ArticleArchives of gynecology and obstetrics2024
Methods to reduce the number of vaginal examinations in labour progress assessment so as to support normality at childbirth.
Article in Archives of gynecology and obstetrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of Interventions to Improve Women's Experience of Pelvic Examinations: A Systematic Review and Meta-Analysis.BJOG : an international journal of obstetrics and gynaecology · 2026Pooled it
- Exploratory Non-invasive Estimation of Cervical Dilation from Electrohysterography and Maternal Data: A Machine-Learning Proof-of-Concept Study.Annals of biomedical engineering · 2026Article
- Determinants of puerperal sepsis among mothers who give birth at Jigjiga Public Hospitals, Jigjiga, Somali Regional State, Eastern Ethiopia: a facility-based unmatched case-control study.BMC pregnancy and childbirth · 2025Article
- Psychosocial needs of women undergoing perinatal intimate examinations.Health SA = SA Gesondheid · 2025Article
- Cervical Dilation Classification from Electrohysterography and Clinical Features: A Machine-Learning-Derived Digital Biomarker.Digital biomarkersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.