Compromised Renal and Hepatic Functions and Unsteady Cellular Redox State during Preeclampsia and Gestational Diabetes Mellitus

Mishra, Jigeesha; Srivastava, Saurabh; Pandey, Kanti Bhooshan

doi:10.1016/j.arcmed.2021.03.003

Cited by 8 publications

(3 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is worth mentioning that there are also studies indicating that BUN is a risk factor for preeclampsia, which may be a direction for future research. 32 In addition, changes in cystatin C were found to be significant in this study. Each 1 mg/dL increase in cystatin C was associated with a 2.04-fold increase in the risk of preeclampsia in pregnant women with HIP (OR = 2.04; 95% CI:1.51-2.79, P<0.001), suggesting that early changes in renal function are of value in predicting the development of PE in pregnant women with HIP.…”

Section: Discussionsupporting

confidence: 53%

A Prediction Model of Preeclampsia in Hyperglycemia Pregnancy

Fang,

Liu,

et al. 2024

DMSO

View full text Add to dashboard Cite

To investigate the risk factors associated with preeclampsia in hyperglycemic pregnancies and develop a predictive model based on routine pregnancy care. Patients and Methods:The retrospective collection of clinical data was performed on 951 pregnant women with hyperglycemia, including those diagnosed with diabetes in pregnancy (DIP) and gestational diabetes mellitus (GDM), who delivered after 34 weeks of gestation at the Maternal and Child Health Hospital Affiliated to Anhui Medical University between January 2017 and December 2019. Observation indicators included liver and kidney function factors testing at 24-29 +6 weeks gestation, maternal age, and basal blood pressure. The indicators were screened univariately, and the "rms" package in R language was applied to explore the factors associated with PE in HIP pregnancy by stepwise regression. Multivariable logistic regression analysis was used to develop the prediction model. Based on the above results, a nomogram was constructed to predict the risk of PE occurrence in pregnant women with HIP. Then, the model was evaluated from three aspects: discrimination, calibration, and clinical utility. The internal validation was performed using the bootstrap procedure. Results: Multivariate logistic regression analysis showed that cystatin C, uric acid, glutamyl aminotransferase, blood urea nitrogen, and basal systolic blood pressure as predictors of PE in pregnancy with HIP. The predictive model yielded an area under curve (AUC) value of 0.8031 (95% CI: 0.7383-0.8679), with an optimal threshold of 0.0805, at which point the sensitivity was 0.8307 and specificity of 0.6604. Hosmer-Lemeshow test values were P = 0.3736, Brier score value was 0.0461. After 1000 Bootstrap resamplings for internal validation, the AUC was 0.7886, the Brier score was 0.0478 and the predicted probability of the calibration curve was similar to the actual probability. A nomogram was constructed based on the above to visualize the model. Conclusion:This study developed a model for predicting PE in pregnant women with HIP, achieving high predictive performance of PE risk through the information of routine pregnancy care.

show abstract

Section: Discussionsupporting

confidence: 53%

A Prediction Model of Preeclampsia in Hyperglycemia Pregnancy

Fang,

Liu,

et al. 2024

DMSO

View full text Add to dashboard Cite

show abstract

“…In our study, BUN was a protective factor for patients with PE, and an increase in their levels can to some extent reduce the risk of PE. It is worth mentioning that there are also studies indicating that BUN is a risk factor for preeclampsia, which may be a direction for future research 32 . In addition, changes in cystatin C were found to be signi cant in this study.…”

