Using Extracorporeal Shockwave Therapy in Patients with Orthopedic Conditions
Bibliographic record
Abstract
Background: Among other non-invasive procedures, Extracorporeal Shockwave Treatment (ESWT) has been used to resolve many musculoskeletal ailments. The authors completed a systematic review to study articles that reported the effectiveness of focused shockwave therapy in patients with orthopedic conditions. Methods: A comprehensive search was conducted across reputable databases including Pub Med, The Cochrane Library, Science Direct, PEDro, Clinicaltrials.gov, and Google Scholar, ensuring a thorough review of the literature until October 10, 2022. Original articles of any design reporting on the use of ESWT in orthopedic patients were meticulously selected. Information related to study design, sample size, participants, intervention, and key findings of the study were extracted. The PEDro classification scale, a recognized tool, was used to evaluate the quality of the studies, further enhancing the credibility of findings. Results: Nineteen research articles (including 1157 participants) were retrieved and included for qualitative analysis. The sample size ranged from twenty-one to one hundred fifteen subjects, and the articles were published between 2001 and 2022. Out of 19 studies published, five were conducted in China, three in Germany, two in Iran and Turkey, and one in the United States, Canada, Italy, Denmark, Spain, Taiwan, and Saudi Arabia. The risk of bias was either moderate or low among the included studies. In patients with various orthopedic conditions, considerable moderate evidence of ESWT’s effectiveness and success in lowering pain levels, increasing treatment success rates, promoting patient-reported functional recovery, and raising performance-based functional outcomes was seen in the results. Conclusion: The systematic literature review provided compelling evidence of the successful application of ESWT in treating a wide range of musculoskeletal problems. These positive outcomes were achieved without severe complications and morbidities, offering a promising outlook for the future of orthopedic treatment.
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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 | 0.014 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".