Effect of dry cupping therapy and acupuncture on the pain scale in low back pain in postpartum women: A systematic review and meta-analysis
Bibliographic record
Abstract
Context: Dry cupping and acupuncture are complementary treatments that can be used to decrease low back pain (LBP) in postpartum mothers. Aims: To analyze the pain intensity after each treatment measured by visual analog scale (VAS) in postpartum mothers with LBP. Methods: Articles for this systematic review and meta-analysis were retrieved from Web of Science, Science Direct, PubMed, Google Scholar, and Scopus (10/1/2013-12/31/2022), adjusted for inclusion and exclusion criteria, and filtered according to PRISMA guidelines, and the meta-analysis was using Review Manager 5.4. The Newcastle-Ottawa scale was selected to ascertain the quality of each included paper. Results: Four randomized controlled- trials (RCTs) with 157 patients were included. VAS scores from these studies showed that after acupuncture and dry cupping treatment, the VAS scores were significantly lower in LBP-postpartum mothers than in controls (SMD IV, Random 95%: 1.69 [95% I2 = 83%; p = 0.00001]) and (SMD IV, Random, 95%: 2.06 [95% I2 = 63 %; p = 0.0001]), respectively. The LBP among these postpartum mothers can be triggered by perinatal stress, postpartum baby blues, and other back pain-related morbidities. Conclusions: Both acupuncture and dry cupping effectively reduced LBP in postpartum mothers. However, dry cupping showed a higher impact and was arguably more beneficial due to this method's non-invasiveness. Furthermore, acupuncture and dry cupping are considered safe treatments after giving birth because they do not interfere with breast milk production.
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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 | 0.126 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".