ArticleJournal of clinical laboratory analysis2022
The diagnostic model for early detection of gestational diabetes mellitus and gestational diabetic nephropathy.
Article in Journal of clinical laboratory analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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2 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Association of immune-inflammation indexes with incidence and prognosis of diabetic nephropathy: a systematic review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- The diagnostic model for early detection of gestational diabetes mellitus and gestational diabetic nephropathy.Journal of clinical laboratory analysis · 2022Article
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6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundGestational diabetes mellitus (GDM) and gestational diabetic nephropathy (GDN) have become an increasingly serious problem worldwide, which can cause a large number of adverse pregnancy consequences for mothers and infants. However, the diagnosis of GDM and GDN remains a challenge due to the lack of optimal biomarkers, and the examination has high requirements for patient compliance. We aimed to establish a simple early diagnostic model for GDM and GDN.
methodsWe recruited 50 healthy pregnant (HP), 99 GDM patients, 99 GDN patients at Daping Hospital. Renal function indicators and blood cell indicators were collected for all patients.
resultsCompared with HP, GDM, and GDN patients exhibited significantly higher urea/creatinine ratio and NEU. The diagnostic model1 based on the combination of urea/creatinine ratio and NEU was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.77 (0.7, 0.84) in distinguishing GDM from HP, and the AUC of the diagnostic model was 0.94 (0.9, 0.97) in distinguishing GDN from HP. Meanwhile, the diagnostic model2 based on the combination of β2-mG, PLT, and NEU in GDM and GDN patients was built using logistic regression, and the area under the ROC curve (AUC ROC) was 0.79 (0.73, 0.85), which was larger than the individual biomarker AUC.
conclusionOur study demonstrated that the diagnostic model established by the combination of renal function indicators and blood cell indicators could facilitate the differential diagnosis of GDM and GDN patients.
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