Gestational diabetes mellitus is the most common endocrine disorder in pregnancy and a cause of maternal and fetal morbidities and mortalities. The oral glucose tolerance test is the gold standard for diagnosing gestational diabetes mellitus. Nevertheless, the oral glucose tolerance test is time-consuming and requires patient preparation. On the contrary, Glycated albumin does not require patient preparation or administration of any substance. Most studies on glycated albumin in pregnancy were among the non-African population, and black Americans have higher glycated albumin levels than Caucasians. This study determined the use of glycated albumin in diagnosing gestational diabetes mellitus among pregnant women. The study was a prospective study of 160 pregnant women between 24 and 28 weeks of gestation at the University of Port Harcourt Teaching Hospital. The diagnosis of gestational diabetes mellitus was based on the World Health Organization 2013 criteria. The diagnostic value of glycated albumin was determined using the area under the receiver operator characteristic curve. The prevalence of gestational diabetes mellitus was 9.4% and the mean glycated albumin was 16.91% (±2.77). The area under the receiver operator characteristic curve for glycated albumin was 0.845 (95% CI 0.733 - 0.956;p = 0.0001). The optimal cut-off value of glycated albumin in the diagnosis of gestational diabetes mellitus was 18.9%. Glycated albumin was useful in the diagnosis of gestational diabetes mellitus at 24 to 28 weeks of gestation.
目的探讨双胎妊娠孕妇孕期体重增加(gestational weight gain,GWG)与不良围产结局的关系。方法回顾性纳入2012年1月至2022年10月在北京大学人民医院孕周≥25周活产分娩的双胎妊娠孕妇及其子代为研究对象。孕期总GWG按照孕周进行标准化处理,并根据2009年美国医学研究所(Institute of Medicine,IOM)指南分为增重不足(GWG低于IOM指南推荐)、增重适宜(GWG在IOM指南推荐范围之内)和增重过多(GWG高于IOM指南推荐)3组。3组间一般资料及围产结局比较采用方差分析、Kruskal-Wallis检验及Bonferroni校正或χ^(2)分割法。采用多变量logistic回归模型和广义估计方程中的logistic回归模型分别分析GWG对母亲及新生儿不良结局的独立影响。结果本研究共纳入794例双胎妊娠孕妇及其1588例活产新生儿。增重适宜、增重不足和增重过多3组孕妇分别有360例(45.3%)、356例(44.8%)和78例(9.8%)。增重不足和增重过多均与早产的风险增加有关[校正OR值分别为1.39(95%CI:1.04~1.88)和1.70(95%CI:1.05~2.78)]。GWG增重不足与妊娠期糖尿病(校正OR=1.42,95%CI:1.00~2.01)、低出生体重儿(校正OR=2.04,95%CI:1.57~2.66)的风险增加有关;与子痫或子痫前期(校正OR=0.50,95%CI:0.33~0.75)、剖宫产(校正OR=0.48,95%CI:0.30~0.77)、双胎发育不一致(校正OR=0.56,95%CI:0.37~0.85)、大于胎龄儿(校正OR=0.46,95%CI:0.35~0.61)的风险降低有关。增重过多与子痫或子痫前期(校正OR=2.85,95%CI:1.65~4.91)、大于胎龄儿(校正OR=2.49,95%CI:1.60~3.86)风险增加有关,与低出生体重儿的风险降低有关(校正OR=0.42,95%CI:0.27~0.65)。结论半数以上双胎妊娠孕妇GWG不在指南推荐范围。GWG低于或高于IOM指南推荐均与不良围产结局有关,尤其与早产风险增加有关。
BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy outcomes.It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus(GDM)is significantly higher than that born to healthy pregnant women.However,traditional methods for the diagnosis of LGA have limitations.Therefore,this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants.AIM To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM,and provide strategies for the effective prevention and timely intervention of LGA.METHODS The multivariable prediction model was developed by carrying out the following steps.First,the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses,for which the P value was<0.10.Subsequently,Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations,and the optimal combination factors were se-lected by choosing lambda 1se as the criterion.The final predictors were deter-mined by multiple backward stepwise logistic regression analysis,in which only the independent variables were associated with LGA risk,with a P value<0.05.Finally,a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve,calibration curve and decision curve analyses.RESULTS After using a multistep screening method,we establish a predictive model.Several risk factors for delivering an LGA infant were identified(P<0.01),including weight gain during pregnancy,parity,triglyceride-glucose index,free tetraiodothyronine level,abdominal circumference,alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks.The nomogram’s prediction ability was supported by the area under the curve(0.703,0.709,and 0.699 for the training cohort,validation cohort,and t
