Nonpharmacologic Approaches for Pain Management During Labor Compared with Usual Care: A Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVES: To assess the effects of nonpharmacologic approaches to pain relief during labor, according to their endogenous mechanism of action, on obstetric interventions, maternal, and neonatal outcomes. DATA SOURCE: Cochrane library, Medline, Embase, CINAHL and the MRCT databases were used to screen studies from January 1990 to December 2012. STUDY SELECTION: According to Cochrane criteria, we selected randomized controlled trials that compared nonpharmacologic approaches for pain relief during labor to usual care, using intention-to-treat method. RESULTS: Nonpharmacologic approaches, based on Gate Control (water immersion, massage, ambulation, positions) and Diffuse Noxious Inhibitory Control (acupressure, acupuncture, electrical stimulation, water injections), are associated with a reduction in epidural analgesia and a higher maternal satisfaction with childbirth. When compared with nonpharmacologic approaches based on Central Nervous System Control (education, attention deviation, support), usual care is associated with increased odds of epidural OR 1.13 (95% CI 1.05-1.23), cesarean delivery OR 1.60 (95% CI 1.18-2.18), instrumental delivery OR 1.21 (95% CI 1.03-1.44), use of oxytocin OR 1.20 (95% CI 1.01-1.43), labor duration (29.7 min, 95% CI 4.5-54.8), and a lesser satisfaction with childbirth. Tailored nonpharmacologic approaches, based on continuous support, were the most effective for reducing obstetric interventions. CONCLUSION: Nonpharmacologic approaches to relieve pain during labor, when used as a part of hospital pain relief strategies, provide significant benefits to women and their infants without causing additional harm.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.052 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".