Cardiovascular diabetology · 2024
Association between atherogenic index of plasma and gestational diabetes mellitus: a prospective cohort study based on the Korean population.
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Zhang Juan, Suo Yaoyu, Wang Li, Liu Dong, Jia Yue, Fu Yajuan, Fan Weining, Jiang Yideng
Аннотация
BACKGROUND: Atherogenic index of plasma (AIP) is a non-traditional lipid parameter that can reflect the burden of atherosclerosis. A lipid profile resembling atherosclerosis emerged during pregnancy. Although lipid metabolism is pivotal in diabetes pathogenesis, there is no evidence linking AIP to gestational diabetes mellitus (GDM). Therefore, our objective was to explore the relationship between AIP and GDM and assess AIP's predictive capability for GDM.
METHODS: This was a secondary analysis based on data from a prospective cohort study in Korea involving 585 single pregnant women. AIP was calculated as log10 (TG/HDL). We examined the relationship between AIP and GDM using logistic regression models, curve fitting, sensitivity analyses, and subgroup analyses. Receiver operating characteristic (ROC) analysis was also used to determine the ability of AIP to predict GDM.
RESULTS: The average age of the participants was 32.06 ± 3.76 years. The AIP was 0.24 ± 0.20 on average. The GDM incidence was 6.15%. After adjustment for potentially confounding variables, AIP showed a positive linear relationship with GDM (P for non-linearity: 0.801, OR 1.58, 95% CI 1.27-1.97). The robustness of the connection between AIP and GDM was demonstrated by sensitivity analyses and subgroup analyses. An area under the ROC curve of 0.7879 (95% CI 0.7087-0.8671) indicates that AIP is an excellent predictor of GDM. With a specificity of 75.41% and sensitivity of 72.22%, the ideal AIP cut-off value for identifying GDM was 0.3557.
CONCLUSIONS: This study revealed that the AIP at 10-14 weeks of gestation was independently and positively correlated with GDM risk. AIP could serve as an early screening and monitoring tool for pregnant women at high risk of GDM, thereby optimizing GDM prevention strategies.
TRIAL REGISTRATION: ClinicalTrials.gov registration no. NCT02276144.
METHODS: This was a secondary analysis based on data from a prospective cohort study in Korea involving 585 single pregnant women. AIP was calculated as log10 (TG/HDL). We examined the relationship between AIP and GDM using logistic regression models, curve fitting, sensitivity analyses, and subgroup analyses. Receiver operating characteristic (ROC) analysis was also used to determine the ability of AIP to predict GDM.
RESULTS: The average age of the participants was 32.06 ± 3.76 years. The AIP was 0.24 ± 0.20 on average. The GDM incidence was 6.15%. After adjustment for potentially confounding variables, AIP showed a positive linear relationship with GDM (P for non-linearity: 0.801, OR 1.58, 95% CI 1.27-1.97). The robustness of the connection between AIP and GDM was demonstrated by sensitivity analyses and subgroup analyses. An area under the ROC curve of 0.7879 (95% CI 0.7087-0.8671) indicates that AIP is an excellent predictor of GDM. With a specificity of 75.41% and sensitivity of 72.22%, the ideal AIP cut-off value for identifying GDM was 0.3557.
CONCLUSIONS: This study revealed that the AIP at 10-14 weeks of gestation was independently and positively correlated with GDM risk. AIP could serve as an early screening and monitoring tool for pregnant women at high risk of GDM, thereby optimizing GDM prevention strategies.
TRIAL REGISTRATION: ClinicalTrials.gov registration no. NCT02276144.