Pregnancy amplifies neurovascular vulnerability: longitudinal retinal high-resolution OCT imaging reveals early, treatment-specific neurodegeneration in gestational and pre-conceptional diabetes

Pregnancy amplifies neurovascular vulnerability: longitudinal retinal high-resolution OCT imaging reveals early, treatment-specific neurodegeneration in gestational and pre-conceptional diabetes | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Pregnancy amplifies neurovascular vulnerability: longitudinal retinal high-resolution OCT imaging reveals early, treatment-specific neurodegeneration in gestational and pre-conceptional diabetes Anne Dathan-Stumpf, Alina Saleh, Georg Röhrborn, Holger Stepan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9103502/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Gestational diabetes mellitus (GDM) and pre-conceptional diabetes are linked to increased long-term risk of type 2 diabetes (T2D) and microvascular complications. However, the earliest signs of neurovascular damage during pregnancy remain elusive. Here, we report the first longitudinal analysis of circumpapillary retinal nerve fiber layer thickness (cpRNFLT) using high-resolution 768-A-scan spectral-domain OCT in a population-based cohort of 591 pregnant women, including healthy pregnancies (HPC), diet-treated (dGDM) and insulin-treated GDM (iGDM), and pre-conceptional diabetes (T1D/T2D). We reveal divergent, treatment-specific neuroretinal trajectories: dGDM exhibited early thinning in the temporal-inferior sector (up to −20 µm), while iGDM showed progressive thickening in the temporal-superior sector (up to +22 µm), correlating with insulin exposure duration. Notably, women with pre-conceptional diabetes displayed profound and sustained thinning (up to −30 µm), exceeding levels seen in non-pregnant diabetic individuals. Using Euclidean nested case-control matching, these differences were confirmed after rigorous adjustment for confounders. Our findings demonstrate that glucose dysregulation during pregnancy induces measurable neuroretinal changes at an earlier stage than previously recognized, suggesting that the retina may serve as a non-invasive window into systemic metabolic vulnerability. These results position cpRNFLT as a potential biomarker for early detection of long-term diabetes risk, with implications for prenatal screening and preventive strategies. Health sciences/Medical research/Translational research Health sciences/Biomarkers/Predictive markers Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Gestational diabetes Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Type 2 diabetes Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Diabetes complications Optical coherence tomography circumpapillary retinal nerve fibre layer thickness gestational diabetes mellitus cpRNFLT A-scan resolution Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction The percentage of women with gestational diabetes mellitus (GDM) has increased markedly over the last ten years, e.g. in Germany from 9.4 % in 2010 to 15.1 % in 2020 [1]. Many factors, which are more common in socioeconomically disadvantaged groups, have been linked to this increase in prevalence, including physical inactivity, obesity, and significant weight gain during pregnancy [2]. While most women with GDM return to normoglycemia postpartum, the condition confers an increased risk of type 2 diabetes (T2D) [3–5], and its microvascular complications later in life [6]. The eye is increasingly recognized as a non-invasive window to systemic health, offering insights into systemic health conditions [7–9]. The circumpapillary retinal nerve fiber layer thickness (cpRNFLT) has attracted attention as a non-invasive, reproducible marker of neuroretinal health, measurable with spectral domain optical coherence tomography (SD-OCT) [10, 11]. The cpRNFL reflects the integrity of retinal ganglion cell axons and is a sensitive indicator of structural changes associated with ocular and systemic conditions [11]. Given that chronic diabetes is known to affect retinal structures even before clinical signs of diabetic retinopathy appear [12], the question can be raised whether GDM associated transient hyperglycemia in pregnancy may also influence cpRNFLT. Investigating these changes is clinically relevant, as it may provide insights into early neurodegeneration and potential risk stratification for women with GDM. Single previous findings on cpRNFLT in GDM exist, but they heterogeneously reported either subtle thinning [13, 14] associated with altered retinal microcirculation, or even significant changes compared to healthy pregnancies [15]. These inconsistencies may stem from differences in study design, OCT device, sample size, analysis area or the timing of measurements across trimesters and postpartum. Moreover, pregnancy-related hemodynamic fluctuations, hormonal influences, and inter-individual variability in ocular anatomy present additional challenges to interpretation [16]. Examining cpRNFLT changes in pregnancy and GDM is important for understanding the interplay between systemic metabolic disease and ocular health. Clarifying these associations may ultimately contribute to early screening strategies, prevention of long-term neurological as well as cardiovascular morbidity, and improved maternal ophthalmic care, based on disentangling systemic effects. This large (n= 971) population-based study, longitudinally investigates and follow ups women with a physiological pregnancy course as well as pregnant women with GDM or pre-conceptional diabetes and examines the associations with cpRNFLT pattern. Research Design and Methods Study Population This unicentric, prospective study recruited well-phenotyped healthy pregnant women and pregnant women with GDM and pre-existing type 1 (T1D) or type 2 (T2D) diabetes mellitus. Consecutive recruitment took place from April 2023 to May 2025 through the outpatient clinic of the Leipzig University Medical Center, Department of Obstetrics, Germany. Inclusion: Individuals were enrolled into the study at any gestational age during their pregnancy; singleton and multiple pregnancies were assessed independently. Pregnant women were defined as healthy (HPC) if they did not have a hypertensive pregnancy disorder (HPD; pre-eclampsia, pregnancy-induced hypertension, chronic hypertension, HELLP syndrome), intrauterine growth restriction, cholestasis or diabetic metabolic disorders. Women with GDM were defined according to the German Guidelines for Gynaecology and Obstetrics and the German Diabetic Association (DDG) as having impaired glucose tolerance for the first time during pregnancy. The diagnosis is based on an abnormal result in the standardized 75 gram oral glucose tolerance test (fasting value > 5.1 mmol/l; 1 hour ≥ 10.0 mmol/l, 2 hours: > 8.5 mmol/l), which is performed between 24.0 and 28.0 weeks of gestation [4]. Results of the oral glucose tolerance test were obtained from maternity records, and insulin use (iGDM) or purely dietary management (dGDM) of GDM was also recorded. Furthermore, we enrolled individuals who had been previously diagnosed with either T1D or T2D. In these cases of pre-conceptional diabetes mellitus, no oral glucose tolerance test was carried out. Diabetic retinopathy was absent in all of the participants. A group of non-pregnant, eye healthy, non-hypertensive and metabolically healthy women was also recruited. These women received a single measurement of cpRNFLT. Exclusion: Women with diagnosed HPD or GDM in previous pregnancies were excluded from the healthy cohort. Patients with pre-existing (surgically corrected) structural heart disease or heart failure (according to NYHA criteria), pre-existing nephropathies/ glomerulonephritis, known vasculitides and/or collagenoses (e.g. systemic lupus erythematosus), and use of any type of lipid-lowering agents were excluded. These exclusion criteria were chosen because these conditions lead to pregnancy-independent organ damage and an increased risk of CVD. We also excluded fetal chromosomal abnormalities or genetic defects associated with fetal growth restriction, and patients with suspected major fetal structural defects (e.g., heart failure), which can lead to fetal ascites and hydrops fetalis and are therefore associated with maternal mirror syndrome. Women who reported smoking during or before pregnancy were also excluded from the study, irrespectively of the duration of their smoking history [17, 18] as smoking has been demonstrated to be associated with localized reductions in retinal and macular nerve fibre layer thickness. Furthermore, as changes in retinal microvasculature are described for neuro- and musculodegenerative diseases [19], women with such diseases were also excluded from the analysis. In addition, women with pronounced hyperopia or myopia of more than 6 dioptres, laser refractive surgery treatment, or eye disease (e.g. retinal degenerative changes, glaucoma) were excluded. Data acquisition: All maternal and pregnancy-related data were collected prospectively. During the study, participants were phenotyped using a very detailed family and medical history, including information on previous pregnancies, the current pregnancy, current medication history, ethnicity, gestational age and week of pregnancy, results of the 50 gram screening test for GDM and, if abnormal, the results of the 75 gram oral glucose tolerance test [4], and body mass index (BMI) before pregnancy, at the time of measurement and at delivery. All patients had two standardized blood pressure measurements taken at each visit after a five-minute rest [20], with the first measurement discarded and only the second measurement included in the analysis [21–23]. In addition, we documented the mode of delivery, the reason for the cesarean section, the time of active pushing during vaginal deliveries, and the neonatal outcome (pH, 5-minute APGAR score). Optical coherence tomography (OCT) was obtained for the right eye at each visit. Participation in the study was possible as early as the first trimester. Follow-up measurements were taken at least once in each subsequent trimester. Thus, longitudinal analysis of the cpRNFLT was possible. Women who were enrolled early in pregnancy as healthy pregnant women and were subsequently diagnosed with a pregnancy-related complication named above switched cohorts. Consequently, longitudinal measurements are available for pregnant women who underwent cpRNFLT examinations in the first and second trimesters prior to a GDM diagnosis. The first trimester was defined as gestational age up to 13.6 weeks of gestation (wog), the second trimester between 14.0 and 27.6 wog and the third trimester from 28.0 to 42.0 wog. Circumpapillary retinal nerve fiber layer thickness (cpRNFLT) Ophthalmological imaging via spectral domain optical coherence tomography provides cpRNFLT by imaging of a circular B-scan of the retinal nerve fibre layer around the optic nerve head with 768 A-scans on a circle with 3.4 mm (Figure S1) [18, 24]. When RNFL thickness is divided into 4 quadrants, the variability increases due to the averaging within the large sectors. Smaller sectors are better at capturing focal or localized changes. The variability for average RNFL thickness is around 4.5 to 5 µm but increases for quadrants (about 8 µm) and even smaller slices (about 12 µm), meaning larger sectors mask subtle changes [25]. The shape and anatomy of the optic disc cause natural differences in thickness between quadrants. Some sectors, such as the nasal and temporal quadrants, show less reliability and more inconsistency in repeated measurements due to the RNFL being thinner or more complex in these areas [26]. The 768-point measurement profile provides a high-resolution map of cpRNFLT around the optic disc, better capturing spatial RNFL variations. This detailed data supports more precise quantification and improved reproducibility [27]. Furthermore, the use of 768- A-scan data aligns with analysis techniques such as neural networks or statistical software vetted for progression detection, which rely on high-resolution input rather than broad averages. For this study analysis, the 768 A-scan locations of the circular scan were analyzed. Circular B-scan was obtained by averaging 100 single B-scan to provide a very precise measurement quality. The location of the cpRNFLT circle and the coordinate system have been described previously [28]. Furthermore, the global mean and the six standard sectors: T temporal (315° to 45°), TS temporal-superior (45°-90°), TI temporal-inferior (90°-135°), N nasal (135°-225°), NS nasal-superior (225°-270°), and NI nasal-inferior (270°-315°) were analyzed [13, 15, 18]. For the ophthalmological imaging only the right eye of all participants was measured, since studies have shown that changes during pregnancy will affect both eyes simultaneously [24]. Additionally, it had been shown that RNFLT changes are related to race as well as age differences [24, 29, 30]. For that reason, we aimed to target a narrow age difference between the participants. Measurements that did not meet the following quality criteria were excluded: (1) B-scan number per location < 50, (2) signal to noise ratio 5% (excluded N = 4). Statistical analysis In brief, all statistical analyses were carried out in the R environment using version 4.0 (R Foundation for Statistical Computing, Vienna, Austria). ANOVA and unpaired student t-test were used for group-wise comparisons of continuous and categorical data, respectively. cpRNFLT was adjusted for maternal age and refraction. The pre-conceptional BMI value was not utilized for adjustment, as it demonstrated no significant influence on cpRNFLT in correlation analysis. All studies used a two-sided p-value of < .05 to indicate statistical significance. Group analysis was carried out by independent t-test group analysis. Here measurements in GDM pregnancies were compared to healthy pregnancy data for the first half the third trimester in order to present the effect of GDM. Furthermore, differences for dGDM and iGDM as well as pre-conceptional diabetes mellitus (T1D and T2D) were presented for the same investigation time point. An Euclidean nested case-control matching procedure was applied on our dataset in order to pair the patients with GDM to the healthy pregnant controls (HPC). For the matching procedure only women of Caucasian ethnicity were considered because significant differences in cpRNFLT were observed among different ethnic groups (results not presented here). The matching variables included maternal age, focus/ refraction, gestational age, systolic and diastolic blood pressure as well as the BMI at time of measurement (Model 1). Despite the exclusion of women with hypertensive pregnancy disorders from the present analysis, blood pressure differences of up to 8 mmHg were observed between the HPC and iGDM patient subgroups within the normal blood pressure range. In patients without specific cardiovascular disease, an increase in the inter-arm systolic blood pressure difference (SBPD) of 5 mm has been shown to result in a 12% increase in the risk of vascular events [31]. Consequently, blood pressure was a factor taken into account. All variables were Z-transformed. For missing values, the median of the variable for the respective group was imputed. Within each gestational age category, the matching was performed iteratively in the following way: For each unmatched GDM patient, a matching score, defined as the sum of Euclidean distances across all matching variables, was calculated against all available healthy controls. The HPC participant with the lowest score was then selected as a match for the GDM woman. Each healthy control could be matched only once (Figure 1). Only pairs with a matching score ≤ 2 were retained to