Fatigue in adults with traumatic brain injury: predictors and consequences. A systematic review of longitudinal study protocols
Bibliographic record
Abstract
BACKGROUND: Despite strong indications that fatigue is the most common and debilitating symptom after traumatic brain injury, little is known about its frequency, natural history, or relation to other factors. The current protocol outlines a strategy for a systematic review that will identify, assess, and critically appraise studies that assessed predictors for fatigue and the consequences of fatigue on at least two separate time points following traumatic brain injury. METHODS/DESIGN: MEDLINE, EMBASE, the Cochrane Database of Systematic Reviews, CINAHL, and PsycINFO will be systematically searched for relevant peer-reviewed studies. Reference lists of eligible papers will also be searched. All English language studies with a longitudinal design that focus on fatigue in adults with primary-impact traumatic brain injury will be included. Studies on fatigue following brain injury due to secondary pathological processes (intracranial complications, edema, ischemia/infarction, and systemic intracranial conditions) will be excluded. Excluded studies, along with the reasons for exclusion will be reported. Two independent reviewers will conduct all levels of screening, data abstraction, and quality appraisal. Randomized control trial data will be treated as a cohort. The quality will be assessed using the criteria defined by Hayden and colleagues. The review will be conducted and reported in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. CONCLUSIONS: The review will summarize the current knowledge in the field with the aim of increasing understanding and guiding future research on the associations between fatigue and clinically important factors, as well as the consequences of fatigue in traumatic brain injury. PROSPERO registry number: CRD42013004262.
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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 | 0.130 | 0.242 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.018 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".