Nonneurologic Hand Pain Versus Carpal Tunnel Syndrome
Bibliographic record
Abstract
OBJECTIVE: To determine whether psychological measures would differentiate a group of patients with physician-diagnosed nonneurologic hand pain from patients with carpal tunnel syndrome (CTS). Many patients, who also displayed symptoms of psychological distress, were referred to an electrodiagnostic clinic with a diagnosis of possible CTS; they subsequently had normal nerve conduction studies. DESIGN: Sixty patients with hand pain were referred to either of two university clinics for electrophysiologic testing, were assigned to either the CTS or nonneurologic group, and were compared on a series of psychometric tests. RESULTS: The Beck Depression Inventory and McGill Pain Questionnaire showed that the physician-assigned nonneurologic patients have a greater degree of depression, use more affective adjectives, and choose more words on the McGill Pain Questionnaire than the physician-assigned CTS group. The nonneurologic group also scored higher on indices of self-reported disability on the Pain Disability Inventory in five of seven categories. Although the CTS group perceived more control over their pain, no differences were observed in the types of coping strategies used on the Coping Strategy Questionnaire. Finally, the nonneurologic group had more Workers' Compensation Board claims. CONCLUSION: Evidence of important psychological issues in some patients with hand pain suggests a need for greater awareness among treating physicians.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".