognosis risk was lowest at SBP 110-122 mmHg; a U-shaped correlation existed between SBP and prognosis. The Nomogram and interpretable XGBoost model provide a basis for individualized blood pressure management, coagulation monitoring, and surgical decision-making. ChiCTR2500103926, registered on May 9, 2025, PID: 275507. © 2025. The Author(s). DOI: 10.1038/s41746-025-02249-y PMCID: PMC12804734

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