Fernando C Barros1, Aris T Papageorghiou2, Cesar G Victora3, Julia A Noble4, Ruyan Pang5, Jay Iams6, Leila Cheikh Ismail2, Robert L Goldenberg7, Ann Lambert2, Michael S Kramer8, Maria Carvalho9, Agustin Conde-Agudelo10, Yasmin A Jaffer11, Enrico Bertino12, Michael G Gravett13, Doug G Altman14, Eric O Ohuma15, Manorama Purwar16, Ihunnaya O Frederick17, Zulfiqar A Bhutta18, Stephen H Kennedy2, José Villar2. 1. Programa de Pós-Graduação em Saúde e Comportamento, Universidade Católica de Pelotas, Pelotas, Rio Grande do Sul, Brazil2Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil. 2. Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, England. 3. Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil. 4. Department of Engineering Science, University of Oxford, Oxford, England. 5. School of Public Health, Peking University, Beijing, China. 6. Department of Obstetrics and Gynecology, Ohio State University, Columbus, Ohio. 7. Department of Obstetrics and Gynecology, Columbia University, New York, New York. 8. Department of Pediatrics and Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada. 9. Faculty of Health Sciences, Aga Khan University, Nairobi, Kenya. 10. Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland11Perinatology Research Branch, Eunice Kennedy Shriver. 11. Department of Family and Community Health, Ministry of Health, Muscat, Sultanate of Oman. 12. Dipartimento di Scienze Pediatriche e dell'Adolescenza, Cattedradi Neonatologia, Università degli Studi di Torino, Torino, Italy. 13. University of Washington School of Medicine, Seattle. 14. Centre for Statistics in Medicine, University of Oxford Botnar Research Centre, Oxford, England. 15. Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, England15Centre for Statistics in Medicine, University of Oxford Botnar Research Centre, Oxford, Engla. 16. Nagpur INTERGROWTH-21st Research Centre, Ketkar Hospital, Nagpur, India. 17. Center for Perinatal Studies, Swedish Medical Center, Seattle, Washington. 18. Center of Excellence in Women and Child Health, The Aga Khan University, Karachi, Pakistan19Center for Global Child Health, Hospital for Sick Children, Toronto, Ontario, Canada.
Abstract
IMPORTANCE: Preterm birth has been difficult to study and prevent because of its complex syndromic nature. OBJECTIVE: To identify phenotypes of preterm delivery syndrome in the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. DESIGN, SETTING, AND PARTICIPANTS: A population-based, multiethnic, cross-sectional study conducted at 8 geographically demarcated sites in Brazil, China, India, Italy, Kenya, Oman, the United Kingdom, and the United States. A total of 60,058 births over a 12-month fixed period between April 27, 2009, and March 2, 2014. Of these, 53,871 had an ultrasonography estimate of gestational age, among which 5828 were preterm births (10.8%). Pregnancies were prospectively studied using a standardized data collection and online data management system. Newborns had anthropometric and clinical examinations using standardized methods and identical equipment and were followed up until hospital discharge. MAIN OUTCOMES AND MEASURES: The main study outcomes were clusters of preterm phenotypes and for each cluster, we analyzed signs of presentation at hospital admission, admission rates for neonatal intensive care for 7 days or more, and neonatal mortality rates. RESULTS: Twelve preterm birth clusters were identified using our conceptual framework. Eleven consisted of combinations of conditions known to be associated with preterm birth, 10 of which were dominated by a single condition. However, the most common single cluster (30.0% of the total preterm cases; n = 1747) was not associated with any severe maternal, fetal, or placental condition that was clinically detectable based on the information available; within this cluster, many cases were caregiver initiated. Only 22% (n = 1284) of all the preterm births occurred spontaneously without any of these severe conditions. Maternal presentation on hospital admission, newborn anthropometry, and risk for death before hospital discharge or admission for 7 or more days to a neonatal intensive care unit, none of which were used to construct the clusters, also differed according to the identified phenotypes. The prevalence of preterm birth ranged from 8.2% in Muscat, Oman, and Oxford, England, to 16.6% in Seattle, Washington. CONCLUSIONS AND RELEVANCE: We identified 12 preterm birth phenotypes associated with different patterns of neonatal outcomes. In 22% of all preterm births, parturition started spontaneously and was not associated with any of the phenotypic conditions considered. We believe these results contribute to an improved understanding of this complex syndrome and provide an empirical basis to focus research on a more homogenous set of phenotypes.
IMPORTANCE: Preterm birth has been difficult to study and prevent because of its complex syndromic nature. OBJECTIVE: To identify phenotypes of preterm delivery syndrome in the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. DESIGN, SETTING, AND PARTICIPANTS: A population-based, multiethnic, cross-sectional study conducted at 8 geographically demarcated sites in Brazil, China, India, Italy, Kenya, Oman, the United Kingdom, and the United States. A total of 60,058 births over a 12-month fixed period between April 27, 2009, and March 2, 2014. Of these, 53,871 had an ultrasonography estimate of gestational age, among which 5828 were preterm births (10.8%). Pregnancies were prospectively studied using a standardized data collection and online data management system. Newborns had anthropometric and clinical examinations using standardized methods and identical equipment and were followed up until hospital discharge. MAIN OUTCOMES AND MEASURES: The main study outcomes were clusters of preterm phenotypes and for each cluster, we analyzed signs of presentation at hospital admission, admission rates for neonatal intensive care for 7 days or more, and neonatal mortality rates. RESULTS: Twelve preterm birth clusters were identified using our conceptual framework. Eleven consisted of combinations of conditions known to be associated with preterm birth, 10 of which were dominated by a single condition. However, the most common single cluster (30.0% of the total preterm cases; n = 1747) was not associated with any severe maternal, fetal, or placental condition that was clinically detectable based on the information available; within this cluster, many cases were caregiver initiated. Only 22% (n = 1284) of all the preterm births occurred spontaneously without any of these severe conditions. Maternal presentation on hospital admission, newborn anthropometry, and risk for death before hospital discharge or admission for 7 or more days to a neonatal intensive care unit, none of which were used to construct the clusters, also differed according to the identified phenotypes. The prevalence of preterm birth ranged from 8.2% in Muscat, Oman, and Oxford, England, to 16.6% in Seattle, Washington. CONCLUSIONS AND RELEVANCE: We identified 12 preterm birth phenotypes associated with different patterns of neonatal outcomes. In 22% of all preterm births, parturition started spontaneously and was not associated with any of the phenotypic conditions considered. We believe these results contribute to an improved understanding of this complex syndrome and provide an empirical basis to focus research on a more homogenous set of phenotypes.
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Authors: Chang Chen; Jin Wen Zhang; Hong Wei Xia; Hui Xin Zhang; Ana Pilar Betran; Lin Zhang; Xiao Lin Hua; Li Ping Feng; Dan Chen; Kang Sun; Chun Ming Guo; Hong Bo Qi; Tao Duan; Jun Zhang Journal: Am J Public Health Date: 2019-09-19 Impact factor: 9.308