Maternal Liver Shear Wave Elastography in Pregnancies Complicated by Gestational Diabetes Mellitus: A Prospective Study

Maternal Liver Shear Wave Elastography in Pregnancies Complicated by Gestational Diabetes Mellitus: A Prospective Study | 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 Research Article Maternal Liver Shear Wave Elastography in Pregnancies Complicated by Gestational Diabetes Mellitus: A Prospective Study Eda GÜNER ÖZEN, Mustafa Melih ERKAN, Uygar TANYERİ, Pınar ANKAYA, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7706599/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Gestational diabetes mellitus (GDM) is associated with adverse maternal and fetal outcomes. Recent advances in imaging have introduced shear wave elastography (SWE) as a non-invasive method for evaluating soft tissue stiffness. This study aimed to assess maternal liver stiffness using SWE in pregnancies with and without GDM and evaluate its potential utility in GDM risk stratification. Methods: This prospective observational study included 130 women with singleton pregnancies between 24 and 28 weeks’ gestation. All participants underwent a 75 g oral glucose tolerance test (OGTT) and were categorized into GDM (n = 65) or non-GDM (n = 65) groups based on ADA/IADPSG criteria. Liver stiffness was measured transabdominally using SWE targeting segment 8 of the right hepatic lobe. Five measurements were obtained per participant, and the median value was used for analysis. Liver stiffness values were classified based on established hepatology thresholds. Demographic, biochemical, and elastographic variables were compared between groups. Correlation and receiver operating characteristic (ROC) analyses were performed to assess associations and diagnostic performance. Results: Mean body mass index was significantly higher in the GDM group (30.3 ± 2.3 kg/m²) than in the non-GDM group (24.5 ± 2.3 kg/m²) (p < 0.001). Liver stiffness was also significantly elevated in women with GDM (6.17 ± 0.87 kPa vs. 5.63 ± 0.61 kPa, p < 0.001). Stiffness values ≥ 6.1 kPa (suggestive of fibrosis) were observed in 61.5% of GDM and 23.1% of non-GDM cases (p < 0.001). SWE values correlated positively with fasting glucose (r = 0.173) and LDL cholesterol (r = 0.199), and inversely with HDL cholesterol (r = − 0.226). ROC analysis identified a cut-off value of 5.79 kPa (AUC: 0.699), with 61.5% sensitivity and 72.3% specificity for predicting GDM. Conclusions: Maternal liver stiffness is significantly increased in GDM and shows moderate discriminative power during OGTT screening. SWE may serve as a useful adjunct for non-invasive metabolic assessment in pregnancy. Diabetes Gestational Elastography Shear Wave Liver Pregnancy Ultrasonography Figures Figure 1 Key Points • Maternal liver stiffness, measured via shear wave elastography (SWE), was significantly higher in women with gestational diabetes mellitus (GDM) compared to those with normal glucose tolerance at 24–28 weeks of gestation. • SWE demonstrated moderate diagnostic performance for predicting GDM, suggesting it may serve as a supportive, non-invasive adjunct to traditional glycemic testing during routine antenatal care. • The correlation of SWE values with metabolic parameters such as fasting glucose and HDL cholesterol highlights the potential role of liver stiffness as a surrogate marker of maternal metabolic adaptation in pregnancy. Introduction Gestational diabetes mellitus (GDM) is a common pregnancy-specific metabolic disorder characterized by glucose intolerance with onset or first recognition during gestation. According to the American Diabetes Association (ADA), GDM affects approximately 6–25% of pregnancies, depending on diagnostic criteria and population characteristics [ 1 ]. It is associated with adverse short- and long-term outcomes for both mother and fetus, including preeclampsia, fetal overgrowth, neonatal hypoglycemia, increased lifelong risk of type 2 diabetes and metabolic syndrome, and even elevated levels of pregnancy-related anxiety [ 2 , 3 ]. The current diagnostic approach recommended by the ADA and the International Association of Diabetes and Pregnancy Study Groups (IADPSG) involves a one-step 75-gram oral glucose tolerance test (OGTT) performed between 24 and 28 weeks of gestation. A diagnosis of GDM is established if one or more of the following thresholds are met: fasting glucose ≥ 92 mg/dL, 1-hour ≥ 180 mg/dL, or 2-hour ≥ 153 mg/dL [ 1 ]. The liver plays a central role in glucose and lipid metabolism, particularly