ensure high similarity between cases and controls. As women with iGDM had a significantly higher mean BMI (30.17 vs. 26.99 kg/m²) before pregnancy than women with dGDM, but gained less weight during pregnancy, we created a second Euclidean nested case-control model (Model 2) that included weight gain as an additional variable to Model 1. This methodological approach indirectly considered the pre-conceptional biometric baseline of pregnant women, calculated as the difference between their weight at the beginning of pregnancy and the respective measurement point, in addition to their BMI at the time of measurement. Weight gain was included in Model 2 on the assumption that all clinically relevant parameters, which influence the metabolic situation would be considered, and changes in cpRNFLT then could be attributed solely to the diabetic metabolic status of the pregnant woman. Ethics Measurements were performed under the umbrella of the PAPYRUS study, which aims to predict the individual cardiovascular risk after (i) hypertensive pregnancy disorders or (ii) GDM by measuring retinal layer thicknesses and microvasculature (German Clinical Trial Register number: DRKS00032530). Written informed consent was obtained from all participants. Research related to human use complied with all relevant national regulations, institutional policies and in accordance the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board (IRB00001750, 052/23-ek). Results Baseline characteristics of the current study population In total, a sample of 591 right eyes from 591 women were selected for the present analysis, in accordance with the criteria outlined in the Methods section. The composition of the study cohort, after consideration given to the exclusion criteria, is illustrated in Figure 2. The baseline characteristics of the entire cohort, as well as characteristics for women stratified according to glucose tolerance status (healthy pregnant women versus GDM versus pre-conceptional diabetes), are displayed in Table 1. Healthy pregnant women Pregnant women with GDM Pregnant women with T1D or T2D p-values (Ref. Healthy) GDM/Diabetes N (%) mean SD N (%) mean SD N (%) mean SD Maternal age at conception [years] 483 32.2 5.6 97 33.6 4.9 11 29.1 6.7 0.01 / 0.16 Ethnicity European/ Caucasian 426 (88.4) 71 (73.2) 7 (63.6) Asian 18 (3.7) 8 (8.3) 0 Black 11 (2.3) 1 (1.0) 1 (9.1) Arabs 18 (3.7) 17 (17.5) 3 (27.3) Mixed 9 (1.9) 0 0 Gravidity 2.2 1.4 2.9 2.4 2.6 1.4 Parity 0.7 0.9 1.3 1.7 0.6 0.7 0.40 / 0.46 BMI before pregnancy [kg/m2] 24.7 5.3 28.4 6.9 33.5 8.0 <0.001 / 0.005 Value socio-economic status (SES) 16.0 3.3 16.3 3.1 11.7 3.2 0.37 / 0.001 Number of measurements 1st trimester [N] 40 0 0 Maternal age at measurement 34.5 4.7 Gestational age 1st trimester [weeks.days] 13.0 0.4 Systolic blood pressure 1nd trimester [mmHg] 116.2 13.1 Diastolic blood pressure 1nd trimester [mmHg] 73.2 9.4 Aspirin intake 3 (7.5) 0 Number of measurements 2nd trimester [N] 161 10 2 Maternal age at measurement 32.6 5.1 35.5 8.0 32.9 6.8 0.29 / 0.96 Gestational age 2nd trimester [weeks+days] 21.1 2.2 21.1 3.0 22.1 0.3 0.99 / 0.99 Systolic blood pressure 2nd trimester [mmHg] 114.9 11.2 114.7 17.2 118.0 11.3 0.97 / 0.77 Diastolic blood pressure 2nd trimester [mmHg] 70.2 8.5 76.4 10.6 70.0 7.1 0.10 / 0.97 BMI 2nd trimester [kg/m 2 ] 26.6 5.8 33.0 9.7 28.4 1.9 0.07 / 0.42 Aspirin intake 11 (6.8) 1 (10.0) 0 Number of pregnant women 3rd trimester [N] 361 91 9 Maternal age at measurement 33.0 5.6 34.5 4.8 29.1 6.8 0.01 / 0.12 Gestational age 3rd trimester [weeks.days] 35.1 2.6 35.5 2.7 34.6 3.4 0.21 / 0.67 Systolic blood pressure 3rd trimester [mmHg] 116.1 11.7 116.3 12.6 129.9 10.7 0.89 / 0.005 Diastolic blood pressure 3rd trimester [mmHg] 73.2 8.8 73.5 9.4 80.1 7.2 0.77 / 0.02 BMI 3rd trimester [kg/m2] 28.4 4.9 31.9 6.1 37.3 6.1 <0.001 / 0.002 Aspirin intake 16 (4.4) 4 (4.4) 1 (11.1) Gestational age at delivery [weeks.days] 483 39.4 1.9 97 39.2 1.4 11 38.4 1.7 0.23 / 0.08 BMI gain during pregnancy [kg/m 2 ] 5.0 2.3 4.1 2.8 3.3 3.3 0.004 / 0.12 Delivery Mode Vaginal birth 233 (64.9) 60 (66.7) 4 (40.0) Vacuumextraction or Forceps 34 (9.5) 3 (3.3) 0 C-section (electiv and secondary) 92 (25.6) 27 (30.0) 6 (60.0) Birth weigt [g] 3417.2 503.3 3518.7 492.8 3691.0 513.2 0.07 / 0.11 Growth percentile 48.0 27.5 56.2 27.5 69.8 26.7 0.008 / 0.02 Systolic blood pressure 48-96h postpartum [mmHg] 118.4 12.5 118.5 12.1 126.0 8.6 0.94 / 0.02 Diastolic blood pressure 48-96h postpartum [mmHg] 72.0 10.0 72.7 10.1 83.4 12.3 0.53 / 0.01 Table 1 Presentation of the composition of the study group of healthy pregnant women, women with GDM, and pregnant women with pre-conceptional diabetes mellitus (T1D or T2D). The significance of demographic differences between the cohorts was determined through the implementation of a t-test for independent samples, with the healthy pregnant women cohort serving as the reference in each instance. Significant differences are highlighted in bold. With regard to maternal age, parity, and socioeconomic status, the GDM and HPC groups exhibited comparable characteristics, although the mean age at conception of the GDM group was approximately one year higher (p=0.01). Pregnant women with GDM as well as pre-conceptional T1D and T2D had significantly higher BMI values at the start of pregnancy. In all subgroups, the majority of subjects were women of Caucasian origin. Women of Arab origin, specifically from Western Asia and North Africa, constituted the second large ethic group of our study. Based on the consecutive enrollment into the study cohort, no women measured in the first trimester developed GDM during their course of pregnancy. Consequently, group comparisons in the first trimester are omitted below. The majority of measurements were obtained during the third trimester. All groups were comparable in the second and third trimesters, with regard to gestational age at the time of cpRNFLT measurement. In the third trimester and 48–96 hours postpartum, subjects in the diabetes cohort (T1D and T2D) exhibited significantly elevated systolic and diastolic blood pressure values in comparison to the HPC, although these values remained, on average, within the normotensive range. The distribution of delivery modes within the HPC group corresponded exactly to the annual distribution of delivery modes at Leipzig University Hospital, a perinatal center with the highest level of care. A higher frequency of caesarean sections was observed in women in the T1D and T2D groups, with a rate more than twice that of the HPC group. Longitudinal changes in cpRNFLT during the physiological course of pregnancy Collecting circumpapillary data ensures that measurement geometry matches the biology of the visual system. All retinal ganglion cell axons converge toward the optic nerve head and must pass through the circumpapillary region before exiting the eye. Sampling this annular zone therefore captures a complete cross-section of the output of the retina—effectively a census of all fibres transmitting visual information to the brain. Few biological systems offer such a naturally constrained bottleneck that can be interrogated non-invasively. The comparison between non-pregnant healthy controls (singleton measurement) and HPC is illustrated in Figures 3A-E. The cpRNFLT is displayed by A-scan resolution obtained for the circular B-scan around the optic nerve head, with the analysis adjusted for individual refraction values and maternal age. In the first trimester, HPC differed from healthy, non-pregnant controls at only 0.9% of examined A-scan locations. This significance was determined by a thinning of up to 10 µm in the N sector. As gestational age increased, the trend of thinning in the N sector decreased in both width and extent. In the second trimester, with the exception of the N sector, HPC showed thickening of the cpRNFLT especially in the superior and inferior sectors by up to 10 µm. There was significant thickening in 7% of examined retinal locations compared to non-pregnant women. This thickening trend persisted until 34 weeks of gestation (maximum difference approximately 12 µm, significant change in 5.2% of A-scan locations). Toward the end of pregnancy, no clear trend or significantly areas between groups could be identified (Figure 3E). As illustrated in Table 2, a comparison has been made of the mean values in µm for the first named cohort minus the second named cohort, respectively. In addition, the results of the t-tests conducted on these data are also presented. Note that Table 2 presents six arbitrary sectors that are not anatomically related to the foveal structure [32], and compares the average difference values across an entire sector. In contrast, Figures 3A-E and 4 analyse 768 individual A-scans spanning 360 degrees. Thus, significant differences between depicted groups are lost due to averaging in the table. However, such averaged data is provided to enable comparability with former studies. A subgroup analysis compares healthy Caucasian singleton pregnancies (n = 361) to healthy Caucasian twin pregnancies (n = 29) in the third trimester. Although no statistically significant difference in retinal location was observed, possibly due to the small number of cases, twin pregnancies showed cpRNFLT thickening of approximately 12 µm between 240° and 280° in the NI sector compared to singleton pregnancies (Figure S2). This thickening was more pronounced than that observed for the HPC pregnancies compared to non-pregnant control subjects (Figure 3). comparison groups sector Gestational age until 13.6 14.0 - 27.6 28.0 - 33.6 34.0 - 42.0 28.0 - 42.0 mean diff. p value mean diff. p value mean diff. p value mean diff. p value mean diff. p value Singelton: HPC versus non-pregnant mean RNFLT G -0.46 0.80 2.29 0.10 2.83 0.06 0.41 0.73 1.04 0.38 mean RNFLT T 1.41 0.56 1.00 0.54 2.56 0.19 -0.72 0.64 0.07 0.96 mean RNFLT TS -1.14 0.72 2.60 0.33 3.32 0.26 -0.39 0.87 0.42 0.86 mean RNFLT TI 0.82 0.79 4.67 0.07 5.61 0.07 1.37 0.57 2.62 0.26 mean RNFLT N -3.76 0.18 -0.68 0.73 0.03 0.99 -0.02 0.99 0.02 0.99 mean RNFLT NS 2.24 0.54 5.14 0.08 4.45 0.16 1.70 0.51 2.50 0.32 mean RNFLT NI -0.94 0.83 5.24 0.09 4.10 0.25 2.11 0.45 2.58 0.33 Twin: HPC (N=29) versus non-pregnant mean RNFLT G not available due to small case numbers 1.04 0.38 mean RNFLT T 0.20 0.89 mean RNFLT TS 0.17 0.94 mean RNFLT TI 2.62 0.26 mean RNFLT N 0.02 0.99 mean RNFLT NS 2.25 0.37 mean RNFLT NI 2.88 0.28 GDM versus HPC mean RNFLT G not available 5.72 0.08 -2.22 0.31 2.27 0.08 1.19 0.29 mean RNFLT T 2.72 0.60 -3.50 0.34 -1.63 0.36 -1.70 0.30 mean RNFLT TS 5.63 0.27 -3.75 0.31 1.58 0.51 0.30 0.88 mean RNFLT TI 17.76 0.02 -6.06 0.11 1.55 0.59 -0.47 0.84 mean RNFLT N 5.29 0.33 -0.21 0.95 4.11 0.07 2.65 0.16 mean RNFLT NS -6.33 0.22 -0.93 0.86 3.82 0.13 2.86 0.21 mean RNFLT NI 12.66 0.03 0.40 0.95 6.25 0.04 4.93 0.09 iGDM versus dGDM mean cpRNFLT G not available due to small case numbers -1.15 0.63 mean RNFLT T 1.01 0.74 mean RNFLT TS -1.08 0.80 mean RNFLT TI -0.11 0.98 mean RNFLT N -1.15 0.73 mean RNFLT NS 0.40 0.93 mean RNFLT NI -8.13 0.10 pre-conceptional diabetes (N= 11) versus HPC mean cpRNFLT G not available due to small case numbers -8.04 0.30 mean RNFLT T -8.62 0.15 mean RNFLT TS -18.58 0.18 mean RNFLT TI -12.71 0.31 mean RNFLT N -2.35 0.75 mean RNFLT NS -3.99 0.68 mean RNFLT NI -7.07 0.44 Table 2 Group comparisons of mean sector analyses. The group comparison of the mean difference (cpRNFLT of the first named cohort minus the second named cohort), as well as the respective p-values, are presented average of different optic nerve head sectors (G, global (mean overall); N, nasal sector; NI, nasal-inferior sector; NS, nasal-superior sector; T, temporal sector; TI, temporal-inferior sector; TS, temporal-superior sector)in the first (HPC: N= 40), second (HPC: N = 161; GDM: N = 10) and third (28.0–33.6 weeks of gestation HPC: N = 91; GDM: N = 24; 34.0–42.0 weeks of gestation HPC: N = 361; GDM: N = 91) trimesters. For the total third trimester (28.0–42.0 wog), the following case numbers were obtained: HPC: N = 361; twin healthy: N = 29; GDM: N = 91; dGDM: N = 57; iGDM: N = 34; T1D and T2D: N = 11. A total of 76 non-pregnant, healthy controls were included in the analysis. Furthermore, the results of the initial measurements of a subject in the third trimester were presented, with the objective of preventing the repetition of measurements on the same woman within a single trimester. Due to the limited number of cases within the subgroups of women with insulin-dependent GDM (iGDM) and diet-managed GDM (dGDM) as well as T1D and T2D, the subdivision of the third trimester and the analysis in the second trimester were omitted. Longitudinal changes in cpRNFLT due to GDM In comparison with HPC, pregnant women with GDM demonstrated an increased thickening trend of cpRNFL in the third trimester, with the exception of a significant thinning of an average of 8 µm between 300 and 335° in the T and TI sectors (Figure 5B). A comparative analysis of pregnant women with GDM and HPC revealed 9.9% of measured A-scan locations across groups. It is noteworthy that this pattern (statistically significant thickening of the NI and in the TI sectors up to 300° as well as the thinning of cpRNFLT between 305-345°) manifested in trend as early as the second trimester (at an average of 21.1 weeks of gestation), for women who were diagnosed with GDM between 24 and 28 weeks of gestation. Note that, statistically significant thickening of cpRNFLT in the TI region evident in this group was combined with a thinning in the NS area (Figure 5A). Average sector data supported this, whereby the TI and NI sectors showed significant thickening of 18 µm and 13 µm, respectively, for GDM compared to the HPC (Table 2). For the third trimester the analysis was additionally carried out separated for GDM management in dGDM and iGDM. This highlighted a specific pattern of cpRNFLT in the third trimester, especially in women whose GDM was managed with diet. Statistically significant thinning of 12 µm was observed in the TI region between 300° and 340°, accompanied by significant thickening of approximately 10 µm at 220° and 240° in the N and NI sectors (Figure 5C). For dGDM 17.6% of measured A-scan locations differed significantly from those in the HPC group. In pregnant women with GDM who required insulin treatment during the latter stages of pregnancy, the pattern observed for dGDM was no longer detectable in the third trimester (Figure 5D). In these iGDM women, a depicted 12 µm thickening in the axon-rich superior sectors remained only a trend due to the sample size. Other regions presented no differences in cpRNFLT compared to the overall HPC cohort. Differences in cpRNFLT in pre-conceptional diabetes mellitus (T1D and T2D) When combining T1D and T2D diabetics to form the cohort with pre-conceptional diabetes, a consistent thinning of cpRNFLT was observed compared to HPC. The most statistically and clinically significant thinning was observed at the -30 µm TS level (Fig. 5E). All subgroup analyses for gestational diabetes (dGDM, iGDM, pre-conceptional versus HPC) were repeated for singleton versus twin pregnancies in the third trimester (HPC twin n = 29; dGDM twin n = 4; iGDM twin n = 0; T1D twin n = 0; T2D twin n = 0) (Figure S3). Despite the fact that only 0.8% of retinal locations differ significantly (e.g. due to the limited number of cases), the thickening between 225° and 300° and the thinning between 300° and 350° in the TI sector, as demonstrated for the dGDM cohort of singleton pregnancies (Fig. 5C), were even more pronounced in twins with GDM (Figure S3). Euclidean Nested Case-Control Matching – Model 1 An Euclidean nested case-control comparison of Caucasian HPC versus matched Caucasian GDM pregnant women (n = 69) at the 768 individual A-scan measurement