The Impact of Sensory, Motor and Pain Impairments on Patient- Reported and Performance Based Function in Carpal Tunnel Syndrome
Bibliographic record
Abstract
BACKGROUND: Research has suggested that persistent sensory and motor impairments predominate the symptoms experienced by patients with carpal tunnel syndrome (CTS); with intermittent pain symptoms, being less predominant. OBJECTIVE: The study aims to determine the relative contribution of sensory, motor and pain impairments as contributors to patient-report or performance-based hand function. METHODS: Fifty participants with a diagnosis of CTS confirmed by a hand surgeon and electrodiagnosis were evaluated on a single occasion. Impairments were measured for sensibility, pain and motor performance. A staged regression analysis was performed. In the first step, variables with each of the 3 impairment categories were regressed on the Symptom Severity Scale (SSS) to identify the key variables from this domain. Models were created for both self report (Quick Disabilities of arm, shoulder and hand- Quick DASH) and performance based (Dexterity) functional outcomes. Backward regression modelling was performed for SSS and then, to allow comparability of the importance of different impairments across models, the 7 significant variables from the SSS model were forced into the models. RESULTS: Variables: age, touch threshold and vibration threshold of the little finger of unaffected hand, median-ulnar vibration threshold ratio of affected hand, mean pain tolerance of unaffected hand, grip strength and pinch strength of affected hand, explained 31%, 36% and 63% of the variance in SSS, Quick DASH and dexterity scores, respectively. CONCLUSION: Hand function in patients with CTS is described by variables that reflect sensory status of the median and ulnar nerves, the persons pain threshold, grip and pinch strength impairments and age.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".