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ORIGINAL RESEARCH article

Front. Neurol.
Sec. Neurotrauma
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1512125
This article is part of the Research Topic Unraveling Neuroinflammatory Mechanisms in TBI: Implications for Post-Traumatic Syndromes View all 3 articles

Development and validation of a nomogram for predicting early neurological deterioration in patients with moderate traumatic brain injury: A retrospective analysis

Provisionally accepted
Shen Wang Shen Wang 1*Ruhai Wang Ruhai Wang 2*Chao Han Chao Han 2*Haicheng Hu Haicheng Hu 2*Hongtao Sun Hongtao Sun 1*
  • 1 The first school of clinical medical, Lanzhou University, Lanzhou, China
  • 2 Fuyang Fifth People’s Hospital, anhui, China

The final, formatted version of the article will be published soon.

    Objective: Early neurological deterioration (END) greatly affects prognosis of moderate traumatic brain injury (TBI). This study aimed to develop and validate a nomogram to predict the occurrence of END in patients with moderate TBI.Methods: A total of 371 patients with moderate TBI were enrolled and divided into the training (n=260) and validation (n=111) groups at a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to identify the significant factors for END, which were used to develop a nomogram. The discrimination of the nomogram was evaluated using area under the receiver operating characteristic curves (AUC), the calibration was evaluated using calibration curves and Hosmer-Lemeshow tests. Decision curve analysis (DCA) was used to evaluate the net benefit of the model for patients.Results: In the training group, multivariate logistic regression demonstrated that GCS score, epidural hematoma, intracerebral hemorrhage, fibrinogen, and D-dimer were independent risk factors for END in patients with moderate TBI. A nomogram was constructed using the logistic regression prediction model. The AUCs of the nomogram in the training and validation groups were 0.901 and 0.927, respectively. The calibration curves showed that the predicted probability was consistent with the actual situation in both the training and validation sets. DCA curves demonstrated significantly better net benefit with the model. Then a web-based calculator was generated to facilitate clinical application.Conclusion: The present study developed and validated a model to predict END in patients with moderate TBI. The nomogram that had good discrimination, calibration, and clinical utility can provide clinicians with an effective and accurate tool for evaluating the occurrence of END after moderate TBI.

    Keywords: Moderate traumatic brain injury, Early neurological deterioration, nomogram, Risk factors, Prediction model

    Received: 16 Oct 2024; Accepted: 22 Jan 2025.

    Copyright: © 2025 Wang, Wang, Han, Hu and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Shen Wang, The first school of clinical medical, Lanzhou University, Lanzhou, China
    Ruhai Wang, Fuyang Fifth People’s Hospital, anhui, China
    Chao Han, Fuyang Fifth People’s Hospital, anhui, China
    Haicheng Hu, Fuyang Fifth People’s Hospital, anhui, China
    Hongtao Sun, The first school of clinical medical, Lanzhou University, Lanzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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