during pregnancy when physiological insulin resistance increases to support fetal demands. This adaptive process involves dynamic hepatic changes, including alterations in enzyme levels such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), and alkaline phosphatase (ALP), which have been proposed as potential indicators of maternal metabolic status [ 4 ]. Increasing evidence suggests that hepatic metabolic and structural changes may be associated with gestational disorders, including GDM; however, their direct contribution to GDM pathophysiology remains unclear. Liver stiffness can be evaluated non-invasively using ultrasound-based techniques such as shear wave elastography (SWE), which has gained attention for its ability to detect hepatic structural changes in pregnancy. Physiological adaptations—including increased plasma volume and hepatic blood flow—may influence liver stiffness values, further supporting the utility of SWE in monitoring maternal hepatic and metabolic alterations during gestation [ 5 , 6 ]. Despite growing interest in the hepatic involvement in pregnancy complications, research evaluating liver stiffness via quantitative imaging techniques in GDM is limited. Prior studies have largely focused on biochemical markers of liver function, while the role of SWE remains underexplored [ 7 , 8 ]. Given the increasing global burden of GDM and the metabolic role of the liver, assessing maternal liver stiffness may provide valuable complementary information for risk stratification of liver complications. Recent advances in shear wave elastography (SWE) have enabled non-invasive evaluation of fetal and maternal tissues in GDM. For instance, Bayraktar et al. demonstrated increased placental and fetal lung stiffness in pregnancies complicated by GDM, linking SWE findings with neonatal respiratory morbidity [ 9 ]. Building on recent calls to investigate the role of liver stiffness in pregnancy complications [ 10 ], this prospective study is, to our knowledge, one of the few to assess maternal liver SWE during pregnancy. Our findings highlight the promise of SWE as a non-invasive adjunct in pregnancies complicated by GDM, particularly for enhancing risk stratification and supporting early identification of metabolic dysfunction. Materials and Methods Study Design and Setting This prospective observational study was conducted at the Department of Obstetrics and Gynecology, İzmir City Hospital, between January 2025 and July 2025. A total of 130 pregnant women aged 18–45 years with singleton pregnancies between 24 and 28 weeks of gestation were voluntarily enrolled after undergoing a 75-gram oral glucose tolerance test (OGTT). Participants and Data Collection Eligible participants were recruited during routine antenatal visits. Inclusion criteria were: maternal age 18–45 years, singleton pregnancy, completed OGTT between 24–28 weeks of gestation, and provision of written informed consent. Exclusion criteria included: pre-existing type 1 or type 2 diabetes mellitus, previous GDM history, multiple pregnancy, hypertensive disorders of pregnancy (preeclampsia or gestational hypertension), obesity (BMI ≥ 30 kg/m²), and known chronic liver disease (e.g., hepatitis B/C, autoimmune liver disease). Demographic and clinical data were collected, including age, gravidity, parity, abortion history, and BMI. Laboratory parameters included OGTT results (fasting, 1-hour, and 2-hour plasma glucose levels) and biochemical markers (ALT, AST, GGT, ALP, total cholesterol, LDL, HDL, and triglycerides). Biochemical analyses were performed using a Roche Cobas 6000 analyzer (Roche Diagnostics, Mannheim, Germany) in the hospital’s central laboratory. Based on OGTT outcomes, participants were stratified into two groups: the GDM group (diagnosed with gestational diabetes mellitus) and the Non-GDM group (normal glucose tolerance). Liver Elastography Protocol Liver Elastography Protocol SWE was performed using a transabdominal ultrasound probe targeting segment 8 of the right hepatic lobe, avoiding large vessels and bile ducts. Patients were positioned in the right lateral decubitus position. For each participant, five valid SWE measurements were obtained, and the median value (in kilopascals, kPa) was recorded for analysis. All scans were performed by a single experienced obstetrician (E.G.