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April 20, 2026SHILAP Revista de lepidopterología2 citationsOpen Access

Prediction models for aspiration risk in stroke patients: a systematic review

XLXiang-Ru LiHZHong ZhouFMFang-Ju Mao

Key Points

  • The aim is to evaluate the performance and applicability of aspiration risk prediction models in stroke patients.
  • Comprehensive search across nine electronic databases until January 2025.
  • Inclusion of studies on development or validation of aspiration risk prediction models in adults with stroke.
  • Data extraction followed the CHARMS checklist, assessing bias and applicability using the PROBAST tool.
  • Eighteen model development studies included, most showing good discrimination (AUC/C-index: 0.756–0.955).
  • Sixteen studies demonstrated good applicability.
  • High risk of bias noted in all studies due to factors like retrospective designs and small sample sizes.

Abstract

Background Stroke is a leading cause of disability and death, with post-stroke dysphagia significantly increasing aspiration risk, leading to complications, such as aspiration pneumonia and higher mortality. Various prediction models for aspiration exist, but their clinical utility is limited by methodological heterogeneity. Aim This review aimed to evaluate the performance and applicability of these models for stroke patients, informing future model optimization and clinical use. Study design A comprehensive search was conducted across nine electronic databases until 20 January 2025. Studies on the development or validation of aspiration risk prediction models in adult stroke patients were included. Data extraction followed the CHARMS checklist, and bias risk and applicability were assessed using the PROBAST tool. The review was prospectively registered with PROSPERO (CRD420251007112). Results Eighteen model development studies were included. Most demonstrated good discrimination (AUC/C-index: 0. 756–0. 955), with 16 showing good applicability. However, all studies had a high risk of bias, mainly due to retrospective designs, small sample sizes (events per variable 20), inadequate missing data handling, univariate variable selection, and limited external validation. Key predictors included age, NIHSS score, Kubota Water Swallowing Test, history of aspiration, and Glasgow Coma Scale score. Conclusion Aspiration risk prediction models for stroke patients show promising predictive performance but are limited by methodological bias and heterogeneity. Future research should prioritize rigorous reporting and multi-center, large-sample external validation to improve model robustness and clinical applicability. Systematic review registration PROSPERO CRD420251007112, URL: https: //www. crd. york. ac. uk/prospero/displayᵣecord. php? ID=CRD420251007112.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69e5c1c203c29399140287d8https://doi.org/10.3389/fneur.2026.1700285
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