Natural history of recovery after intracerebral haemorrhage: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Clinical trials for intracerebral haemorrhage typically measure outcomes in the same way and at the same time points as trials for ischaemic stroke. However, there is growing evidence that the trajectory of recovery following intracerebral haemorrhage may differ significantly from that following ischaemic stroke. A better understanding of current approaches to outcome assessment is essential to ensure that future trials examining treatments for intracerebral haemorrhage are designed appropriately. OBJECTIVE: To determine when and how outcomes are measured in patients with intracerebral haemorrhage. METHODS AND ANALYSIS: With the assistance of an information specialist, we will conduct a scoping review by searching MEDLINE, Embase, Cochrane Central Register of Controlled Trials and Web of Science for prospective studies of adults with primary intracerebral haemorrhage and documented outcomes with specified times. Two reviewers will independently collect data on included studies pertaining to publication data, study population information, timing of outcome and details of the outcome measurement tools used. The extracted data will be used to demonstrate the type and timing of outcome measures. ETHICS AND DISSEMINATION: Primary data will not be collected therefore formal ethics is not required. The findings of this study will be disseminated through peer-reviewed publications and through presentation at academic conferences.
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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 | 0.082 | 0.070 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.016 | 0.013 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.071 | 0.015 |
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".