Analysis of Causes of Stillbirth in a Tertiary Care Hospital using ReCoDe Classification System: A Prospective Observational Study

Author:

Gupta Anju,Kaur Parneet,Aggarwal Sangeeta Rani

Abstract

Introduction: Stillbirths account for a major proportion of perinatal deaths. In many cases of stillbirth, the cause remains unexplained. The ReCoDe system (classification of stillbirths by relevant condition at death) is a frequently used classification system that has helped us to improve the understanding of the causes of stillbirths. Aim: To identify factors associated with stillbirths and to classify the causes of stillbirths using the ReCoDe system. Materials and Methods: A prospective observational study was conducted in the Department of Obstetrics and Gynaecology, Government Medical College and Rajindra Hospital, Patiala, Punjab, India, from February 2020 to January 2021. All the mothers with a history of antepartum and intrapartum foetal mortality with the diagnosis of intrauterine foetal death after 20 weeks of gestation were included in the study. A detailed history of the mother was taken and an examination of the mother, stillborn babies, placenta, and umbilical cord was done. ReCoDe system was used to classify the causes of stillbirth. For statistical analysis mean and percentages were used. Results: There were 287 women with intrauterine foetal death admitted during the study period. Maternal age ranged from 18- 40 years, majority (n=157, 54.7%) women belonged to the age group of 24-29 years. The stillbirth rate was 78.95 per 1000 live births. The cause of stillbirth could be explained in 235 (81.89%) cases by using the ReCoDe system. Hypertensive disorders in 91 (31.71%) were the most common cause followed by foetal growth restriction in 46 (16.02%). Conclusion: ReCoDe system was useful in classifying the causes of stillbirths in the resource-limited settings.

Publisher

JCDR Research and Publications

Subject

Clinical Biochemistry,General Medicine

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Foetal Health Classification Using Input Dataset and Fine Tuning it using K-nearest Neighbour, Naïve Bayes and Decision Tree Classifier;2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI);2023-10-19

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