Discriminative validity and test–retest reliability of the Dellon‐modified Moberg pick‐up test in carpal tunnel syndrome patients
Bibliographic record
Abstract
There is a scarcity of validated hand performance tests with proven reliability for quantifying functional deficits in patients with carpal tunnel syndrome (CTS). The Dellon-modified Moberg pick-up test (DMMPUT), composed of commonly used daily objects, is potentially well suited for that purpose. This study was designed to evaluate the test-retest reliability and discriminative validity of the DMMPUT in CTS patients. We compared 162 CTS patients with 116 age-matched controls. CTS severity was determined based on electrophysiological parameters and Levine's Self-Assessment Questionnaire. The mean time to complete each subset of the DMMPUT by the CTS patients was compared with that by the healthy subjects. Test-retest reliability was examined in 46 CTS patients. Discriminative validity was demonstrated through a significant difference in test completion time between the CTS subjects and their age-matched controls. With few exceptions, the test scores declined with increasing severity of electrophysiological abnormalities and subjective symptom severity. Test-retest reliability of the DMMPUT was high with an intra-class correlation coefficient of 0.91. The DMMPUT has discriminative validity and high test-retest reliability in patients with CTS. It can be a useful standardized outcome measure to gauge disease severity.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".