Ö.), blinded to participants’ GDM status, using a standardized protocol. Shear wave elastography was conducted using a GE LOGIQ P9 ultrasound system (General Electric, Bloomington, IL, USA) equipped with a convex 1–6 MHz transducer and abdominal preset, with crossbeam imaging disabled during SWE acquisition. Liver stiffness was categorized according to established hepatology cut-off values (EASL 2021; AASLD 2018) [ 11 , 12 ]: normal (≤ 6.0 kPa), mild fibrosis (6.1–7.0 kPa), moderate fibrosis (7.1–9.5 kPa), advanced fibrosis (9.6–12.5 kPa), and cirrhosis (> 12.5 kPa). Statistical Analysis Sample size was calculated based on a two-tailed hypothesis to detect a medium effect size (Cohen’s d = 0.6) with 90% power at α = 0.05, yielding a required minimum of 59 participants per group. A total of 130 participants were included. This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Statistical analyses were conducted using SPSS version 29 (IBM Corp., Armonk, NY, USA). The distribution of continuous variables was assessed visually using histograms and analytically using the Shapiro–Wilk test. For normally distributed variables, comparisons between groups were made using independent samples t-tests, while non-normally distributed data were analyzed using Mann–Whitney U tests. Categorical variables were compared using chi-square tests. Pearson or Spearman correlation coefficients were calculated to assess associations between liver SWE values and biochemical parameters, depending on data distribution. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of SWE in predicting GDM, and the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were reported. A p-value of < 0.05 was considered statistically significant. Results A total of 130 pregnant women between 24 and 28 weeks of gestation were included in the study. Based on OGTT results, participants were divided into two groups: the GDM group and the Non-GDM group, consisting of those with normal glucose tolerance. Demographic characteristics of the study population are presented in Table 1 . There were no significant differences between groups in terms of demographic data except BMI. BMI was significantly higher in the GDM group compared to the Non-GDM group (p < 0.001). Table 1 Demographic Characteristics of Participants (Mean ± SD) Variable GDM (Mean ± SD) Non-GDM (Mean ± SD) p-value Age 30.74 ± 5.83 31.49 ± 5.43 0.439 BMI 30.29 ± 2.31 24.46 ± 2.27 < 0.001 Gravida 2.63 ± 1.4 2.83 ± 1.4 0.442 Parity 1.29 ± 1.18 1.34 ± 1.14 0.761 Note: GDM = Gestational Diabetes Mellitus. BMI = Body Mass Index. Data are presented as mean ± standard deviation (SD). p-values are derived from Mann–Whitney U tests comparing the GDM and Non-GDM groups. Logistic regression analysis was performed to identify independent biochemical predictors of GDM (Table 2 ). In univariate analysis, fasting glucose (OR: 1.14, 95% CI: 1.02–1.28, p = 0.021), GGT (OR: 1.07, 95% CI: 1.00–1.15, p = 0.048), LDL cholesterol (OR: 1.02, 95% CI: 1.00–1.03, p = 0.038), and HDL cholesterol (OR: 0.94, 95% CI: 0.89–0.99, p = 0.017) were significantly associated with GDM. In the multivariate model, fasting glucose (OR: 1.12, 95% CI: 1.00–1.26, p = 0.048) and HDL cholesterol (OR: 0.95, 95% CI: 0.90–1.00, p = 0.049) remained independent predictors. GGT and LDL showed borderline significance (p = 0.072 and p = 0.085, respectively). Table 2 Univariate and Multivariate Logistic Regression Analyses of Glucose and Biochemical Parameters Associated with GDM Variable Odds Ratio (Univariate) 95% CI p-value Odds Ratio (Multivariate) 95% CI p-value Fasting Glucose 1.14 1.02–1.28 0.021 1.12 1.00–1.26 0.048 1-hour Glucose 1.03 0.99–1.06 0.122 – – – 2-hour Glucose 1.01 0.98–1.05 0.322 – – – ALT 1.02 0.98–1.06 0.261 – – – AST 1.00 0.97–1.04 0.763 – – – GGT 1.07 1.00–1.15 0.048 1.06 0.99–1.14 0.072 Total Cholesterol 1.01 1.00–1.02 0.071 – – – LDL 1.02 1.00–1.03 0.038 1.01 0.99–1.03 0.085 HDL 0.94 0.89–0.99 0.017 0.95 0.90–1.00 0.049 Triglyceride 1.01 1.00–1.02 0.089 – – – Note: Odds ratios (OR) and 95% confidence intervals (CI) were calculated to assess the association between each parameter and the presence of gestational diabetes mellitus (GDM). Variables with p < 0.05 in univariate analysis were considered for multivariate analysis. As shown in Table 3 , the mean SWE value was significantly elevated in the GDM group (6.17 ± 0.87 kPa) compared to the Non-GDM group (5.63 ± 0.61 kPa) (p < 0.001). When liver stiffness was categorized according to fibrosis thresholds, mild and moderate fibrosis were more frequently observed in the GDM group, whereas normal SWE values were predominant in the Non-GDM group. This distribution difference was statistically significant (χ² = 19.82, p < 0.001). Table 