RYUNG S. KIM, LIHUA LI, CARMEN R. ISASI, ATHENA PHILIS-TSIMIKAS, JEE-YOUNG MOON, JUNXIU LIU, DIANA S. WOLFE, CAROL J. LEVY
{"title":"1245-P: GDM 患者及其继发 2 型糖尿病的预后因素--电子队列回顾","authors":"RYUNG S. KIM, LIHUA LI, CARMEN R. ISASI, ATHENA PHILIS-TSIMIKAS, JEE-YOUNG MOON, JUNXIU LIU, DIANA S. WOLFE, CAROL J. LEVY","doi":"10.2337/db24-1245-p","DOIUrl":null,"url":null,"abstract":"Introduction: GDM affects 8-10% of pregnancies in the US and nearly 50% of these women have subsequent diabetes diagnosis. However, research on the prognostic factors of T2D incidence among women with GDM is scarce, due to the limited sample sizes. We aim 1) to construct a large electronic cohort of GDM and 2) to build a prognostic model for T2D incidence among patients with GDM. Methods: We extracted EMRs of patients diagnosed with GDM between 2016 and 2022 from two health systems in NYC: Montefiore (MMC) and Mt. Sinai. Only MMC patients were analyzed in this report. Prognostic factors during pregnancy included 32 baseline & pregnancy characteristics, 76 office visit variables, 418 lab tests, and prescription of 31 drugs. Time from GDM diagnosis to T2D was analyzed using proportional hazards models. Results: We collected EMRs of 6,014 GDM patients at MMC who were racially diverse with a median age of 32, BMI of 31.8 kg/m2. Among them, 355 (5.9%) later developed T2D, yielding a high T2D incidence rate (21.1 per 1,000 PY). There was an immediate heightened risk: T2D incidence proportions were 3.8% by 1 year after GDM diagnosis, and 11.9% by 5 years. The risk was elevated in Hispanic White (HR=2.3), Hispanic Non-White (HR=2.0), and Black (HR=2.3) compared to non-Hispanic White (p<0.00001). The risk was associated with higher BMI during pregnancy, insulin or oral-agent control compared to diet therapy, younger gestational age at GDM diagnosis, and Caesarean delivery. Lab findings associated with T2D risk included maternal glucose levels, erythrocyte MCH, monocytes, and ketone. T2D incidence was also associated with prescription of insulin therapy, oral treatment, aspirin, and iron supplements likely indicating underlying obstetric complications. Conclusions: A large electronic cohort of GDM patients identified potential prognostic factors of subsequent T2D. Future directions include calibration of 2 cohorts to establish the largest electronic cohort of GDM to date and building prognostic models for T2D risk. Disclosure R.S. Kim: None. L. Li: None. C.R. Isasi: None. A. Philis-Tsimikas: Advisory Panel; Dexcom, Inc., Lilly Diabetes, Novo Nordisk, Sanofi, Medtronic, Bayer Inc. J. Moon: None. J. Liu: None. D.S. Wolfe: None. C.J. Levy: Research Support; Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; MannKind Corporation, T1D Exchange, Tandem Diabetes Care, Inc., Abbott, Insulet Corporation. Funding New York Regional Center for Diabetes Translation Research Pilot & Feasibility Project","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"26 1","pages":""},"PeriodicalIF":6.2000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"1245-P: GDM Patients and Prognostic Factors for Subsequent Type 2 Diabetes Mellitus—An Electronic Cohort Review\",\"authors\":\"RYUNG S. KIM, LIHUA LI, CARMEN R. ISASI, ATHENA PHILIS-TSIMIKAS, JEE-YOUNG MOON, JUNXIU LIU, DIANA S. WOLFE, CAROL J. LEVY\",\"doi\":\"10.2337/db24-1245-p\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Introduction: GDM affects 8-10% of pregnancies in the US and nearly 50% of these women have subsequent diabetes diagnosis. However, research on the prognostic factors of T2D incidence among women with GDM is scarce, due to the limited sample sizes. We aim 1) to construct a large electronic cohort of GDM and 2) to build a prognostic model for T2D incidence among patients with GDM. Methods: We extracted EMRs of patients diagnosed with GDM between 2016 and 2022 from two health systems in NYC: Montefiore (MMC) and Mt. Sinai. Only MMC patients were analyzed in this report. Prognostic factors during pregnancy included 32 baseline & pregnancy characteristics, 76 office visit variables, 418 lab tests, and prescription of 31 drugs. Time from GDM diagnosis to T2D was analyzed using proportional hazards models. Results: We collected EMRs of 6,014 GDM patients at MMC who were racially diverse with a median age of 32, BMI of 31.8 kg/m2. Among them, 355 (5.9%) later developed T2D, yielding a high T2D incidence rate (21.1 per 1,000 PY). There was an immediate heightened risk: T2D incidence proportions were 3.8% by 1 year after GDM diagnosis, and 11.9% by 5 years. The risk was elevated in Hispanic White (HR=2.3), Hispanic Non-White (HR=2.0), and Black (HR=2.3) compared to