Predictive factors of gestational diabetes in pregnancies following assisted reproductive technology: a nested case–control study

Azam Kouhkan, Mohammad E. Khamseh, Ashraf Moini, Reihaneh Pirjani, Ameneh Ebrahim Valojerdi, Arezoo Arabipoor, Roya Hosseini, Hamid Reza Baradaran*

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Purpose: To evaluate predictive factors for gestational diabetes mellitus (GDM) in singleton pregnancy following assisted reproductive technology (ART). Methods: This nested case–control study was performed during October 2016–June 2017. Pregnant women who conceived following ART procedures referred to infertility clinic were selected and categorized into GDM and non-GDM based on ADA/IAPDSG criteria. The study variables including age, educational status, first-degree family history of chronic diseases, systolic and diastolic blood pressure, previous obstetric and perinatal outcomes, infertility history, and ART cycle characteristics were collected from medical records. Prediction model to develop GDM was employed by binary logistic regression analysis after adjustment for age and body mass index, family history of diabetes, and gravidity. Results: In total, 270 women with singleton pregnancies (consisted of 135 GDM and 135 non-GDM women) conceived were studied. According to the final model, significant predictors of GDM were history of polycystic ovarian syndrome (PCOS), previous ovarian hyper-stimulation syndrome (OHSS) risk and progesterone injections. Administration of injectable progesterone during the first 10–12 weeks of pregnancy was associated with an approximately twofold increased risk of developing GDM [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.27–4.09)] compared to vaginal progesterone. In addition, the regression analysis revealed that previous OHSS risk (OR 2.40, 95% CI 1.34–4.31) and history of PCOS (OR 2.76, 95% CI 1.26–6.06) were other most important predictors of GDM. Conclusions: The route of progesterone administration, previous OHSS risk and history of PCOS seem to be putative risk factors for GDM in women conceived by ART.

Original languageEnglish
Pages (from-to)199-206
Number of pages8
JournalArchives of Gynecology and Obstetrics
Volume298
Issue number1
Early online date5 May 2018
DOIs
Publication statusPublished - 1 Jul 2018

Fingerprint

Assisted Reproductive Techniques
Gestational Diabetes
Pregnancy
Progesterone
Ovulation Induction
Polycystic Ovary Syndrome
Odds Ratio
Confidence Intervals
Infertility
Diabetes Mellitus
Regression Analysis
Gravidity
Blood Pressure
Educational Status
Injections
Obstetrics
Medical Records
Pregnant Women
Body Mass Index
Chronic Disease

Keywords

  • Assisted reproductive technology
  • Gestational diabetes mellitus
  • Predictive factors

ASJC Scopus subject areas

  • Obstetrics and Gynaecology

Cite this

Predictive factors of gestational diabetes in pregnancies following assisted reproductive technology : a nested case–control study. / Kouhkan, Azam; Khamseh, Mohammad E.; Moini, Ashraf; Pirjani, Reihaneh; Valojerdi, Ameneh Ebrahim; Arabipoor, Arezoo; Hosseini, Roya; Baradaran, Hamid Reza.

In: Archives of Gynecology and Obstetrics, Vol. 298, No. 1, 01.07.2018, p. 199-206.

Research output: Contribution to journalArticle

Kouhkan, Azam ; Khamseh, Mohammad E. ; Moini, Ashraf ; Pirjani, Reihaneh ; Valojerdi, Ameneh Ebrahim ; Arabipoor, Arezoo ; Hosseini, Roya ; Baradaran, Hamid Reza. / Predictive factors of gestational diabetes in pregnancies following assisted reproductive technology : a nested case–control study. In: Archives of Gynecology and Obstetrics. 2018 ; Vol. 298, No. 1. pp. 199-206.
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abstract = "Purpose: To evaluate predictive factors for gestational diabetes mellitus (GDM) in singleton pregnancy following assisted reproductive technology (ART). Methods: This nested case–control study was performed during October 2016–June 2017. Pregnant women who conceived following ART procedures referred to infertility clinic were selected and categorized into GDM and non-GDM based on ADA/IAPDSG criteria. The study variables including age, educational status, first-degree family history of chronic diseases, systolic and diastolic blood pressure, previous obstetric and perinatal outcomes, infertility history, and ART cycle characteristics were collected from medical records. Prediction model to develop GDM was employed by binary logistic regression analysis after adjustment for age and body mass index, family history of diabetes, and gravidity. Results: In total, 270 women with singleton pregnancies (consisted of 135 GDM and 135 non-GDM women) conceived were studied. According to the final model, significant predictors of GDM were history of polycystic ovarian syndrome (PCOS), previous ovarian hyper-stimulation syndrome (OHSS) risk and progesterone injections. Administration of injectable progesterone during the first 10–12 weeks of pregnancy was associated with an approximately twofold increased risk of developing GDM [odds ratio (OR) 2.28, 95{\%} confidence interval (CI) 1.27–4.09)] compared to vaginal progesterone. In addition, the regression analysis revealed that previous OHSS risk (OR 2.40, 95{\%} CI 1.34–4.31) and history of PCOS (OR 2.76, 95{\%} CI 1.26–6.06) were other most important predictors of GDM. Conclusions: The route of progesterone administration, previous OHSS risk and history of PCOS seem to be putative risk factors for GDM in women conceived by ART.",
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T2 - a nested case–control study

