Tracy M Tomlinson1, Dorothea J Mostello2, Kee-Hak Lim3, Jennifer S Pritchard4, Gil Gross2. 1. Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology and Women's Health, Saint Louis University School of Medicine, 6420 Clayton Road, Suite 2800, Saint Louis, MO, 63117, USA. tracy.tomlinson@health.slu.edu. 2. Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology and Women's Health, Saint Louis University School of Medicine, 6420 Clayton Road, Suite 2800, Saint Louis, MO, 63117, USA. 3. Department of Obstetrics and Gynecology, Boston Maternal-Fetal Medicine, South Shore Hospital, Weymouth, MA, USA. 4. New England Quality Care Alliance, Braintree, MA, USA.
Abstract
PURPOSE: To develop an index to predict fetal overgrowth in pregnancies complicated by diabetes. METHODS: Data were derived from a cohort of 275 women with singleton gestations in a collaborative diabetes in pregnancy program. Regression analysis incorporated clinical factors available in the first 20-30 weeks of pregnancy that were assigned beta-coefficient-based weights, the sum of which yielded a fetal overgrowth index (composite score). RESULTS: Fifty-one (18.5%) pregnancies were complicated by fetal overgrowth. The derived index included five clinical factors: age ≤ 30, history of macrosomia, excessive gestational weight gain, enlarged fetal abdominal circumference, and fasting hyperglycemia. Area under the curve (AUC) for the index is 0.88 [95% confidence interval (CI) 0.82-0.92]. Cut-points were selected to identify "high-risk" and "low-risk" ranges (≥ 8 and ≤ 3) that have positive and negative predictive values of 84% (95% CI 70-98%) and 95% (95% CI 92-98%), respectively. The majority of women in our cohort (n = 182, 66%) had a "low-risk" index while 9% (n = 25) had a "high-risk" index. Sub-analyses of nulliparous women and women with gestational and pre-gestational diabetes revealed that the overgrowth index was equally or more predictive when applied separately to each of these groups. CONCLUSION: This fetal overgrowth index that incorporates five clinical factors provides a means of predicting fetal overgrowth and thereby serves as a tool for targeting the allocation of healthcare resources and treatment individualization.
PURPOSE: To develop an index to predict fetal overgrowth in pregnancies complicated by diabetes. METHODS: Data were derived from a cohort of 275 women with singleton gestations in a collaborative diabetes in pregnancy program. Regression analysis incorporated clinical factors available in the first 20-30 weeks of pregnancy that were assigned beta-coefficient-based weights, the sum of which yielded a fetal overgrowth index (composite score). RESULTS: Fifty-one (18.5%) pregnancies were complicated by fetal overgrowth. The derived index included five clinical factors: age ≤ 30, history of macrosomia, excessive gestational weight gain, enlarged fetal abdominal circumference, and fasting hyperglycemia. Area under the curve (AUC) for the index is 0.88 [95% confidence interval (CI) 0.82-0.92]. Cut-points were selected to identify "high-risk" and "low-risk" ranges (≥ 8 and ≤ 3) that have positive and negative predictive values of 84% (95% CI 70-98%) and 95% (95% CI 92-98%), respectively. The majority of women in our cohort (n = 182, 66%) had a "low-risk" index while 9% (n = 25) had a "high-risk" index. Sub-analyses of nulliparous women and women with gestational and pre-gestational diabetes revealed that the overgrowth index was equally or more predictive when applied separately to each of these groups. CONCLUSION: This fetal overgrowth index that incorporates five clinical factors provides a means of predicting fetal overgrowth and thereby serves as a tool for targeting the allocation of healthcare resources and treatment individualization.
Authors: Shamil D Cooray; Lihini A Wijeyaratne; Georgia Soldatos; John Allotey; Jacqueline A Boyle; Helena J Teede Journal: Int J Environ Res Public Health Date: 2020-04-27 Impact factor: 3.390
Authors: Shamil D Cooray; Jacqueline A Boyle; Georgia Soldatos; Javier Zamora; Borja M Fernández Félix; John Allotey; Shakila Thangaratinam; Helena J Teede Journal: BMJ Open Date: 2020-11-05 Impact factor: 2.692