non-Hispanic White (p<0.00001). The risk was associated with higher BMI during pregnancy, insulin or oral-agent control compared to diet therapy, younger gestational age at GDM diagnosis, and Caesarean delivery. Lab findings associated with T2D risk included maternal glucose levels, erythrocyte MCH, monocytes, and ketone. T2D incidence was also associated with prescription of insulin therapy, oral treatment, aspirin, and iron supplements likely indicating underlying obstetric complications. Conclusions: A large electronic cohort of GDM patients identified potential prognostic factors of subsequent T2D. Future directions include calibration of 2 cohorts to establish the largest electronic cohort of GDM to date and building prognostic models for T2D risk. Disclosure R.S. Kim: None. L. Li: None. C.R. Isasi: None. A. 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1245-P: GDM Patients and Prognostic Factors for Subsequent Type 2 Diabetes Mellitus—An Electronic Cohort Review
Introduction: GDM affects 8-10% of pregnancies in the US and nearly 50% of these women have subsequent diabetes diagnosis. However, research on the prognostic factors of T2D incidence among women with GDM is scarce, due to the limited sample sizes. We aim 1) to construct a large electronic cohort of GDM and 2) to build a prognostic model for T2D incidence among patients with GDM. Methods: We extracted EMRs of patients diagnosed with GDM between 2016 and 2022 from two health systems in NYC: Montefiore (MMC) and Mt. Sinai. Only MMC patients were analyzed in this report. Prognostic factors during pregnancy included 32 baseline & pregnancy characteristics, 76 office visit variables, 418 lab tests, and prescription of 31 drugs. Time from GDM diagnosis to T2D was analyzed using proportional hazards models. Results: We collected EMRs of 6,014 GDM patients at MMC who were racially diverse with a median age of 32, BMI of 31.8 kg/m2. Among them, 355 (5.9%) later developed T2D, yielding a high T2D incidence rate (21.1 per 1,000 PY). There was an immediate heightened risk: T2D incidence proportions were 3.8% by 1 year after GDM diagnosis, and 11.9% by 5 years. The risk was elevated in Hispanic White (HR=2.3), Hispanic Non-White (HR=2.0), and Black (HR=2.3) compared to non-Hispanic White (p<0.00001). The risk was associated with higher BMI during pregnancy, insulin or oral-agent control compared to diet therapy, younger gestational age at GDM diagnosis, and Caesarean delivery. Lab findings associated with T2D risk included maternal glucose levels, erythrocyte MCH, monocytes, and ketone. T2D incidence was also associated with prescription of insulin therapy, oral treatment, aspirin, and iron supplements likely indicating underlying obstetric complications. Conclusions: A large electronic cohort of GDM patients identified potential prognostic factors of subsequent T2D. Future directions include calibration of 2 cohorts to establish the largest electronic cohort of GDM to date and building prognostic models for T2D risk. Disclosure R.S. Kim: None. L. Li: None. C.R. Isasi: None. A. Philis-Tsimikas: Advisory Panel; Dexcom, Inc., Lilly Diabetes, Novo Nordisk, Sanofi, Medtronic, Bayer Inc. J. Moon: None. J. Liu: None. D.S. Wolfe: None. C.J. Levy: Research Support; Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; MannKind Corporation, T1D Exchange, Tandem Diabetes Care, Inc., Abbott, Insulet Corporation. Funding New York Regional Center for Diabetes Translation Research Pilot & Feasibility Project
期刊介绍:
Diabetes is a scientific journal that publishes original research exploring the physiological and pathophysiological aspects of diabetes mellitus. We encourage submissions of manuscripts pertaining to laboratory, animal, or human research, covering a wide range of topics. Our primary focus is on investigative reports investigating various aspects such as the development and progression of diabetes, along with its associated complications. We also welcome studies delving into normal and pathological pancreatic islet function and intermediary metabolism, as well as exploring the mechanisms of drug and hormone action from a pharmacological perspective. Additionally, we encourage submissions that delve into the biochemical and molecular aspects of both normal and abnormal biological processes.
However, it is important to note that we do not publish studies relating to diabetes education or the application of accepted therapeutic and diagnostic approaches to patients with diabetes mellitus. Our aim is to provide a platform for research that contributes to advancing our understanding of the underlying mechanisms and processes of diabetes.