目的探讨妊娠期糖尿病(gestational diabetes mellitus,GDM)患者妊娠早期甘油三酯葡萄糖指数(the triglyceride-gluscose index,TyG指数)与分娩小于胎龄儿(small for gestational age infant,SGA)之间的关系。方法选取2018年1月至2023年6月复旦大学附属上海市第五人民医院和新疆喀什地区第二人民医院产科孕早期建档并符合纳入标准的孕妇1532例为研究对象,根据孕妇24~28周行口服葡萄糖耐量试验(oral glucose tolerance test,OGTT)结果,将其分为GDM组(754例)及非GDM组(778例)。GDM组患者根据新生儿体重,将其分为SGA组、大于胎龄儿(large for gestational age infant,LGA)组和适于胎龄儿(appropriate for gestational age infant,AGA)组。分析GDM患者分娩SGA的独立影响因素,采用Logistic回归模型分析TyG指数与发生SGA的相关性。绘制ROC曲线以分析妊娠早期TyG指数对GDM患者分娩SGA的预测价值。结果GDM患者SGA组TyG指数显著低于LGA组、AGA组及非GDM组(P<0.05);多因素Logistic回归分析结果显示,TyG指数与GDM患者分娩SGA的发生独立相关(P<0.05);ROC曲线结果显示,妊娠早期TyG指数对GDM患者分娩SGA具有较好的预测价值(AUC=0.821,95%CI:0.763~0.879,P<0.001)。结论GDM患者妊娠早期TyG指数与分娩SGA之间存在独立相关,对于GDM患者分娩SGA具有较好的预测价值。
Gestational Diabetes Mellitus (GDM) is a significant health concern affecting pregnant women worldwide. It is characterized by elevated blood sugar levels during pregnancy and poses risks to both maternal and fetal health. Maternal complications of GDM include an increased risk of developing type 2 diabetes later in life, as well as hypertension and preeclampsia during pregnancy. Fetal complications may include macrosomia (large birth weight), birth injuries, and an increased risk of developing metabolic disorders later in life. Understanding the demographics, risk factors, and biomarkers associated with GDM is crucial for effective management and prevention strategies. This research aims to address these aspects comprehensively through the analysis of a dataset comprising 600 pregnant women. By exploring the demographics of the dataset and employing data modeling techniques, the study seeks to identify key risk factors associated with GDM. Moreover, by analyzing various biomarkers, the research aims to gain insights into the physiological mechanisms underlying GDM and its implications for maternal and fetal health. The significance of this research lies in its potential to inform clinical practice and public health policies related to GDM. By identifying demographic patterns and risk factors, healthcare providers can better tailor screening and intervention strategies for pregnant women at risk of GDM. Additionally, insights into biomarkers associated with GDM may contribute to the development of novel diagnostic tools and therapeutic approaches. Ultimately, by enhancing our understanding of GDM, this research aims to improve maternal and fetal outcomes and reduce the burden of this condition on healthcare systems and society. However, it’s important to acknowledge the limitations of the dataset used in this study. Further research utilizing larger and more diverse datasets, perhaps employing advanced data analysis techniques such as Power BI, is warranted to corroborate and expand upon the findings of this re
目的探讨极低出生体重儿(very low birth weight,VLBW)中适于胎龄儿(appropriate for gestational age,AGA)和小于胎龄儿(small for gestational age,SGA)身长增长对经外周中心静脉置管(peripherally inserted central catheter,PICC)尖端移位的影响,并横向比较影响程度,帮助医护人员更好地把握导管尖端位置监测的时机。方法回顾性分析2021年1月—2022年6月在医院NICU住院并使用PICC的VLBW,按出生体质量和胎龄关系分为AGA组45例和SGA组19例,记录首次置管当日身长(Ht_(1))以及PICC尖端位置、置管期间胸片检查当日身长(Ht_(n))以及PICC尖端位置,并计算相应的身长增长率。身长增长率与PICC尖端移位的相关性用Spearman秩相关分析。将AGA和SGA的身长增长率分别与PICC尖端移位进行简单线性回归分析,构建回归模型,用协方差分析比较两组回归直线。结果VLBW中AGA组97.8%患儿出现移位,SGA组所有的患儿都出现移位,占比最多的均为移位3个椎体。Spearman秩相关分析结果显示,两组患儿身长增长率与PICC尖端移位均具有相关性(AGA组rs=-0.719,P<0.001;SGA组rs=-0.769,P<0.001),随着VLBW身长增长,PICC尖端逐渐移位远离心脏。简单线性回归分析结果显示,AGA组回归模型(R^(2)=0.517,调整后R^(2)=0.513,F=129.487,P<0.001),SGA组回归模型(R^(2)=0.591,调整后R^(2)=0.585,F=95.385,P<0.001)。协方差分析结果显示,由于回归系数检验没有统计学意义,两条直线平行,说明身长增长率对两组患儿位移的影响一致。截距比较有统计学意义(F=9.265,P=0.003),说明两组患儿位移的起点不同(即增长率为零时的位移位置),说明位移与是否为AGA、SGA有关。结论随着VLBW中AGA和SGA身长增长,PICC尖端逐渐移位远离心脏,但相同的身长增长率,SGA引起的导管尖端移位幅度更大。建议AGA身长增长率12.4%、SGA身长增长率9.5%可作为监测导管尖端位置的重要时机,以免导管尖端进一步移位至非中心静脉,