locations on the peripapillary circle scan was carried out according to the matching criteria described above, found no difference of cpRNFLT between both groups. When treatment method (dietary versus insulin-dependent) was added to the model, women with dGDM (n = 44) showed significant thinner values in the TI sector between 295 and 315° compared to the respective HPC (Fig. 6iI-ii). In contrast, women with iGDM (n = 24) exhibited a tendency towards thickening across the entire cpRNFLT, reaching significance in the TS sector (57-78°) with an increase of 13 µm as well as between 130-137° with up to 20 µm (Fig. 6Bi-ii). These results essentially correspond to the changes that were found for the entire group comparison shown for the cohort in the third trimester (Fig. 5B). However, the Euclidean nested case-control model also revealed interesting new results, particularly in the iGDM cohort, through targeted case-control matching. Further differentiation of these overall group results into pregnancy trimesters within the nested case-control pairs revealed a significant difference for global cpRNFLT in the third trimester between iGDM and HPC (n = 23; p = 0.01). No significant difference in global cpRNFLT was found for dGDM vs. HPC in either the second trimester (n = 4; p = 0.76) or the third trimester (n = 40; p = 0.47). Figure 7A-B showed the variation of difference in cpRNFLT between dGDM, respectively iGDM, versus HPC at 768 A-scan locations on the circular B-Scan for comparisons by gestational age. During the third trimester, women with iGDM typically exhibited a tendency toward thickening of the cpRNFLT. This trend increased with gestational age, and corresponds to prolongated duration of insulin therapy. The increase in cpRNFLT thickness was most pronounced with 22 µm in the axon bundle- and vascular density-rich TS sector. In contrast, women with dGDM experienced significant thinning of the cpRNFLT compared to matched HPC pairs in the third trimester, as illustrated in Fig. 5C, with a decrease of up to 20 µm in the TI sector. Euclidean Nested Case-Control Matching – Model 2 (incl. weight gain) The matching procedure including weight gain for Model 2 resulted in a more balanced mean weight gain between compared groups, as expected (Model 2 iGDM vs. HPC 10.52 kg vs. 10.76 kg whereas Model 1 was 11.08 kg vs. 13.38 kg; Model 2 dGDM vs. HPC 10.14 kg vs. 9.98 kg, whereas Model 1 was 10.14 kg vs. 11.48 kg). The incorporation of weight gain as the seventh matching variable resulted in the establishment of new matching pairs, which led to an increase in variance of the cpRNFLT in the HPC cohort. Furthermore, the algorithm revealed that no suitable partners could be identified for three GDM women, resulting in a final analysis sample of 65 matched pairs. Here, the results showed no significant difference in global cpRNFLT between dGDM and HPC in either the second (n = 4; p = 0.79) or third (n = 40; p = 0.57) trimesters. Contrary to Model 1, there now was no significant difference in global cpRNFLT between iGDM (n = 21) and HPC in the third trimester (p = 0.97) and women with dGDM presented significantly thicker values in the NI sector between 220° and 255° compared to the respective HPC. In Model 2, in contrast to Model 1, women with iGDM showed significant thinning in the same sector (Fig. S5A-B). Additionally, the significant thickening of 23 µm for cpRNFLT of iGDM women in the TS sector shown in Model 1 could still be demonstrated. Figures S4Ai-ii (dGDM) and Bi-ii (iGDM) demonstrate the differences in cpRNFLT three dimensional and from a circumpapillary, bird's-eye perspective. Because Model 1 and 2 match women for gestational age, the results are not presented by weeks of gestation. An analysis of Euclidean nested case-control matching between HPC and women with T1D or T2D was not performed due to the very small number of cases. Discussion The retinal nerve fibre layer, made up of retinal ganglion cell axons is the only accessible structure of the central nervous system, as axons converge at the optic disc. Axonal damage is visible here and reflects neuroprotection and neurodegeneration [33]. This prospective study was the first to define longitudinal changes in cpRNFLT by means of a 768 single A-scan analysis on a circular B-scan around the optic disc in a well-phenotyped, predominantly Caucasian, healthy pregnant cohort. Moreover, to the best of our knowledge, this is the first study to longitudinally map changes in GDM and pre-conceptional diabetes mellitus for cpRNFLT. We demonstrate that patterns of change in cpRNFLT in women with GDM are already detectable in the early second trimester, even before diagnosis of GDM by oral glucose tolerance test. Furthermore, we show that different treatment strategies for GDM lead to different patterns of change in cpRNFLT. Previously the study by Wu et al. is the only documented research on cpRNFLT measurements in healthy pregnant women in cross sectional analyses for all three trimesters, involving 45 women per trimester. This Chinese cohort of 135 women exhibited thickening in the NS and NI sectors with advancing gestational age [33]. Our study followed a group of HPC and GDM overtime. This enables detection of longitudinal effects on cpRNFLT not detectable from cross-sectional data. First, for HPC, predominantly Caucasians, our study revealed a comparable trend to Wu et al. for sectoral data, as Wu et al. did not present A-scan level findings. However, commencing from 34 weeks of gestation, our measurements commenced a decline towards non-pregnant values. As demonstrated in the study by Wu et al., the third trimester measurements, which they obtained at an average of 31.1 weeks of gestation [33], did not capture the subsequent decrease in thickness we found. Changes to the RNFL during pregnancy are caused multifactorial by blood volume changes, hormones, eye biomechanics and general systemic status [34–36]. This results in fluid retention due to activation of the RAAS, changes to blood volume and hormones and mechanical factors [37]. Such pregnancy related changes may enhance ocular perfusion in some regions, contributing to localized thickening of the RNFL, particularly in superior and inferior sectors where nerve fibre bundles are densest and metabolically more active [33]. Additionally, the peripapillary retina receives blood supply from both the central retinal artery and short posterior ciliary arteries, leading to uneven flow rates across different quadrants and causing asymmetric fluid accumulation [33]. Progesterone and estrogen further amplify these effects by modulating vascular tone and fluid dynamics [38]. The retina is able to locally absorb more fluid. Increased capillary hydrostatic pressure leads to accumulation of fluid, which in turn results in thickening of the RNFLT, which can be characterized as mild oedema [35]. Twin pregnancies result in more significant maternal cardiovascular changes, with increased plasma volume and total body water, leading to greater fluid shifts compared to singleton pregnancies [39]. Due to larger structural volumes and denser peripapillary capillary networks in the inferior sectors of cpRNFLT (inferior ≥ superior ≥ nasal ≥ temporal), additional interstitial fluid results in more measurable thickness changes in these areas [34]. These amplified physiological changes likely explain the more pronounced thickening observed in the NI sector (240–280°) in twin pregnancies compared to singleton pregnancies. Conversely, the relative thinning observed in healthy twin pregnancies in the TS and NS sectors may be indicative of differential vascular responsiveness, venous outflow patterns, or reduced adaptive reserves in response to increased systemic demand. In certain regions, autoregulatory mechanisms may mitigate hyperperfusion, resulting in relative thinning of the peripapillary architecture during pregnancy [36]. Additionally, the temporal cpRNFL, which is naturally thinner due to fewer nerve fiber bundles, may be more susceptible to changes from pregnancy-related metabolic stress, exhibiting detectable reductions in thickness. Later stages of pregnancy were shown to cause a decrease in systemic vascular resistance, potentially normalizing or slightly reducing thickness [40], as shown in our results. Previous data on cpRNFLT for GDM exist only for a small cross-sectional sample in the third trimester. Here Sasikumar presented cpRNFLT subdivided into four sectors and demonstrated significant thinning of the superior, nasal, and inferior quadrants for the 32nd week of pregnancy compared to healthy pregnant women. Those authors found no link between HbA1c levels and cpRNFLT in GDM, concluding that GDM patients with poor blood sugar control may experience neurodegeneration even in the absence of microvascular changes seen in insulin-dependent diabetes [14]. Acmaz et al. divided the OCT circular scan into six sectors and showed significant thinning of the TI region for GDM eyes compared to healthy pregnant women. However, the exact measurement time is not provided in their paper (>24 wog) [13]. Our current study shows, that for GDM a large part of the TI sector thickens (270-300°) with clinical and statistical significance in the second trimester. Furthermore, in the third trimester of our sample, the thinning for GDM that emanates from the T sector also shifts noticeably to the TI sector (from 300-315°). Tengku-Fatishah et al. compared four quadrants of 78 women with GDM versus 72 HPC, measured on average between the 28th and 32nd wog. Women with GDM had an average global RNFLT that was 2.56 µm thinner [15]. In our cohort, the global difference was a thinning of 2.22 µm for GDM eyes. In Acmaz et al., this was 2.52 µm [13] when gestational age was ignored, making the results comparable across all three cohorts. However, due to the division into averaged quadrants or sectors in other studies, and the partial lack of information on the mean gestational age at the time of measurement, it was not possible to provide a more detailed context for the averaged sector data shown for our study (Table 2). Insulin sensitivity decreases progressively during pregnancy, especially in the second and third trimesters, necessitating increased insulin production to maintain glucose homeostasis for both mother and fetus [41, 42]. Impaired insulin sensitivity and dysregulated glucose metabolism cause RNFL thinning through a combination of neuronal cell damage, metabolic stress and vascular dysfunction, and RNFL thickness is therefore a useful biomarker for metabolic retinal neurodegeneration in diabetes and related conditions [43–45]. Women with GDM who require insulin typically have a more severe form of glucose intolerance than women whose GDM is managed by diet alone. Hyperglycaemia triggers oxidative stress, resulting in the up-regulation of vascular endothelial growth factor (VEGF) and other vasoactive mediators. This leads to endothelial dysfunction, increased vascular permeability and the breakdown of the inner blood-retinal barrier [46, 47]. The resulting axonal and glial oedema leads to an increase in tissue water content and 'thickening' of the cpRNFLT [48], particularly in the superior sectors, where the density of axon bundles is higher and perfusion vulnerability is greater [34, 49–51]. In addition, insulin therapy itself may promote fluid retention [47]. By contrast, women with dGDM are likely to experience milder degrees of metabolic stress. Consequently, the dominant process may shift more quickly towards neurodegenerative axonal loss, which manifests as thinning of the RNFL. The TI sector is particularly vulnerable to damage and exhibits sectoral predilections in neurodegeneration and axonal loss [52–54]. These pathomechanisms may explain the different patterns of cpRNFLT between iGDM and dGDM pregnant women and suggest that the RNFLT responds more sensitively and rapidly to fluctuations in glucose metabolism than previously hypothesized. Our data showed unprecedented data for both group comparison and additionally in the detailed Euclidean nested case control investigation for a subpopulation of matched GDM and HPC pairs. No previous study directly measured (gestational) weight gain and its association with cpRNFLT. We were able to investigate this further aspect and offer direct comparison, as both models showed that women with iGDM exhibited a significant 20 µm increase in cpRNFLT thickness in the axon bundle-rich and high vascular sector TS with increasing gestational age, and consequently, longer duration of insulin therapy. Furthermore, both models demonstrated significant thickening in TI sector between 270° and 300° until the end of pregnancy for the dGDM group. This thickening at 270-300° was already evident in the second trimester, specifically at 22 weeks of gestation. Interestingly, we highlight that none of the women were undergoing insulin therapy at that time. It is hypothesized that the differing behavior of cpRNFLT within the TI sector (thickening up to approximately 300° followed by a thinning of approximately 20 µm) depends on anatomical architecture. Axonal-vascular bundles appear to run between 270° and 300°, resulting in thickening in these areas due to the disrupted metabolic environment. From approximately 300° and further towards the temporal region, the density of these filaments decreases [40]. These fibres in turn exhibit detectable reductions in thickness in response to pregnancy-related metabolic stress. An increasing discussion point is provided by the fact that our study was able to measure eyes from pre-conceptional diabetes mellitus (T1D and T2D) pregnancies. The increasing insulin resistance that occurs during pregnancy, in conjunction with the thinning of the RNFLT shown previously for T2D [45], could provide a rationale for the observation that women with pre-conceptional diabetes exhibit a significantly thinner cpRNFLT during pregnancy in comparison to non-pregnant patients with T2D. Since both T1D and T2D subjects showed the same trend of thinning of cpRNFLT compared to HPC, grouping these subjects together as a preconception diabetes group is understandable. Previous greater thinning was observed in cases of poor metabolic control and in individuals with a longer duration of diabetic disease [55, 56]. Early cpRNFL thinning has been identified as a significant biomarker for diabetic retinal neurodegeneration prior to the manifestation of overt vascular retinopathy [57]. In their meta-analysis of 465 diabetics and 389 healthy subjects, Chen et al. report a mean thinning of 2.88 µm in global cpRNFLT in non-pregnant diabetics [57]. In our pregnant cohort, a trend toward thinning for pre-conceptional diabetic pregnancies was observed across the entire cpRNFL, with the most extreme differences being found in the TS sector, with up to 30 µm thinning compared to the HPC. In addition to the well-phenotyped cohort and the longitudinal design, the key advantage of our study over all other published work to date is that the current cpRNFLT analysis was not based on globally averaged sectors, respectively quadrants. Furthermore, it is highly valuable that results are presented for the first time for women with GDM prior to diagnosis (our presented sample received GDM diagnosis approximately five weeks later, i.e. at approximately 21.1 weeks of gestation). Unfortunately, it was not possible to conduct longitudinal follow-ups with all women recruited in the first trimester during the second and third trimesters. Nevertheless, no other data set exists in the literature presenting case numbers as high as the current study. Moreover, recruitment for the study is ongoing, so higher case numbers can be expected in future publications. A second limitation of our study is the small number of cases in the