Development of supraspinatus imaging guidance for primary care physicians with a focus on patient selection
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Primary care physicians frequently encounter patients with supraspinatus pathology and face a difficult task of managing this subset of patients using limited imaging resources. The purpose of this study was to develop a guidance that could help primary care physicians choose appropriate imaging tests judiciously for patients with suspected supraspinatus pathology. METHODS: The imaging reports of one hundred patients who underwent ultrasound and MRI for suspected supraspinatus tendinopathy were retrospectively assessed. The supraspinatus tendon was recorded as intact, partial tear (articular or bursal), or full-thickness tear (focal or complete width). The agreement between imaging modalities was then evaluated using factors such as pathology type and age. RESULTS: There was agreement between modalities in 48/100 patients (Kappa statistic = 0.30). The consistency varied with type of pathology: intact tendons by ultrasound had 55.8% agreement with MRI, partial sided bursal tears 50%, partial sided articular tears 25%, and full-thickness focal tears 33.3%. Full-thickness complete-width tears had a much better agreement with MRI at 90.9%. Age was also significant, with increased disagreement between ultrasound and MRI in patients over 50 years old. CONCLUSIONS: Our data showed that ultrasound findings correlated well with MRI in patients under 50 years of age and also in patients with full-thickness supraspinatus tears. We recommend that primary care physicians may consider using ultrasound as the initial test in younger patients and in patients with suspected full supraspinatus tears, based on clinical exam, with MRI as an option for further evaluation to quantify supraspinatus muscle atrophy. These patient selection recommendations will help promote mindful utilization of scarce resources.
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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 it