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Self-assessment risk scoring system for early screening of preterm birth in low resource settings
Lisa Novianti1, Rima Irwinda2, Yudianto Budi Saroyo3
1Obstetrics and Gynaecology Department, Faculty of Medicine, Universitas Indonesia/Cipto-Mangunkusumo Hospital, Jakarta, Indonesia.
Insights
A new scoring system effectively predicts preterm birth risk using socioeconomic factors, antenatal visits, and pregnancy history. This tool aids early detection in low-resource settings, improving maternal and neonatal outcomes.
Area of Science:
- Obstetrics and Gynecology
- Public Health
- Neonatal Medicine
Background:
- Preterm birth is a major global cause of neonatal mortality and morbidity.
- Indonesia faces a high burden of preterm births, necessitating effective screening.
- Low-resource settings often lack advanced equipment for early preterm birth detection.
Purpose of the Study:
- To develop a simple, fast, and inexpensive scoring system for predicting preterm birth.
- To identify key socio-demographic, nutritional, lifestyle, and clinical factors associated with preterm birth.
- To enable early screening and intervention in resource-limited environments.
Main Methods:
- A case-control study conducted at Cipto Mangunkusumo General Hospital, Jakarta.
- Clinical data collected via history taking and medical records.
- Multivariable logistic regression and Receiver Operating Characteristic (ROC) analysis used to develop and validate the scoring system.
Main Results:
- Socioeconomic level, antenatal visits, history of preterm birth, hypertension, and weight gain were independent predictors.
- The scoring system demonstrated good predictive ability with an Area Under the Curve (AUC) of 0.844.
- A cut-off score of ≥4 achieved 81.3% sensitivity and 82.2% specificity for predicting preterm birth.
Conclusions:
- Identified key predictors for preterm birth: socioeconomic status, antenatal care, previous preterm delivery, hypertension, and gestational weight gain.
- The developed scoring system is a valid and reliable tool for early preterm birth prediction.
- This scoring system offers a practical solution for preterm birth screening in low-resource settings.
Introduction:
Preterm birth is a leading cause of neonatal mortality and morbidity globally. According to the World Health Organization (WHO), 15 million babies were born prematurely in 2010. Indonesia has the fifth-highest number of preterm births in the world, with 675,700 occurring every year. Early screening for preterm birth is crucial, but many health centers in low-resource settings lack the equipment required to do so. This study aims to develop a scoring system that can predict preterm birth based on socio-demographics, nutrition, lifestyle, previous pregnancy history, and maternal condition. The goal is to create a simple, fast, and inexpensive method that can be easily accessed for early screening in low-resource settings.
Methods:
This case-control study was conducted between June 2021 and June 2022 at Cipto Mangunkusumo General Hospital, Jakarta. Subjects were categorized into preterm and control groups. Clinical data were obtained through history taking and medical records and analyzed using IBM SPSS 23. Significant variables in bivariate analysis underwent multivariable analysis through logistic regression. The receiver operating characteristics (ROC) indicate how accurately the risk-scoring system performs. The validity of the scoring formula was analyzed using the Hosmer-Lemeshow test. The performance of the score was assessed using the area under the curve parameter.
Results:
Multivariate analysis showed that socioeconomic level, antenatal visits, history of preterm, hypertension, and weight gain during pregnancy were independent predictors of preterm birth, with an area under the curve of 0.844 (95% CI 0.802-0.885) and p < 0.001, indicating a good predictive ability. Hosmer-Lemeshow test showed a well-fitted model (p = 0.26). Based on the scoring system in this study, the cut-off ≥ 4 had a sensitivity and specificity of 81.3% and 82.2%, respectively, in predicting preterm birth.
Conclusion:
Socioeconomic level, history of preterm delivery, antenatal visits, weight gain during pregnancy, and history of hypertension were independent predictors associated with preterm birth.
