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Objective: To explore the changes in the feature of serum lipid in different trimester of normal pregnancy and GDM, analysis of the effect of diet therapy on blood lipid level on GDM and the relationship between serum and lipid. Methods: 92 normal pregnant women and 85 GDM women were inclusive in this study. The maternal serum lipid levels, diet intake and newborn weight of both groups were recorded. After diet therapy, GDM group was further divided into two subgroups, one with blood glucose under control and one with poor glycemic control according to the blood glucose monitoring. Results: LDL-C and apoB were significantly increased in GDM group compared to normal group in the first trimester(P < 0.05); GDM patients consume more energy having higher weight gain/ pregravid BMI compared to normal group till gestational diabetes was confirmed (P <0.05). Compared to early trimester, TC,TG, LDL-C, LDL-C,apoA1 and apoB were increased in the normal group in late trimester(P <0.05); Compared to the control group in late phase, there was higher apoB, but lower TG in glucose control group. There were higher TC, TG and neonatal weight in the poor glycemic group compared to the control group in late phase (P < 0.05); There was a positive correlation between TC, TG and newbornweight (P < 0.05). Conclusion: With increasing gestational age, there is increasing level of blood lipid profile during pregnancy. Excessive nutrient intake and incidence of GDM may be related. Diet therapy can improve blood lipid status which may help control neonatal weight.

Background The objective of this study was to establish a risk assessment model for lower extremity deep venous thrombosis in critically ill patients and compared with Caprini, Padua and Wells risk assessment model to evaluate its efficacy. Methods We conducted a pooled analysis of prospective cohort studies. The outcomes of interest were lower extremity deep vein thrombosis group and Non-lower extremity deep vein thrombosis group were determined by univariate analysis, and SPSS was used to establish the back propagation artificial neural network prediction model. ROC curve was used to evaluate the predictive effectiveness of the model. Medcalc15.2 was used to compare the predictive capabilities of different models. Results 600 cases of intensive care unit patients were selected in this study. The prevalence of lower extremity venous thromboembolism after ICU admission was 12.5%. The results of univariate analysis that showed 16 statistically significant difference influencing factors. The ROC curve area of BP-ANN risk assessment model was 0.828, showing good predictive efficacy. In addition to the ROC curve area of BP-ANN risk assessment model was higher than Caprini, Padua and Wells model. Conclusion BP-ANN risk assessment model can play an auxiliary role in predicting the occurrence of lower extremity venous thromboembolism in critically ill patients. This model can provide a reference for medical staff to take preventive management measures.