Exercise for the prevention of low back and pelvic girdle pain in pregnancy: A meta‐analysis of randomized controlled trials
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background and objective The effect of exercise in prevention of low back and pelvic girdle pain during pregnancy is uncertain. This study aimed to assess the effect of exercise on low back pain, pelvic girdle pain and associated sick leave. Databases and data treatment Literature searches were conducted in PubMed, EMBASE, Cochrane Library, Google Scholar, ResearchGate and ClinicalTrials.gov databases from their inception through May 2017. Randomized controlled trials (RCTs) were eligible for inclusion in the review if they compared an exercise intervention with usual daily activities and at least some of the participants were free from low back pain and/or pelvic girdle pain at baseline. Methodological quality of included studies was evaluated using the Cochrane Collaboration's tool. A random‐effects meta‐analysis was performed, and heterogeneity and publication bias were assessed. Results Eleven randomized controlled trials (2347 pregnant women) qualified for meta‐analyses. Exercise reduced the risk of low back pain in pregnancy by 9% (pooled risk ratio (RR) = 0.91, 95% CI 0.83–0.99, I 2 = 0%, seven trials, N = 1175), whereas it had no protective effect on pelvic girdle pain (RR = 0.99, CI 0.81–1.21, I 2 = 0%, four RCTs, N = 565) or lumbopelvic pain (RR = 0.96, CI 0.90–1.02, I 2 = 0%, eight RCTs, N = 1737). Furthermore, exercise prevented new episodes of sick leave due to lumbopelvic pain (RR = 0.79, CI 0.64–0.99, I 2 = 0%, three RCTs, N = 1168). There was no evidence of publication bias. Conclusion Exercise appears to reduce the risk of low back pain in pregnant women, and sick leave because of lumbopelvic pain, but there is no clear evidence for an effect on pelvic girdle pain. Significance Exercise has a small protective effect against low back pain during pregnancy.
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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 | 0.253 | 0.155 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.027 | 0.014 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it