pre-conception diabetes group (T1D and T2D). In summary, the divergent treatment approaches (dGDM and iGDM) and the extreme thinning of cpRNFLT in women with pre-conceptional diabetes, far exceeding the described thinning in non-pregnant diabetics, suggest that pregnancy and impaired glucose tolerance metabolism affect the RNFL much more severely and sensitively than previously assumed. Further studies are required to ascertain whether these specific patterns associated with impaired glucose tolerance and pregnancy can be observed postpartum. In addition, it should be examined whether the persistence of specific patterns can be used to identify women who will develop manifest glucose tolerance disorders as a result of GDM, and how this correlates with other cardiovascular risk factors. Abbreviations cpRNFLT circumpapillary retinal nerve fibre layer thickness dGDM gestational diabetes mellitus treated with diet HPC healthy pregnant controls iGDM gestational diabetes mellitus treated with insulin N nasal sector (135° to 225°) NI nasal-inferior sector (270° to 315°) NS nasal-superior sector (225° to 270°) OCT optical coherence tomography RNFL retinal nerve fibre layer T temporal sector (315° to 45°) T1D diabetes mellitus typ 1 T2D diabetes mellitus typ 2 TI temporal-inferior sector (90° to 135°) TS temporal-superior sector (45° to 90°) wog week of gestation Declarations Data availability The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University. Funding This work was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG); project number 493646873 – MD-LEICS. FG Rauscher was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG); project number 497989466. Competing interests The authors have no conflict of interest. Author’s contributions A.D.S. is the guarantor of this work. A.D.S., F.G.R and H.S. designed the study. A.D.S. and A.S. performed the measurements and acquisition of data. T.E., F.G.R., A.D.S. and G.R. performed data analysis and interpretation. A.D.S and F.G.R. drafted the article. A.D.S., F.G.R., A.S., T.E., G.R. and H.S. reviewed the article critically and gave important intellectual content. All authors gave their final approval of the version to be published. References Lappe V, Greiner GG, Linnenkamp U et al (2023) Gestational diabetes in Germany-prevalence, trend during the past decade and utilization of follow-up care: An observational study. 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JAMA Ophthalmol 137:1125–1132 Bhaskaran A, Babu M, Sudhakar NA, Kudlu KP, Shashidhara BC (2023) Study of retinal nerve fiber layer thickness in diabetic patients using optical coherence tomography. Indian J Ophthalmol 71:920–926 Chen X, Nie C, Gong Y et al (2015) Peripapillary retinal nerve fiber layer changes in preclinical diabetic retinopathy: A meta-analysis. PLoS One 10:e0125919 Additional Declarations There is NO Competing Interest. Supplementary Files Supplements.pdf Additional Figures (S1-S5) Cite Share Download PDF Status: Under Review Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-9103502","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":607891986,"identity":"d1f70938-de09-446b-8ffb-c0a0f1539085","order_by":0,"name":"Anne Dathan-Stumpf","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-4331-6569","institution":"University Hospital Leipzig","correspondingAuthor":true,"prefix":"","firstName":"Anne","middleName":"","lastName":"Dathan-Stumpf","suffix":""},{"id":607891987,"identity":"d96f9c91-7b7d-43a6-acd8-975d5286ffee","order_by":1,"name":"Alina Saleh","email":"","orcid":"","institution":"University Hospital Leipzig","correspondingAuthor":false,"prefix":"","firstName":"Alina","middleName":"","lastName":"Saleh","suffix":""},{"id":607891988,"identity":"1dcd2b66-ef6a-4673-9dd4-266106258414","order_by":2,"name":"Georg Röhrborn","email":"","orcid":"","institution":"Leipzig University","correspondingAuthor":false,"prefix":"","firstName":"Georg","middleName":"","lastName":"Röhrborn","suffix":""},{"id":607891989,"identity":"fc210dc4-577d-43fd-8c5b-92e6f99e0319","order_by":3,"name":"Holger Stepan","email":"","orcid":"","institution":"University Hospital Leipzig","correspondingAuthor":false,"prefix":"","firstName":"Holger","middleName":"","lastName":"Stepan","suffix":""},{"id":607891990,"identity":"94cd07e7-7adf-4e23-a9a4-8a8651ca70b4","order_by":4,"name":"Tobias Elze","email":"","orcid":"https://orcid.org/0000-0002-2032-0496","institution":"Massachusetts Eye and Ear","correspondingAuthor":false,"prefix":"","firstName":"Tobias","middleName":"","lastName":"Elze","suffix":""},{"id":607891991,"identity":"83e2f6c8-1e03-4c9d-9bcd-3b41c42dda7e","order_by":5,"name":"Franziska Rauscher","email":"","orcid":"https://orcid.org/0000-0003-0183-0340","institution":"Leipzig University","correspondingAuthor":false,"prefix":"","firstName":"Franziska","middleName":"","lastName":"Rauscher","suffix":""}],"badges":[],"createdAt":"2026-03-12 10:19:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9103502/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9103502/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106533651,"identity":"11e2f946-e002-4659-a9d0-ecd5e8171c4d","added_by":"auto","created_at":"2026-04-09 14:57:54","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":225891,"visible":true,"origin":"","legend":"\u003cp\u003ePresentation of the Euclidean nested case-control approach: Only women of Caucasian ethnicity were considered. The matching variables included maternal age, refractive error, gestational age, systolic and diastolic blood pressure, and BMI at the time of measurement (Model 1), as well as weight gain (Model 2). Within each gestational age category, matching was performed iteratively as follows: For each unmatched GDM patient, a matching score was calculated. This score was defined as the sum of the Euclidean distances across all the matching variables and was calculated against all the available healthy controls. The control participant from the HPC group with the lowest matching score was then selected. Only pairs with a matching score of 2 or less were retained to ensure high similarity between cases and controls.\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/0f38fe5ca51c6c711c5bf46c.jpg"},{"id":106533655,"identity":"0b765b9f-82cd-4698-a246-9367bf86bb62","added_by":"auto","created_at":"2026-04-09 14:57:54","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":372593,"visible":true,"origin":"","legend":"\u003cp\u003ePresentation of the total study population. The first trimester was defined as gestational age up to 13.6 weeks of gestation, the second trimester between 14.0 and 27.6 weeks of gestation and the third trimester from 28.0 to 42.0 weeks of pregnancy.\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/4dd8a3983bc4fc12c01dd343.jpg"},{"id":106533653,"identity":"2bb6c44d-4dd3-4db6-b9ba-7d288559b071","added_by":"auto","created_at":"2026-04-09 14:57:54","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":455631,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3A-E:\u003c/strong\u003eThe following representation provided the longitudinal differences in cpRNFLT [µm] for the HPC versus non-pregnant control group (first-mentioned minus second-mentioned) from 768 individual points over 360 degrees at different gestational ages (\u003cstrong\u003e(A)\u003c/strong\u003e first trimester, \u003cstrong\u003e(B)\u003c/strong\u003e second trimester, \u003cstrong\u003e(C)\u003c/strong\u003ethird trimester, \u003cstrong\u003e(D)\u003c/strong\u003e first half of the third trimester and \u003cstrong\u003e(E)\u003c/strong\u003esecond half of the third trimester including exceeding the calculated delivery date). The six standard sectors are plotted along the circular scan as follows: T temporal (315° to 45°), TS temporal-superior (45° to 90°), TI temporal-inferior (90° to 135°), N nasal (135° to 225°), NS nasal-superior (225° to 270°), and NI nasal-inferior (270° to 315°). Each measurement point was adjusted for the individual refraction of each pregnant woman. Negative deflections on the y-axis are indicative of thinning, while positive deflections are indicative of thickening of the nerve fibre layer thickness in the aforementioned group compared to the latter group. The areas of significant difference are indicated by a red color scheme.\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/56ae0e10b8042c97752b016a.jpg"},{"id":106533682,"identity":"06dd02df-6dbe-4356-a833-82e4b4b8e231","added_by":"auto","created_at":"2026-04-09 14:57:56","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":443981,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4\u003c/strong\u003eshows the longitudinal development of cpRNFLT values within the Caucasian cohort of healthy singleton pregnancies (n= 483) in even greater detail over gestational age. After the estimated delivery date has been reached, the cpRNFLT appears thinner with time. Note that for standard ophthalmological reporting, the horizontal diameter through the centre of the measurement circle is shown, along which cpRNFLT is depicted as originating at zero. However, by doing so, the T sector (315° to 45°) is invariably divided into two segments in the graphics. In order to facilitate comprehension, the temporal sector is shown as a whole in this figure. Thus, cpRNFLT is displayed from 270° for scaling of the circular scan here.\u003c/p\u003e","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/52f94909ac366318d222f478.jpg"},{"id":106533588,"identity":"f47b0df7-0169-4db2-80bc-888c058702e4","added_by":"auto","created_at":"2026-04-09 14:57:48","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":444832,"visible":true,"origin":"","legend":"\u003cp\u003eMean difference in cpRNFLT represented along 768 points of a circular scan for GDM and healthy pregnant women, taking into account gestational age \u003cstrong\u003e(A)\u003c/strong\u003e GDM (n = 10) vs. HPC (n = 161) in the second trimester (all measurements took place between 14.0-22.6 weeks of gestation); \u003cstrong\u003e(B)\u003c/strong\u003e GDM (n = 91) vs. HPC (n = 361) in the third trimester, and the form of therapy \u003cstrong\u003e(C)\u003c/strong\u003e diet-managed GDM (dGDM; n = 57) vs. HPC in third trimester (n = 361); \u003cstrong\u003e(D)\u003c/strong\u003e insulin-dependent GDM in third trimester (iGDM; n = 34) vs. HPC as well as the group comparison to \u003cstrong\u003e(E) \u003c/strong\u003epre-conception diabetes in third trimester (T1D or T2D; n = 11) vs. HPC (n= 361). The six standard sectors are plotted along the circular scan as follows: T temporal (315° to 45°), TS temporal-superior (45° to 90°), TI temporal-inferior (90° to 135°), N nasal (135° to 225°), NS nasal-superior (225° to 270°), and NI nasal-inferior (270° to 315°). Each measurement point was adjusted for the individual refraction of each pregnant woman. Negative deflections on the y-axis are indicative of thinning, while positive deflections are indicative of thickening of the nerve fibre layer thickness in the aforementioned group compared to the latter group. The areas of significant difference are indicated by a red colour scheme. During the third trimester, the GDM group exhibited significant thinning in the TI and T regions, a trend that was more pronounced in women with dGDM.\u003c/p\u003e","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/840f6446e1cc465788ff4548.jpg"},{"id":106533586,"identity":"9217b092-cfec-4dd8-a97d-fa2acf2e6f97","added_by":"auto","created_at":"2026-04-09 14:57:48","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":528630,"visible":true,"origin":"","legend":"\u003cp\u003eThis visualization shows the differences in cpRNFLT at 768 A-scan locations on the circular scan for the Euclidean nested case-control matching of Model 1 (matching for maternal age, gestational age at the time of measurement, refraction, systolic and diastolic blood pressure, and BMI at the time of examination) between: \u003cstrong\u003eA\u003c/strong\u003e. Women with dGDM (n= 44, green); \u003cstrong\u003eB\u003c/strong\u003e. Women with iGDM (n= 24, purple) to their matched HPC (blue) in \u003cstrong\u003ei.\u003c/strong\u003e Bird's eye perspective and \u003cstrong\u003eii\u003c/strong\u003e. three-dimensional (due to the high magnification and bird's-eye perspective, the circular scan appears more oval-shaped). Significant differences at the 768 individual measurement points (p \u0026lt; .05) are marked in red. Women with dGDM had significantly thinner cpRNFLT in the TI sector compared to their matched HPC. Women with iGDM presented with cpRNFLT of up to 20 µm thicker in both the NS and TS regions.\u003c/p\u003e","description":"","filename":"fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/564da4082676d3227ca77494.jpg"},{"id":106533687,"identity":"6423146a-23ed-4658-9dff-eb6d3f9fa666","added_by":"auto","created_at":"2026-04-09 14:57:57","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":553929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigures 7A-D\u003c/strong\u003e show the variation of the difference in cpRNFLT along the 768 individual A-scan measurement locations between dGDM (green) and iGDM (purple) versus HPC for different gestational age groups as well as the third trimester for Model 1 (Fig. 7A+B) of the Euclidean nested case-control approach.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn Figure 7B\u003c/strong\u003e, plotted for gestational age within the 3\u003csup\u003erd\u003c/sup\u003e trimester, the width of the shaded area between two depicted curves represents the change of cpRNFLT at the respective measurement location. Wider shaded areas depict a larger evident change for the A-scan measurement region on the circular B-scan between 28.0 and 42.0 weeks of gestation. Narrow shaded areas depict stable cpRNFLT. Areas colored red indicates statistically significant differences (p \u0026lt;.05) for cpRNFLT of GDM to HPC. The graphs also represent the comparison between matched pairs for iGDM with HPC and matched dGDM with HPC. The dotted lines below indicate whether the differences in cpRNFLT mean thickening or thinning compared to the HPC. It should be noted that the data is only represented for weeks of gestation with sufficient measurement points to form matching pairs. Consequently, other data is not displayed.\u003c/p\u003e\n\u003cp\u003eTaking gestational age into account, women with iGDM showed a significant increase in cpRNFLT thickness of over 22 µm in the axon bundle and vascular-rich sector TS, with increasing gestational age and consequently longer duration of insulin therapy, in both Model 1 and Model 2.\u003c/p\u003e\n\u003cp\u003eDuring the second trimester (14.0 to 22.6), a thickening pattern of cpRNFLT between 270° to 300° was observed in the TI sector of the GDM group (Fig. 5A). At this time, none of the women who were later diagnosed with GDM were on insulin therapy. Significant thickening of the cpRNFLT persisted in this area until the end of pregnancy in the dGDM group, suggesting that observed changes in the cpRNFLT may act as an early predictor of impaired glucose metabolism in the early second trimester.\u003c/p\u003e","description":"","filename":"fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/6031e89b3e14db0e47cce18a.jpg"},{"id":106960579,"identity":"c66e851a-09f9-42eb-9217-c833f0724d51","added_by":"auto","created_at":"2026-04-15 09:21:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4246809,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/0b333657-6cfa-495a-95b1-c09429c88f52.pdf"},{"id":106533654,"identity":"cd396cfd-263f-4a88-84c9-e037bba37cb9","added_by":"auto","created_at":"2026-04-09 14:57:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1131857,"visible":true,"origin":"","legend":"Additional Figures (S1-S5)","description":"","filename":"Supplements.