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Background <p>Precise prognostication of functional outcomes in individuals with prolonged disorders of consciousness (PDOC) is crucial for clinical decision-making. We systematically reviewed and meta-analyzed prognostic models for functional outcomes, as well as promising prognostic factors in PDOC.</p> Methods <p>We conducted a TRIPOD-SRMA-compliant systematic review, searching four databases through July 15, 2024. Risk of bias (ROB) was assessed by Prediction Model Risk of Bias Assessment Tool. Pooled sensitivity, specificity and the area under the summary receiver operating characteristic curve (SROC-AUC) were calculated based on outcome classifications (consciousness recovery, consciousness improvement, and favorable prognosis) and modality types (neurophysiological and demographic &amp; clinical). Candidate predictors were ranked across studies, and promising factors were identified from models with both sensitivity and specificity exceeding 80%.</p> Results <p>38 studies comprising 54 prognostic models were included in the systematic review, and 20 models from 19 studies were included in the meta-analysis. None of the included studies were assessed as having a low ROB. The overall pooled sensitivity was 82% (95% CI: 75–87%) and specificity was 85% (95% CI: 80–89%). The pooled SROC-AUC was 0.875 (95% CI: 0.842–0.911). Neurophysiological models demonstrated higher sensitivity. Both sensitivity and specificity exceeded 80% in predicting consciousness improvement but not in consciousness recovery or favorable prognosis. Male sex, minimally conscious state, and traumatic etiology indicated better outcomes, whereas no specific neurophysiological factor could be confirmed due to heterogeneity across studies. Most studies reported limited model performance metrics, especially clinical utility.</p> Conclusions <p>Although neurophysiological factors improve prognostic sensitivity, models’ clinical impact remains limited without external validation. Future work must enhance clinical translation through more rigorous model development and validation.</p>

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Prediction models for functional outcomes in prolonged disorders of consciousness: a systematic review and meta-analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月5日

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  • Tian Shu,
  • Hong Yang,
  • Guangli Zhao,
  • Minxia Jin,
  • Penny Ping Qin,
  • Cengceng Xie,
  • Yaya Guan,
  • Pengjiang Xian,
  • Lin Chen,
  • Jingming Hou,
  • Rebecca Laidi Kan

摘要

Background

Precise prognostication of functional outcomes in individuals with prolonged disorders of consciousness (PDOC) is crucial for clinical decision-making. We systematically reviewed and meta-analyzed prognostic models for functional outcomes, as well as promising prognostic factors in PDOC.

Methods

We conducted a TRIPOD-SRMA-compliant systematic review, searching four databases through July 15, 2024. Risk of bias (ROB) was assessed by Prediction Model Risk of Bias Assessment Tool. Pooled sensitivity, specificity and the area under the summary receiver operating characteristic curve (SROC-AUC) were calculated based on outcome classifications (consciousness recovery, consciousness improvement, and favorable prognosis) and modality types (neurophysiological and demographic & clinical). Candidate predictors were ranked across studies, and promising factors were identified from models with both sensitivity and specificity exceeding 80%.

Results

38 studies comprising 54 prognostic models were included in the systematic review, and 20 models from 19 studies were included in the meta-analysis. None of the included studies were assessed as having a low ROB. The overall pooled sensitivity was 82% (95% CI: 75–87%) and specificity was 85% (95% CI: 80–89%). The pooled SROC-AUC was 0.875 (95% CI: 0.842–0.911). Neurophysiological models demonstrated higher sensitivity. Both sensitivity and specificity exceeded 80% in predicting consciousness improvement but not in consciousness recovery or favorable prognosis. Male sex, minimally conscious state, and traumatic etiology indicated better outcomes, whereas no specific neurophysiological factor could be confirmed due to heterogeneity across studies. Most studies reported limited model performance metrics, especially clinical utility.

Conclusions

Although neurophysiological factors improve prognostic sensitivity, models’ clinical impact remains limited without external validation. Future work must enhance clinical translation through more rigorous model development and validation.