Section: Discussionmentioning

confidence: 97%

A prediction model of preeclampsia in hyperglycemia pregnancy

Fang,

Liu,

et al. 2023

Preprint

View full text Add to dashboard Cite

Background Hyperglycemia in pregnancy (HIP) and preeclampsia (PE) are common pregnancy complications. Identifying high-risk factors for preeclampsia in pregnant women with hyperglycemia and predicting the occurrence of preeclampsia can contribute to disease grading management. This study aimed to develop a predictive model for the development of PE in pregnant women with HIP through the information of routine pregnancy care to provide a primary screening for more effective interventions. Method The clinical data from 951 pregnant women with hyperglycemia who delivered after 34 weeks of gestation were collected retrospectively. Observation indicators included liver and kidney function factors testing at 24–29+ 6 weeks gestation, maternal age, and basal blood pressure. The indicators were screened univariately, and the "rms" package was applied to explore the factors associated with PE in HIP pregnancy by stepwise regression. Multivariable logistic regression analysis was used to develop the prediction model. Based on the above results, a nomogram was constructed to predict the risk of PE occurrence in pregnant women with HIP. Then, evaluate the model from different perspectives. The internal validation was performed using the bootstrap procedure. Results Multivariate logistic regression analysis showed that cystatin C, uric acid, glutamyl aminotransferase, urea nitrogen, and basal systolic blood pressure as predictors of PE in pregnancy with HIP. The predictive model yielded an area under curve (AUC) value of 0.8031 (95% CI:0.7383–0.8679), with an optimal threshold of 0.0805, at which point the sensitivity was 0.8307 and specificity of 0.6604. Hosmer–Lemeshow test values were P = 0.3736, Brier score value was 0.0461. After 1000 Bootstrap re-samplings for internal validation, the AUC was 0.7886, the Brier score was 0.0478 and the predicted probability of the calibration curve was similar to the actual probability. A nomogram was constructed based on the above to visualize the model. Conclusion This study developed a model for predicting PE in pregnant women with HIP, achieving high predictive performance of PE risk through the information of routine pregnancy care.

show abstract

“…Mothers with GDM are at risk of caesarean delivery, hypertension, preeclampsia (PE) and higher incidence of type 2 diabetes mellitus (T2DM) and cardiovascular disease incidence later on [ 6 ]. Moreover, diabetes leads to important renal complications in adults and young people that can interest mothers affected by gestational diabetes and their children [ 7 , 8 , 9 , 10 ]. Thus, an early diagnosis and treatment of GDM is very important to prevent possible complications of this pregnancy disorder.…”

Section: Introductionmentioning

confidence: 99%

HtrA1 in Gestational Diabetes Mellitus: A Possible Biomarker?

et al. 2022

View full text Add to dashboard Cite

Background: The high-temperature requirement A 1 (HtrA1) is a multidomain secretory protein with serine-protease activity, expressed in many tissues, including placenta, where its expression is higher in the first trimester, suggesting an association of this serine protease in early phases of human placenta development. In this study, we evaluated maternal serum HtrA1 levels in the first and third trimester of gestation. In particular, we evaluated a possible role of HtrA1 as an early marker of gestational diabetes mellitus (GDM) in the first trimester of gestation. Methods: We evaluated HtrA1 serum levels in the third trimester (36–40 weeks) in normal pregnancies (n = 20) and GDM pregnancies (n = 20) by using ELISA analysis. Secondly, we performed the same analysis by using the first trimester sera (10–12 weeks) of healthy pregnant women that will develop a normal pregnancy (n = 210) or GDM (n = 28) during pregnancy. Results: We found that HtrA1 serum levels in the third trimester were higher in pregnancies complicated by GDM. Interestingly, higher HtrA1 serum levels were also found in the first trimester in women developing GDM later during the second–third trimester. No significant differences in terms of maternal age and gestational age were found between cases and controls. Women with GDM shown significantly higher pre-pregnancy BMI values compared to controls. Moreover, the probability of GDM occurrence significantly increased with increasing HtrA1 levels and BMI values. The ROC curve showed a good accuracy in predicting GDM, with an AUC of 0.74 (95%CI: 0.64–0.92). Conclusions: These results suggest an important role of HtrA1 as an early predictive marker of GDM in the first trimester of gestation, showing a significative clinical relevance for prevention of this disease.

show abstract

Compromised Renal and Hepatic Functions and Unsteady Cellular Redox State during Preeclampsia and Gestational Diabetes Mellitus

Cited by 8 publications

References 31 publications

A Prediction Model of Preeclampsia in Hyperglycemia Pregnancy

A Prediction Model of Preeclampsia in Hyperglycemia Pregnancy

A prediction model of preeclampsia in hyperglycemia pregnancy

HtrA1 in Gestational Diabetes Mellitus: A Possible Biomarker?

Contact Info

Product

Resources

About