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9103502/v1/998d49b303b192f70df9a283.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Pregnancy amplifies neurovascular vulnerability: longitudinal retinal high-resolution OCT imaging reveals early, treatment-specific neurodegeneration in gestational and pre-conceptional diabetes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe percentage of women with gestational diabetes mellitus (GDM) has increased markedly over the last ten years, e.g. in Germany from 9.4 % in 2010 to 15.1 % in 2020 [1]. Many factors, which are more common in socioeconomically disadvantaged groups, have been linked to this increase in prevalence, including physical inactivity, obesity, and significant weight gain during pregnancy [2]. \u0026nbsp;While most women with GDM return to normoglycemia postpartum, the condition confers an increased risk of type 2 diabetes (T2D) [3\u0026ndash;5], and its microvascular complications later in life [6].\u003c/p\u003e\n\u003cp\u003eThe eye is increasingly recognized as a non-invasive window to systemic health, offering insights into systemic health conditions [7\u0026ndash;9]. The circumpapillary retinal nerve fiber layer thickness (cpRNFLT) has attracted attention as a non-invasive, reproducible marker of neuroretinal health, measurable with spectral domain optical coherence tomography (SD-OCT) [10, 11]. The cpRNFL reflects the integrity of retinal ganglion cell axons and is a sensitive indicator of structural changes associated with ocular and systemic conditions [11]. Given that chronic diabetes is known to affect retinal structures even before clinical signs of diabetic retinopathy appear [12], the question can be raised whether GDM associated transient hyperglycemia in pregnancy may also influence cpRNFLT. Investigating these changes is clinically relevant, as it may provide insights into early neurodegeneration and potential risk stratification for women with GDM. Single previous findings on cpRNFLT in GDM exist, but they heterogeneously reported either subtle thinning [13, 14] associated with altered retinal microcirculation, or even significant changes compared to healthy pregnancies [15]. These inconsistencies may stem from differences in study design, OCT device, sample size, analysis area or the timing of measurements across trimesters and postpartum. Moreover, pregnancy-related hemodynamic fluctuations, hormonal influences, and inter-individual variability in ocular anatomy present additional challenges to interpretation [16].\u003c/p\u003e\n\u003cp\u003eExamining cpRNFLT changes in pregnancy and GDM is important for understanding the interplay between systemic metabolic disease and ocular health. Clarifying these associations may ultimately contribute to early screening strategies, prevention of long-term neurological as well as cardiovascular morbidity, and improved maternal ophthalmic care, based on disentangling systemic effects. \u0026nbsp;This large (n= 971) population-based study, longitudinally investigates and follow ups women with a physiological pregnancy course as well as pregnant women with GDM or pre-conceptional diabetes and examines the associations with cpRNFLT pattern.\u003c/p\u003e"},{"header":"Research Design and Methods","content":"\u003ch2\u003eStudy Population\u003c/h2\u003e\n\u003cp\u003eThis unicentric, prospective study recruited well-phenotyped healthy pregnant women and pregnant women with GDM and pre-existing type 1 (T1D) or type 2 (T2D) diabetes mellitus. Consecutive recruitment took place from April 2023 to May 2025 through the outpatient clinic of the Leipzig University Medical Center, Department of Obstetrics, Germany.\u003c/p\u003e\n\u003cp\u003eInclusion: Individuals were enrolled into the study at any gestational age during their pregnancy; singleton and multiple pregnancies were assessed independently. Pregnant women were defined as healthy (HPC) if they did not have a hypertensive pregnancy disorder (HPD; pre-eclampsia, pregnancy-induced hypertension, chronic hypertension, HELLP syndrome), intrauterine growth restriction, cholestasis or diabetic metabolic disorders. Women with GDM were defined according to the German Guidelines for Gynaecology and Obstetrics and the German Diabetic Association (DDG) as having impaired glucose tolerance for the first time during pregnancy. The diagnosis is based on an abnormal result in the standardized 75 gram oral glucose tolerance test (fasting value \u0026gt; 5.1 mmol/l; 1 hour \u0026ge; 10.0 mmol/l, 2 hours: \u0026gt; 8.5 mmol/l), which is performed between 24.0 and 28.0 weeks of gestation [4]. Results of the oral glucose tolerance test were obtained from maternity records, and insulin use (iGDM) or purely dietary management (dGDM) of GDM was also recorded. \u0026nbsp;Furthermore, we enrolled individuals who had been previously diagnosed with either T1D or T2D. In these cases of pre-conceptional diabetes mellitus, no oral glucose tolerance test was carried out. Diabetic retinopathy was absent in all of the participants.\u003c/p\u003e\n\u003cp\u003eA group of non-pregnant, eye healthy, non-hypertensive and metabolically healthy women was also recruited. These women received a single measurement of cpRNFLT.\u003c/p\u003e\n\u003cp\u003eExclusion: Women with diagnosed HPD or GDM in previous pregnancies were excluded from the healthy cohort. Patients with pre-existing (surgically corrected) structural heart disease or heart failure (according to NYHA criteria), pre-existing nephropathies/ glomerulonephritis, known vasculitides and/or collagenoses (e.g. systemic lupus erythematosus), and use of any type of lipid-lowering agents were excluded. These exclusion criteria were chosen because these conditions lead to pregnancy-independent organ damage and an increased risk of CVD. We also excluded fetal chromosomal abnormalities or genetic defects associated with fetal growth restriction, and patients with suspected major fetal structural defects (e.g., heart failure), which can lead to fetal ascites and hydrops fetalis and are therefore associated with maternal mirror syndrome. Women who reported smoking during or before pregnancy were also excluded from the study, irrespectively of the duration of their smoking history [17, 18] as smoking has been demonstrated to be associated with localized reductions in retinal and macular nerve fibre layer thickness. Furthermore, as changes in retinal microvasculature are described for neuro- and musculodegenerative diseases [19], women with such diseases were also excluded from the analysis. In addition, women with pronounced hyperopia or myopia of more than 6 dioptres, laser refractive surgery treatment, or eye disease (e.g. retinal degenerative changes, glaucoma) were excluded.\u003c/p\u003e\n\u003cp\u003eData acquisition: All maternal and pregnancy-related data were collected prospectively. During the study, participants were phenotyped using a very detailed family and medical history, including information on previous pregnancies, the current pregnancy, current medication history, ethnicity, gestational age and week of pregnancy, results of the 50 gram screening test for GDM and, if abnormal, the results of the 75 gram oral glucose tolerance test [4], and body mass index (BMI) before pregnancy, at the time of measurement and at delivery.\u003c/p\u003e\n\u003cp\u003eAll patients had two standardized blood pressure measurements taken at each visit after a five-minute rest [20],\u0026nbsp;with the first measurement discarded and only the second measurement included in the analysis\u0026nbsp;[21\u0026ndash;23].\u0026nbsp;In addition, we documented the mode of delivery, the reason for the cesarean section, the time of active pushing during vaginal deliveries, and the neonatal outcome (pH, 5-minute APGAR score).\u003c/p\u003e\n\u003cp\u003eOptical coherence tomography (OCT) was obtained for the right eye at each visit. Participation in the study was possible as early as the first trimester. Follow-up measurements were taken at least once in each subsequent trimester. Thus, longitudinal analysis of the cpRNFLT was possible.\u003c/p\u003e\n\u003cp\u003eWomen who were enrolled early in pregnancy as healthy pregnant women and were subsequently diagnosed with a pregnancy-related complication named above switched cohorts. Consequently, longitudinal measurements are available for pregnant women who underwent cpRNFLT examinations in the first and second trimesters prior to a GDM diagnosis.\u003c/p\u003e\n\u003cp\u003eThe first trimester was defined as gestational age up to 13.6 weeks of gestation (wog), the second trimester between 14.0 and 27.6 wog and the third trimester from 28.0 to 42.0 wog.\u003c/p\u003e\n\u003ch2\u003eCircumpapillary retinal nerve fiber layer thickness (cpRNFLT)\u003c/h2\u003e\n\u003cp\u003eOphthalmological imaging via spectral domain optical coherence tomography provides cpRNFLT by imaging of a circular B-scan of the retinal nerve fibre layer around the optic nerve head with 768 A-scans on a circle with 3.4 mm (Figure S1) [18, 24]. When RNFL thickness is divided into 4 quadrants, the variability increases due to the averaging within the large sectors. Smaller sectors are better at capturing focal or localized changes. The variability for average RNFL thickness is around 4.5 to 5 \u0026micro;m but increases for quadrants (about 8 \u0026micro;m) and even smaller slices (about 12 \u0026micro;m), meaning larger sectors mask subtle changes [25]. The shape and anatomy of the optic disc cause natural differences in thickness between quadrants. Some sectors, such as the nasal and temporal quadrants, show less reliability and more inconsistency in repeated measurements due to the RNFL being thinner or more complex in these areas [26]. The 768-point measurement profile provides a high-resolution map of cpRNFLT around the optic disc, better capturing spatial RNFL variations. This detailed data supports more precise quantification and improved reproducibility [27]. Furthermore, the use of 768- A-scan data aligns with analysis techniques such as neural networks or statistical software vetted for progression detection, which rely on high-resolution input rather than broad averages.\u003c/p\u003e\n\u003cp\u003eFor this study analysis, the 768 A-scan locations of the circular scan were analyzed. Circular B-scan was obtained by averaging 100 single B-scan to provide a very precise measurement quality. The location of the cpRNFLT circle and the coordinate system have been described previously\u0026nbsp;[28]. Furthermore, the global mean and the six standard sectors: T temporal (315\u0026deg; to 45\u0026deg;), TS temporal-superior (45\u0026deg;-90\u0026deg;), TI temporal-inferior (90\u0026deg;-135\u0026deg;), N nasal (135\u0026deg;-225\u0026deg;), NS nasal-superior (225\u0026deg;-270\u0026deg;), and NI nasal-inferior (270\u0026deg;-315\u0026deg;) were analyzed [13, 15, 18].\u003c/p\u003e\n\u003cp\u003eFor the ophthalmological imaging only the right eye of all participants was measured, since studies have shown that changes during pregnancy will affect both eyes simultaneously [24]. Additionally, it had been shown that RNFLT changes are related to race as well as age differences [24, 29, 30]. For that reason, we aimed to target a narrow age difference between the participants.\u003c/p\u003e\n\u003cp\u003eMeasurements that did not meet the following quality criteria were excluded: (1) B-scan number per location \u0026lt; 50, (2) signal to noise ratio \u0026lt; 20 dB, and (3) missing or unreliable RNFLT A-scans \u0026gt; 5% (excluded N = 4).\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eIn brief, all statistical analyses were carried out in the R environment using version 4.0 (R Foundation for Statistical Computing, Vienna, Austria). ANOVA and unpaired student t-test were used for group-wise comparisons of continuous and categorical data, respectively. cpRNFLT was adjusted for maternal age and refraction. The pre-conceptional BMI value was not utilized for adjustment, as it demonstrated no significant influence on cpRNFLT in correlation analysis. All studies used a two-sided p-value of \u0026lt; .05 to indicate statistical significance.\u003c/p\u003e\n\u003cp\u003eGroup analysis was carried out by independent t-test group analysis. Here measurements in GDM pregnancies were compared to healthy pregnancy data for the first half the third trimester in order to present the effect of GDM. Furthermore, differences for dGDM and iGDM as well as pre-conceptional diabetes mellitus (T1D and T2D) were presented for the same investigation time point.\u003c/p\u003e\n\u003cp\u003eAn Euclidean nested case-control matching procedure was applied on our dataset in order to pair the patients with GDM to the healthy pregnant controls (HPC). For the matching procedure only women of Caucasian ethnicity were considered because significant differences in cpRNFLT were observed among different ethnic groups (results not presented here). The matching variables included maternal age, focus/ refraction, gestational age, systolic and diastolic blood pressure as well as the BMI at time of measurement (Model 1). Despite the exclusion of women with hypertensive pregnancy disorders from the present analysis, blood pressure differences of up to 8 mmHg were observed between the HPC and iGDM patient subgroups within the normal blood pressure range. In patients without specific cardiovascular disease, an increase in the inter-arm systolic blood pressure difference (SBPD) of 5 mm has been shown to result in a 12% increase in the risk of vascular events [31]. Consequently, blood pressure was a factor taken into account. All variables were Z-transformed. For missing values, the median of the variable for the respective group was imputed.\u003c/p\u003e\n\u003cp\u003eWithin each gestational age category, the matching was performed iteratively in the following way: For each unmatched GDM patient, a matching score, defined as the sum of Euclidean distances across all matching variables, was calculated against all available healthy controls. The HPC participant with the lowest score was then selected as a match for the GDM woman. Each healthy control could be matched only once (Figure 1). Only pairs with a matching score \u0026le; 2 were retained to ensure high similarity between cases and controls.\u003c/p\u003e\n\u003cp\u003eAs women with iGDM had a significantly higher mean BMI (30.17 vs. 26.99 kg/m\u0026sup2;) before pregnancy than women with dGDM, but gained less weight during pregnancy, we created a second Euclidean nested case-control model (Model 2) that included weight gain as an additional variable to Model 1. This methodological approach indirectly considered the pre-conceptional biometric baseline of pregnant women, calculated as the difference between their weight at the beginning of pregnancy and the respective measurement point, in addition to their BMI at the time of measurement. Weight gain was included in Model 2 on the assumption that all clinically relevant parameters, which influence the metabolic situation would be considered, and changes in cpRNFLT then could be attributed solely to the diabetic metabolic status of the pregnant woman.\u003c/p\u003e\n\u003ch2\u003eEthics\u003c/h2\u003e\n\u003cp\u003eMeasurements were performed under the umbrella of the PAPYRUS study, which aims to predict the individual cardiovascular risk after (i) hypertensive pregnancy disorders or (ii) GDM by measuring retinal layer thicknesses and microvasculature (German Clinical Trial Register number: DRKS00032530). Written informed consent was obtained from all participants. Research related to human use complied with all relevant national regulations, institutional policies and in accordance the tenets of the Helsinki Declaration, and has been approved by the authors\u0026rsquo; institutional review board (IRB00001750, 052/23-ek).