Application of Bayesian Latent Variable Model for Early Detection of Gestational Diabetes Mellitus without a Perfect Reference Standard Test by B-Human Chorionic Gonadotropin

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AMINI M.; KAZEMNEJAD A.; ZAYERI F.; AMIRIAN A.; KARIMAN N.

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Journal: Iranian Journal of Epidemiology Year:2020 | Volume:16 | Issue:1 Page(s): 71-80

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Title

Application of Bayesian Latent Variable Model for Early Detection of Gestational Diabetes Mellitus without a Perfect Reference Standard Test by B-Human Chorionic Gonadotropin

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Keywords

Latent variable modelingQ1

Receiver operating characteristic (ROC) curveQ1

Bayesian approachQ2

Gestational diabetesQ2

Human chorionic gonadotropinQ1

Abstract

Background and Objectives: Gestational diabetes mellitus (GDM) is a medical problem in pregnancy, and its late diagnosis can cause adverse effects in the mother and fetus. The purpose of this research was to estimate the accuracy parameters of a biomarker for early prediction of Gestational diabetes in the absence of a perfect reference standard test. Methods: This study was conducted in 523 pregnant women who presented to Mahdieh Hospital and Taleghani Hospital affiliated with Shahid Beheshti University of Medical Sciences, Tehran, Iran 2017-2018. As a predictor for detecting GDM, beta-Human chorionic gonadotropin (β-hCG) measurements were recorded during 14-17th weeks’ gestation in a checklist. The Bayesian latent variable model was used to estimate the sensitivity, specificity, and area under receiver operating characteristic curve (AUC). Bayesian parameter estimation was calculated using the R2OpenBUGS package in R version 3. 5. 3. Results: The median gestational age was 33 years. In the absence of a perfect reference test, the applied model had a sensitivity, specificity, and AUC of 78% (95% credible interval (CrI): 0. 66-0. 83), 83% (95% CrI: 0. 74-0. 89), and 0. 72 (95% CrI: 0. 64-0. 88) for β-hCG, respectively. Conclusion: According to the results of this study, β-hCG may be an acceptable biomarker for early diagnosis of diabetes in pregnant women in the absence of a perfect reference test.

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APA: Copy

AMINI, M., KAZEMNEJAD, A., ZAYERI, F., AMIRIAN, A., & KARIMAN, N.. (2020). Application of Bayesian Latent Variable Model for Early Detection of Gestational Diabetes Mellitus without a Perfect Reference Standard Test by B-Human Chorionic Gonadotropin. IRANIAN JOURNAL OF EPIDEMIOLOGY, 16(1 ), 71-80. SID. https://sid.ir/paper/404399/en

Vancouver: Copy

AMINI M., KAZEMNEJAD A., ZAYERI F., AMIRIAN A., KARIMAN N.. Application of Bayesian Latent Variable Model for Early Detection of Gestational Diabetes Mellitus without a Perfect Reference Standard Test by B-Human Chorionic Gonadotropin. IRANIAN JOURNAL OF EPIDEMIOLOGY[Internet]. 2020;16(1 ):71-80. Available from: https://sid.ir/paper/404399/en

IEEE: Copy

M. AMINI, A. KAZEMNEJAD, F. ZAYERI, A. AMIRIAN, and N. KARIMAN, “Application of Bayesian Latent Variable Model for Early Detection of Gestational Diabetes Mellitus without a Perfect Reference Standard Test by B-Human Chorionic Gonadotropin,” IRANIAN JOURNAL OF EPIDEMIOLOGY, vol. 16, no. 1 , pp. 71–80, 2020, [Online]. Available: https://sid.ir/paper/404399/en

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