Alexa A Freedman1,2, Lauren S Keenan-Devlin3, Ann Borders3,4,5, Gregory E Miller1,6, Linda M Ernst7. 1. Institute for Policy Research, Northwestern University, Evanston, Illinois. 2. Department of Obstetrics and Gynecology, NorthShore University HealthSystem, Evanston, Illinois. 3. Department of Obstetrics and Gynecology, NorthShore University HealthSystem, University of Chicago Pritzker School of Medicine, Evanston, Illinois. 4. Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois. 5. Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, Illinois. 6. Department of Psychology, Northwestern University, Evanston, Illinois. 7. Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, University of Chicago Pritzker School of Medicine, Evanston, Illinois.
Abstract
INTRODUCTION: While many placental lesions have been identified and defined, the significance of multiple overlapping lesions has not been addressed. The purpose of our analysis was to evaluate overlapping patterns of placental pathology and determine meaningful phenotypes associated with adverse birth outcomes. METHODS: Placental pathology reports were obtained from a single hospital between 2009 and 2018. Placental lesions were grouped into four major categories: acute inflammation (AI), chronic inflammation (CI), maternal vascular malperfusion (MVM), and fetal vascular malperfusion (FVM). Within each category, lesions were classified as not present, low grade or high grade. Combinations of pathologies were evaluated in relation to preterm birth (<37 weeks) and small for gestational age (SGA) infant (birthweight <10th percentile). RESULTS: During the study period, 19,027 placentas were reviewed by pathologists. Results from interaction models indicate that MVM and MVM in combination with CI and/or FVM are associated with the greatest odds of SGA infant and PTB. When incorporating grade, we identified 21 phenotype groups, each with characteristic associations with the SGA infant and patterns of PTB. DISCUSSION: We have developed a comprehensive and meaningful placental phenotype that incorporates severity and multiplicity of placental lesions. We have also developed a web application to facilitate phenotype determination (https://placentaexpression.shinyapps.io/phenotype).
INTRODUCTION: While many placental lesions have been identified and defined, the significance of multiple overlapping lesions has not been addressed. The purpose of our analysis was to evaluate overlapping patterns of placental pathology and determine meaningful phenotypes associated with adverse birth outcomes. METHODS: Placental pathology reports were obtained from a single hospital between 2009 and 2018. Placental lesions were grouped into four major categories: acute inflammation (AI), chronic inflammation (CI), maternal vascular malperfusion (MVM), and fetal vascular malperfusion (FVM). Within each category, lesions were classified as not present, low grade or high grade. Combinations of pathologies were evaluated in relation to preterm birth (<37 weeks) and small for gestational age (SGA) infant (birthweight <10th percentile). RESULTS: During the study period, 19,027 placentas were reviewed by pathologists. Results from interaction models indicate that MVM and MVM in combination with CI and/or FVM are associated with the greatest odds of SGA infant and PTB. When incorporating grade, we identified 21 phenotype groups, each with characteristic associations with the SGA infant and patterns of PTB. DISCUSSION: We have developed a comprehensive and meaningful placental phenotype that incorporates severity and multiplicity of placental lesions. We have also developed a web application to facilitate phenotype determination (https://placentaexpression.shinyapps.io/phenotype).
Entities:
Keywords:
birth weight; infant; inflammation; pathologist; placenta; premature birth; small for gestational age birth
Authors: J Man; J C Hutchinson; A E Heazell; M Ashworth; I Jeffrey; N J Sebire Journal: Ultrasound Obstet Gynecol Date: 2016-10-25 Impact factor: 7.299
Authors: Solange N Eloundou; JiYeon Lee; Dan Wu; Jun Lei; Mia C Feller; Maide Ozen; Yan Zhu; Misun Hwang; Bei Jia; Han Xie; Julia L Clemens; Michael W McLane; Samar AlSaggaf; Nita Nair; Marsha Wills-Karp; Xiaobin Wang; Ernest M Graham; Ahmet Baschat; Irina Burd Journal: PLoS One Date: 2019-04-03 Impact factor: 3.240
Authors: Alexa A Freedman; Britney P Smart; Lauren S Keenan-Devlin; Ann Borders; Linda M Ernst; Gregory E Miller Journal: J Epidemiol Community Health Date: 2021-10-04 Impact factor: 3.710