The course and factors associated with recovery of whiplash-associated disorders: an updated systematic review by the Ontario protocol for traffic injury management (OPTIMa) collaboration
Bibliographic record
Abstract
To update the findings of the Bone and Joint Decade 2000–2010 Task Force on Neck Pain and Its Associated Disorders (Neck Pain Task Force) on prognostic factors for whiplash-associated disorder (WAD) outcomes. We conducted a systematic review and best-evidence synthesis. We systematically searched MEDLINE, EMBASE, CINAHL and PsycINFO from 2000–2017. Random pairs of reviewers critically appraised eligible studies using the Scottish Intercollegiate Guidelines Network criteria. We retrieved 10,081 articles. Of those, 100 met inclusion criteria. After critical appraisal, 74 were judged to have low risk of bias. This adds to the 47 admissible studies found by the Neck Pain Task Force. Twenty-two related to course of recovery; 59 to prognostic factors in recovery; and 16 reported other WADs outcomes. Some studies related to more than one category. Findings suggest that half of those with WADs will experience substantial improvement within three months and cessation of symptoms within six months. Among factors associated with recovery are post-crash psychological factors, including expectations for recovery and coping. Our review adds to the Neck Pain Task Force by clarifying the role of prognostic factors. Evidence supports the important role of post-crash psychological factors in WADs recovery. CRD42013004610
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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 | 0.039 | 0.094 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".