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Research Article Open access CC BY 4.0

Predictive Score of Maternal and Foetal Prognosis during Labour in Primiparous Woman in a Congolese Hospital

Sihalikyolo Vuyiambite Jean-Jeannot Juakali, Mike-Antoine Alongo Maindo, Emmanuel Likwekwe Komanda, Jean-Pascal Okenge Manga

Journal of Advances in Medicine and Medical Research · pp. 1–7 · Published 20 Nov 2017

10.9734/JAMMR/2017/37613

Abstract

Background: In Africa, primiparity is associated with high maternal and neonatal morbidity and mortality during pregnancy and childbirth. This study aims to establish a clinical score to identify the primiparous parturients at risk of pejorative evolution. Methodology: This was a case-control study nested in ROC analysis, aiming diagnosis. During the period from April 1st, 2012 to June 30th 2013, the 1230 primiparous who gave birth at the Oïcha General Reference Hospital in the Democratic Republic of Congo were selected for this study. The primiparous were divided into an evaluation group (n = 686) and a validation group (n = 544). The evaluation group was subjected to a multi-variate analysis with conditional logistic regression to search for risk factors for the pejorative evolution of labour, which allowed the construction of the "Juakali score" for alerting about a bad prognosis of labour. The ROC analysis had revealed the threshold value and the area below the ROC curve, the discriminatory power. Results: The overall prevalence of pejorative evolution was 14.8%. Risk factors: age = 26 years, Height <150cm, Weight <50Kg, BMI (Body Mass Index) ≥ 30Kg / m2, cervical dilatation rate <1cm / h at the latent phase. The score varied from 0 to 9 with a threshold value of 6, from which the positive predictive value was 75.3% in the assessment group (AUC = 0.924) and 63% (AUC = 0.922) for the validation. Conclusion: The Juakali Score is a reliable tool for predicting the pejorative evolution of labour, which can be used to adjust driving behaviour early in labour monitoring.

Predictive score prognosis labour primiparous congolese

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