Neural Correlates of Clinical Scores in Patients with Anterior Shoulder Apprehension
Bibliographic record
Abstract
INTRODUCTION: Anterior shoulder apprehension is a commonly reported complaint in anterior shoulder instability, which may lead to patient morbidity and impede shoulder function. It is the result of a cognitively complex mechanism, which includes anxiety, salience, fear, and anticipation. PURPOSE: The aim of this prospective case-control study was to correlate five clinically established scores using functional magnetic resonance imaging to assess brain activation patterns in patients with apprehension related to anterior shoulder instability. METHODS: This study includes 28 consecutive male right-handed patients (mean ± SEM, 26.8 ± 1.2 yr) with positive shoulder apprehension test and 10 healthy matched control participants without apprehension or a history of instability. Task-related and functional connectivity functional magnetic resonance imaging activation patterns occurring during apprehension video cue stimulation were correlated with five clinical tests and scores: Visual Analog Scale (VAS), Rowe score for instability, Simple Shoulder Test, Subjective Shoulder Value (SSV), and Western Ontario Shoulder Instability (WOSI). RESULTS: Rowe, pain VAS, and WOSI scores correlated with prefrontal cortex, dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, somatosensory area, and parieto-occipital and temporal areas (default mode network). Rowe score additionally correlated with frontal pole, anterior midcingulate cortex, and visual areas. Moreover, SSV correlated with task-related brain activity in the bilateral precentral gyrus, bilateral postcentral gyrus, and bilateral superior parietal lobe. CONCLUSIONS: Overall, Rowe score provides the strongest link between shoulder apprehension and brain level alterations as it correlates with the highest number of independent components involving areas responsible for both motor and cognitive functions, whereas pain VAS and WOSI occupy an intermediately strong link recruiting less brain networks. Finally, Simple Shoulder Test and SSV have the weakest link at the brain level.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".