\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eBaseline characteristics of the current study population\u003c/h2\u003e\n\u003cp\u003eIn total, a sample of 591 right eyes from 591 women were selected for the present analysis, in accordance with the criteria outlined in the Methods section. \u0026nbsp; The composition of the study cohort, after consideration given to the exclusion criteria, is illustrated in Figure 2. The baseline characteristics of the entire cohort, as well as characteristics for women stratified according to glucose tolerance status (healthy pregnant women versus GDM versus pre-conceptional diabetes), are displayed in Table 1.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"953\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"3\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy pregnant women\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"3\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePregnant women with GDM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"3\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePregnant women with T1D or T2D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-values\u0026nbsp;\u003c/strong\u003e(Ref. Healthy) GDM/Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMaternal age at conception [years]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e33.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u0026nbsp;\u003c/strong\u003e/ 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;European/ Caucasian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e426 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e71 (73.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e7 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e18 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e8 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e11 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Arabs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e18 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e17 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e9 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.40 / 0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eBMI before pregnancy [kg/m2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e33.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001 / 0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eValue socio-economic status (SES)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.37 /\u003cstrong\u003e\u0026nbsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eNumber of measurements 1st trimester [N]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMaternal age at measurement\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eGestational age 1st trimester [weeks.days]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eSystolic blood pressure 1nd trimester [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e116.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDiastolic blood pressure 1nd trimester [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e73.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAspirin intake\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eNumber of measurements 2nd trimester [N]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMaternal age at measurement\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e32.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e35.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.29 / 0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eGestational age 2nd trimester [weeks+days]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.99 / 0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eSystolic blood pressure 2nd trimester [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e114.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e114.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e118.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.97 / 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDiastolic blood pressure 2nd trimester [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e70.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e76.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e70.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.10 / 0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eBMI 2nd trimester [kg/m\u003csup\u003e2\u003c/sup\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.07 / 0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAspirin intake\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e11 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eNumber of pregnant women 3rd trimester [N]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMaternal age at measurement\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e / 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eGestational age 3rd trimester [weeks.days]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e35.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e34.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.21 / 0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eSystolic blood pressure 3rd trimester [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e116.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e116.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e129.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.89 / \u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDiastolic blood pressure 3rd trimester [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e73.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e73.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e80.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.77 / \u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eBMI 3rd trimester [kg/m2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e31.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e37.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001 / 0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAspirin intake\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e16 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e4 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eGestational age at delivery [weeks.days]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e39.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e39.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e38.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.23 / 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eBMI gain during pregnancy [kg/m\u003csup\u003e2\u003c/sup\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e / 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDelivery Mode\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Vaginal birth\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e233 (64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e60 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e4 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Vacuumextraction or Forceps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e34 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;C-section (electiv and secondary)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e92 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e27 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\n \u003cp\u003e6 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eBirth weigt [g]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3417.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e503.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3518.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e492.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3691.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e513.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.07 / 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eGrowth percentile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e48.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e56.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e69.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008 / 0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eSystolic blood pressure 48-96h postpartum [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e118.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e118.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e126.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.94 / \u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDiastolic blood pressure 48-96h postpartum [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e72.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 46px;\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e72.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e83.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 45px;\"\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.53 / \u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Presentation of the composition of the study group of healthy pregnant women, women with GDM, and pregnant women with pre-conceptional diabetes mellitus (T1D or T2D).\u003c/strong\u003e The significance of demographic differences between the cohorts was determined through the implementation of a t-test for independent samples, with the healthy pregnant women cohort serving as the reference in each instance. Significant differences are highlighted in bold. With regard to maternal age, parity, and socioeconomic status, the GDM and HPC groups exhibited comparable characteristics, although the mean age at conception of the GDM group was approximately one year higher (p=0.01). Pregnant women with GDM as well as pre-conceptional T1D and T2D had significantly higher BMI values at the start of pregnancy. In all subgroups, the majority of subjects were women of Caucasian origin. Women of Arab origin, specifically from Western Asia and North Africa, constituted the second large ethic group of our study. Based on the consecutive enrollment into the study cohort, no women measured in the first trimester developed GDM during their course of pregnancy. Consequently, group comparisons in the first trimester are omitted below.\u003c/p\u003e\n\u003cp\u003eThe majority of measurements were obtained during the third trimester. All groups were comparable in the second and third trimesters, with regard to gestational age at the time of cpRNFLT measurement. In the third trimester and 48\u0026ndash;96 hours postpartum, subjects in the diabetes cohort (T1D and T2D) exhibited significantly elevated systolic and diastolic blood pressure values in comparison to the HPC, although these values remained, on average, within the normotensive range. The distribution of delivery modes within the HPC group corresponded exactly to the annual distribution of delivery modes at Leipzig University Hospital, a perinatal center with the highest level of care. A higher frequency of caesarean sections was observed in women in the T1D and T2D groups, with a rate more than twice that of the HPC group.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003eLongitudinal changes in cpRNFLT during the physiological course of pregnancy\u003c/h2\u003e\n\u003cp\u003eCollecting circumpapillary data ensures that measurement geometry matches the biology of the visual system. All retinal ganglion cell axons converge toward the optic nerve head and must pass through the circumpapillary region before exiting the eye. Sampling this annular zone therefore captures a complete cross-section of the output of the retina\u0026mdash;effectively a census of all fibres transmitting visual information to the brain. Few biological systems offer such a naturally constrained bottleneck that can be interrogated non-invasively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe comparison between non-pregnant healthy controls (singleton measurement) and HPC is illustrated in Figures 3A-E. The cpRNFLT is displayed by A-scan resolution obtained for the circular B-scan around the optic nerve head, with the analysis adjusted for individual refraction values and maternal age. In the first trimester, HPC differed from healthy, non-pregnant controls at only 0.9% of examined A-scan locations. This significance was determined by a thinning of up to 10 \u0026micro;m in the N sector. As gestational age increased, the trend of thinning in the N sector decreased in both width and extent. In the second trimester, with the exception of the N sector, HPC showed thickening of the cpRNFLT especially in the superior and inferior sectors by up to 10 \u0026micro;m. There was significant thickening in 7% of examined retinal locations compared to non-pregnant women. This thickening trend persisted until 34 weeks of gestation (maximum difference approximately 12 \u0026micro;m, significant change in 5.2% of A-scan locations). Toward the end of pregnancy, no clear trend or significantly areas between groups could be identified (Figure 3E).\u003c/p\u003e\n\u003cp\u003eAs illustrated in Table 2, a comparison has been made of the mean values in \u0026micro;m for the first named cohort minus the second named cohort, respectively. In addition, the results of the t-tests conducted on these data are also presented. Note that Table 2 presents six arbitrary sectors that are not anatomically related to the foveal structure \u0026nbsp;[32], and compares the average difference values across an entire sector. In contrast, Figures 3A-E and 4 analyse 768 individual A-scans spanning 360 degrees. Thus, significant differences between depicted groups are lost due to averaging in the table. However, such averaged data is provided to enable comparability with former studies.\u003c/p\u003e\n\u003cp\u003eA subgroup analysis compares healthy Caucasian singleton pregnancies (n = 361) to healthy Caucasian twin pregnancies (n = 29) in the third trimester. Although no statistically significant difference in retinal location was observed, possibly due to the small number of cases, twin pregnancies showed cpRNFLT thickening of approximately 12 \u0026micro;m between 240\u0026deg; and 280\u0026deg; in the NI sector compared to singleton pregnancies (Figure S2). This thickening was more pronounced than that observed for the HPC pregnancies compared to non-pregnant control subjects (Figure 3).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"952\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ecomparison groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003esector\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"10\" style=\"width: 680px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestational age\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003euntil 13.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.0 - 27.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.0 - 33.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e34.0 - 42.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.0 - 42.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emean diff.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emean diff.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emean diff.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emean diff.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emean diff.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSingelton: HPC versus non-pregnant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTwin: HPC (N=29) versus non-pregnant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"8\" rowspan=\"7\" style=\"width: 544px;\"\u003e\n \u003cp\u003enot available due to small case numbers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDM versus HPC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"7\" style=\"width: 136px;\"\u003e\n \u003cp\u003enot available\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-6.