Fasting plasma glucose in the first trimester is related to Gestational Diabetes Mellitus and adverse pregnancy outcomes

Fasting plasma glucose in the first trimester is related to Gestational Diabetes Mellitus and adverse pregnancy outcomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fasting plasma glucose in the first trimester is related to Gestational Diabetes Mellitus and adverse pregnancy outcomes Jia-Ning Tong, Lin-Lin Wu, Yi-Xuan Chen, Xiao-Nian Guan, Fu-Ying Tian, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-459897/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Aug, 2021 Read the published version in Endocrine → Version 1 posted 4 You are reading this latest preprint version Abstract Purpose To investigate and identify first-trimester fasting plasma glucose (FPG) is related to gestational diabetes mellitus (GDM) and other adverse pregnancy outcomes in Shenzhen population. Methods We used data of 48,444 pregnant women that had been retrospectively collected between 2017 and 2019. Logistic regression analysis was used to evaluated the associations between first-trimester FPG and GDM and adverse pregnancy outcomes, and used to construct a nomogram model for predicting the risk of GDM. The performance of the nomogram was evaluated by using ROC and calibration curves. Decision curve analysis (DCA) was used to determine the clinical usefulness of the first-trimester FPG by quantifying the net benefits at different threshold probabilities. Results The mean first-trimester FPG was 4.62±0.42 mmol/L. A total of 6998(14.4%) pregnancies developed GDM.489(1.01%) pregnancies developed polyhydramnios, the prevalence rates of gestational hypertensive disorder (GHD), cesarean section, primary cesarean section, preterm delivery before 37 weeks (PD) and dystocia was 1130(2.33%), 20426(42.16%), 7237(14.94%), 2386(4.93%) and 1865(3.85%), respectively. 4233(8.74%) of the newborns were LGA, and the number of macrosomia was 2272(4.69%), LBW was 1701(3.51%) and 5084(10.49%) newborns had admission to the ICU, which all showed significances between GDM and non-GDM groups (all P1, all P<0.05), furthermore, the risks of GDM, primary cesarean section and LGA was increasing with first-trimester FPG as early as it was at 4.19-4.63 mmol/L. The multivariable analysis showed that the risks of GDM (ORs for FPG 4.19-4.63, 4.63-5.11 and 5.11-7.0 mmol/L were 1.137, 1.592 and 4.031, respectively, all P <0.05) increased as early as first-trimester FPG was at 4.19-4.63 mmol/L,and first-trimester FPG which was also associated with the risks of cesarean section, macrosomia and LGA (OR for FPG 5.11-7.0 mmol/L of cesarean section: 1.128; OR for FPG 5.11-7.0 mmol/L of macrosomia: 1.561; OR for FPG 4.63-5.11 and 5.11-7.0 mmol/L of LGA: 1.149 and 1.426, respectively, all P <0.05) and with its increasing, the risks of LGA increased. Furthermore, the nomogram had a C-indices 0.771(95%CI: 0.763~0.779) and 0.770(95%CI:0.758~0.781) in training and testing validation respectively, which showed an acceptable consistency between the observed, validation and nomogram-predicted probabilities, the DAC curve analysis indicated that the nomogram had important clinical application value for GDM risk prediction. Conclusions FPG in the first trimester was an independent risk factor for GDM which can be used as a screening test for identifying pregnancies at risk of GDM and adverse pregnancy outcomes. Endocrinology & Metabolism Obstetrics & Gynecology Surgical Obstetrics & Gynecology FPG GDM The first trimester Adverse pregnancy outcomes Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Gestational diabetes mellitus (GDM) refers to an abnormality of glycometabolism that occurs for the first time in the second or third trimester of pregnancy and does not include type 1 or type 2 diabetes, which exists before pregnancy [1]. GDM is associated with adverse maternal and fetal outcomes and maternal complications in pregnancy and later in life. The prevalence of GDM is increasing; this is closely linked to the prevalence of obesity and type 2 diabetes in specific countries, and the prevalence of obesity among women of childbearing age partly explains this increase [1]. The risks posed to mothers with GDM range from direct pregnancy complications, particularly the need for cesarean section and risk of gestational hypertension, to their lifetime risk of developing type 2 diabetes and cardiovascular diseases. Regarding their children, there is an increased short-term risk of obesity, premature birth, shoulder dystocia and neonatal hypoglycemia, as well as a long-term risk of obesity and abnormal plasma glucose (PG) metabolism. Therefore, GDM is associated with a particularly poor prognosis [1-3] and early detection of GDM is of great importance to help with prevention and treatment. Epidemiological studies of hyperglycemia and adverse pregnancy outcomes (HAPO) in multiple countries have recommended that a fasting plasma glucose (FPG) value of 5.1 mmol/l (92 mg/dl) in the first trimester can be the threshold for elevated blood glucose. It also indicated that for if FPG≤4.4 mmol/l (80 mg/dl), the risks of some adverse pregnancy outcomes are low[4]. Furthermore, several researchers examined whether first-trimester FPG is also consistently associated with obstetric complications, and a retrospective study of 6,129 pregnant women by Riskin-Masiah who observed first-trimester FPG found that FPG is associated with adverse outcomes and a risk of GDM [5]. Therefore, it is valuable to provide more data about first-trimester FPG from a single medical database where there might be some homogeneity in the patient population. Due to metabolic changes during pregnancy, blood glucose between 6 and 10 weeks in the first trimester can drop by approximately 2 mg/dL, and many scholars have pointed out that a specific lower limit of first-trimester FPG should be defined [6]. This study hoped to provide new evidence which could identify the relationships with first-trimester FPG, GDM and other obstetrical outcomes in the Shenzhen population. Materials And Methods This survey was an analysis of retrospectively collected data from the clinical database of the Shenzhen Maternity and Child Healthcare System between 2017 and 2019. Patients younger than 18 years old or with incomplete information, diagnosed pregestational diabetes, multiple pregnancy, or pregnancies conceived by assisted reproductive technology were excluded. Patients included were singleton pregnancies who attended our hospital to establish a maternal-natal manual in the first trimester, performed regular visits and gave birth in our hospital. They also received routine FPG testing in the first trimester. Finally, the selected patients included only those with an available FPG in the first trimester (<14 weeks) performed under the standard conditions and who had complete data on all outcomes (Figure 1). All patients were managed according to standard clinical protocols, and throughout the research periods, protocols were in accordance with the screening and management of GDM, followed by the recommendation of the International Diabetes and Pregnancy Research Group (IADASG) [1]. Diagnostic criterion Gestational Diabetes Mellitus (GDM) American Diabetes Association (ADA) has been using the one-step approach of the IADASG as the screening and diagnostic standard for GDM since 2011; here, in this study, the 2019 reviewed version was used [7]. Specifically, the IADPSG recommends that all pregnant women with no previous history of diabetes take a 75-g oral glucose tolerance test (OGTT) at 24 to 28 gestational weeks. Any value above baseline before glucose consumption (0 h) or PG levels at 1 h and 2 h after glucose consumption that are abnormal were diagnosed as GDM, namely, 0 h≥ 5.1 mmol/L (92 mg/dl), 1 h ≥ 10.0 mmol/L (180 mg/dl), and 2 h ≥ 8.5 mmol/L (153 mg/dl). Gestational hypertensive disorder (GHD) Preeclampsia was defined as systolic pressure ≥140 mm Hg or diastolic pressure ≥90 mm Hg on two or more occasions a minimum of 6 h apart, proteinuria ≥1+ or more on a dipstick test or urine protein ≥300 mg for a 24-h period. Gestational hypertension was diagnosed when elevated blood pressure met the criteria but without protein urine [8]. Prepregnancy Body Mass Index (BMI) To calculate BMI, prepregnancy weight (kg) was divided by the squared height (m2). Prepregnancy BMI was categorized according to the WHO standard [9]: women were underweight (BMI<18.5 kg/m2), normal (18.5-25 kg/m 2 ), overweight (25-30 kg/m 2 ), obese ≥ 30 kg/m 2 ), obese grade 1 (30-35 kg/m 2 ), obese grade 2 (35-40 kg/m 2 ), or obese grade 3 (≥ 40 kg/m 2 ). Gestational weight gain The gestational weight gain (GWG) in kg of the first trimester was calculated as the weight at 13+6 gestational weeks minus the prepregnancy weight. The GWG of the first trimester was categorized by the IOM (Institute of Medicine) standard[10]: inadequate (GWG＜0.5 kg), adequate (GWG 0.5-2.0 kg), and excessive (GWG＞2.0 kg). Macrosomia, Large for Gestational Age (LGA) and Low birth weight (LBW) Macrosomia was defined as a newborn weight in g ≥4000. Large for gestational age (LGA) was defined as newborn birth weight of above the 90th percentile if the birth weight was greater than the estimated 90th percentile for the same gestational age. Low birth weight (LBW) was defined as newborn birth weight < 2500 g[4.11]. All patients were considered when analyzing GDM and FPG in the first trimester. To analyze other obstetrical and maternal-fetal outcomes, patients with GDM were excluded to avoid bias arising from different treatments for GDM. Data collection We collected the descriptive statistics, clinical biochemical information and pregnancy outcomes of the patients. The descriptive statistics referred to age, height prepregnancy BMI,etc. Pregnant women generally had their first visits at gestational weeks 9-13+6. Clinical and biochemical data were collected retrospectively from the first prenatal visit, and data about the neonatal outcomes were collected after birth and saved into standardized maternal-natal information systems for the following statistical analysis. Clinical information also covered a history of hypertension and diabetes, among other conditions. Pregnancy outcomes included complications for pregnancies and newborns. Diagnostic method The OGTT and FPG results were measured by using the enzyme electrode method (DXC800, Beckman). The standard laboratory procedure is to centrifuge samples within 20 minutes of collection. The results were collected retrospectively from the report system of the laboratory. Outcomes The obstetrical adverse outcomes included GDM, cesarean section, primary cesarean section, polyhydramnios, preterm delivery before 37weeks (PD), dystocia and GHD, which included high blood pressure during pregnancy and preeclampsia. The neonatal outcomes included macrosomia, LGA, LBW, and ICU attendance of newborns. The main outcomes for this survey were the risk of GDM, primary cesarean section and LGA, while the others were secondary outcomes. Statistical analysis Analyses were performed using R statistical software version 3.6.1. Continuous variables were presented as the means with standard deviations, while categorical data were expressed as counts and percentages. Summary statistics between both groups were compared using either unpaired Student’s t-test or Mann-Whitney tests for continuous data, and chi-squared tests or Fisher’s Exact Test for categorical data. Univariate and multivariable adjusted odds ratios (OR) with 95% confidence interval (CI) of FPG for associations between first-trimester FPG and GDM and adverse pregnancy outcomes were estimated using the logistical regression model. Nomogram