The Rivermead Post-Concussion Questionnaire score is associated with disability and self-reported recovery six months after mild traumatic brain injury in older adults
Bibliographic record
Abstract
Background/Objectives: Post-concussion syndrome refers to the adverse group of symptoms following a mild traumatic brain injury (mTBI). The Rivermead post-concussion syndrome questionnaire (RPQ) is a common clinical tool for assessing baseline post-concussion syndrome symptomology; however, it is unknown if scores on this questionnaire are associated with future disability. Therefore, the goal of this study was to determine the association between baseline RPQ scores and future disability in older adults with mTBI.Methods and Findings: This study used a prospective cohort design, using the RPQ to measure baseline post-concussion syndrome symptomatology. Disability at 6 months was measured using the Glasgow Outcome Scale-Extended (GOSE; disability), short-form 12 (SF-12; physical and mental quality of life), and self-reported recovery. Linear and logistic models adjusted for confounding factors were estimated using 200 bootstrapped samples. Individuals with higher levels of baseline symptomatology were more likely to have poor GOSE scores (RR = 2.13, 95% CI [1.51, 2.31]) and self-reported recovery (RR = 2.64, 95% CI [1.31, 8.98]) 6 months later.Conclusions: High levels of baseline symptomatology may be associated with overall disability and individual perceptions of recovery 6 months post-MTBI. While the RPQ is valid in assessing a patient’s post-concussive symptoms following mTBI, it may not predict long-term physical or mental health in older adults.
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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 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".