Surgical approaches of shoulder calcific tendonitis: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Calcific tendonitis is a painful shoulder disorder characterized by calcium deposits (CDs) in the rotator cuff tendon. This systematic review and meta-analysis examined the most efficient surgical procedure for calcific tendonitis. This includes the comparison between the three main surgical techniques: CD removal, CD removal with subacromial decompression (SAD) and CD removal with tendon repair with respect to functional outcomes and pain control scores. Methods: Four electronic databases (MEDLINE, EMBASE, CINAHL, and Cochrane Central Register of Controlled Trials) were searched in February 2023. Studies were eligible for inclusion if they were peer-reviewed, and participants were patients diagnosed with calcific tendonitis of one or more rotator cuff tendon based on diagnostic imaging who underwent shoulder calcific tendonitis surgery. Other shoulder pathology diagnoses were excluded. Meta-analyses were conducted for results that were sufficiently homogeneous in terms of statistical, clinical, and methodological characteristics. Subgroup analyses were performed to determine if effect sizes differed based on the patient's position during the surgery, physiotherapy, and follow-up time. Results: All surgical interventions resulted in significant improvements in shoulder function and pain control. There were no significant differences between CD removal vs. CD removal with SAD or CD removal vs. CD removal with tendon repair. However, there was a trend in favor of CD removal alone or CD removal with SAD approaches, as they provided better outcome scores than CD removal with tendon repair in terms of shoulder function and pain control. Conclusions: All surgical interventions provide substantial improvement in shoulder functions and pain control scores with no significant difference between these surgical techniques.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".