and calibration curve were performed with the “rms” package, then, a nomogram diagram for predicting the risk of GDM with first-trimester FPG for GDM was established by using the stepAIC filter variables, which nomogram model was used for predicting the risk of GDM and enabling the user to easily compute output probabilities. Decision curve analysis (DCA) was performed with the “dca” package, which was conducted to determine the clinical usefulness of the first-trimester FPG nomogram by quantifying the net benefits at different threshold probabilities. A p value of < 0.05 was considered to indicate statistical significance. Results Baseline Demographic and adverse outcome The baseline demographic and adverse outcomes according to the presence of GDM were summarized in Table 1 . Among 148,479 pregnancies delivered between 2017 and 2019, a total of 48,444 pregnant women were included in this study and 6,998(14.4%) pregnancies were diagnosed as GDM. The mean maternal age was 30.85±4.04 years, which showed a significant difference between non-GDM and GDM groups (30.57±3.94 vs. 32.52±4.22, P<0.001). The pre-gestational BMI was 20.65±2.65 kg/m2, which was higher in GDM groups (20.50±2.56 vs. 21.69±3.01, P<0.001) when compared with non-GDM groups. And first-trimester FPG was 4.62±0.42 mmol/L, of which 12.18% were first-trimester FPG ≤ 4.19 mmol/L,73.29% were 4.19-4.62 mmol/L,37.61% were 4.63-5.10 mmol/L, and 9.31% were 5.11-7.0 mmol/L, and the results indicated that first-trimester FPG was higher in GDM groups(P<0.001). The mean OGTT results at 0 h, 1 h, and 2 h were 2.52±2.17, 4.41±3.87, and 3.91±3.41 mmol/L, respectively. For newborns, the weight of newborns was 3281.52±440.43 g, which was a significant difference between non-GDM and GDM groups (3284.19±434.95 vs. 3265.74±471.30, P<0.001), the scores of Apgar 1min and Apgar 5min was 9.92±0.50 and 9.99±0.63, respectively.489(1.01%) pregnancies developed polyhydramnios, the prevalence rates of GHD, cesarean section, primary cesarean section, PD and dystocia was 1130(2.33%), 20426(42.16%), 7237(14.94%), 2386(4.93%) and 1865(3.85%), respectively, which all showed significances between two groups (all P<0.05). 4233(8.74%) of the newborns were LGA, and the number of macrosomia was 2272(4.69%), LBW was 1701(3.51%) and 5084(10.49%) newborns had admission to the ICU, all the prevalence rates were higher in the GDM group than those in the non-GDM groups (all P<0.05). Effects of first-trimester FPG on GDM and adverse outcomes Table 2 presented the effects of first-trimester FPG on GDM and adverse pregnancy outcomes. The univariate analysis showed first-trimester FPG was strongly associated with risks of outcomes including GDM, cesarean section, macrosomia, GHD, primary cesarean section and LGA (all OR>1, all P<0.05), furthermore, the risks of GDM, primary cesarean section and LGA was increasing with first-trimester FPG as early as it was at 4.19-4.63 mmol/L. At the same time, first-trimester FPG was a protective factor of LBW and ICU admission of the newborn (all OR<1, all P<0.05).After adjustments for multifactor, every stage of first-trimester FPG was associated with the risk of GDM (ORs for FPG 4.19-4.63, 4.63-5.11 and 5.11-7.0 mmol/L were 1.137, 1.592 and 4.031, respectively, and 95% CIs were 1.002-1.289, 1.406-1.801 and 3.513-4.625, respectively, all P <0.05) and with increasing first-trimester FPG, the risks of GDM increased (the OR value increased). It was also associated with the risks of cesarean section, macrosomia and LGA (OR for FPG 5.11-7.0 mmol/L of cesarean section: 1.128, 95% CI: 1.025-1.241; OR for FPG 5.11-7.0 mmol/L of macrosomia: 1.561, 95% CI: 1.26-1.933; OR for FPG 4.63-5.11 and 5.11-7.0 mmol/L of LGA: 1.149 and 1.426, 95% CI: 1.004-1.314 and 1.214-1.675, respectively, all P <0.05) and with its increasing, the risks of LGA increased. At the same time, first-trimester FPG was a protective factor against LBW and ICU admission of the newborn (all OR<1, all P<0.05). We also conducted a subgroup analysis, which revealed both the GDM and the non-GDM subgroups had the similar trends. In the GDM group, first-trimester FPG was associated with the risks of macrosomia, LGA and dystocia (all OR>1, all P1, all P<0.05), and it was a protective factor against GHD, LBW, primary cesarean section and ICU admission of the newborn (all OR<1, all P<0.05) (Table S1, S2). The establishment nomogram model for predicting the risk of GDM Based on Table 1 , maternal age, pre-pregnancy BMI, first-trimester FPG, delivery times, delivery weeks, major birth malformation of past history, GHD, OGTT at 0h, OGTT at 1h and OGTT at 2h were all significant different from pregnancies with and without GDM, a nomogram that could predict the risk of GDM was constructed. As the dataset was divided into the training and test datasets at a ratio of 7:3. The prediction results were shown in Figure 2 and Figure 3 . As shown in Figure 4 , the training and testing validated C-indices for the nomogram were 0.771(95%CI:0.763~0.779) and 0.770(95%CI:0.758~0.781),respectively. Additionally, the calibration curves of the nomogram model in training and testing validation were shown in Figure 5 , from which we could see that the calibration curves of both training and testing were validation close to the ideal line, indicating an acceptable consistency between the nomogram model that predicted probability and the actual observed probability. Decision curve analysis used to evaluate prediction models The DCA was used to evaluate prediction models from the perspective of first-trimester FPG consequences, which revealed that compared with the conventional staging systems, the nomogram-yielded superior net clinical benefit whose threshold probabilities ranged from 0.1-0.6 in both the training validation and testing validation ( Figure 6 ). The DAC curve analysis in this clinical validity suggested that if threshold probabilities of the maternity was ranged from 0.1-0.6 predicted risk of GDM based on the nomogram showed more benefit than either the treat-all scheme or the treat-none. Discussion This survey shows that in Shenzhen population, first-trimester FPG was not only strongly associated with GDM but also with other adverse pregnancy outcomes. In the univariate and multivariable analysis, the risks of GDM, macrosomia, primary cesarean section and LGA can increase as early as when first-trimester FPG was at 4.19-4.63 mmol/L, and with increasing first-trimester FPG, the risks of adverse outcomes increased (the OR value increased). Furthermore, we creatively used statistical models to demonstrate that first-trimester FPG can be used to predict GDM. The nomogram showed an acceptable consistency between the observed, validation and nomogram-predicted probabilities, the DAC curve analysis indicated that the nomogram had important clinical application value for GDM risk prediction. The above results demonstrate that first-trimester FPG could be used to identify adverse pregnancy risks and intervene as early as possible due to the specific metabolic changes during pregnancy. HAPO was a prospective observational study of 25,505 pregnant women which showed that maternal FPG is associated with increased birth weight and primary cesarean section [4,11]. The maternal metabolic state in the first trimester may affect the outcomes of the mothers and newborns. Riskin-Mashiah et al. reported that mild increased levels of FPG in the first trimester can lead to adverse outcomes, and they found a strong correlation between first-trimester FPG and GDM development [5]. We also demonstrated a consistent correlation between FPG and adverse obstetric outcomes in non-GDM patients, similar to the HAPO study [4]. Our study showed that the FPG results of HAPO also applied equally to our database in Shenzhen, China. In addition, higher first-trimester FPG, though below the diagnostic FPG criterion, was associated with adverse pregnancy outcomes. In our study, as early as when first-trimester FPG was in the range of 4.19-4.63 mmol/L, the risks of GDM appeared, which may be a clue of the risks of GDM. According to the ADA, GDM is a kind of diabetes diagnosed in the middle or late stages of pregnancy, and its symptoms are not obvious before pregnancy [7]. However, the diagnosis of GDM remains a controversial issue with multiple diagnostic criteria existing; its importance lies in its association with maternal and child health in pregnancy and later life [1]. Furthermore, it is agreed that GDM, regardless of symptoms, is associated with a significant risk of adverse perinatal outcomes [1-3]. Several studies have shown that addressing GDM as early as possible can improve outcomes [1-3], but there is much debate about its diagnosis and treatment. The main controversy involves the importance of FPG or the OGTT in the first trimester, and addressing the biases of first-trimester FPG to improve adverse outcomes for the future health of mothers and newborns stills remains discussion [1,4,11]. In the study by Sacks et al, it was indicated that FPG screening for detecting early GDM was less specific, but the AUC was 0.7, which suggested that FPG still had diagnostic accuracy in predicting GDM (AUC>0.5)[6]. Zhu et al. conducted a study of 17,186 pregnancies in China by using the IDPSG standard which showed a strong correlation between first-trimester FPG and GDM diagnosed at 24-28 weeks of pregnancy [12]. In our research, it was also found that the diagnostic model (AUC was around 0.770) of first-trimester FPG in predicting GDM had a similar trend when using the IDPSG standard. The HAPO study indicated that there is a linear relationship between maternal FPG and macrosomia [11],which was similar with our study. On the other hand, there is growing evidence showing that first-trimester FPG is a sign of maternal and newborn health. HAPO indicated that first-trimester FPG can be used to stratify the risks and set intervention thresholds. It also showed that in the one-step OGTT, the risks of birth weight, 90th percentile of C peptides, neonatal hypoglycemia, and primary cesarean section increased linearly as the FPG of mothers increased. Some of our findings were accordance with the HAPO results. However, the effectiveness of FPG in predicting GDM is not generally accepted because the diagnostic criteria vary and the choice of gestational week or race is different [4,11]. Previous studies have shown that FPG can be used to predict the risk of diabetes in later trimesters [2,3,5]. Riskin-Mashiah et al. studied a large number of pregnant women from Israel (n=6129) and obtained similar results to ours, namely, that first-trimester FPG has an independent relationship with the risks of GDM and LGA[5]. In addition, studies of lifestyle interventions to prevent GDM have shown that it works best in the early stages of pregnancy [13-14]. Conclusions We found a strong correlation between first-trimester FPG and GDM, LGA, and other adverse obstetric outcomes, and identify its clinical significance in Shenzhen population. Therefore, we recommend that FPG be used as a marker of obstetric risk, but the diagnosis of GDM may need comprehensive consideration. The current diagnostic standards for GDM in China should be re-examined. Further research to find the optimal cutoff value for first-trimester FPG and determine the optimal treatment based on the classification of FPG will be challenging. Limitations Our research has some limitations. The nutritional status of pregnancies may affect fetal growth and other perinatal outcomes, but we lack the related data. The value of PG and bilirubin of newborns is also very important for the survey, but the data are unavailable now. A number of confounded factors, such as microsomia