One Year After Mild Injury: Comparison of Health Status and Quality of Life Between Patients with Whiplash Versus Other Injuries
Bibliographic record
Abstract
OBJECTIVE: To compare health status, effect on family, occupational consequences, and quality of life (QOL) 1 year after an accident between patients with whiplash versus other mild injuries, and to explore the relationship between initial injury (whiplash vs other) and QOL. METHODS: This was a prospective cohort study. The study used data from the ESPARR cohort (a representative cohort of road accident victims) and included 173 individuals with "pure" whiplash and 207 with other mild injuries. QOL at 1-year followup was assessed on the World Health Organization Quality of Life questionnaire. Correlations between explanatory variables and QOL were explored by Poisson regression to provide adjusted relative risks, with ANOVA for the various QOL scores explored. RESULTS: One year post-accident, more patients who had whiplash than other casualties complained of nonrecovery of health status (56% vs 43%) and of the occupational effect of pain (31% vs 23%). QOL and posttraumatic stress disorder (PTSD) were similar in the 2 groups. Impaired QOL did not correlate with whiplash when models were adjusted on sociodemographic variables and history of psychological distress. Whatever the initial lesion, PTSD was a determining factor for poorer QOL. CONCLUSION: Sociodemographic factors, preaccident psychological history prior to the accident, and PTSD were the main factors influencing QOL, rather than whether the injury was whiplash. PTSD may also be related to pain.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".