3 Comparison of Liver SWE Categories and Mean Values Between GDM and Non-GDM Groups SWE Interpretation GDM (n) GDM SWE (kPa) Non-GDM (n) Non-GDM SWE (kPa) Total (n) Total SWE (kPa) Mild Fibrosis 30 6.35 ± 0.36 12 6.33 ± 0.28 42 6.35 ± 0.34 Moderate Fibrosis 10 7.66 ± 0.48 3 7.41 ± 0.17 13 7.60 ± 0.44 Normal 25 5.35 ± 0.33 50 5.35 ± 0.27 75 5.35 ± 0.29 Mean SWE (kPa) 65 6.17 ± 0.87 65 5.63 ± 0.61 130 - Note: SWE = Shear Wave Elastography. GDM = Gestational Diabetes Mellitus. Values are presented as mean ± standard deviation (SD). A Mann–Whitney U test showed a statistically significant difference in SWE values between groups (U = 2954.0, p < 0.001). A chi-square test also demonstrated a significant difference in SWE interpretation categories between groups (χ² = 19.82, p < 0.001). A Kruskal–Wallis H test revealed significant differences in SWE values across stiffness categories (H = 95.13, p < 0.001). To evaluate the diagnostic utility of SWE in identifying GDM, a receiver operating characteristic (ROC) analysis was performed (Fig. 1 ). The area under the curve (AUC) was 0.699, indicating moderate discriminative ability. The optimal SWE cut-off value was 5.79 kPa, corresponding to a sensitivity of 61.5%, specificity of 72.3%, positive predictive value (PPV) of 68.4%, and negative predictive value (NPV) of 64.4%. Discussion Our study demonstrated that maternal liver stiffness, as measured by shear wave elastography (SWE), was significantly higher in women with gestational diabetes mellitus (GDM) compared XXXaya i-GDM controls. The diagnostic performance of SWE was moderate (AUC: 0.699; sensitivity: 61.5%; specificity: 72.3%), suggesting that SWE may serve as a supportive, non-invasive biomarker rather than a primary diagnostic tool. To our knowledge, this is among the few prospective studies evaluating maternal hepatic SWE in pregnancies complicated by GDM, highlighting its potential utility in early detection and risk stratification. These findings align with and build upon prior research underscoring the interplay between hepatic alterations and gestational metabolic disorders. In a recent prospective cohort study, Liu et al. (2024) reported that elevated liver enzymes (ALT, AST, GGT, ALP) during early pregnancy were independently associated with increased GDM risk, with ALT showing the strongest relationship [ 4 ]. While that study focused on biochemical markers, our data suggest that non-invasive imaging of liver stiffness may reflect similar underlying metabolic alterations. Moreover, studies in NAFLD and NASH populations have demonstrated that increased liver stiffness, as measured by SWE, is associated with hepatic fibrosis and adverse metabolic outcomes [ 13 , 14 ], reinforcing the central role of the liver in the pathophysiology of GDM. Importantly, liver stiffness naturally fluctuates during pregnancy due to physiological hemodynamic adaptations. Ribeiro et al. (2019), for instance, showed that liver stiffness and hepatic fat content increase during the third trimester and normalize postpartum, likely due to increased portal blood flow [ 5 ]. These reversible changes should be differentiated from pathological elevations. Previous elastography studies in GDM have largely focused on placental tissue [ 15 – 18 ], a downstream organ affected by maternal metabolic status. In contrast, our study targeted the maternal liver—an upstream organ central to glucose and lipid metabolism. This distinction is clinically meaningful, as liver-based SWE may detect early alterations such as insulin resistance and hepatic steatosis, possibly before placental involvement. Supporting this organ-specific focus, Carmiel-Haggai et al. (2023) reported significantly higher liver stiffness and hepatic steatosis in women with preeclampsia compared with healthy pregnancies, with persistence into the postpartum period [ 6 ]. These findings suggest that while mild elevations in stiffness may reflect physiological adaptations, more pronounced increases—as observed in our GDM cohort—likely indicate metabolic or vascular pathology. While our study focused on maternal liver stiffness, other researchers have examined fetal and placental tissues in GDM. For example, Bayraktar et al. (2025) demonstrated increased SWE values in both central and peripheral placenta and fetal lung tissue in women with GDM, with higher fetal lung stiffness predicting neonatal respiratory complications [ 9 ]. Together, these studies support the systemic impact of GDM on maternal and fetal soft tissue properties, reinforcing