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e3.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e12.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eiGDM versus dGDM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean cpRNFLT G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"8\" rowspan=\"7\" style=\"width: 544px;\"\u003e\n \u003cp\u003enot available due to small case numbers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-8.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epre-conceptional diabetes (N= 11) versus HPC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean cpRNFLT G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"8\" rowspan=\"7\" style=\"width: 544px;\"\u003e\n \u003cp\u003enot available due to small case numbers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-8.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-8.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-18.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT TI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-12.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 144px;\"\u003e\n \u003cp\u003emean RNFLT NI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 79px;\"\u003e\n \u003cp\u003e-7.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Group comparisons of mean sector analyses.\u0026nbsp;\u003c/strong\u003eThe group comparison of the mean difference (cpRNFLT of the first named \u0026nbsp;cohort minus the second named cohort), as well as the respective p-values, are presented average of different optic nerve head sectors (G, global (mean overall); N, nasal sector; NI, nasal-inferior sector; NS, nasal-superior sector; T, temporal sector; TI, temporal-inferior sector; TS, temporal-superior sector)in the first (HPC: N= 40), second (HPC: N = 161; GDM: N = 10) and third (28.0\u0026ndash;33.6 weeks of gestation HPC: N = 91; GDM: N = 24; 34.0\u0026ndash;42.0 weeks of gestation HPC: N = 361; GDM: N = 91) trimesters. For the total third trimester (28.0\u0026ndash;42.0 wog), the following case numbers were obtained: HPC: N = 361; twin healthy: N = 29; GDM: N = 91; dGDM: N = 57; iGDM: N = 34; T1D and T2D: N = 11. A total of 76 non-pregnant, healthy controls were included in the analysis. Furthermore, the results of the initial measurements of a subject in the third trimester were presented, with the objective of preventing the repetition of measurements on the same woman within a single trimester. Due to the limited number of cases within the subgroups of women with insulin-dependent GDM (iGDM) and diet-managed GDM (dGDM) as well as T1D and T2D, the subdivision of the third trimester and the analysis in the second trimester were omitted.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003eLongitudinal changes in cpRNFLT due to GDM\u003c/h2\u003e\n\u003cp\u003eIn comparison with HPC, pregnant women with GDM demonstrated an increased thickening trend of cpRNFL in the third trimester, with the exception of a significant thinning of an average of 8 \u0026micro;m between 300 and 335\u0026deg; in the T and TI sectors\u003cem\u003e\u0026nbsp;\u003c/em\u003e(Figure 5B). A comparative analysis of pregnant women with GDM and HPC revealed 9.9% of measured A-scan locations across groups. It is noteworthy that this pattern (statistically significant thickening of the NI and in the TI sectors up to 300\u0026deg; as well as the thinning of cpRNFLT between 305-345\u0026deg;) manifested in trend as early as the second trimester (at an average of 21.1 weeks of gestation), for women who were diagnosed with GDM between 24 and 28 weeks of gestation. Note that, statistically significant thickening of cpRNFLT in the TI region evident in this group was combined with a thinning in the NS area (Figure 5A). Average sector data supported this, whereby the TI and NI sectors showed significant thickening of 18 \u0026micro;m and 13 \u0026micro;m, respectively, for GDM compared to the HPC (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the third trimester the analysis was additionally carried out separated for GDM management in dGDM and iGDM. This highlighted a specific pattern of cpRNFLT in the third trimester, especially in women whose GDM was managed with diet. Statistically significant thinning of 12 \u0026micro;m was observed in the TI region between 300\u0026deg; and 340\u0026deg;, accompanied by significant thickening of approximately 10 \u0026micro;m at 220\u0026deg; and 240\u0026deg; in the N and NI sectors (Figure 5C). For dGDM 17.6% of measured A-scan locations differed significantly from those in the HPC group.\u003c/p\u003e\n\u003cp\u003eIn pregnant women with GDM who required insulin treatment during the latter stages of pregnancy, the pattern observed for dGDM was no longer detectable in the third trimester (Figure 5D). In these iGDM women, a depicted 12 \u0026micro;m thickening in the axon-rich superior sectors remained only a trend due to the sample size. Other regions presented no differences in cpRNFLT compared to the overall HPC cohort.\u003c/p\u003e\n\u003ch2\u003eDifferences in cpRNFLT in pre-conceptional diabetes mellitus (T1D and T2D)\u003c/h2\u003e\n\u003cp\u003eWhen combining T1D and T2D diabetics to form the cohort with pre-conceptional diabetes, a consistent thinning of cpRNFLT was observed compared to HPC. The most statistically and clinically significant thinning was observed at the -30 \u0026micro;m TS level (Fig. 5E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll subgroup analyses for gestational diabetes (dGDM, iGDM, pre-conceptional versus HPC) were repeated for singleton versus twin pregnancies in the third trimester (HPC twin n = 29; dGDM twin n = 4; iGDM twin n = 0; T1D twin n = 0; T2D twin n = 0) (Figure S3). Despite the fact that only 0.8% of retinal locations differ significantly (e.g. due to the limited number of cases), the thickening between 225\u0026deg; and 300\u0026deg; and the thinning between 300\u0026deg; and 350\u0026deg; in the TI sector, as demonstrated for the dGDM cohort of singleton pregnancies (Fig. 5C), were even more pronounced in twins with GDM (Figure S3).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEuclidean Nested Case-Control Matching\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ndash; Model 1\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAn Euclidean nested case-control comparison of Caucasian HPC versus matched Caucasian GDM pregnant women (n = 69) at the 768 individual A-scan measurement locations on the peripapillary circle scan was carried out according to the matching criteria described above, found no difference of cpRNFLT between both groups. When treatment method (dietary versus insulin-dependent) was added to the model, women with dGDM (n = 44) showed significant thinner values in the TI sector between 295 and 315\u0026deg; compared to the respective HPC (Fig. 6iI-ii). In contrast, women with iGDM (n = 24) exhibited a tendency towards thickening across the entire cpRNFLT, reaching significance in the TS sector (57-78\u0026deg;) with an increase of 13 \u0026micro;m as well as between 130-137\u0026deg; with up to 20 \u0026micro;m (Fig. 6Bi-ii). These results essentially correspond to the changes that were found for the entire group comparison shown for the cohort in the third trimester (Fig. 5B). However, the Euclidean nested case-control model also revealed interesting new results, particularly in the iGDM cohort, through targeted case-control matching.\u003c/p\u003e\n\u003cp\u003eFurther differentiation of these overall group results into pregnancy trimesters within the nested case-control pairs revealed a significant difference for global cpRNFLT in the third trimester between iGDM and HPC (n = 23; p = 0.01). No significant difference in global cpRNFLT was found for dGDM vs. HPC in either the second trimester (n = 4; p = 0.76) or the third trimester (n = 40; p = 0.47). Figure 7A-B showed the variation of difference in cpRNFLT between dGDM, respectively iGDM, versus HPC at 768 A-scan locations on the circular B-Scan for comparisons by gestational age. During the third trimester, women with iGDM typically exhibited a tendency toward thickening of the cpRNFLT. This trend increased with gestational age, and corresponds to prolongated duration of insulin therapy. The increase in cpRNFLT thickness was most pronounced with 22 \u0026micro;m in the axon bundle- and vascular density-rich TS sector. In contrast, women with dGDM experienced significant thinning of the cpRNFLT compared to matched HPC pairs in the third trimester, as illustrated in Fig. 5C, with a decrease of up to 20 \u0026micro;m in the TI sector.\u003c/p\u003e\n\u003ch2\u003eEuclidean Nested Case-Control Matching \u0026ndash; Model 2 (incl. weight gain)\u003c/h2\u003e\n\u003cp\u003eThe matching procedure including weight gain for Model 2 resulted in a more balanced mean weight gain between compared groups, as expected (Model 2 iGDM vs. HPC 10.52 kg vs. 10.76 kg whereas Model 1 was 11.08 kg vs. 13.38 kg; Model 2 dGDM vs. HPC 10.14 kg vs. 9.98 kg, whereas Model 1 was 10.14 kg vs. 11.48 kg). The incorporation of weight gain as the seventh matching variable resulted in the establishment of new matching pairs, which led to an increase in variance of the cpRNFLT in the HPC cohort. Furthermore, the algorithm revealed that no suitable partners could be identified for three GDM women, resulting in a final analysis sample of 65 matched pairs.\u003c/p\u003e\n\u003cp\u003eHere, the results showed no significant difference in global cpRNFLT between dGDM and HPC in either the second (n = 4; p = 0.79) or third (n = 40; p = 0.57) trimesters. Contrary to Model 1, there now was no significant difference in global cpRNFLT between iGDM (n = 21) and HPC in the third trimester (p = 0.97) and women with dGDM presented significantly thicker values in the NI sector between 220\u0026deg; and 255\u0026deg; compared to the respective HPC. In Model 2, in contrast to Model 1, women with iGDM showed significant thinning in the same sector (Fig. S5A-B). Additionally, the significant thickening of 23 \u0026micro;m for cpRNFLT of iGDM women in the TS sector shown in Model 1 could still be demonstrated. Figures S4Ai-ii (dGDM) and Bi-ii (iGDM) demonstrate the differences in cpRNFLT three dimensional and from a circumpapillary, bird\u0026apos;s-eye perspective. Because Model 1 and 2 match women for gestational age, the results are not presented by weeks of gestation. An analysis of Euclidean nested case-control matching between HPC and women with T1D or T2D was not performed due to the very small number of cases.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe retinal nerve fibre layer, made up of retinal ganglion cell axons is the only accessible structure of the central nervous system, as axons converge at the optic disc. Axonal damage is visible here and reflects neuroprotection and neurodegeneration [33].\u003c/p\u003e\n\u003cp\u003eThis prospective study was the first to define longitudinal changes in cpRNFLT by means of a 768 single A-scan analysis on a circular B-scan around the optic disc in a well-phenotyped, predominantly Caucasian, healthy pregnant cohort. Moreover, to the best of our knowledge, this is the first study to longitudinally map changes in GDM and pre-conceptional diabetes mellitus for cpRNFLT. We demonstrate that patterns of change in cpRNFLT in women with GDM are already detectable in the early second trimester, even before diagnosis of GDM by oral glucose tolerance test. Furthermore, we show that different treatment strategies for GDM lead to different patterns of change in cpRNFLT.\u003c/p\u003e\n\u003cp\u003ePreviously the study by Wu et al. is the only documented research on cpRNFLT measurements in healthy pregnant women in cross sectional analyses for all three trimesters, involving 45 women per trimester. This Chinese cohort of 135 women exhibited thickening in the NS and NI sectors with advancing gestational age [33]. Our study followed a group of HPC and GDM overtime. This enables detection of longitudinal effects on cpRNFLT not detectable from cross-sectional data. First, for HPC, predominantly Caucasians, our study revealed a comparable trend to Wu et al. for sectoral data, as Wu et al. did not present A-scan level findings. \u0026nbsp; However, commencing from 34 weeks of gestation, our measurements commenced a decline towards non-pregnant values. As demonstrated in the study by Wu et al., the third trimester measurements, which they obtained at an average of 31.1 weeks of gestation [33], did not capture the subsequent decrease in thickness we found.\u003c/p\u003e\n\u003cp\u003eChanges to the RNFL during pregnancy are caused multifactorial by blood volume changes, hormones, eye biomechanics and general systemic status [34\u0026ndash;36]. This results in fluid retention due to activation of the RAAS, changes to blood volume and hormones and mechanical factors [37]. Such pregnancy related changes may enhance ocular perfusion in some regions, contributing to localized thickening of the RNFL, particularly in superior and inferior sectors where nerve fibre bundles are densest and metabolically more active [33]. Additionally, the peripapillary retina receives blood supply from both the central retinal artery and short posterior ciliary arteries, leading to uneven flow rates across different quadrants and causing asymmetric fluid accumulation [33]. Progesterone and estrogen further amplify these effects by modulating vascular tone and fluid dynamics [38]. The retina is able to locally absorb more fluid. Increased capillary hydrostatic pressure leads to accumulation of fluid, which in turn results in thickening of the RNFLT, which can be characterized as mild oedema [35]. Twin pregnancies result in more significant maternal cardiovascular changes, with increased plasma volume and total body water, leading to greater fluid shifts compared to singleton pregnancies [39]. Due to larger structural volumes and denser peripapillary capillary networks in the inferior sectors of cpRNFLT (inferior \u0026ge; superior \u0026ge; nasal \u0026ge; temporal), additional interstitial fluid results in more measurable thickness changes in these areas [34]. These amplified physiological changes likely explain the more pronounced thickening observed in the NI sector (240\u0026ndash;280\u0026deg;) in twin pregnancies compared to singleton pregnancies. Conversely, the relative thinning observed in healthy twin pregnancies in the TS and NS sectors may be indicative of differential vascular responsiveness, venous outflow patterns, or reduced adaptive reserves in response to increased systemic demand.\u003c/p\u003e\n\u003cp\u003eIn certain regions, autoregulatory mechanisms may mitigate hyperperfusion, resulting in relative thinning of the peripapillary architecture during pregnancy [36]. Additionally, the temporal cpRNFL, which is naturally thinner due to fewer nerve fiber bundles, may be more susceptible to changes from pregnancy-related metabolic stress, exhibiting detectable reductions in thickness. Later stages of pregnancy were shown to cause a decrease in systemic vascular resistance, potentially normalizing or slightly reducing thickness [40], as shown in our results.