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\begin{document}

\title{Maternal age and body mass index and risk of labour dystocia after
spontaneous labour onset among nulliparous women: A clinical prediction
model}



\author[1]{Nina Nathan}%
\author[2]{Thomas Bergholt}%
\author[1]{Christoffer Sejling}%
\author[1]{Anne Ersboll}%
\author[3]{Kim Ekelund}%
\author[4]{Thomas Gerds}%
\author[5]{Christiane Bourgin Folke Gam}%
\author[6]{Line Rode}%
\author[1]{Hanne Hegaard}%
\affil[1]{Copenhagen University Hospital - Rigshospitalet}%
\affil[2]{Herlev Hospital}%
\affil[3]{Rigshospitalet Juliane Marie Centret}%
\affil[4]{University of Copenhagen}%
\affil[5]{Nordsjaellands Hospital}%
\affil[6]{Rigshospitalet Glostrup}%


\vspace{-1em}



  
  \date{May 18, 2024}


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\begin{abstract}
Objective: To develop a prediction model for labour dystocia, suitable
for risk stratification at onset of labour. Design: A cohort-based
registry design was employed using data from the Copenhagen Pregnancy
Cohort and the Danish Medical Birth Registry. Setting: The study was
conducted at Copenhagen University Hospital -- Rigshospitalet, Denmark
Population: Nulliparous women with a singleton pregnancy and cephalic
presentation in spontaneous labour at term from 2014 to 2020. Methods:
Logistic regression analysis was employed to construct the prediction
model. Candidate predictors were pre-selected based on clinical
reasoning and existing evidence. These were maternal age, pre-pregnancy
body mass index, height, gestational age, physical activity,
self-reported medical condition, WHO-5 score, and fertility treatment.
Main outcome measures: The candidate predictors ability to predict
labour dystocia. For model performance, we calculated the area under the
receiver operating characteristics curve (AUC) for discriminative
capacity and Brier score for model calibration. Results: A total of
12,445 women involving 5,525 events of labour dystocia (44\%) were
included. All candidate predictors were retained in the final model,
which demonstrated moderate discriminative ability with AUC was 62.3\%
(95\% CI:60.7-64.0) and Brier score of 0.24. Conclusions: Our model
represents an initial advancement in the prediction of labour dystocia
utilizing readily available information obtainable upon admission in
active labour. As means of facilitating risk stratification the
development of a user-friendly online tool for clinicians is a logical
next step. Nevertheless, further model development and external testing
across other populations is warranted.%
\end{abstract}%



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