Application of Bayesian Latent Variable Model for Early Detection of Gestational Diabetes Mellitus Without A Perfect Reference Standard Test by β‐human Chorionic Gonadotropin
| Autor: | M Amini, A Kazemnejad, F Zayeri, A Amirian, N Kariman |
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| Jazyk: | perština |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | مجله اپیدمیولوژی ایران, Vol 16, Iss 1, Pp 71-80 (2020) |
| Druh dokumentu: | article |
| ISSN: | 1735-7489 2228-7507 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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