in the past, may influence the clinical decision, such as the choice of delivery method. The lack of an identified cutoff value for first-trimester FPG to date needs further exploration and indicates that the survey needs additional, more thorough research. However, our study did find a significant correlation between adverse outcomes and higher maternal first-trimester FPG under the diagnostic criterion for GDM (in the total population and non-GDM group), suggesting a need to reconsider current criteria for diagnosing and addressing first-trimester FPG. Declarations Funding The survey was supported by the National Natural Science Foundation of China(81830041,81771611),Shen Zhen Science and Technology Innovation Committee Special Funding for Future Industry（JCYJ20170412140326739） Conflicts of interest None Availability of data and material All data generated or analyzed during this study were included in this published article Code availability The codes used during and/or analyzed during the current study are available from the corresponding authors (JM Niu) on reasonable request. Author contributions JM Niu were responsible for the study conception and design. JN Tong did the statistical analysis and wrote the script. LL Wu, YX Chen, XN Guan, and XX Wu collected the data. FY Tian and HF Zhang gave help to the data interpretation. K Liu and AQ Yin helped to revise part of the script. All authors contributed to the study design, including data collection, data interpretation and manuscript revision, and gave final approval of the version to be published. Ethics approval This research was approved by the Review Board for Human Investigation and the Ethics Committee of Shenzhen Maternal and Children Hospital. Informed consent was obtained from every patient, and the investigations were performed in accordance with the principles of the Declaration of Helsinki. Consent to participate Written informed consent was obtained from individual or guardian participants. Consent for publication Not applicable Acknowledgements The authors thank Prof. Xin Zhou at Tianjin University General Hospital about the structure suggestion of the manuscript. References [1]. I.A.o. 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Huvinen, Gestational diabetes mellitus can be prevented by lifestyle intervention: the Finnish Gestational Diabetes Prevention Study (RADIEL): a randomized controlled trial, 39(1) (2016) 24-30. Tables Table1 Baseline demographic and adverse pregnancy outcome Characteristics Overall No GDM GDM P value n 48444 41446(85.6%) 6998(14.4%) Maternal Characteristics Maternal age, years a 30.85±4.04 30.57±3.94 32.52±4.22 <0.001 Height, m 1.60±0.07 1.60±0.07 1.59±0.07 <0.001 Prepregnancy BMI, kg/m 2 20.65±2.65 20.50±2.56 21.69±3.01 <0.001 Category of prepregnancy BMI b (n, %) <0.001 ≤18.5kg/m 2 7530 (20.5) 6960 (21.6) 570 (12.4) 18.5-24.9 kg/m 2 26941 (73.3) 23513 (73.1) 3428 (74.5) 25.0-29.9 kg/m 2 2099 (5.7) 1552 (4.8) 547 (11.9) 30.0-34.9 kg/m 2 163 (0.4) 116 (0.4) 47 (1.0) 35.0-39.9 kg/m 2 17 (0.0) 12 (0.0) 5 (0.1) ≥40.0 kg/m 2 7 (0.0) 5 (0.0) 2 (0.0) FPG in first trimester, mmol/L 4.62±0.42 4.59±0.39 4.80±0.55 <0.001 Category of FPG in first trimester (n, %) <0.001 ≤ 4.19mmol/L 5889 (12.2) 5355 (12.9) 534 (7.7) 4.19-4.62 mmol/L 19770 (40.9) 17621 (42.6) 2149 (30.9) 4.63-5.10 mmol/L 18184 (37.6) 15384 (37.2) 2800 (40.2) 5.11-7.0 mmol/L 4503 (9.3) 3029 (7.3) 1474 (21.2) Delivery Times. 0.37±0.53 0.35±0.51 0.49±0.57 <0.001 OGTT at 0h, mmol/L d 2.52±2.17 2.42±2.14 3.10±2.23 <0.001 OGTT at 1h, mmol/L d 4.41±3.87 4.08±3.66 6.35±4.51 <0.001 OGTT at 2h, mmol/L d 3.91±3.41 3.62±3.22 5.61±3.99 <0.001 Delivery mode (n, %) <0.001 Obstetric Forceps 282 (0.6) 234 (0.6) 48 (0.7) Eutocia 27294 (56.3) 23799 (57.4) 3495 (49.9) Vacuum Extraction 424 (0.9) 347 (0.8) 77 (1.1) Breech Presentation 18 (0.0) 18 (0.0) 0 (0.0) Cesarean Section 20426 (42.2) 17048 (41.1) 3378 (48.3) <0.001 Primary Cesarean Section 7237 (14.9) 5691 (13.7) 1546 (22.1) <0.001 Gestational weight gain (GWG), Kg 2.21±2.58 2.21±2.57 2.20±2.60 0.768 Category of GWG c (n, %) 0.264 ＜0.5kg 6212 (22.8) 5280 (22.7) 932 (23.5) 0.5-2kg 7798 (28.6) 6703 (28.8) 1095 (27.7) 0.5-2kg 13227 (48.6) 11296 (48.5) 1931 (48.8) Major birth malformation of past history (n, %) 9062 (18.7) 7509 (18.1) 1553 (22.2) <0.001 Bleeding amount in 24h, ml 287.82±98.80 287.68±97.77 288.64 ±104.72 0.455 Newborn characteristics Gestational age at delivery, wk 38.88±1.48 38.93±1.47 38.58±1.48 <0.001 Weigh of newborn, g 3281.52±440.43) 3284.19±434.95 3265.74±471.30 0.001 Apgar 1min 9.92±0.50 9.92±0.50 9.92±0.51 0.228 Apgar 5min 9.99±0.63 9.99±0.68 9.99±0.18 0.854 Apgar 1min﹤7 (n,%) 0.872 NO 48215(99.54) 41251(99.53) 6964(99.56) Yes 224(0.46) 193(0.47) 31(0.44) Adverse outcome Polyhydramnios (%) 0.530 NO 47955(98.99) 41033(99.00) 6922(98.91) Yes 489(1.01) 413(1.00) 76(1.09) GHD (n, %) 0.001 NO 47314(97.67) 40518(97.76) 6796(97.11) Yes 1130(2.33) 928(2.24) 202(2.89) gestational hypertension 301 Preeclampsia 829 Cesarean Section (%) <0.001 NO 28018(57.84) 24398(58.87) 3620(51.73) Yes 20426(42.16) 17048(41.13) 3378(48.27) Primary Cesarean Section (%) <0.001 NO 41207(85.06) 35755(86.27) 5452(77.91) Yes 7237(14.94) 5691(13.73) 1546(22.09) PD (n, %) <0.001 NO 46058(95.07) 39520(95.35) 6538(93.43) Yes 2386(4.93) 1926(4.65) 460(6.57) Dystocia (n, %) 0.001 NO 46579(96.15) 39800(96.03) 6779(96.87) Yes 1865(3.85) 1646(3.97) 219(3.13) LGA (%) <0.001 NO 44211(91.26) 37990(91.66) 6221(88.90) Yes 4233(8.74) 3456(8.34) 777(11.10) Macrosomia (%) 0.004 NO 46172(95.31) 39550(95.43) 6622(94.63) Yes 2272(4.69) 1896(4.57) 376(5.37) LBW (%) <0.001 NO 46743(96.49) 40056(96.65) 6687(95.56) Yes 1701(3.51) 1390(3.35) 311(4.44) ICU attendance of newborns (n, %) <0.001 NO 43360(89.51) 37283(89.96) 6077(86.84) Yes 5084(10.49) 4163(10.04) 921(13.16) a: At delivery b: Categorized by WHO standard c: Categorized by Institute of Medicine standard LBW: Low Birth Weight LGA: Large for Gestational Age GHD: Gestational Hypertensive Disorder PD: Preterm Delivery before 37weeks Dystocia: Shoulder dystocia or birth injury Table2 OR for GDM and adverse pregnancy outcomes according to first-trimester FPG* Outcomes FPG Crude ORs P Adjusted ORs P GDM Reference 1 1 4.19-4.62 1.223(1.107~1.351) <0.001 1.137(1.002~1.289) 0.046 4.63-5.10 1.825(1.655~2.012) <0.001 1.592(1.406~1.801) <0.001 5.11-6.99 4.880(4.378~5.439) <0.001 4.031(3.513~4.625) <0.001 Adverse pregnancy outcome Cesarean Section Reference 1 1 4.19-4.62 1.054(0.993~1.118) 0.086 0.984(0.916~1.057) 0.656 4.63-5.10 1.235(1.163~1.312) <0.001 1.071(0.996~1.151) 0.064 5.11-6.99 1.440(1.331~1.557) <0.001 1.128(1.025~1.241) 0.014 GHD Reference 1 1 4.19-4.62 0.852(0.700~1.036) 0.109 0.746(0.594~0.935) 0.011 4.63-5.10 1.021(0.841~1.240) 0.831 0.922(0.737~1.152) 0.475 5.11-6.99 1.496(1.185~1.887) 0.001 1.250(0.956~1.634) 0.103 LGA Reference 1 1 4.19-4.62 1.251(1.113~1.406) <0.001 1.090(0.952~1.247) 0.213 4.63-5.10 1.549(1.380~1.740) <0.001 1.149(1.004~1.314) 0.044 5.11-6.99 2.124(1.853~2.436) <0.001 1.426(1.214~1.675) <0.001 Polyhydramnios Reference 1 1 4.19-4.62 0.841(0.639~1.106) 0.216 0.830(0.614~1.123) 0.228 4.63-5.10 0.780(0.589~1.032) 0.082 0.757(0.555~1.033) 0.080 5.11-6.99 0.971(0.677~1.393) 0.874 0.971(0.653~1.442) 0.883 Dystocia Reference 1 1 4.19-4.62 0.980(0.843~1.140) 0.793 1.081(0.909 ~ 1.286) 0.379 4.63-5.10 1.006(0.864~1.171) 0.941 1.164(0.977 ~ 1.388) 0.090 5.11-6.99 0.946(0.772~1.160) 0.593 1.187(0.940 ~ 1.500) 0.150 Primary Cesarean Section Reference 1 1 4.19-4.62 1.183(1.081~1.294) <0.001 0.893(0.780~1.022) 0.101 4.63-5.10 1.532(1.401~1.674) <0.001 0.998(0.873~1.142) 0.982 5.11-6.99 1.819(1.631~2.028) <0.001 0.977(0.828~1.154) 0.786 ICU attendance Reference 1 1 4.19-4.62 0.879(0.801~0.964) 0.006 0.887(0.791~0.995) 0.041 4.63-5.10 0.890(0.810~0.977) 0.014 0.887(0.789~0.997) 0.044 5.11-6.99 0.943(0.834~1.067) 0.353 0.918(0.787~1.070) 0.274 Macrosomia Reference 1 1 4.19-4.62 1.259(1.076~1.473) 0.004 1.117(0.932~1.338) 0.232 4.63-5.10 1.518(1.299~1.773) <0.001 1.172(0.978~1.405) 0.085 5.11-6.99 2.067(1.721~2.481) <0.001 1.561(1.260~1.933) <0.001 LBW Reference 1 1 4.19-4.62 0.768(0.665~0.888) <0.001 0.771(0.613~0.970) 0.026 4.63-5.10 0.711(0.613~0.824) <0.001 0.718(0.567~0.909) 0.006 5.11-6.99 0.760(0.620~0.930) 0.008 0.734(0.533~1.012) 0.059 PD Reference 1 1 4.19-4.62 1.021(0.890 ~ 1.171) 0.768 1.559(0.589 ~ 4.125) 0.371 4.63-5.10 1.069(0.931 ~ 1.227) 0.344 1.300(0.486 ~ 3.482) 0.601 5.11-6.99 1.170(0.981 ~ 1.396) 0.081 2.232(0.673 ~ 7.406) 0.190 *FPG: FPG in the first-trimester Reference: First category of early FPG≤4.19 mmol/L as the reference Adjusted ORs:adjusted by maternal age,prepregancy BMI,height,delivery times and delivery weeks Bold: OR＞1,P＜0.05; Italics: OR＜1,P＜0.05 Supplementary Files supplementalmaterials.docx Cite Share Download PDF Status: Published Journal Publication published 03 Aug, 2021 Read the published version in Endocrine → Version 1 posted Reviews received at journal 29 Apr, 2021 Editor assigned by journal 26 Apr, 2021 Reviewers invited by journal 26 Apr, 2021 First submitted to journal 23 Apr, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-459897","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":23894898,"identity":"c17e3804-7911-416c-be24-01c0f17aa13b","order_by":0,"name":"Jia-Ning Tong","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jia-Ning","middleName":"","lastName":"Tong","suffix":""},{"id":23894899,"identity":"0d01f1ac-75e0-4374-8ca5-cf645fb886ee","order_by":1,"name":"Lin-Lin Wu","email":"","orcid":"","institution":"Southern Medical 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12:29:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1036736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-459897/v1/40884f3a-695c-487f-a91c-336961149544.pdf"},{"id":8642669,"identity":"dc7652a9-ff9f-467e-a810-0d0a22605d8f","added_by":"auto","created_at":"2021-04-30 15:07:51","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":28395,"visible":true,"origin":"","legend":"","description":"","filename":"supplementalmaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-459897/v1/7ac34713435dd47f189d4ff3.docx"}],"financialInterests":"","formattedTitle":"Fasting plasma glucose in the first trimester is related to Gestational Diabetes Mellitus and adverse pregnancy outcomes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGestational diabetes mellitus (GDM) refers to an abnormality of glycometabolism that occurs for the first time in the second or third trimester of pregnancy and does not include type 1 or type 2 diabetes, which exists before pregnancy [1]. GDM is associated with adverse maternal and fetal outcomes and maternal complications in pregnancy and later in life. The prevalence of GDM is increasing; this is closely linked to the prevalence of obesity and type 2 diabetes in specific countries, and the prevalence of obesity among women of childbearing age partly explains this increase [1]. The risks posed to mothers with GDM range from direct pregnancy complications, particularly the need for cesarean section and risk of gestational hypertension, to their lifetime risk of developing type 2 diabetes and cardiovascular diseases. Regarding their children, there is an increased short-term risk of obesity, premature birth, shoulder dystocia and neonatal hypoglycemia, as well as a long-term risk of obesity and abnormal plasma glucose (PG) metabolism. Therefore, GDM is associated with a particularly poor prognosis [1-3]\u0026nbsp;and early detection of GDM is of great importance to help with prevention and treatment.