Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western Kenya
Abstract Background Preterm birth is the leading cause of neonatal and under-five mortality worldwide. It is a complex syndrome characterized by numerous etiologic pathways shaped by both maternal and fetal factors. To better understand preterm birth trends, the Global Alliance to Prevent Prematurit...
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| Format: | Article |
| Language: | English |
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BMC
2023-10-01
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| Series: | BMC Pregnancy and Childbirth |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12884-023-06012-7 |
| _version_ | 1797451120150315008 |
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| author | Lara Miller Christina N. Schmidt Phillip Wanduru Anthony Wanyoro Nicole Santos Elizabeth Butrick Felicia Lester Phelgona Otieno Dilys Walker |
| author_facet | Lara Miller Christina N. Schmidt Phillip Wanduru Anthony Wanyoro Nicole Santos Elizabeth Butrick Felicia Lester Phelgona Otieno Dilys Walker |
| author_sort | Lara Miller |
| collection | DOAJ |
| description | Abstract Background Preterm birth is the leading cause of neonatal and under-five mortality worldwide. It is a complex syndrome characterized by numerous etiologic pathways shaped by both maternal and fetal factors. To better understand preterm birth trends, the Global Alliance to Prevent Prematurity and Stillbirth published the preterm birth phenotyping framework in 2012 followed by an application of the model to a global dataset in 2015 by Barros, et al. Our objective was to adapt the preterm birth phenotyping framework to retrospective data from a low-resource, rural setting and then apply the adapted framework to a cohort of women from Migori, Kenya. Methods This was a single centre, observational, retrospective chart review of eligible births from November 2015 – March 2017 at Migori County Referral Hospital. Adaptations were made to accommodate limited diagnostic capabilities and data accuracy concerns. Prevalence of the phenotyping conditions were calculated as well as odds of adverse outcomes. Results Three hundred eighty-seven eligible births were included in our study. The largest phenotype group was none (no phenotype could be identified; 41.1%), followed by extrauterine infection (25.1%), and antepartum stillbirth (16.7%). Extrauterine infections included HIV (75.3%), urinary tract infections (24.7%), malaria (4.1%), syphilis (3.1%), and general infection (3.1%). Severe maternal condition was ranked fourth (15.6%) and included anaemia (69.5%), chronic respiratory distress (22.0%), chronic hypertension prior to pregnancy (5.1%), diabetes (3.4%), epilepsy (3.4%), and sickle cell disease (1.7%). Fetal anaemia cases were the most likely to transfer to the newborn unit (OR 5.1, 95% CI 0.8, 30.9) and fetal anomaly cases were the most likely to result in a pre-discharge mortality (OR 3.9, 95% CI 0.8, 19.2). Conclusions Using routine data sources allowed for a retrospective analysis of an existing dataset, requiring less time and fewer resources than a prospective study and demonstrating a feasible approach to preterm phenotyping for use in low-resource settings to inform local prevention strategies. |
| first_indexed | 2024-03-09T14:50:19Z |
| format | Article |
| id | doaj.art-5b6709bd30ac4479976db96760055597 |
| institution | Directory Open Access Journal |
| issn | 1471-2393 |
| language | English |
| last_indexed | 2024-03-09T14:50:19Z |
| publishDate | 2023-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pregnancy and Childbirth |
| spelling | doaj.art-5b6709bd30ac4479976db967600555972023-11-26T14:31:40ZengBMCBMC Pregnancy and Childbirth1471-23932023-10-0123111210.1186/s12884-023-06012-7Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western KenyaLara Miller0Christina N. Schmidt1Phillip Wanduru2Anthony Wanyoro3Nicole Santos4Elizabeth Butrick5Felicia Lester6Phelgona Otieno7Dilys Walker8University of California San Francisco, Institute for Global Health SciencesUniversity of California San Francisco, School of MedicineSchool of Public Health, Makerere University, New Mulago Gate RdDepartment of Obstetrics and Gynaecology, Kenyatta UniversityUniversity of California San Francisco, Institute for Global Health SciencesUniversity of California San Francisco, Institute for Global Health SciencesDepartment of Obstetrics, University of California San Francisco, Gynaecology & Reproductive SciencesKenya Medical Research InstituteUniversity of California San Francisco, Institute for Global Health SciencesAbstract Background Preterm birth is the leading cause of neonatal and under-five mortality worldwide. It is a complex syndrome characterized by numerous etiologic pathways shaped by both maternal and fetal factors. To better understand preterm birth trends, the Global Alliance to Prevent Prematurity and Stillbirth published the preterm birth phenotyping framework in 2012 followed by an application of the model to a global dataset in 2015 by Barros, et al. Our objective was to adapt the preterm birth phenotyping framework to retrospective data from a low-resource, rural setting and then apply the adapted framework to a cohort of women from Migori, Kenya. Methods This was a single centre, observational, retrospective chart review of eligible births from November 2015 – March 2017 at Migori County Referral Hospital. Adaptations were made to accommodate limited diagnostic capabilities and data accuracy concerns. Prevalence of the phenotyping conditions were calculated as well as odds of adverse outcomes. Results Three hundred eighty-seven eligible births were included in our study. The largest phenotype group was none (no phenotype could be identified; 41.1%), followed by extrauterine infection (25.1%), and antepartum stillbirth (16.7%). Extrauterine infections included HIV (75.3%), urinary tract infections (24.7%), malaria (4.1%), syphilis (3.1%), and general infection (3.1%). Severe maternal condition was ranked fourth (15.6%) and included anaemia (69.5%), chronic respiratory distress (22.0%), chronic hypertension prior to pregnancy (5.1%), diabetes (3.4%), epilepsy (3.4%), and sickle cell disease (1.7%). Fetal anaemia cases were the most likely to transfer to the newborn unit (OR 5.1, 95% CI 0.8, 30.9) and fetal anomaly cases were the most likely to result in a pre-discharge mortality (OR 3.9, 95% CI 0.8, 19.2). Conclusions Using routine data sources allowed for a retrospective analysis of an existing dataset, requiring less time and fewer resources than a prospective study and demonstrating a feasible approach to preterm phenotyping for use in low-resource settings to inform local prevention strategies.https://doi.org/10.1186/s12884-023-06012-7Premature birthPhenotypeMaternal infectionPerinatal mortality |
| spellingShingle | Lara Miller Christina N. Schmidt Phillip Wanduru Anthony Wanyoro Nicole Santos Elizabeth Butrick Felicia Lester Phelgona Otieno Dilys Walker Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western Kenya BMC Pregnancy and Childbirth Premature birth Phenotype Maternal infection Perinatal mortality |
| title | Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western Kenya |
| title_full | Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western Kenya |
| title_fullStr | Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western Kenya |
| title_full_unstemmed | Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western Kenya |
| title_short | Adapting the preterm birth phenotyping framework to a low-resource, rural setting and applying it to births from Migori County in western Kenya |
| title_sort | adapting the preterm birth phenotyping framework to a low resource rural setting and applying it to births from migori county in western kenya |
| topic | Premature birth Phenotype Maternal infection Perinatal mortality |
| url | https://doi.org/10.1186/s12884-023-06012-7 |
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