Evidence map›Paper›PMID 35971093›Full record

ArticleBMC pregnancy and childbirth2022

Development and validation of a predictive model to identify the active phase of labor.

Simona Fumagalli, Laura Antolini, Greta Cosmai, Teresa Gramegna, Antonella Nespoli, Astrid Pedranzini, Elisabetta Colciago, Maria Grazia Valsecchi, Patrizia Vergani, Anna Locatelli

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Alternative approach to monitoring labor: purple line.BMC pregnancy and childbirth · 2025
    Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Simona FumagalliSchool of Medicine and Surgery, University of Milano-Bicocca, Via Cadore 48, 20900, Monza, Italy. simona.fumagalli@unimib.it.
Laura AntoliniSchool of Medicine and Surgery, University of Milano-Bicocca, Via Cadore 48, 20900, Monza, Italy.
Greta CosmaiDepartment of Obstetrics and Gynecology, MBBM Foundation at San Gerardo Hospital, Monza, Italy.
Teresa GramegnaDepartment of Obstetrics and Gynecology, MBBM Foundation at San Gerardo Hospital, Monza, Italy.
Antonella NespoliSchool of Medicine and Surgery, University of Milano-Bicocca, Via Cadore 48, 20900, Monza, Italy.
Astrid PedranziniDepartment of Obstetrics and Gynecology, MBBM Foundation at San Gerardo Hospital, Monza, Italy.
Elisabetta ColciagoSchool of Medicine and Surgery, University of Milano-Bicocca, Via Cadore 48, 20900, Monza, Italy.
Maria Grazia ValsecchiSchool of Medicine and Surgery, University of Milano-Bicocca, Via Cadore 48, 20900, Monza, Italy.
Patrizia VerganiDepartment of Obstetrics and Gynecology, MBBM Foundation at San Gerardo Hospital, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Anna LocatelliDepartment of Obstetrics and Gynecology, Carate Brianza Hospital, ASST Brianza, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe diagnosis of the active phase of labor is a crucial clinical decision, thus requiring an accurate assessment. This study aimed to build and to validate a predictive model, based on maternal signs and symptoms to identify a cervical dilatation ≥4 cm.

methodsA prospective study was conducted from May to September 2018 in a II Level Maternity Unit (development data), and from May to September 2019 in a I Level Maternity Unit (validation data). Women with singleton, term pregnancy, cephalic presentation and presence of contractions were consecutively enrolled during the initial assessment to diagnose the stage of labor. Women < 18 years old, with language barrier or induction of labor were excluded. A nomogram for the calculation of the predictions of cervical dilatation ≥4 cm on the ground of 11 maternal signs and symptoms was obtained from a multivariate logistic model. The predictive performance of the model was investigated by internal and external validation.

resultsA total of 288 assessments were analyzed. All maternal signs and symptoms showed a significant impact on increasing the probability of cervical dilatation ≥4 cm. In the final logistic model, "Rhythm" (OR 6.26), "Duration" (OR 8.15) of contractions and "Show" (OR 4.29) confirmed their significance while, unexpectedly, "Frequency" of contractions had no impact. The area under the ROC curve in the model of the uterine activity was 0.865 (development data) and 0.927 (validation data), with an increment to 0.905 and 0.956, respectively, when adding maternal signs. The Brier Score error in the model of the uterine activity was 0.140 (development data) and 0.097 (validation data), with a decrement to 0.121 and 0.092, respectively, when adding maternal signs.

conclusionOur predictive model showed a good performance. The introduction of a non-invasive tool might assist midwives in the decision-making process, avoiding interventions and thus offering an evidenced-base care.

Indexed as

Labor, ObstetricAdolescentFemaleHumansLabor, InducedLabor Stage, FirstLogistic ModelsPregnancyProspective StudiesROC CurveActive laborActive phaseMaternal behaviorMidwifery diagnosis

Identifiers

PMID35971093
PMCPMC9377074

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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.