\u003c/p\u003e\n\u003cp\u003eEpidemiological studies of hyperglycemia and adverse pregnancy outcomes (HAPO) in multiple countries have recommended that a fasting plasma glucose (FPG) value of 5.1 mmol/l (92 mg/dl) in the first trimester can be the threshold for elevated blood glucose. It also indicated that for if FPG\u0026le;4.4 mmol/l (80 mg/dl), the risks of some adverse pregnancy outcomes are low[4]. Furthermore, several researchers examined whether first-trimester FPG is also consistently associated with obstetric complications, and a retrospective study of 6,129 pregnant women by Riskin-Masiah who observed first-trimester FPG found that FPG is associated with adverse outcomes and a risk of GDM [5]. Therefore, it is valuable to provide more data about first-trimester FPG from a single medical database where there might be some homogeneity in the patient population. Due to metabolic changes during pregnancy, blood glucose between 6 and 10 weeks in the first trimester can drop by approximately 2 mg/dL, and many scholars have pointed out that a specific lower limit of first-trimester FPG should be defined [6].\u003c/p\u003e\n\u003cp\u003eThis study hoped to provide new evidence which could identify the relationships with first-trimester FPG, GDM and other obstetrical outcomes in the Shenzhen population.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003eThis survey was an analysis of retrospectively collected data from the clinical database of the Shenzhen\u0026nbsp;Maternity\u0026nbsp;and Child\u0026nbsp;Healthcare\u0026nbsp;System between 2017 and 2019. Patients younger than 18 years old or with incomplete information, diagnosed pregestational diabetes, multiple pregnancy, or pregnancies conceived by assisted reproductive technology were excluded. Patients included were singleton pregnancies who attended our hospital to establish a maternal-natal manual in the first trimester, performed regular visits and gave birth in our hospital. They also received routine FPG testing in the first trimester. Finally, the selected patients included only those with an available FPG in the first trimester (\u0026lt;14 weeks) performed under the standard conditions and who had complete data on all outcomes (Figure 1). All patients were managed according to standard clinical protocols, and throughout the research periods, protocols were in accordance with the screening and management of GDM, followed by the recommendation of the International Diabetes and Pregnancy Research Group (IADASG) [1].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic criterion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGestational Diabetes Mellitus (GDM) \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAmerican Diabetes Association (ADA) has been using the one-step approach of the IADASG as the screening and diagnostic standard for GDM since 2011; here, in this study, the 2019 reviewed version was used [7]. Specifically, the IADPSG recommends that all pregnant women with no previous history of diabetes take a 75-g oral glucose tolerance test (OGTT) at 24 to 28 gestational weeks. Any value above baseline before glucose consumption (0 h) or PG levels at 1 h and 2 h after glucose consumption that are abnormal were diagnosed as GDM, namely, 0 h\u0026ge; 5.1 mmol/L (92 mg/dl), 1 h \u0026ge; 10.0 mmol/L (180 mg/dl), and 2 h \u0026ge; 8.5 mmol/L (153 mg/dl).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGestational hypertensive disorder (GHD)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePreeclampsia was defined as systolic pressure \u0026ge;140 mm Hg or diastolic pressure \u0026ge;90 mm Hg on two or more occasions a minimum of 6 h apart, proteinuria \u0026ge;1+ or more on a dipstick test or urine protein \u0026ge;300 mg for a 24-h period. Gestational hypertension was diagnosed when elevated blood pressure met the criteria but without protein urine [8].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrepregnancy Body Mass Index (BMI)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo calculate BMI, prepregnancy weight (kg) was divided by the squared height (m2). Prepregnancy BMI was categorized according to the WHO standard [9]: women were underweight (BMI\u0026lt;18.5 kg/m2), normal (18.5-25 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25-30 kg/m\u003csup\u003e2\u003c/sup\u003e), obese \u0026ge; 30 kg/m\u003csup\u003e2\u003c/sup\u003e), obese grade 1 (30-35 kg/m\u003csup\u003e2\u003c/sup\u003e), obese grade 2 (35-40 kg/m\u003csup\u003e2\u003c/sup\u003e), or obese grade 3 (\u0026ge; 40 kg/m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGestational weight gain\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe gestational weight gain (GWG) in kg of the first trimester was calculated as the weight at 13+6 gestational weeks minus the prepregnancy weight. The GWG of the first trimester was categorized by the IOM (Institute of Medicine) standard[10]: inadequate (GWG＜0.5 kg), adequate (GWG 0.5-2.0 kg), and excessive (GWG＞2.0 kg).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMacrosomia, Large for Gestational Age (LGA) and Low birth weight (LBW)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMacrosomia was defined as a newborn weight in g \u0026ge;4000. Large for gestational age (LGA) was defined as newborn birth weight of above the 90th percentile if the birth weight was greater than the estimated 90th percentile for the same gestational age. Low birth weight (LBW) was defined as newborn birth weight \u0026lt; 2500 g[4.11].\u003c/p\u003e\n\u003cp\u003eAll patients were considered when analyzing GDM and FPG in the first trimester. To analyze other obstetrical and maternal-fetal outcomes, patients with GDM were excluded to avoid bias arising from different treatments for GDM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe collected the descriptive statistics, clinical biochemical information and pregnancy outcomes of the patients. The descriptive statistics referred to age, height prepregnancy BMI,etc. Pregnant women generally had their first visits at gestational weeks 9-13+6. Clinical and biochemical data were collected retrospectively from the first prenatal visit, and data about the neonatal outcomes were collected after birth and saved into standardized maternal-natal information systems for the following statistical analysis. Clinical information also covered a history of hypertension and diabetes, among other conditions. Pregnancy outcomes included complications for pregnancies and newborns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe OGTT and FPG results were measured by using the enzyme electrode method (DXC800, Beckman). The standard laboratory procedure is to centrifuge samples within 20 minutes of collection. The results were collected retrospectively from the report system of the laboratory.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe obstetrical adverse outcomes included GDM, cesarean section, primary cesarean section, polyhydramnios, preterm delivery before 37weeks (PD), dystocia and GHD, which included high blood pressure during pregnancy and preeclampsia. The neonatal outcomes included macrosomia, LGA, LBW, and ICU attendance of newborns. The main outcomes for this survey were the risk of GDM, primary cesarean section and LGA, while the others were secondary outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalyses were performed using R statistical software version 3.6.1. Continuous variables were presented as the means with standard deviations, while categorical data were expressed as counts and percentages. Summary statistics between both groups were compared using either unpaired Student\u0026rsquo;s t-test or Mann-Whitney tests for continuous data, and chi-squared tests or Fisher\u0026rsquo;s Exact Test for categorical data. Univariate and multivariable adjusted odds ratios (OR) with 95% confidence interval (CI) of FPG for associations between first-trimester FPG and GDM and adverse pregnancy outcomes were estimated using the logistical regression model. Nomogram and calibration curve were performed with the \u0026ldquo;rms\u0026rdquo; package, then, a nomogram diagram for predicting the risk of GDM with first-trimester FPG for GDM was established by using the stepAIC filter variables, which nomogram model was used for predicting the risk of GDM and enabling the user to easily compute output probabilities. Decision curve analysis (DCA) was performed with the \u0026ldquo;dca\u0026rdquo; package, which was conducted to determine the clinical usefulness of the first-trimester FPG nomogram by quantifying the net benefits at different threshold probabilities. A p value of \u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline Demographic and adverse outcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline demographic and adverse outcomes according to the presence of GDM were summarized in \u003cstrong\u003eTable\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e. Among 148,479 pregnancies delivered between 2017 and 2019, a total of 48,444 pregnant women were included in this study and 6,998(14.4%) pregnancies were diagnosed as GDM. The mean maternal age was 30.85\u0026plusmn;4.04 years, which showed a significant difference between non-GDM and GDM groups (30.57\u0026plusmn;3.94 vs. 32.52\u0026plusmn;4.22, P\u0026lt;0.001). The pre-gestational BMI was 20.65\u0026plusmn;2.65 kg/m2, which was higher in GDM groups (20.50\u0026plusmn;2.56 vs. 21.69\u0026plusmn;3.01, P\u0026lt;0.001) when compared with non-GDM groups. And first-trimester FPG was 4.62\u0026plusmn;0.42 mmol/L, of which 12.18% were first-trimester FPG \u0026le; 4.19 mmol/L,73.29% were 4.19-4.62 mmol/L,37.61% were 4.63-5.10 mmol/L, and 9.31% were 5.11-7.0 mmol/L, and the results indicated that first-trimester FPG was higher in GDM groups(P\u0026lt;0.001). The mean OGTT results at 0 h, 1 h, and 2 h were 2.52\u0026plusmn;2.17, 4.41\u0026plusmn;3.87, and 3.91\u0026plusmn;3.41 mmol/L, respectively. For newborns, the weight of newborns was 3281.52\u0026plusmn;440.43 g, which was a significant difference between non-GDM and GDM groups (3284.19\u0026plusmn;434.95 vs. 3265.74\u0026plusmn;471.30, P\u0026lt;0.001), the scores of Apgar 1min and Apgar 5min was 9.92\u0026plusmn;0.50 and 9.99\u0026plusmn;0.63, respectively.489(1.01%) pregnancies developed polyhydramnios, the prevalence rates of GHD, cesarean section, primary cesarean section, PD and dystocia was 1130(2.33%), 20426(42.16%), 7237(14.94%), 2386(4.93%) and 1865(3.85%), respectively, which all showed significances between two groups (all P\u0026lt;0.05). 