A predictive model of macrosomic birth based upon real-world clinical data from pregnant women

Gao, Jing; Shi, Huwei; Chen, Chao; Chen, Lei; Wang, Ping; Xiao, Zhongzhou; Yang, Sen; Chen, Jia-Yuan; Chen, Ruiyao; Lu, Lu; Shuqing, Luo; Yang, Kai; Xu, Jianpeng; Cheng, Weiwei

doi:10.1186/s12884-022-04981-9

Cited by 3 publications

References 33 publications

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A Model to Predict the Risk of Adverse Ocular Outcomes in Pregnant Women

Liu,

Wen,

Zou

et al. 2024

Br J Hosp Med

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Aims/Background Pregnancy can affect various bodily functions, including metabolism, cardiovascular function, and eyesight. Pathological ocular changes observed during pregnancy are linked to the development of pregnancy-specific conditions, such as preeclampsia/eclampsia and gestational diabetes. This study aims to analyze clinical data disease history and maternal characteristics collected during pregnancy, to determine ocular parameters and develop a risk prediction model for adverse ocular outcomes. Methods We retrospectively analyzed the medical records of 760 pregnant women (1520 eyes) from September 2020 to September 2022 at The Third Affiliated Hospital of Guangzhou Medical University. We identified maternal variables that could influence adverse ocular outcomes, including maternal age, pregnancy-induced hypertension (PIH), gestational diabetes mellitus (GDM), eclampsia, pre-eclampsia, uterine disease, fetal abnormalities, in vitro fertilization with embryo transfer, hypoproteinemia, and major comorbidities during pregnancy. Univariate and multivariate logistic regression analyses were conducted to evaluate the effects of these independent predictors on adverse ocular outcomes. Additionally, receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off probability with for optimal sensitivity and specificity. Results Eclampsia, pre-eclampsia, GDM, a history of chronic hypertension, and hypoproteinemia were identified as independent predictors of adverse ocular outcomes during pregnancy (p < 0.05). Maternal age, PIH, intrauterine growth retardation (IUGR), obesity, and pregnancy with immunoglobulin A nephropathy were predictors of moderate and severe retinal arteriole sclerosis during pregnancy (p < 0.05). Additionally, hemolysis, elevated liver enzymes, and low platelets (HELLP) syndrome were predictors of retinal hemorrhage and exudate during pregnancy (p < 0.05). The area under the ROC curve for adverse ocular outcomes were 0.75 and 0.74, respectively. Conclusion Our predictive model effectively forecasts adverse ocular outcomes during pregnancy, incorporating risk factors such as maternal age, eclampsia and pre-eclampsia, GDM, obesity, a history of chronic hypertension, hypoproteinemia, IUGR, pregnancy with immunoglobulin A nephropathy, and HELLP syndrome.

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A Model to Predict the Risk of Adverse Ocular Outcomes in Pregnant Women

Liu,

Wen,

Zou

et al. 2024

Br J Hosp Med

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A model to predict the risk of adverse ocular outcomes in pregnant women

Liu,

Wen,

Zou

et al. 2024

Preprint

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Purpose This study aims to analyze common clinical data obtained during pregnancy, disease history, and maternal characteristics to determine ocular parameters and develop a risk prediction model for adverse ocular outcomes. Methods We retrospectively analyzed the medical records of 760 pregnant women (1,520 eyes) from September 2020 to September 2022 at the Third Affiliated Hospital of Guangzhou Medical University. The maternal variables that could influence adverse ocular outcomes were identified, including maternal age, pregnancy-induced hypertension (PIH), gestational diabetes mellitus (GDM), eclampsia and pre-eclampsia, uterine disease, fetal abnormalities, in vitro fertilization with embryo transfer, hypoproteinemia, and major comorbidities during pregnancy. Univariate and multivariate logistic regression analyses were performed to evaluate the effects of the independent predictors on adverse ocular outcomes. The receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off probability with optimum sensitivity and specificity. Results Eclampsia and pre-eclampsia, GDM, history of chronic hypertension, and hypoproteinemia were independent predictors of adverse ocular outcomes during pregnancy (P < 0.05). Maternal age, PIH, intrauterine growth retardation (IUGR), obesity, and pregnancy with immunoglobulin A nephropathy were predictors of moderate and severe retinal arteriole sclerosis during pregnancy (P < 0.05). Moreover, hemolysis, elevated liver enzymes, and low platelet (HELLP) syndrome was a predictor of retinal hemorrhage and exudate during pregnancy (P < 0.05). Adverse ocular outcomes showed area under the ROC curve values of 0.75 and 0.74. Conclusion Our predictive model could effectively predict adverse ocular outcomes during pregnancy, with the risk factors including maternal age, eclampsia and pre-eclampsia, GDM, obesity, history of chronic hypertension, hypoproteinemia, IUGR, pregnancy with immunoglobulin A nephropathy, and HELLP syndrome.

