Sex differences in outcomes after mechanical thrombectomy for acute ischemic stroke in the ‘real world’: protocol for a systematic review and meta-analysis study
Bibliographic record
Abstract
Introduction Mechanical thrombectomy (MT) had been regarded as the first-line therapy for acute ischaemic stroke patients. The sex differences in post-MT treatment outcomes were analysed by randomised controlled trial (RCT) studies with inconsistent conclusions. We suggest the results from the real-world data may differ from RCT containing studies. Therefore, the sex difference in non-clinical trial populations needs to be clarified. Methods and analysis In order to obtain relative studies comprehensively, we will search the main document databases, consisting of Web of Science, Medline in Ovid, Embase in Ovid and Cochrane Library, and trials registers, including Clinical Trails register. The clinical outcomes of real-world studies published between January 2015 and March 2022 will be included. The assessment methods of bias risk will be performed according to study type. The inclusion of studies, evaluation of risk and publication bias, data extraction will be implemented by two reviewers, respectively. The primary outcomes include successful recanalisation and 90-day favourable outcome. Secondary outcomes include vascular complication, hospital-related complications, death during hospital stay and follow-up, and intracerebral haemorrhage. The risk bias of observational studies will be evaluated by Newcastle-Ottawa Scale. I2 statistic will be used to perform the assessment of study heterogeneity. Ethics and dissemination With no need of ethics approval in this review, results in this review ground on public data. The results of the study will be eventually presented at international conferences or in a related journal. PROSPERO registration number CRD42021242597.
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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 | 0.070 | 0.085 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.026 | 0.036 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.034 | 0.004 |
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".