4233(8.74%) of the newborns were LGA, and the number of macrosomia was 2272(4.69%), LBW was 1701(3.51%) and 5084(10.49%) newborns had admission to the ICU, all the prevalence rates were higher in the GDM group than those in the non-GDM groups (all P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects of first-trimester FPG on GDM and adverse outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e presented the effects of first-trimester FPG on GDM and adverse pregnancy outcomes. The univariate analysis showed first-trimester FPG was strongly associated with risks of outcomes including GDM, cesarean section, macrosomia, GHD, primary cesarean section and LGA (all OR\u0026gt;1, all P\u0026lt;0.05), furthermore, the risks of GDM, primary cesarean section and LGA was increasing with first-trimester FPG as early as it was at 4.19-4.63 mmol/L. At the same time, first-trimester FPG was a protective factor of LBW and ICU admission of the newborn (all OR\u0026lt;1, all P\u0026lt;0.05).After adjustments for multifactor, every stage of first-trimester FPG was associated with the risk of GDM (ORs for FPG 4.19-4.63, 4.63-5.11 and 5.11-7.0 mmol/L were 1.137, 1.592 and 4.031, respectively, and 95% CIs were 1.002-1.289, 1.406-1.801 and 3.513-4.625, respectively, all P \u0026lt;0.05) and with increasing first-trimester FPG, the risks of GDM increased (the OR value increased). It was also associated with the risks of cesarean section, macrosomia and LGA (OR for FPG 5.11-7.0 mmol/L of cesarean section: 1.128, 95% CI: 1.025-1.241; OR for FPG 5.11-7.0 mmol/L of macrosomia: 1.561, 95% CI: 1.26-1.933; OR for FPG 4.63-5.11 and 5.11-7.0 mmol/L of LGA: 1.149 and 1.426, 95% CI: 1.004-1.314 and 1.214-1.675, respectively, all P \u0026lt;0.05) and with its increasing, the risks of LGA increased. At the same time, first-trimester FPG was a protective factor against LBW and ICU admission of the newborn (all OR\u0026lt;1, all P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eWe also conducted a subgroup analysis, which revealed both the GDM and the non-GDM subgroups had the similar trends. In the GDM group, first-trimester FPG was associated with the risks of macrosomia, LGA and dystocia (all OR\u0026gt;1, all P\u0026lt;0.05). While in the non-GDM subgroup, FPG in first trimester was identified as a significant predictor for the risks of cesarean section, macrosomia, and LGA (all OR\u0026gt;1, all P\u0026lt;0.05), and it was a protective factor against GHD, LBW, primary cesarean section and ICU admission of the newborn (all OR\u0026lt;1, all P\u0026lt;0.05) (Table S1, S2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe establishment nomogram model for predicting the risk of GDM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on \u003cstrong\u003eTable 1\u003c/strong\u003e, maternal age, pre-pregnancy BMI, first-trimester FPG, delivery times, delivery weeks, major birth malformation of past history, GHD, OGTT at 0h, OGTT at 1h and OGTT at 2h were all significant different from pregnancies with and without GDM, a nomogram that could predict the risk of GDM was constructed. As the dataset was divided into the training and test datasets at a ratio of 7:3. The prediction results were shown in\u0026nbsp;\u003cstrong\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7049836/figure/fig2/\"\u003eFigure 2\u003c/a\u003e\u003c/strong\u003e and\u003cstrong\u003e\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7049836/figure/fig2/\"\u003eFigure 3\u003c/a\u003e\u003c/strong\u003e. As shown in \u003ca href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426514/figure/F3/\"\u003e\u003cstrong\u003eFigure 4\u003c/strong\u003e,\u003c/a\u003e the training and testing validated C-indices for the nomogram were 0.771(95%CI:0.763~0.779) and 0.770(95%CI:0.758~0.781),respectively. Additionally, the calibration curves of the nomogram model in training and testing validation were shown in\u0026nbsp;\u003cstrong\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7049836/figure/fig3/\"\u003eFigure 5\u003c/a\u003e\u003c/strong\u003e, from which we could see that the calibration curves of both training and testing were validation close to the ideal line, indicating an acceptable consistency between the nomogram model that predicted probability and the actual observed probability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecision curve analysis used to evaluate prediction models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe DCA was used to evaluate prediction models from the perspective of first-trimester FPG consequences, which revealed that compared with the conventional staging systems, the nomogram-yielded superior net clinical benefit whose threshold probabilities ranged from 0.1-0.6 in both the training validation and testing validation (\u003cstrong\u003eFigure 6\u003c/strong\u003e). The DAC curve analysis in this clinical validity suggested that if threshold probabilities of the maternity was ranged from 0.1-0.6 predicted risk of GDM based on the nomogram showed more benefit than either the treat-all scheme or the treat-none.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis survey shows that in Shenzhen population, first-trimester FPG was not only strongly associated with GDM but also with other adverse pregnancy outcomes. In the univariate and multivariable analysis, the risks of GDM, macrosomia, primary cesarean section and LGA can increase as early as when first-trimester FPG was at 4.19-4.63 mmol/L, and with increasing first-trimester FPG, the risks of adverse outcomes increased (the OR value increased). Furthermore, we creatively used statistical models to demonstrate that first-trimester FPG can be used to predict GDM. The nomogram showed an acceptable consistency between the observed, validation and nomogram-predicted probabilities, the DAC curve analysis indicated that the nomogram had important clinical application value for GDM risk prediction. The above results demonstrate that first-trimester FPG could be used to identify adverse pregnancy risks and intervene as early as possible due to the specific metabolic changes during pregnancy.\u003c/p\u003e\n\u003cp\u003eHAPO was a prospective observational study of 25,505 pregnant women which showed that maternal FPG is associated with increased birth weight and primary cesarean section [4,11]. The maternal metabolic state in the first trimester may affect the outcomes of the mothers and newborns. Riskin-Mashiah et al. reported that mild increased levels of FPG in the first trimester can lead to adverse outcomes, and they found a strong correlation between first-trimester FPG and GDM development [5]. We also demonstrated a consistent correlation between FPG and adverse obstetric outcomes in non-GDM patients, similar to the HAPO study [4]. Our study showed that the FPG results of HAPO also applied equally to our database in Shenzhen, China. In addition, higher first-trimester FPG, though below the diagnostic FPG criterion, was associated with adverse pregnancy outcomes. In our study, as early as when first-trimester FPG was in the range of 4.19-4.63 mmol/L, the risks of GDM appeared, which may be a clue of the risks of GDM.\u003c/p\u003e\n\u003cp\u003eAccording to the ADA, GDM is a kind of diabetes diagnosed in the middle or late stages of pregnancy, and its symptoms are not obvious before pregnancy [7]. However, the diagnosis of GDM remains a controversial issue with multiple diagnostic criteria existing; its importance lies in its association with maternal and child health in pregnancy and later life [1]. Furthermore, it is agreed that GDM, regardless of symptoms, is associated with a significant risk of adverse perinatal outcomes [1-3]. Several studies have shown that addressing GDM as early as possible can improve outcomes [1-3], but there is much debate about its diagnosis and treatment. The main controversy involves the importance of FPG or the OGTT in the first trimester, and addressing the biases of first-trimester FPG to improve adverse outcomes for the future health of mothers and newborns stills remains discussion [1,4,11].\u0026nbsp;In the study by Sacks et al, it was indicated that FPG screening for detecting early GDM was less specific, but the AUC was 0.7, which suggested that FPG still had diagnostic accuracy in predicting GDM (AUC\u0026gt;0.5)[6]. Zhu et al. conducted a study of 17,186 pregnancies in China by using the IDPSG standard which showed a strong correlation between first-trimester FPG and GDM diagnosed at 24-28 weeks of pregnancy [12]. In our research, it was also found that the diagnostic model (AUC was around 0.770) of first-trimester FPG in predicting GDM had a similar trend when using the IDPSG standard. The HAPO study indicated that there is a linear relationship between maternal FPG and macrosomia [11],which was similar with our study.\u003c/p\u003e\n\u003cp\u003eOn the other hand, there is growing evidence showing that first-trimester FPG is a sign of maternal and newborn health. HAPO indicated that first-trimester FPG can be used to stratify the risks and set intervention thresholds. It also showed that in the one-step OGTT, the risks of birth weight, 90th percentile of C peptides, neonatal hypoglycemia, and primary cesarean section increased linearly as the FPG of mothers increased. Some of our findings were accordance with the HAPO results. However, the effectiveness of FPG in predicting GDM is not generally accepted because the diagnostic criteria vary and the choice of gestational week or race is different [4,11]. Previous studies have shown that FPG can be used to predict the risk of diabetes in later trimesters [2,3,5]. Riskin-Mashiah et al. studied a large number of pregnant women from Israel (n=6129) and obtained similar results to ours, namely, that first-trimester FPG has an independent relationship with the risks of GDM and LGA[5]. In addition, studies of lifestyle interventions to prevent GDM have shown that it works best in the early stages of pregnancy [13-14].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe found a strong correlation between first-trimester FPG and GDM, LGA, and other adverse obstetric outcomes, and identify its clinical significance in Shenzhen population. Therefore, we recommend that FPG be used as a marker of obstetric risk, but the diagnosis of GDM may need comprehensive consideration. The current diagnostic standards for GDM in China should be re-examined. Further research to find the optimal cutoff value for first-trimester FPG and determine the optimal treatment based on the classification of FPG will be challenging.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eOur research has some limitations. The nutritional status of pregnancies may affect fetal growth and other perinatal outcomes, but we lack the related data. The value of PG and \u003ca href=\"https://fanyi.so.com/?src=onebox#bilirubin\"\u003ebilirubin\u003c/a\u003e of newborns is also very important for the survey, but the data are unavailable now. A number of confounded factors, such as microsomia in the past, may influence the clinical decision, such as the choice of delivery method. The lack of an identified cutoff value for first-trimester FPG to date needs further exploration and indicates that the survey needs additional, more thorough research. However, our study did find a significant correlation between adverse outcomes and higher maternal first-trimester FPG under the diagnostic criterion for GDM (in the total population and non-GDM group), suggesting a need to reconsider current criteria for diagnosing and addressing first-trimester FPG.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey was supported by the National Natural Science Foundation of China(81830041,81771611),Shen Zhen Science and Technology Innovation Committee Special Funding for Future Industry（JCYJ20170412140326739）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study were included in this published article\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe codes used during and/or analyzed during the current study are available from the corresponding authors (JM Niu) on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJM Niu were responsible for the study conception and design. JN Tong did the statistical analysis and wrote the script. LL Wu, YX Chen, XN Guan, and XX Wu collected the data. FY Tian and HF Zhang gave help to the data interpretation. K Liu and AQ Yin helped to revise part of the script. All authors contributed to the study design, including data collection, data interpretation and manuscript revision, and gave final approval of the version to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was approved by the Review Board for Human Investigation and the Ethics Committee of Shenzhen Maternal and Children Hospital. Informed consent was obtained from every patient, and the investigations were performed in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from individual or guardian participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Prof. Xin Zhou at Tianjin University General Hospital about the structure suggestion of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e[1]. I.A.o. Diabetes, P.S.G.C.P.J.D. care, International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy, 33 (2010) 676-682.