Treatments for carpal tunnel syndrome: who does what, when ... and why?
Bibliographic record
Abstract
OBJECTIVE: To determine how frequently treatments had been offered to patients with suspected diagnoses of carpal tunnel syndrome (CTS) who had been referred for confirmatory nerve conduction studies (NCSs) and to identify potential predictors of such treatment. A follow-up survey was conducted to determine the effect of NCS results on subsequent treatment. DESIGN: Self-administered survey questionnaire and follow-up telephone survey. SETTING: Royal University Hospital at the University of Saskatchewan in Saskatoon. PARTICIPANTS: Two hundred eleven patients with clinically suspected CTS who had been referred for confirmatory NCS. MAIN OUTCOME MEASURES: Results of NCSs, number of patients prescribed wrist splints or nonsteroidal anti-inflammatory drugs (NSAIDs) before and after NCSs, patient characteristics associated with being prescribed therapy, and reporting benefit of therapy. RESULTS: Nerve conduction studies confirmed CTS in 121 (57.3%) of the 211 study patients. Before NCSs, wrist splints and NSAIDs had been prescribed to 33.2% and 38.8% of patients, respectively. Splints and NSAIDs were reported to alleviate symptoms by 78.3% and 74% of patients, respectively, who received such treatments. No significant differences in age, sex, body mass index, symptom duration, symptom or function scores, or subsequent NCS results were noted between patients who were and were not prescribed these therapies or between those who did or did not report improvement in symptoms. Results of the follow-up survey indicated that the number of recommendations for splints and NSAIDs had doubled after NCSs were completed and that surgical intervention had been at least discussed in most cases. Treatment recommendations, including surgery, however, were not associated with identifiable patient factors, including patients' NCS results. CONCLUSION: Some patients were prescribed conservative treatments before NCSs. Following NCSs, prescriptions for wrist splints or NSAIDs approximately doubled. Interestingly, NCS results did not appear to influence subsequent therapeutic decision-making for either conservative treatment or surgical options. We think these findings suggest a lack of confidence in electrodiagnostic study results. It would be interesting to evaluate a larger population of primary care patients prospectively to examine further the use of NCSs in current clinical decision-making.
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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 | 0.008 |
| 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 | 0.001 |
| 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 | 0.001 |
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".