The importance of screening for functional neurological disorders in patients with persistent post-concussion symptoms
Bibliographic record
Abstract
BACKGROUND: Functional neurological disorder (FND) may commonly co-occur with persistent symptoms following a psychological trauma or physical injury such as concussion. OBJECTIVE: To explore the occurrence of FND in a population with persistent post-concussion symptoms (PPCS) and the associations between FND and depression as well as anxiety in participants with PPCS. METHODS: Sixty-three individuals with PPCS presenting to a specialized brain injury clinic completed the following questionnaires: screening for somatoform disorder conversion disorder subscale (SOM-CD), Rivermead post-concussion symptom questionnaire (RPQ), patient health questionnaire-9 (PHQ-9), and generalized anxiety disorder questionnaire- 7 (GAD-7). Both multiple linear regression and logistic regression were conducted to evaluate the relationship between questionnaires and adjust for covariates. RESULTS: We found that total RPQ score (βˆ= 0.27; 95% CI = [0.16, 0.38]), GAD-7 score (βˆ= 0.71; 95% CI = [0.50, 0.92]) and PHQ-9 score (βˆ= 0.54; 95% CI = [0.32, 0.76]) were positively associated with SOM-CD score individually, after consideration of other covariates. Participants meeting the criteria for severe FND symptoms were 4.87 times more likely to have high PPCS symptom burden (95% CI = [1.57, 22.84]), 8.95 times more likely to have severe anxiety (95% CI = [3.31, 35.03]) and 4.11 times more likely to have severe depression symptom burden (95% CI = [1.77, 11.53]). CONCLUSION: The findings of this study indicate an association between FND and post-concussion symptoms as well as an association between FND and symptoms of depression and anxiety in patients with PPCS. Patients with PPCS should be screened for FND to provide a more targeted treatment approach that includes somatic-focused interventions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".