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Association between the Maternal Gut Microbiome and Macrosomia

Zhong,

An,

et al. 2024

Biology

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Fetal macrosomia is defined as a birthweight ≥4000 g and causes harm to pregnant women and fetuses. Studies reported that the maternal intestinal microbiome plays a key role in the establishment, growth, and development of the fetal intestinal microbiome. However, whether there is a relationship between maternal gut microbiota and macrosomia remains unclear. Our study aimed to identify gut microbiota that may be related to the occurrence of macrosomia, explore the possible mechanisms by which it causes macrosomia, and establish a prediction model to determine the feasibility of predicting macrosomia by early maternal gut microbiota. We conducted a nested case-control study based on an early pregnancy cohort (ChiCTR1900020652) in the Maternity and Child Health Hospital of Hunan Province on fecal samples of 93 women (31 delivered macrosomia as the case group and 62 delivered normal birth weight newborns as the control group) collected and included in this study. We performed metagenomic analysis to compare the composition and function of the gut microbiome between cases and controls. Correlation analysis was used to explore the association of differential species and differential functional pathways. A random forest model was used to construct an early pregnancy prediction model for macrosomia. At the species level, there were more Bacteroides salyersiae, Bacteroides plebeius, Ruminococcus lactaris, and Bacteroides ovatus in the intestinal microbiome of macrosomias’ mothers compared with mothers bearing fetuses that had normal birth weight. Functional pathways of the gut microbiome including gondoate biosynthesis, L-histidine degradation III, cis-vaccenate biosynthesis, L-arginine biosynthesis III, tRNA processing, and mannitol cycle, which were more abundant in the macrosomia group. Significant correlations were found between species and functional pathways. Bacteroides plebeius was significantly associated with the pathway of cis-vaccenate biosynthesis (r = 0.28, p = 0.005) and gondoate biosynthesis (r = 0.28, p < 0.001) and Bacteroides ovatus was positively associated with the pathway of cis-vaccenate biosynthesis (r = 0.29, p = 0.005) and gondoate biosynthesis (r = 0.32, p = 0.002). Bacteroides salyersiae was significantly associated with the pathway of cis-vaccenate biosynthesis (r = 0.24, p = 0.018), gondoate biosynthesis (r = 0.31, p = 0.003), and L–histidine degradation III (r = 0.22, p = 0.291). Finally, four differential species and four clinical indicators were included in the random forest model for predicting macrosomia. The areas under the working characteristic curves of the training and validation sets were 0.935 (95% CI: 0.851~0.979) and 0.909 (95% CI: 0.679~0.992), respectively. Maternal gut microbiota in early pregnancy may play an important role in the development of macrosomia and can be used as potential predictors to prevent macrosomia.

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A predictive model of macrosomic birth based upon real-world clinical data from pregnant women

Cited by 3 publications

References 33 publications

A Model to Predict the Risk of Adverse Ocular Outcomes in Pregnant Women

A Model to Predict the Risk of Adverse Ocular Outcomes in Pregnant Women

A model to predict the risk of adverse ocular outcomes in pregnant women

Association between the Maternal Gut Microbiome and Macrosomia

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