Prevalence and risk factors of paediatric acute ischaemic stroke: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
INTRODUCTION: Paediatric acute ischaemic stroke (AIS) is a rare but severe neurological condition, often leading to long-term disability and considerable societal burden. Compared with adults, paediatric AIS exhibits distinct clinical characteristics and aetiologies, making early identification and prevention more challenging. This study aims to systematically review the prevalence and risk factors of paediatric AIS, providing a comprehensive evidence base for clinical prevention and management. METHODS AND ANALYSIS: A systematic search will be conducted across major databases, including PubMed, Embase, Web of Science and Cochrane Library, from inception to August 2025. We will include observational studies reporting on the prevalence or risk factors of paediatric AIS. Two independent reviewers will screen the literature, extract data and assess study quality using the Newcastle-Ottawa scale. Meta-analysis will be performed using RevMan 5.4 and StataMP 16.0. Heterogeneity will be evaluated using the I² statistic, and subgroup and sensitivity analyses will be conducted as needed. The Grading of Recommendations Assessment, Development and Evaluation system will be used to assess the quality of evidence. ETHICS AND DISSEMINATION: Because no patients were involved, ethical approval was not required. The final results of this research will be submitted to a peer-reviewed journal or presented at relevant conferences, and any deviations from this protocol will be recorded and explained in the final report. REGISTRATION: This study has been registered in the PROSPERO (PROSPERO Registration Number: CRD420251067538).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.065 | 0.076 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.019 | 0.021 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.076 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".