\u003c/p\u003e\n\u003cp\u003ePrevious data on cpRNFLT for GDM exist only for a small cross-sectional sample in the third trimester. Here Sasikumar presented cpRNFLT subdivided into four sectors and demonstrated significant thinning of the superior, nasal, and inferior quadrants for the 32nd week of pregnancy compared to healthy pregnant women. Those authors found no link between HbA1c levels and cpRNFLT in GDM, concluding that GDM patients with poor blood sugar control may experience neurodegeneration even in the absence of microvascular changes seen in insulin-dependent diabetes [14]. Acmaz et al. divided the OCT circular scan into six sectors and showed significant thinning of the TI region for GDM eyes compared to healthy pregnant women. However, the exact measurement time is not provided in their paper (\u0026gt;24 wog) [13]. Our current study shows, that for GDM a large part of the TI sector thickens (270-300\u0026deg;) with clinical and statistical significance in the second trimester. Furthermore, in the third trimester of our sample, the thinning for GDM that emanates from the T sector also shifts noticeably to the TI sector (from 300-315\u0026deg;). Tengku-Fatishah et al. compared four quadrants of 78 women with GDM versus 72 HPC, measured on average between the 28th and 32nd wog. Women with GDM had an average global RNFLT that was 2.56 \u0026micro;m thinner [15]. In our cohort, the global difference was a thinning of 2.22 \u0026micro;m for GDM eyes. In Acmaz et al., this was 2.52 \u0026micro;m [13] when gestational age was ignored, making the results comparable across all three cohorts. However, due to the division into averaged quadrants or sectors in other studies, and the partial lack of information on the mean gestational age at the time of measurement, it was not possible to provide a more detailed context for the averaged sector data shown for our study (Table 2).\u003c/p\u003e\n\u003cp\u003eInsulin sensitivity decreases progressively during pregnancy, especially in the second and third trimesters, necessitating increased insulin production to maintain glucose homeostasis for both mother and fetus [41, 42]. Impaired insulin sensitivity and dysregulated glucose metabolism cause RNFL thinning through a combination of neuronal cell damage, metabolic stress and vascular dysfunction, and RNFL thickness is therefore a useful biomarker for metabolic retinal neurodegeneration in diabetes and related conditions [43\u0026ndash;45]. Women with GDM who require insulin typically have a more severe form of glucose intolerance than women whose GDM is managed by diet alone. Hyperglycaemia triggers oxidative stress, resulting in the up-regulation of vascular endothelial growth factor (VEGF) and other vasoactive mediators. This leads to endothelial dysfunction, increased vascular permeability and the breakdown of the inner blood-retinal barrier [46, 47]. The resulting axonal and glial oedema leads to an increase in tissue water content and \u0026apos;thickening\u0026apos; of the cpRNFLT [48], particularly in the superior sectors, where the density of axon bundles is higher and perfusion vulnerability is greater [34, 49\u0026ndash;51]. In addition, insulin therapy itself may promote fluid retention [47]. By contrast, women with dGDM are likely to experience milder degrees of metabolic stress. Consequently, the dominant process may shift more quickly towards neurodegenerative axonal loss, which manifests as thinning of the RNFL. The TI sector is particularly vulnerable to damage and exhibits sectoral predilections in neurodegeneration and axonal loss [52\u0026ndash;54]. These pathomechanisms may explain the different patterns of cpRNFLT between iGDM and dGDM pregnant women and suggest that the RNFLT responds more sensitively and rapidly to fluctuations in glucose metabolism than previously hypothesized. Our data showed unprecedented data for both group comparison and additionally in the detailed Euclidean nested case control investigation for a subpopulation of matched GDM and HPC pairs.\u003c/p\u003e\n\u003cp\u003eNo previous study directly measured (gestational) weight gain and its association with cpRNFLT. We were able to investigate this further aspect and offer direct comparison, as both models showed that women with iGDM exhibited a significant 20 \u0026micro;m increase in cpRNFLT thickness in the axon bundle-rich and high vascular sector TS with increasing gestational age, and consequently, longer duration of insulin therapy. Furthermore, both models demonstrated significant thickening in TI sector between 270\u0026deg; and 300\u0026deg; until the end of pregnancy for the dGDM group. This thickening at 270-300\u0026deg; was already evident in the second trimester, specifically at 22 weeks of gestation. Interestingly, we highlight that none of the women were undergoing insulin therapy at that time. It is hypothesized that the differing behavior of cpRNFLT within the TI sector (thickening up to approximately 300\u0026deg; followed by a thinning of approximately 20 \u0026micro;m) depends on anatomical architecture. Axonal-vascular bundles appear to run between 270\u0026deg; and 300\u0026deg;, resulting in thickening in these areas due to the disrupted metabolic environment. From approximately 300\u0026deg; and further towards the temporal region, the density of these filaments decreases [40]. These fibres in turn exhibit detectable reductions in thickness in response to pregnancy-related metabolic stress.\u003c/p\u003e\n\u003cp\u003eAn increasing discussion point is provided by the fact that our study was able to measure eyes from pre-conceptional diabetes mellitus (T1D and T2D) pregnancies. The increasing insulin resistance that occurs during pregnancy, in conjunction with the thinning of the RNFLT shown previously for T2D [45], could provide a rationale for the observation that women with pre-conceptional diabetes exhibit a significantly thinner cpRNFLT during pregnancy in comparison to non-pregnant patients with T2D. Since both T1D and T2D subjects showed the same trend of thinning of cpRNFLT compared to HPC, grouping these subjects together as a preconception diabetes group is understandable. Previous greater thinning was observed in cases of poor metabolic control and in individuals with a longer duration of diabetic disease [55, 56].\u0026nbsp;Early cpRNFL thinning has been identified as a significant biomarker for diabetic retinal neurodegeneration prior to the manifestation of overt vascular retinopathy\u0026nbsp;[57]. In their meta-analysis of 465 diabetics and 389 healthy subjects, Chen et al. report a mean thinning of 2.88 \u0026micro;m in global cpRNFLT in non-pregnant diabetics\u0026nbsp;[57]. In our pregnant cohort, a trend toward thinning for pre-conceptional diabetic pregnancies was observed across the entire cpRNFL, with the most extreme differences being found in the TS sector, with up to 30 \u0026micro;m thinning compared to the HPC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to the well-phenotyped cohort and the longitudinal design, the key advantage of our study over all other published work to date is that the current cpRNFLT analysis was not based on globally averaged sectors, respectively quadrants. Furthermore, it is highly valuable that results are presented for the first time for women with GDM prior to diagnosis (our presented sample received GDM diagnosis approximately five weeks later, i.e. at approximately 21.1 weeks of gestation).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnfortunately, it was not possible to conduct longitudinal follow-ups with all women recruited in the first trimester during the second and third trimesters. Nevertheless, no other data set exists in the literature presenting case numbers as high as the current study. Moreover, recruitment for the study is ongoing, so higher case numbers can be expected in future publications. A second limitation of our study is the small number of cases in the pre-conception diabetes group (T1D and T2D).\u003c/p\u003e\n\u003cp\u003eIn summary, the divergent treatment approaches (dGDM and iGDM) and the extreme thinning of cpRNFLT in women with pre-conceptional diabetes, far exceeding the described thinning in non-pregnant diabetics, suggest that pregnancy and impaired glucose tolerance metabolism affect the RNFL much more severely and sensitively than previously assumed. Further studies are required to ascertain whether these specific patterns associated with impaired glucose tolerance and pregnancy can be observed postpartum. In addition, it should be examined whether the persistence of specific patterns can be used to identify women who will develop manifest glucose tolerance disorders as a result of GDM, and how this correlates with other cardiovascular risk factors.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ecpRNFLT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;circumpapillary retinal nerve fibre layer thickness\u003c/p\u003e\n\u003cp\u003edGDM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;gestational diabetes mellitus treated with diet\u003c/p\u003e\n\u003cp\u003eHPC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;healthy pregnant controls\u003c/p\u003e\n\u003cp\u003eiGDM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;gestational diabetes mellitus treated with insulin\u003c/p\u003e\n\u003cp\u003eN \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;nasal sector (135\u0026deg; to 225\u0026deg;)\u003c/p\u003e\n\u003cp\u003eNI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;nasal-inferior sector (270\u0026deg; to 315\u0026deg;)\u003c/p\u003e\n\u003cp\u003eNS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;nasal-superior sector (225\u0026deg; to 270\u0026deg;)\u003c/p\u003e\n\u003cp\u003eOCT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;optical coherence tomography\u003c/p\u003e\n\u003cp\u003eRNFL\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;retinal nerve fibre layer\u003c/p\u003e\n\u003cp\u003eT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;temporal sector (315\u0026deg; to 45\u0026deg;)\u003c/p\u003e\n\u003cp\u003eT1D\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;diabetes mellitus typ 1\u003c/p\u003e\n\u003cp\u003eT2D\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;diabetes mellitus typ 2\u003c/p\u003e\n\u003cp\u003eTI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;temporal-inferior sector (90\u0026deg; to 135\u0026deg;)\u003c/p\u003e\n\u003cp\u003eTS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;temporal-superior sector (45\u0026deg; to 90\u0026deg;)\u003c/p\u003e\n\u003cp\u003ewog \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; week of gestation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG); project number 493646873 \u0026ndash; MD-LEICS. FG Rauscher was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG); project number 497989466.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest.\u003c/p\u003e\n\u003cp\u003eAuthor\u0026rsquo;s contributions\u003c/p\u003e\n\u003cp\u003eA.D.S. is the guarantor of this work. A.D.S., F.G.R and H.S. designed the study. A.D.S. and A.S. performed the measurements and acquisition of data. T.E., F.G.R., A.D.S. and G.R. performed data analysis and interpretation. A.D.S and F.G.R. drafted the article. A.D.S., F.G.R., A.S., T.E., G.R. and H.S. reviewed the article critically and gave important intellectual content. All authors gave their final approval of the version to be published.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLappe V, Greiner GG, Linnenkamp U et al (2023) Gestational diabetes in Germany-prevalence, trend during the past decade and utilization of follow-up care: An observational study. Sci Rep 13:16157\u003c/li\u003e\n\u003cli\u003eReitzle L, Heidemann C, Krause L, Hoebel J, Scheidt-Nave C (2024) Prevalence of gestational diabetes mellitus in Germany: Temporal trend and differences by regional socioeconomic deprivation. J Health Monit 9:e12086\u003c/li\u003e\n\u003cli\u003eShah BR, Retnakaran R, Booth GL (2008) Increased risk of cardiovascular disease in young women following gestational diabetes mellitus. 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J Glaucoma 25:865\u0026ndash;872\u003c/li\u003e\n\u003cli\u003eLim HB, Shin YI, Lee MW, Park GS, Kim JY (2019) Longitudinal Changes in the Peripapillary Retinal Nerve Fiber Layer Thickness of Patients With Type 2 Diabetes. JAMA Ophthalmol 137:1125\u0026ndash;1132\u003c/li\u003e\n\u003cli\u003eBhaskaran A, Babu M, Sudhakar NA, Kudlu KP, Shashidhara BC (2023) Study of retinal nerve fiber layer thickness in diabetic patients using optical coherence tomography. Indian J Ophthalmol 71:920\u0026ndash;926\u003c/li\u003e\n\u003cli\u003eChen X, Nie C, Gong Y et al (2015) Peripapillary retinal nerve fiber layer changes in preclinical diabetic retinopathy: A meta-analysis. PLoS One 10:e0125919\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Optical coherence tomography, circumpapillary retinal nerve fibre layer thickness, gestational diabetes mellitus, cpRNFLT, A-scan resolution","lastPublishedDoi":"10.21203/rs.3.rs-9103502/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9103502/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Gestational diabetes mellitus (GDM) and pre-conceptional diabetes are linked to increased long-term risk of type 2 diabetes (T2D) and microvascular complications. However, the earliest signs of neurovascular damage during pregnancy remain elusive. Here, we report the first longitudinal analysis of circumpapillary retinal nerve fiber layer thickness (cpRNFLT) using high-resolution 768-A-scan spectral-domain OCT in a population-based cohort of 591 pregnant women, including healthy pregnancies (HPC), diet-treated (dGDM) and insulin-treated GDM (iGDM), and pre-conceptional diabetes (T1D/T2D). We reveal divergent, treatment-specific neuroretinal trajectories: dGDM exhibited early thinning in the temporal-inferior sector (up to −20 µm), while iGDM showed progressive thickening in the temporal-superior sector (up to +22 µm), correlating with insulin exposure duration. Notably, women with pre-conceptional diabetes displayed profound and sustained thinning (up to −30 µm), exceeding levels seen in non-pregnant diabetic individuals. Using Euclidean nested case-control matching, these differences were confirmed after rigorous adjustment for confounders. Our findings demonstrate that glucose dysregulation during pregnancy induces measurable neuroretinal changes at an earlier stage than previously recognized, suggesting that the retina may serve as a non-invasive window into systemic metabolic vulnerability. These results position cpRNFLT as a potential biomarker for early detection of long-term diabetes risk, with implications for prenatal screening and preventive strategies.","manuscriptTitle":"Pregnancy amplifies neurovascular vulnerability: longitudinal retinal high-resolution OCT imaging reveals early, treatment-specific neurodegeneration in gestational and pre-conceptional diabetes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 14:57:09","doi":"10.21203/rs.3.rs-9103502/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-medicine","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsmed","sideBox":"Learn more about [Communications Medicine](http://www.nature.com/commsmed)","snPcode":"43856","submissionUrl":"https://mts-commsmed.nature.com/cgi-bin/main.plex","title":"Communications Medicine","twitterHandle":"@commsmedicine","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6461fdc4-24e4-4841-9065-fedbfc31d45c","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":64683891,"name":"Health sciences/Medical research/Translational research"},{"id":64683892,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":64683893,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Gestational diabetes"},{"id":64683894,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Type 2 diabetes"},{"id":64683895,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Diabetes complications"}],"tags":[],"updatedAt":"2026-04-09T14:57:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 14:57:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9103502","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9103502","identity":"rs-9103502","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}