Abstract

To explore the application value of serum Gal-13, GLP-1 and VEGF in the prevention and guidance of adverse pregnancy outcomes in gestational diabetes (GDM). A retrospective study with case-control method was used to select 1 012 GDM patients from Haikou Maternal and Child Health Hospital from January 2019 to December 2022 as the study objects, and they were divided into poor pregnancy outcome group (n=342) and good pregnancy outcome group (n=670) according to whether they had adverse pregnancy outcomes. The medical records of 521 healthy women with normal glucose metabolism were selected as the control group. Serum Gal-13 and GLP-1 were detected by enzyme-linked immunosorbent assay and VEGF was determined by IAMMGE specific protein analyzer. After comparing the differences of the above factors among the three groups, multivariate logistic regression model was used to analyze the influencing factors of adverse pregnancy outcomes in GDM patients, and ROC curve was drawn to analyze the predictive value of serum Gal-13, GLP-1 and VEGF levels on adverse pregnancy outcomes in GDM patients. The results showed that Fasting blood glucose (FPG), glycosylated hemoglobin (HbA1c) and fasting insulin (FINS) in the adverse pregnancy outcome group were 5.92(4.98, 6.41) mmol/L, 5.32(4.96, 5.47)%, 62.56(49.21,99.50) pmol/L, VEGF was 495.47(389.14, 567.13) ng/L, TSH was 1.48(1.34, 1.58) mIU/L, right ventricular myocardial work index (Tei index) was 0.59(0.45, 0.67), 89 cases of elderly parturients; FPG was 4.45(4.16, 5.03) mmol/L, HbA1c was 5.04(4.86, 5.29)%, FINS was 57.41(46.90, 74.08) pmol/L, VEGF was 405.84(348.02, 462.68) ng/L, TSH was 1.42(1.25, 1.50) mIU/L, Tei index was 0.50(0.47, 0.64), there were 142 cases of old women. In the control group, FPG was 4.33(4.05, 4.75) mmol/L, HbA1c was 5.01(4.13, 5.18)%, FINS was 38.48(36.76, 41.72) pmol/L and VEGF was 302.45(283.14, 336.56) ng/L, TSH was 1.32(1.24, 1.47)mIU/L, Tei index was 0.48(0.39, 0.59), and there were 106 elderly parturiencies. The levels of FPG, HbA1c, FINS, VEGF, TSH and Tei index in the adverse pregnancy outcome group and the good pregnancy outcome group were higher than those in the control group, and the proportion of elderly parturients was higher than that in the control group, and the adverse pregnancy outcome group was higher than that in the good pregnancy outcome group. The differences were statistically significant (H=8.620, P<0.001, H=2.616, P=0.014, H=6.156, P<0.001, H=3.051, P<0.001, H=4.892, P=0.044, χ2=2.548, P=0.045). In the adverse pregnancy outcome group, Gal-13 was 15.27(8.35, 24.45)pg/ml, GLP-1 was 9.27(8.26, 12.35) pmol/L and FT4 was 11.59(9.67, 13.48) pmol/L. In the group with good pregnancy outcome, Gal-13 was 25.34(20.14, 29.73) pg/ml, GLP-1 was 12.38(10.25, 15.63) pmol/L and FT4 was 13.86(10.67, 15.10) pmol/L. In the control group, Gal-13 was 31.21(27.48, 34.45) pg/ml, GLP-1 was 11.34(10.40, 14.37) pmol/L and FT4 was 14.15(10.75, 15.43)pmol/L. The levels of Gal-13, GLP-1 and FT4 in the adverse pregnancy outcome group and the good pregnancy outcome group were significantly lower than those in the control group, and the adverse pregnancy outcome group was lower than that in the good pregnancy outcome group. The differences were statistically significant (H=6.458, P=0.011, H=8.445, P<0.001, H=5.694, P<0.001). The levels of Gal-13 and GLP-1 in normal blood glucose recovery group were higher than those in non-normal blood glucose recovery group, and the levels of VEGF were lower than those in non-normal blood glucose recovery group (P<0.05).In multivariate logistic regression analysis, Gal-13, GLP-1, VEGF, TSH, FT4 and Tei indexes were independent influencing factors for adverse pregnancy outcomes with GDM (P<0.05). ROC curve analysis showed that the AUC of Gal-13, GLP-1 and VEGF alone in predicting adverse pregnancy were 0.779, 0.761 and 0.615, respectively. The value of the combined diagnosis was the highest (AUC=0.912), the sensitivity was 90.1%, and the specificity was 80.0%. In conclusion, Gal-13, GLP-1 and VEGF may be independent influencing factors for adverse pregnancy outcomes in GDM patients, and the combined detection of the three may help to improve the auxiliary diagnostic efficacy for predicting adverse pregnancy outcomes.

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