SynthesisBJOG : an international journal of obstetrics and gynaecology2025
Systematic Review of Clinical Prediction Models for the Risk of Emergency Caesarean Births.
Synthesis in BJOG : an international journal of obstetrics and gynaecology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Cesarean delivery volume and risk of long-term neurodevelopmental disorders in offspring.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026Article
- Predictive Modeling of Preoperative Sleep Disorder Risk in Older Adults by Using Data From Wearable Monitoring Devices: Prospective Cohort Study.JMIR formative research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
backgroundGlobally, caesarean births (CB), including emergency caesareans births (EmCB), are rising. It is estimated that nearly a third of all births will be CB by 2030.
objectivesIdentify and summarise the results from studies developing and validating prognostic multivariable models predicting the risk of EmCBs. Ultimately understanding the accuracy of their development, and whether they are operationalised for use in routine clinical practice. SEARCH STRATEGY: Studies were identified using databases: MEDLINE, CINAHL, Cochrane Central and Scopus with a search strategy tailored to models predicting EmCBs. SELECTION CRITERIA: Prospective studies developing and validating clinical prediction models, with two or more covariates, to predict risk of EmCB. DATA COLLECTION AND ANALYSIS: Data were extracted onto a proforma using the Prediction model Risk Of Bias ASsessment Tool (PROBAST).
resultsIn total, 8083 studies resulted in 56 unique prediction modelling studies and seven validating studies, with a total of 121 different predictors. Frequently occurring predictors included maternal height, maternal age, parity, BMI and gestational age. PROBAST highlighted 33 studies with low overall bias, and these all internally validated their model. Thirteen studies externally validated; only eight of these were graded an overall low risk of bias. Six models offered applications that could be readily used, but only one provided enough time to offer a planned caesarean birth (pCB). These well-refined models have not been recalibrated since development. Only one model, developed in a relatively low-risk population, with data collected a decade ago, remains useful at 36 weeks for arranging a pCB.
conclusionTo improve personalised clinical conversations, there is a pressing need for a model that accurately predicts the timely risk of an EmCB for women across diverse clinical backgrounds.
trial registrationPROSPERO registration number: CRD42023384439.
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.