Radiotherapy for painful shoulder syndrome: a retrospective evaluation
Bibliographic record
Abstract
PURPOSE: We evaluated the efficacy of low-dose radiotherapy for painful shoulder syndrome from an orthopedic perspective. METHODS: Patients with painful shoulder syndrome were recruited for this retrospective clinical quality assessment from January 2011 to December 2017. Patients were treated with a linear accelerator or an orthovoltage device at individual doses of 0.5-1.0 Gy and total doses of 3.0-6.0 Gy. To assess response, we used the von Pannewitz score with five levels: "worsened," "unaffected," "improved," "significantly improved," and "symptom free." "Good treatment success" was defined as "significantly improved" and "symptom free." Within-group and between-group differences were statistically evaluated. RESULTS: Of 236 recruited patients (150 women, 86 men; mean age 66.3 [range 31-96] years), 180 patients underwent radiotherapy with a linear accelerator and 56 with an orthovoltage device. Fractionation was 12 × 0.5 Gy in 120 patients, 6 × 0.5 Gy in 74, and 6 × 1 Gy in 42 patients. Treatments were completed in one series for 223 and in two series at least 6 weeks apart for 13 patients. Of the 236 patients, 163 patients (69.1%) agreed to be re-interviewed at a median of 10.5 (range 4-60) months after radiotherapy completion. Directly after radiotherapy, 30.9% (73 patients) had "good treatment success," which had increased to 55.2% (90 patients) at follow-up. CONCLUSION: Protracted pain improvement with low-dose radiotherapy is possible in painful shoulder syndrome. Patients with refractory pain because of subacromial syndrome or shoulder osteoarthritis should also be evaluated for radiotherapy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".