Dry needling for the treatment of acute myofascial pain syndrome in general practitioners’ clinics: a cohort study
Bibliographic record
Abstract
Abstract Background Musculoskeletal pain is one of the leading complaints in the ambulatory setting. There are many ways to treat it, including pharmacologic and non-pharmacologic approaches. Dry needling (DN) is an option that is easy to learn, cheap and has a good safety profile. The aim of this study was to assess the association between DN performed by GPs for acute myofascial pain syndrome (MPS) and pain relief and to evaluate factors associated with treatment success. Methods In this prospective cohort study, two GPs performed DN in their clinics. Patients were asked to rank their pain using the Short-Form McGill Pain Questionnaire (SF-MPQ) before, 10-min and 1-week after the procedure. The SF-MPQ index consists of 3 parts; visual analog scale (VAS), pain rating index (PRI) and present pain intensity (PPI). Logistic regressions were performed to assess the variables associated with short- and medium- term success. Results Fifty two patients were recruited from September 2019 until August 2020. VAS was 6.0 ± 2.3 (before), 4.1 ± 2.5 (10-min after) and 2.6 ± 2.71 (1-week after), P < 0.05. PRI was 17 ± 9.1 (before), 10.8 ± 8.5 (10-min after) and 5.1 ± 6.5 (1-week after), P < 0.05. PPI was 2.6 ± 1.0 (before), 1.7 ± 1.0 (10-min after) and 1.1 ± 1.2 (1-week after), P < 0.05. Short-term success was associated with the physician who performed the procedure (OR 10.08, 95% CI 1.15,88.4) and with the use of a single needle (vs. multiple needles inserted) (OR 4.55, 95% CI 1.03,20.11). Medium-term success was associated with being a native born (non-immigrant), OR 8.59, 95% CI 1.11,66.28 and with high level of initial pain, OR 11.22, 95% CI 1.82,69.27. Conclusion Our study demonstrated improvement in acute pain 10-min and 1-week after DN performed by a GP, in all parts of the SF-MPQ. Therefore, we believe DN is a good therapeutic option for GPs to aid patients suffering from MPS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.074 | 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 teacher head, 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".