Recurrence of cervical artery dissection: protocol for a systematic review
Bibliographic record
Abstract
INTRODUCTION: Cervical artery dissection, including carotid and vertebral artery dissection, is an important cause of stroke in the young. Risk of developing cervical artery dissection has been associated with physical activity in various forms and has been presumed to be related to minor trauma and mechanical stretching of the cervical arteries. This systematic review will aim to synthesise data on the risk of recurrent cervical artery dissection after an initial dissection. This information may be applied to further understand the natural history of this disease, and potentially to help direct evidence-based discussions on safe return to activity after dissection. METHODS AND ANALYSIS: A broad search of multiple electronic databases (Medline, Embase, Cochrane Central Register of Controlled Trials and Web of Science) will be conducted to identify studies published as of 13 November 2019, examining all-comers with cervical artery dissection observed over time. Studies will be screened by two independent reviewers in a two-level process to determine eligibility for inclusion. Data will be pooled from eligible articles and the main outcome of recurrent cervical artery dissection at 5 years will be determined using quantitative analysis. ETHICS AND DISSEMINATION: Ethics approval is not necessary as no primary data are being collected. The information will be disseminated in the form of a systematic review article which will be submitted to a peer-reviewed medical journal. PROSPERO REGISTRATION NUMBER: CRD42020166105.
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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 | 0.071 | 0.091 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.021 | 0.017 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.089 | 0.011 |
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".