AU - Kouhkan, Azam

AU - Khamseh, Mohammad E.

AU - Moini, Ashraf

AU - Pirjani, Reihaneh

AU - Valojerdi, Ameneh Ebrahim

AU - Arabipoor, Arezoo

AU - Hosseini, Roya

AU - Baradaran, Hamid Reza

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N2 - Purpose: To evaluate predictive factors for gestational diabetes mellitus (GDM) in singleton pregnancy following assisted reproductive technology (ART). Methods: This nested case–control study was performed during October 2016–June 2017. Pregnant women who conceived following ART procedures referred to infertility clinic were selected and categorized into GDM and non-GDM based on ADA/IAPDSG criteria. The study variables including age, educational status, first-degree family history of chronic diseases, systolic and diastolic blood pressure, previous obstetric and perinatal outcomes, infertility history, and ART cycle characteristics were collected from medical records. Prediction model to develop GDM was employed by binary logistic regression analysis after adjustment for age and body mass index, family history of diabetes, and gravidity. Results: In total, 270 women with singleton pregnancies (consisted of 135 GDM and 135 non-GDM women) conceived were studied. According to the final model, significant predictors of GDM were history of polycystic ovarian syndrome (PCOS), previous ovarian hyper-stimulation syndrome (OHSS) risk and progesterone injections. Administration of injectable progesterone during the first 10–12 weeks of pregnancy was associated with an approximately twofold increased risk of developing GDM [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.27–4.09)] compared to vaginal progesterone. In addition, the regression analysis revealed that previous OHSS risk (OR 2.40, 95% CI 1.34–4.31) and history of PCOS (OR 2.76, 95% CI 1.26–6.06) were other most important predictors of GDM. Conclusions: The route of progesterone administration, previous OHSS risk and history of PCOS seem to be putative risk factors for GDM in women conceived by ART.

AB - Purpose: To evaluate predictive factors for gestational diabetes mellitus (GDM) in singleton pregnancy following assisted reproductive technology (ART). Methods: This nested case–control study was performed during October 2016–June 2017. Pregnant women who conceived following ART procedures referred to infertility clinic were selected and categorized into GDM and non-GDM based on ADA/IAPDSG criteria. The study variables including age, educational status, first-degree family history of chronic diseases, systolic and diastolic blood pressure, previous obstetric and perinatal outcomes, infertility history, and ART cycle characteristics were collected from medical records. Prediction model to develop GDM was employed by binary logistic regression analysis after adjustment for age and body mass index, family history of diabetes, and gravidity. Results: In total, 270 women with singleton pregnancies (consisted of 135 GDM and 135 non-GDM women) conceived were studied. According to the final model, significant predictors of GDM were history of polycystic ovarian syndrome (PCOS), previous ovarian hyper-stimulation syndrome (OHSS) risk and progesterone injections. Administration of injectable progesterone during the first 10–12 weeks of pregnancy was associated with an approximately twofold increased risk of developing GDM [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.27–4.09)] compared to vaginal progesterone. In addition, the regression analysis revealed that previous OHSS risk (OR 2.40, 95% CI 1.34–4.31) and history of PCOS (OR 2.76, 95% CI 1.26–6.06) were other most important predictors of GDM. Conclusions: The route of progesterone administration, previous OHSS risk and history of PCOS seem to be putative risk factors for GDM in women conceived by ART.

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