Prognostic Factors Associated With Minimal Improvement Following Acute Whiplash-Associated Disorders
Bibliographic record
Abstract
STUDY DESIGN: Retrospective clinical cohort study. OBJECTIVE: To identify the prognostic factors associated with a poor response to treatment in the early stages of a whiplash-associated disorder (WAD). SUMMARY OF BACKGROUND DATA: Several demographic and clinical factors related to recovery following acute WADs have been identified. However, few longitudinal studies have investigated a multivariable model of recovery that includes socio-demographic, treatment, clinical, and nonclinical factors. METHODS: A study cohort of 2,185 patients with acute or subacute WADs presenting to 48 rehabilitation clinics in 6 Canadian provinces were investigated for factors associated with failure to demonstrate a minimally important clinical change (10%) in the Canadian Back Institute Questionnaire (CBIQ) score between the initial and discharge rehabilitation visits. RESULTS: Multivariable analysis revealed eight prognostic factors associated with a negative outcome: 1) older age, 2) female gender, 3) increasing lag time between injury date and presentation for treatment, 4) initial pain location, 5) province of injury, 6) higher initial pain intensity, 7) lawyer involvement, and 8) at work at entry to the clinic. The effect of lawyer involvement was stronger for patients with less intense pain on initial visit (odds ratio = 2.97; 95% confidence interval, 1.77-4.99). Similarly, the effect of work status was stronger for patients with less intense pain on initial visit (odds ratio = 2.02; 95% confidence interval, 1.18-3.46). CONCLUSIONS: Researchers and clinicians should be aware of the potential for non-injury-related factors to delay recovery, and be aware of the interaction between the initial intensity of a patient's pain and other covariates when confirming these results.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".