\u003c/p\u003e\n\u003cp\u003e[2]. G. Sesmilo, P. Prats, S. Garcia, I. Rodr\u0026iacute;guez, A. Rodr\u0026iacute;guez-Melc\u0026oacute;n, I. Berges, B.J.A.d. Serra, First-trimester fasting glycemia as a predictor of gestational diabetes (GDM) and adverse pregnancy outcomes, 57 (2020) 697-703.\u003c/p\u003e\n\u003cp\u003e[3]. M.E. Bianco, A. Kuang, J.L. Josefson, P.M. Catalano, A.R. Dyer, L.P. Lowe, B.E. Metzger, D.M. Scholtens, W.L.J.D. Lowe, Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study: newborn anthropometrics and childhood glucose metabolism, 64 (2021) 561-570.\u003c/p\u003e\n\u003cp\u003e[4] B.E. Metzger, M. Contreras, D. Sacks, W. Watson, S. Dooley, M. Foderaro, C. Niznik, J. Bjaloncik, P. Catalano, L.J.N.E.j.o.m. Dierker, Hyperglycemia and adverse pregnancy outcomes, 358 (2008) 1991-2002.\u003c/p\u003e\n\u003cp\u003e[5] S. Riskin-Mashiah, A. Damti, G. Younes, R.J.E.J.o.O. Auslender, Gynecology, R. Biology, First trimester fasting hyperglycemia as a predictor for the development of gestational diabetes mellitus, 152 (2010) 163-167.\u003c/p\u003e\n\u003cp\u003e[6]. D.B. Sacks, D.E. Bruns, D.E. Goldstein, N.K. Maclaren, J.M. McDonald, M.J.C.c. Parrott, Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus, 48 (2002) 436-472.\u003c/p\u003e\n\u003cp\u003e[7]. A.D.A.J.C.d.a.p.o.t.A.D. Association, Standards of medical care in diabetes\u0026mdash;2019 abridged for primary care providers, 37 (2019) 11.\u003c/p\u003e\n\u003cp\u003e[8]. M.A. Brown, L.A. Magee, L.C. Kenny, S.A. Karumanchi, F.P. McCarthy, S. Saito, D.R. Hall, C.E. Warren, G. Adoyi, S.J.H. Ishaku, Hypertensive disorders of pregnancy: ISSHP classification, diagnosis, and management recommendations for international practice, 72(1) (2018) 24-43.\u003c/p\u003e\n\u003cp\u003e[9]. W.H. Organization, Obesity: preventing and managing the global epidemic, (2000).\u003c/p\u003e\n\u003cp\u003e[10]. N.R. Council, Weight gain during pregnancy: reexamining the guidelines, (2010).\u003c/p\u003e\n\u003cp\u003e[11]. W.L. Lowe, D.M. Scholtens, A. Kuang, B. Linder, J.M. Lawrence, Y. Lebenthal, D. McCance, J. Hamilton, M. Nodzenski, O.J.D.c. Talbot, Hyperglycemia and adverse pregnancy outcome follow-up study (HAPO FUS): maternal gestational diabetes mellitus and childhood glucose metabolism, 42(3) (2019) 372-380.\u003c/p\u003e\n\u003cp\u003e[12]. W.-w. Zhu, H.-x. Yang, Y.-m. Wei, J. Yan, Z.-l. Wang, X.-l. Li, H.-r. Wu, N. Li, M.-h. Zhang, X.-h.J.D.c. Liu, Evaluation of the value of fasting plasma glucose in the first prenatal visit to diagnose gestational diabetes mellitus in China, 36(3) (2013) 586-590.\u003c/p\u003e\n\u003cp\u003e[13]. E. Cosson, E. Vicaut, N. Berkane, T.L. Cianganu, C. Baudry, J.-J. Portal, J. Boujenah, P. Valensi, L.J.D. Carbillon, Metabolism, Prognosis associated with initial care of increased fasting glucose in early pregnancy: A retrospective study, (2020).\u003c/p\u003e\n\u003cp\u003e[14]. S.B. Koivusalo, K. R\u0026ouml;n\u0026ouml;, M.M. Klemetti, R.P. Roine, J. Lindstr\u0026ouml;m, M. Erkkola, R.J. Kaaja, M. P\u0026ouml;yh\u0026ouml;nen-Alho, A. Tiitinen, E.J.D.c. Huvinen, Gestational diabetes mellitus can be prevented by lifestyle intervention: the Finnish Gestational Diabetes Prevention Study (RADIEL): a randomized controlled trial, 39(1) (2016) 24-30.\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003eTable1 Baseline demographic and adverse pregnancy outcome\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eCharacteristics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003eOverall\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003eNo GDM\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003eGDM\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003en\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e48444\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e41446(85.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6998(14.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e\u003cstrong\u003eMaternal Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eMaternal age, years\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 30.85\u0026plusmn;4.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 30.57\u0026plusmn;3.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp; 32.52\u0026plusmn;4.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eHeight, m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1.60\u0026plusmn;0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1.60\u0026plusmn;0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1.59\u0026plusmn;0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003ePrepregnancy BMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 20.65\u0026plusmn;2.65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 20.50\u0026plusmn;2.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp; 21.69\u0026plusmn;3.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eCategory of prepregnancy BMI\u003csup\u003e b\u003c/sup\u003e(n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e\u0026le;18.5kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 7530 (20.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 6960 (21.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 570 (12.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e18.5-24.9 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 26941 (73.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 23513 (73.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 3428 (74.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e25.0-29.9 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 2099 (5.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1552 (4.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 547 (11.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e30.0-34.9 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 163 (0.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 116 (0.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 47 (1.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e35.0-39.9 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 17 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 12 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 5 (0.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e\u0026ge;40.0 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 7 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 5 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 2 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eFPG in first trimester, mmol/L\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 4.62\u0026plusmn;0.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e4.59\u0026plusmn;0.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e4.80\u0026plusmn;0.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" width=\"215\"\u003e\n\u003cp\u003eCategory of FPG in first trimester (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"88\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e\u0026le; 4.19mmol/L\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 5889 (12.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 5355 (12.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 534 (7.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e4.19-4.62 mmol/L\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 19770 (40.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 17621 (42.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 2149 (30.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e4.63-5.10 mmol/L\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 18184 (37.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 15384 (37.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 2800 (40.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e5.11-7.0 mmol/L\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 4503 (9.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 3029 (7.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1474 (21.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eDelivery Times.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 0.37\u0026plusmn;0.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 0.35\u0026plusmn;0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 0.49\u0026plusmn;0.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" width=\"215\"\u003e\n\u003cp\u003eOGTT at 0h, mmol/L\u003csup\u003e d\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"88\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 2.52\u0026plusmn;2.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 2.42\u0026plusmn;2.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 3.10\u0026plusmn;2.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" width=\"215\"\u003e\n\u003cp\u003eOGTT at 1h, mmol/L\u003csup\u003e d\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"88\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 4.41\u0026plusmn;3.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 4.08\u0026plusmn;3.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 6.35\u0026plusmn;4.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" width=\"215\"\u003e\n\u003cp\u003eOGTT at 2h, mmol/L\u003csup\u003e d\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"88\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 3.91\u0026plusmn;3.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 3.62\u0026plusmn;3.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 5.61\u0026plusmn;3.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eDelivery mode (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eObstetric Forceps\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 282 (0.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 234 (0.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 48 (0.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eEutocia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 27294 (56.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 23799 (57.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 3495 (49.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" width=\"215\"\u003e\n\u003cp\u003eVacuum Extraction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"88\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 424 (0.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 347 (0.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 77 (1.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eBreech Presentation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 18 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 18 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 0 (0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eCesarean Section\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 20426 (42.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 17048 (41.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 3378 (48.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary Cesarean Section\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp; 7237 (14.9) \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp; 5691 (13.7) \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp; 1546 (22.1) \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"212\"\u003e\n\u003cp\u003eGestational weight gain (GWG), Kg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"88\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 2.21\u0026plusmn;2.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 2.21\u0026plusmn;2.