[Persistent shoulder symptoms in calcific tendinitis: clinical and radiological predictors].
Bibliographic record
Abstract
OBJECTIVE: We assessed the most important demographics and radiological characteristics at the time of diagnosis of rotator cuff calcific tendinitis (RCCT), and their associations with long-term clinical outcome. DESIGN: Observational study. METHOD: Baseline characteristics and treatment were evaluated in 342 patients in whom RCCT had been diagnosed. Interobserver agreement of the radiological investigations was analysed. Patients were sent a general questionnaire and 2 shoulder questionnaires, the "Western Ontario rotator cuff" (WORC) and the "Disabilities of the arm, shoulder and hand" (DASH) for evaluation of long-term clinical outcome. Associations between baseline characteristics and long-term outcomes were analysed using logistic regression. RESULTS: Mean age at diagnosis was 49.0 years (SD = 10.0), and 60% were female. The dominant arm was affected in 66%, and 21% had bilateral RCCT. Calcifications were on average 18.7 mm in size (SD = 10.1, ICC = 0.84 (p < 0.001)) and located 10.1 mm (SD = 11.8) medially to the acromion (ICC = 0.77 (p < 0.001)). 32% of the calcifications had a Gärtner type I classification (κ: 0.47 (p<0.001)). After a mean follow-up of 14 years (SD =7.1), median WORC score was 72.5 (range: 3.0-100.0) and median DASH score 17.0 (range: 0.0-82.0). Female gender, dominant arm involvement, bilateral disease, longer duration of symptoms at presentation, and presence of multiple calcifications were associated with inferior long-term outcomes. CONCLUSION: RCCT is not self-limiting. Radiological variations have no significant predictive value. We identified specific prognostic factors for inferior long-term outcome; more intensive follow-up and treatment should be considered in patients with these characteristics.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".