Maternal factors associated with labor dystocia in low-risk nulliparous women. A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To identify maternal factors associated with labor dystocia in low-risk nulliparous women. METHODS: MEDLINE, Embase, ClinicalTrials.gov, Cochrane, and CINAHL were searched for intervention studies and observational studies published from January 2000 to January 2022. Low-risk was defined as nulliparous women with a singleton, cephalic birth in spontaneous labor at term. Labor dystocia was defined by national or international criteria or treatment. Countries were restricted to OECD members. Two authors independently screened 11,374 titles and abstracts, extracted data, and assessed risk of bias using the Newcastle-Ottawa Scale. Results were presented narratively and by meta-analysis when compatible. RESULTS: Seven cohort studies were included. Overall, the certainty of the evidence was moderate. Three studies found that higher maternal age was associated with an increased frequency of labor dystocia (relative risk 1.68; 95% CI 1.43-1.98). Further three studies found that higher maternal BMI was associated with increased frequency of labor dystocia (relative risk 1.20; 95% CI 1.01-1.43). Maternal short stature, fear of childbirth, and high caffeine intake were also associated with an increased frequency of labor dystocia, while maternal physical activity was associated with a decreased frequency. CONCLUSION: Maternal factors associated with an increased frequency of labor dystocia were mainly maternal age, physical characteristics, and fear of childbirth. Maternal physical activity was associated with a decreased frequency. Intervention studies targeting these maternal factors would need to be initiated before or early in pregnancy to test the causality of the identified factors and labor dystocia.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".