The effectiveness of prolotherapy on failed rotator cuff repair surgery.
Bibliographic record
Abstract
OBJECTIVES: The aim of the present study was to investigate the effectiveness of prolotherapy injections in the treatment of failed rotator cuff repair surgery. PATIENTS AND METHODS: Between May 2014 and March 2016, a total of 15 patients (5 males, 10 females; mean age 49.4±10.7 years; range, 33 to 71 years) with failed rotator cuff repair surgery who had at least six months of complaints and were refractory to at least of three months of conservative methods were included. Ultrasound-guided prolotherapy injections were performed under aseptic conditions, and the patients were instructed to carry out a home-based exercise program. Clinical assessment of shoulder function was performed using a visual analog scale (VAS) for pain, Shoulder Pain and Disability Index (SPADI), Western Ontario Rotator Cuff (WORC) Index, patient satisfaction and shoulder range of motion. All patients were examined at baseline, at Week 3, 6, and 12 and at the final follow-up visit. RESULTS: The intra-group comparison showed that the patients achieved significant improvements at all time points, compared to baseline as measured by VAS, SPADI, WORC index, and shoulder range of motion (p<0.001). Twelve patients (80%) reported excellent or good outcomes. CONCLUSION: Our study results show that prolotherapy is effective in the treatment of patients with failed rotator cuff repair surgery with significant improvements in the shoulder functions and pain relief.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".