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 2.20\u0026plusmn;2.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"51\"\u003e\n\u003cp\u003e0.768\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"212\"\u003e\n\u003cp\u003eCategory of GWG\u003csup\u003ec\u003c/sup\u003e (n, %)\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"88\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"51\"\u003e\n\u003cp\u003e0.264\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e＜0.5kg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 6212 (22.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 5280 (22.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; 932 (23.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e0.5-2kg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 7798 (28.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 6703 (28.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1095 (27.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e0.5-2kg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 13227 (48.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 11296 (48.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1931 (48.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eMajor birth malformation of past history (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 9062 (18.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 7509 (18.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 1553 (22.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eBleeding amount in 24h, ml\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;287.82\u0026plusmn;98.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;287.68\u0026plusmn;97.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e288.64 \u0026plusmn;104.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.455\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e\u003cstrong\u003eNewborn characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eGestational age at delivery, wk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 38.88\u0026plusmn;1.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp; 38.93\u0026plusmn;1.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp; 38.58\u0026plusmn;1.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eWeigh of newborn, g\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e3281.52\u0026plusmn;440.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e3284.19\u0026plusmn;434.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e3265.74\u0026plusmn;471.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eApgar 1min\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp; 9.92\u0026plusmn;0.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 9.92\u0026plusmn;0.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 9.92\u0026plusmn;0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.228\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eApgar 5min\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; 9.99\u0026plusmn;0.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 9.99\u0026plusmn;0.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 9.99\u0026plusmn;0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.854\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eApgar 1min﹤7 (n,%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"55\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"55\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.872\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e48215(99.54)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e41251(99.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6964(99.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e224(0.46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e193(0.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e31(0.44)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003e\u003cstrong\u003eAdverse outcome\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003ePolyhydramnios (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.530\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e47955(98.99)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e41033(99.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6922(98.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e489(1.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e413(1.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e76(1.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eGHD (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e47314(97.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e40518(97.76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6796(97.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e1130(2.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e928(2.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e202(2.89)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003egestational hypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e301\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003ePreeclampsia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e829\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eCesarean Section (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e28018(57.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e24398(58.87)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e3620(51.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e20426(42.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e17048(41.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e3378(48.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003ePrimary Cesarean Section (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e41207(85.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e35755(86.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e5452(77.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e7237(14.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e5691(13.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e1546(22.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003ePD (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e46058(95.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e39520(95.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6538(93.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e2386(4.93)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e1926(4.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e460(6.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eDystocia (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e46579(96.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e39800(96.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6779(96.87)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e1865(3.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e1646(3.97)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e219(3.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eLGA (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e44211(91.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e37990(91.66)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6221(88.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e4233(8.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e3456(8.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e777(11.10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eMacrosomia (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e46172(95.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e39550(95.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6622(94.63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e2272(4.69)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e1896(4.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e376(5.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eLBW (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e46743(96.49)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e40056(96.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6687(95.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e1701(3.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e1390(3.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e311(4.44)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eICU attendance of newborns (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e43360(89.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e37283(89.96)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e6077(86.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e5084(10.49)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e4163(10.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e921(13.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"212\"\u003e\n\u003cp\u003ea: At delivery\u003c/p\u003e\n\u003cp\u003eb: Categorized by WHO standard\u003c/p\u003e\n\u003cp\u003ec: Categorized by Institute of Medicine standard\u003c/p\u003e\n\u003cp\u003eLBW: Low Birth Weight\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLGA: Large for Gestational Age\u003c/p\u003e\n\u003cp\u003eGHD: Gestational Hypertensive Disorder\u003c/p\u003e\n\u003cp\u003ePD: Preterm Delivery before 37weeks\u003c/p\u003e\n\u003cp\u003eDystocia: Shoulder dystocia or birth injury\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"92\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable2 OR for GDM and adverse pregnancy outcomes according to first-trimester FPG*\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"115\"\u003e\n\u003cp\u003eOutcomes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eFPG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003eCrude ORs\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003eAdjusted ORs\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eGDM\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.223(1.107~1.351)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.137(1.002~1.289)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.046\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.825(1.655~2.012)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.592(1.406~1.801)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e4.880(4.378~5.439)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e4.031(3.513~4.625)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"201\"\u003e\n\u003cp\u003e\u003cstrong\u003eAdverse \u003c/strong\u003e\u003cstrong\u003epregnancy outcome\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eCesarean