Evidence map›Paper›PMID 37100837›Full record

Observational studyScientific reports2023

Prediction of an effective cervical ripenning in the induction of labour using vaginal dinoprostone.

Nuria López Jiménez, Fiamma García Sánchez, Rafael Hernández Pailos, Valentin Rodrigo Álvaro, Ana Pascual Pedreño, María Moreno Cid, Antonio Hernández Martínez, Milagros Molina Alarcón

Abstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Development of a prediction model for mortality in infants undergoing therapeutic hypothermia for neonatal encephalopathy.Journal of perinatology : official journal of the California Perinatal Association · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
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

8 authors.

Nuria López JiménezDepartment of Obstetrics and Gynecology, Hospital Universitario de Torrevieja, 03186, Torrevieja, Spain.
Fiamma García SánchezDepartment of Obstetrics and Gynecology, Hospital General Universitario Nuestra Señora del Prado, 45600, Talavera de la Reina, Toledo, Spain.
Rafael Hernández PailosDepartment of Gynecology, Hospital Universitario Ramón y Cajal, 28034, Madrid, Spain.
Valentin Rodrigo ÁlvaroDepartment of Obstetrics and Gynecology, Hospital La Mancha Centro, 13600, Alcázar de San Juan, Ciudad Real, Spain.
Ana Pascual PedreñoDepartment of Obstetrics and Gynecology, Hospital La Mancha Centro, 13600, Alcázar de San Juan, Ciudad Real, Spain.
María Moreno CidDepartment of Obstetrics and Gynecology, Hospital La Mancha Centro, 13600, Alcázar de San Juan, Ciudad Real, Spain.
Antonio Hernández MartínezDepartment of Nursing, Physiotherapy and Occupational Therapy, Faculty of Nursing, University of Castilla La Mancha IDINE, 13071, Ciudad Real, Spain. antonio.hmartinez@uclm.es.
Milagros Molina AlarcónDepartment of Nursing, Physiotherapy and Occupational Therapy, Faculty of Nursing, University of Castilla-La Mancha IDINE, 02001, Albacete, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To develop a predictive model for successful cervical ripening in women that undergo induction of labour by means of a vaginal prostaglandin slow-release delivery system (Propess®).  Prospective observational study on 204 women that required induction of labour between February 2019 and May 2020 at "La Mancha Centro" hospital in Alcázar de San Juan, Spain. The main variable studied was effective cervical ripening (Bishop score > 6). Using multivariate analysis and binary logistic regression, we created three initial predictive models (model A: Bishop Score + Ultrasound cervical length + clinical variables (estimated fetal weight, premature rupture of membranes and body mass index)); model B: Ultrasound cervical lenght + clinical variables; and model C: Bishop score + clinical variables) to predict effective cervical ripening. All three predictive models obtained (A, B and C) presented good predictive capabilities, with an area under the ROC curve ≥ 0.76. Predictive model C, composed of the variables: gestational age (OR 1.55, 95% CI 1.18-2.03, p = 0.002), premature rupture of membranes (OR 3.21 95% CI 1.34-7.70, p = 0.09) body mass index (OR 0.93, 95% CI 0.87-0.98, p = 0.012), estimated fetal weight (OR 0.99, 95% CI 0.99-1.00, p = 0.068) and Bishop score (OR 1.49 95% CI 1.18-1.81, p = 0.001), is presented as the model of choice with an area under the ROC curve of 0.76 (95% CI 0.70-0.83, p < 0.001). A predictive model composed of the variables: gestational age, premature rupture of membranes, body mass index, estimated fetal weight and Bishop score upon admission presents good capabilities in predicting successful cervical ripening following administration of prostaglandins. This tool could be useful in making clinical decisions with regard to induction of labour.

Indexed as

Delivery, ObstetricDinoprostoneCervical RipeningCervix UteriFemaleFetal WeightHumansLabor, InducedPregnancyProstaglandinsDinoprostoneProstaglandins

Identifiers

PMID37100837
PMCPMC10133331

What OpenQuestion holds

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Registered trials

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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.