Betatrophin for diagnosis and prognosis of mothers with gestational diabetes mellitus. Issue 2 (February 2019)

• Record Type: Journal Article
• Authors: Pan, Ruirong; Zhang, Haiming; Yu, Shuping; Deng, Jialiang; Ma, Suxian; Li, Yanyan; Yuan, Guoyue; Wang, Jifang
• Is Part Of: Journal of international medical research. Volume 47:Issue 2(2019)
• Page Start: 710
• Page End: 717
• Publication Date: 2019-02
• Subjects: Gestational diabetes mellitus -- postpartum diabetes mellitus -- betatrophin -- biomarker -- prognosis -- homeostatic model assessment–insulin resistance; Medicine -- Periodicals; Pharmacology -- Periodicals; 610.5
• DOI: 10.1177/0300060518808683
• Languages: English
• ISSNs: 0300-0605

Abstract

Objectives: Betatrophin is a widely used diagnostic marker for type 2 diabetes mellitus (DM), but its clinical utility in diagnosing gestational DM (GDM) is unclear. We evaluated the relationship between betatrophin and the risk of GDM as well as the ability of betatrophin to predict postpartum type 2 DM (PDM). Methods: In total, 386 patients were categorized into those with and without PDM. All underwent the oral glucose tolerance test while pregnant. Betatrophin was assessed to examine the diagnostic characteristics of GDM. Results: The betatrophin concentration was remarkably higher in patients with than without GDM. The patients were categorized into three groups; those with a betatrophin concentration of 300 to 600 pg/mL and >600 pg/mL had a higher risk of GDM after adjusting for body mass index, age, homeostatic model assessment–insulin resistance (HOMA-IR) concentration, and betatrophin concentration than those with a betatrophin concentration of <300 pg/mL. The HOMA-IR concentration tended to increase as the betatrophin concentration increased, and betatrophin was independently associated with GDM after adjusting for confounders. The betatrophin concentration was higher among pregnant patients with than without PDM. Conclusions: Betatrophin has high sensitivity but low specificity for diagnosing GDM and may be a promising predictor of PDM.