Section\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1.054(0.993~1.118)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.086\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.984(0.916~1.057)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.235(1.163~1.312)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.071(0.996~1.151)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.064\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.440(1.331~1.557)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.128(1.025~1.241)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eGHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e0.852(0.700~1.036)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.109\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.746(0.594~0.935)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.011\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1.021(0.841~1.240)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.831\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.922(0.737~1.152)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.475\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.496(1.185~1.887)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.250(0.956~1.634)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.103\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eLGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.251(1.113~1.406)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.090(0.952~1.247)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.213\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.549(1.380~1.740)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.149(1.004~1.314)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.044\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.124(1.853~2.436)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.426(1.214~1.675)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003ePolyhydramnios\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e0.841(0.639~1.106)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.216\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.830(0.614~1.123)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.228\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e0.780(0.589~1.032)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.082\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.757(0.555~1.033)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.080\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e0.971(0.677~1.393)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.874\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.971(0.653~1.442)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.883\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eDystocia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e0.980(0.843~1.140)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.793\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.081(0.909 ~ 1.286)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.379\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1.006(0.864~1.171)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.941\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.164(0.977 ~ 1.388)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.090\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e0.946(0.772~1.160)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.593\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.187(0.940 ~ 1.500)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.150\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003ePrimary Cesarean Section\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.183(1.081~1.294)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.893(0.780~1.022)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.532(1.401~1.674)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.998(0.873~1.142)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.982\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.819(1.631~2.028)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.977(0.828~1.154)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.786\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eICU attendance\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.879(0.801~0.964)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.006\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.887(0.791~0.995)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.041\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.890(0.810~0.977)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.014\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.887(0.789~0.997)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.044\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e0.943(0.834~1.067)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.353\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.918(0.787~1.070)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.274\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eMacrosomia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd 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width=\"53\"\u003e\n\u003cp\u003e0.085\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.067(1.721~2.481)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.561(1.260~1.933)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003eLBW\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.768(0.665~0.888)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.771(0.613~0.970)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.026\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.711(0.613~0.824)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.718(0.567~0.909)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.006\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.760(0.620~0.930)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.008\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e0.734(0.533~1.012)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.059\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" width=\"115\"\u003e\n\u003cp\u003ePD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.19-4.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1.021(0.890 ~ 1.171)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.768\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.559(0.589 ~ 4.125)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.371\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e4.63-5.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1.069(0.931 ~ 1.227)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.344\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e1.300(0.486 ~ 3.482)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.601\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.11-6.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"147\"\u003e\n\u003cp\u003e1.170(0.981 ~ 1.396)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"145\"\u003e\n\u003cp\u003e2.232(0.673 ~ 7.406)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"53\"\u003e\n\u003cp\u003e0.190\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*FPG: FPG in the first-trimester\u003c/p\u003e\n\u003cp\u003eReference: First category of early FPG\u0026le;4.19\u0026nbsp;mmol/L as the reference\u003c/p\u003e\n\u003cp\u003eAdjusted ORs:adjusted by maternal age,prepregancy BMI,height,delivery times and delivery weeks\u003c/p\u003e\n\u003cp\u003eBold: OR＞1,P＜0.05; Italics: OR＜1,P＜0.05\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"endocrine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"endo","sideBox":"Learn more about [Endocrine](https://www.springer.com/journal/12020)","snPcode":"12020","submissionUrl":"https://submission.nature.com/new-submission/12020/3","title":"Endocrine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"FPG, GDM, The first trimester, Adverse pregnancy outcomes ","lastPublishedDoi":"10.21203/rs.3.rs-459897/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-459897/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eTo investigate and identify first-trimester fasting plasma glucose (FPG) is related to gestational diabetes mellitus (GDM) and other adverse pregnancy outcomes in Shenzhen population.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eWe used data of 48,444 pregnant women that had been retrospectively collected between 2017 and 2019. Logistic regression analysis was used to evaluated the associations between first-trimester FPG and GDM and adverse pregnancy outcomes, and used to construct a nomogram model for predicting the risk of GDM. The performance of the nomogram was evaluated by using ROC and calibration curves. Decision curve analysis (DCA) was used to determine the clinical usefulness of the first-trimester FPG by quantifying the net benefits at different threshold probabilities.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe mean first-trimester FPG was 4.62±0.42\u0026nbsp;mmol/L. A total of 6998(14.4%) pregnancies developed GDM.489(1.01%) pregnancies developed polyhydramnios, the prevalence rates of gestational hypertensive disorder (GHD), cesarean section, primary cesarean section, preterm delivery before 37 weeks (PD) and dystocia was 1130(2.33%), 20426(42.16%), 7237(14.94%), 2386(4.93%) and 1865(3.85%), respectively. 4233(8.74%) of the newborns were LGA, and the number of macrosomia was 2272(4.69%), LBW was 1701(3.51%) and 5084(10.49%) newborns had admission to the ICU, which all showed significances between GDM and non-GDM groups (all P\u0026lt;0.05). The univariate analysis showed that first-trimester FPG was strongly associated with risks of outcomes including GDM, cesarean section, macrosomia, GHD, primary cesarean section and LGA (all OR\u0026gt;1, all P\u0026lt;0.05), furthermore, the risks of GDM, primary cesarean section and LGA was increasing with first-trimester FPG as early as it was at 4.19-4.63 mmol/L. The multivariable analysis showed that the risks of GDM (ORs for FPG 4.19-4.63, 4.63-5.11 and 5.11-7.0 mmol/L were 1.137, 1.592 and 4.031, respectively, all P \u0026lt;0.05) increased as early as first-trimester FPG was at 4.19-4.63 mmol/L,and first-trimester FPG which was also associated with the risks of cesarean section, macrosomia and LGA (OR for FPG 5.11-7.0 mmol/L of cesarean section: 1.128; OR for FPG 5.11-7.0 mmol/L of macrosomia: 1.561; OR for FPG 4.63-5.11 and 5.11-7.0 mmol/L of LGA: 1.149 and 1.426, respectively, all P \u0026lt;0.05) and with its increasing, the risks of LGA increased. Furthermore, the nomogram had a C-indices 0.771(95%CI: 0.763~0.779) and 0.770(95%CI:0.758~0.781) in training and testing validation respectively, which showed an acceptable consistency between the observed, validation and nomogram-predicted probabilities, the DAC curve analysis indicated that the nomogram had important clinical application value for GDM risk prediction.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eFPG in the first trimester was an independent risk factor for GDM which can be used as a screening test for identifying pregnancies at risk of GDM and adverse pregnancy outcomes.\u003c/p\u003e","manuscriptTitle":"Fasting plasma glucose in the first trimester is related to Gestational Diabetes Mellitus and adverse pregnancy outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-04-30 15:04:48","doi":"10.21203/rs.3.rs-459897/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-04-30T00:00:00+00:00","index":0,"fulltext":""},{"type":"editorAssigned","content":"","date":"2021-04-27T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-04-27T00:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Endocrine","date":"2021-04-23T12:49:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"endocrine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"endo","sideBox":"Learn more about [Endocrine](https://www.springer.com/journal/12020)","snPcode":"12020","submissionUrl":"https://submission.nature.com/new-submission/12020/3","title":"Endocrine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"19c8be1b-3739-440a-a902-d08fd9fc7da2","owner":[],"postedDate":"April 30th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":4014857,"name":"Endocrinology \u0026 Metabolism"},{"id":4014858,"name":"Obstetrics \u0026 Gynecology"},{"id":4014859,"name":"Surgical Obstetrics \u0026 Gynecology"}],"tags":[],"updatedAt":"2021-08-22T15:31:27+00:00","versionOfRecord":{"articleIdentity":"rs-459897","link":"https://doi.org/10.1007/s12020-021-02831-w","journal":{"identity":"endocrine","isVorOnly":false,"title":"Endocrine"},"publishedOn":"2021-08-03 15:06:02","publishedOnDateReadable":"August 3rd, 2021"},"versionCreatedAt":"2021-04-30 15:04:48","video":"","vorDoi":"10.1007/s12020-021-02831-w","vorDoiUrl":"https://doi.org/10.1007/s12020-021-02831-w","workflowStages":[]},"version":"v1","identity":"rs-459897","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-459897","identity":"rs-459897","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}