Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia
Abstract Background Birth weight is one of the most important indicators of neonatal survival. A reliable estimate of foetal weight at different stages of pregnancy would facilitate intervention plans for medical practitioners to prevent the risk of low birth weight delivery. This study has develope...
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| Format: | Article |
| Language: | English |
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BMC
2018-11-01
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| Series: | BMC Pregnancy and Childbirth |
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| Online Access: | http://link.springer.com/article/10.1186/s12884-018-2047-z |
| _version_ | 1828422825056141312 |
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| author | Dewi Anggraini Mali Abdollahian Kaye Marion |
| author_facet | Dewi Anggraini Mali Abdollahian Kaye Marion |
| author_sort | Dewi Anggraini |
| collection | DOAJ |
| description | Abstract Background Birth weight is one of the most important indicators of neonatal survival. A reliable estimate of foetal weight at different stages of pregnancy would facilitate intervention plans for medical practitioners to prevent the risk of low birth weight delivery. This study has developed reliable models to more accurately predict estimated foetal weight at a given gestation age in the absence of ultrasound facilities. Methods A primary health care centre was involved in collecting retrospective non-identified Indonesian data. The best subset model selection criteria, coefficient of determination, standard deviation, variance inflation factor, Mallows Cp, and diagnostic tests of residuals were deployed to select the most significant independent variables. Simple and multivariate linear regressions were used to develop the proposed models. The efficacy of models for predicting foetal weight at a given gestational age was assessed using multi-prediction accuracy measures. Results Four weight prediction models based on fundal height and its combinations with gestational age (between 32 and 41 weeks) and ultrasonic estimates of foetal head circumference and foetal abdominal circumference have been developed. Multiple comparison criteria show that the proposed models were more accurate than the existing models (mean prediction errors between − 0.2 and 2.4 g and median absolute percentage errors between 4.1 and 4.2%) in predicting foetal weight at a given gestational age (between 35 and 41 weeks). Conclusions This research has developed models to more accurately predict estimated foetal weight at a given gestational age in the absence of ultrasound machines and trained ultra-sonographers. The efficacy of the models was assessed using retrospective data. The results show that the proposed models produced less error than the existing clinical and ultrasonic models. This research has resulted in the development of models where ultrasound facilities do not exist, to predict the estimated foetal weight at varying gestational age. This would promote the development of foetal inter growth charts, which are currently unavailable in Indonesian primary health care systems. Consistent monitoring of foetal growth would alleviate the risk of having inter growth abnormalities, such as low birth weight that is the most leading factor of neonatal mortality. |
| first_indexed | 2024-12-10T15:52:16Z |
| format | Article |
| id | doaj.art-3798566ab19b4c53ad35fd3f93c89c78 |
| institution | Directory Open Access Journal |
| issn | 1471-2393 |
| language | English |
| last_indexed | 2024-12-10T15:52:16Z |
| publishDate | 2018-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pregnancy and Childbirth |
| spelling | doaj.art-3798566ab19b4c53ad35fd3f93c89c782022-12-22T01:42:45ZengBMCBMC Pregnancy and Childbirth1471-23932018-11-0118111210.1186/s12884-018-2047-zFoetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in IndonesiaDewi Anggraini0Mali Abdollahian1Kaye Marion2School of Science (Mathematical and Geospatial Sciences), College of Science, Engineering, and Health, RMIT UniversitySchool of Science (Mathematical and Geospatial Sciences), College of Science, Engineering, and Health, RMIT UniversitySchool of Science (Mathematical and Geospatial Sciences), College of Science, Engineering, and Health, RMIT UniversityAbstract Background Birth weight is one of the most important indicators of neonatal survival. A reliable estimate of foetal weight at different stages of pregnancy would facilitate intervention plans for medical practitioners to prevent the risk of low birth weight delivery. This study has developed reliable models to more accurately predict estimated foetal weight at a given gestation age in the absence of ultrasound facilities. Methods A primary health care centre was involved in collecting retrospective non-identified Indonesian data. The best subset model selection criteria, coefficient of determination, standard deviation, variance inflation factor, Mallows Cp, and diagnostic tests of residuals were deployed to select the most significant independent variables. Simple and multivariate linear regressions were used to develop the proposed models. The efficacy of models for predicting foetal weight at a given gestational age was assessed using multi-prediction accuracy measures. Results Four weight prediction models based on fundal height and its combinations with gestational age (between 32 and 41 weeks) and ultrasonic estimates of foetal head circumference and foetal abdominal circumference have been developed. Multiple comparison criteria show that the proposed models were more accurate than the existing models (mean prediction errors between − 0.2 and 2.4 g and median absolute percentage errors between 4.1 and 4.2%) in predicting foetal weight at a given gestational age (between 35 and 41 weeks). Conclusions This research has developed models to more accurately predict estimated foetal weight at a given gestational age in the absence of ultrasound machines and trained ultra-sonographers. The efficacy of the models was assessed using retrospective data. The results show that the proposed models produced less error than the existing clinical and ultrasonic models. This research has resulted in the development of models where ultrasound facilities do not exist, to predict the estimated foetal weight at varying gestational age. This would promote the development of foetal inter growth charts, which are currently unavailable in Indonesian primary health care systems. Consistent monitoring of foetal growth would alleviate the risk of having inter growth abnormalities, such as low birth weight that is the most leading factor of neonatal mortality.http://link.springer.com/article/10.1186/s12884-018-2047-zFundal heightGestational ageEstimated foetal head circumferenceEstimated foetal abdominal circumferenceRegression analysisFoetal weight estimation |
| spellingShingle | Dewi Anggraini Mali Abdollahian Kaye Marion Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia BMC Pregnancy and Childbirth Fundal height Gestational age Estimated foetal head circumference Estimated foetal abdominal circumference Regression analysis Foetal weight estimation |
| title | Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia |
| title_full | Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia |
| title_fullStr | Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia |
| title_full_unstemmed | Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia |
| title_short | Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia |
| title_sort | foetal weight prediction models at a given gestational age in the absence of ultrasound facilities application in indonesia |
| topic | Fundal height Gestational age Estimated foetal head circumference Estimated foetal abdominal circumference Regression analysis Foetal weight estimation |
| url | http://link.springer.com/article/10.1186/s12884-018-2047-z |
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