Biomechanical, psychometric, and clinical evaluation of patients with orthopaedic shoulder instability: a cross-sectional study.
Bibliographic record
Abstract
The main aim of this study was to develop a biomechanical, subjective, and clinical characterisation of shoulder instability patients. 38 adults with glenohumeral instability were enrolled. To assess the outcome variables, a goniometer, dynamometer, ultrasound, MoveUS Test, T-Fast Test, Western Ontario Shoulder Instability Index (WOSI), Quick-Piper fatigue scale, and Questionnaire on the athlete’s self-perception of returning to standardised training after an injury (RTP) were used. Results showed that WOSI was correlated with the range of motion (r = −0.379 to −0.513; <i>p</i> < 0.002), and with the Quick-Piper Fatigue Scale (<i>r</i> = 0.807; <i>p</i> < 0.001). Furthermore, RTP showed correlations with the range of motion (<i>r</i> = 0.357 to 0.370; <i>p</i> < 0.028), 120” T-Fast Test (<i>r</i> = 0.324; <i>p</i> = 0.047), WOSI (r = −0.746; <i>p</i> < 0.001), and Quick Piper Fatigue Scale (r= −0.389; <i>p</i> < 0.001). Likewise, muscle thickness at contraction showed a direct correlation with force peak (<i>r</i> = 0.334; <i>p</i> = 0.040); and T-Fast Test with pressure in push-ups (<i>r</i> = 0.441; <i>p</i> = 0.006), and explosive force peak (<i>r</i> = 0.355; <i>p</i> = 0.029). Moreover, three significant estimation models demonstrated that the quality of life, the capacity to return to play, and the endurance could be estimated using simple strength and mobility tests. Goniometric, ergometric, dynamometric, sonographic, and subjective properties are greatly correlated in patients with glenohumeral instability, facilitating the development of short evaluations to predict the most complex variables.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.036 | 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".