Physical impairments predict hand dexterity function after distal radius fractures: A 2-year prospective cohort study
Bibliographic record
Abstract
Introduction The overall aim of this study was to determine whether physical impairments – loss of range of motion and grip strength – could be used to predict hand dexterity functions in patients at 1 and 2 years after distal radius fracture. Methods This was a prospective cohort study. Hand dexterity was assessed at three different levels using the NK hand dexterity test. We used a manual goniometer to measure the active range of motion in the affected hand for wrist flexion and extension movements, and a J-Tech grip strength device to measure patients’ hand grip strength levels. Assessments were performed at 1- and 2-year follow-ups. Separate multivariable regression analyses were performed to determine if range of motion predicts hand dexterity functions at 1 and 2 years after distal radius fracture. Results A total of 160 patients with distal radius fracture were included in this study. Range of motion (flexion and extension) and grip strength were both statistically significant (p < 0.05) independent variables in predicting hand dexterity functions at all three levels among patients after distal radius fracture at 1-year follow-up. Range of motion and strength levels accounted for 31%, 33% and 22% of the variance in patients’ large, medium and small hand dexterity functions, respectively. At 2 years, grip strength remained the only statistically significant (p < 0.001) independent variable in predicting hand dexterity functions at all three levels. Conclusions Physical impairments (loss of range of motion and grip strength) have higher predictive values for large and medium hand dexterity functions, than small hand dexterity functions, in patients after distal radius fracture, at both 1- and 2-year follow-up periods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".