the potential utility of SWE as a multiparametric tool in obstetric care. SWE has been recognized as a reproducible and clinically applicable method for assessing hepatic metabolic changes. Given that GDM and NAFLD share common features such as hepatic fat accumulation, insulin resistance, and dyslipidemia, the higher SWE values observed in our GDM group are consistent with existing evidence linking liver stiffness to metabolic dysfunction. Thus, maternal liver SWE may serve not only as a pregnancy-specific diagnostic adjunct but also as a marker of long-term metabolic health. Recent editorial commentary further supports this XXXaya i. Hassam et al. (2023) emphasized that increased liver stiffness during pregnancy may serve as an early marker of both preeclampsia and GDM, especially among women with high BMI and metabolic risk factors [ 10 ]. Addressing this hypothesis, our study evaluated maternal liver SWE during the critical diagnostic window (24–28 weeks) and demonstrated significantly elevated values in GDM patients. Although the diagnostic performance was modest, an AUC of 0.699 supports the potential of SWE as a non-invasive adjunct to traditional glycemic markers. The main strength of this study is its prospective design and the timing of hepatic elastography performed concurrently with routine OGTT—SWE was conducted during the same gestational window, enhancing its clinical relevance. Additionally, the observed correlations between SWE values and metabolic parameters such as fasting glucose and HDL cholesterol further support the role of liver stiffness as a surrogate indicator of maternal metabolic adaptation. These findings align with growing calls for integrating non-invasive elastography into obstetric care and contribute novel insights to the field. However, our study has limitations. It was conducted at a single center with a modest sample size, potentially limiting generalizability. Moreover, maternal and neonatal outcomes (e.g., insulin use, fetal growth, delivery complications) were not analyzed, precluding assessment of the prognostic utility of SWE. Future multicenter studies with larger cohorts and longitudinal follow-up are warranted to address these gaps and to explore the potential value of serial SWE measurements throughout pregnancy. Conclusion Maternal liver stiffness, as measured by shear wave elastography (SWE), was significantly higher in women with GDM compared XXXaya i-GDM controls at 24–28 weeks of gestation, supporting its potential role as a non-invasive adjunctive tool in GDM risk assessment. SWE offers a bedside, radiation-free, and clinically feasible method for enhancing metabolic risk stratification in pregnancy. While the diagnostic performance of SWE was modest, its ability to differentiate GDM from non-GDM suggests that it may complement, rather than replace, OGTT. Larger multicenter studies are needed to validate these findings and assess whether liver stiffness measurements can help predict adverse pregnancy outcomes or guide individualized management strategies. Additionally, future research should investigate whether SWE performed earlier in gestation (e.g., 11–14 weeks) XXXaya id in the early prediction of GDM. Abbreviations • ADA American Diabetes Association • AUC Area Under the Curve • ALP Alkaline Phosphatase • ALT Alanine Aminotransferase • AST Aspartate Aminotransferase • BMI Body Mass Index • CI Confidence Interval • GDM Gestational Diabetes Mellitus • GGT Gamma–Glutamyl Transferase • HDL High–Density Lipoprotein • IADPSG International Association of Diabetes and Pregnancy Study Groups • kPa Kilopascal • LDL Low–Density Lipoprotein • NAFLD Non–Alcoholic Fatty Liver Disease • NASH Non–Alcoholic Steatohepatitis • NPV Negative Predictive Value • OGTT Oral Glucose Tolerance Test • OR Odds Ratio • PPV Positive Predictive Value • ROC Receiver Operating Characteristic • SD Standard Deviation • SWE Shear Wave Elastography Declarations Ethics approval and consent to participate The study protocol was approved by the Institutional Ethics Committee of İzmir City Hospital (Approval No: 2025/170). Written informed consent was obtained from all participants. All procedures were conducted in accordance with the Declaration of Helsinki. SWE is a non-invasive, radiation-free imaging modality, and no intervention posing risk to maternal or fetal health was performed. Consent for publication Not applicable. This manuscript does not include identifiable individual data. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study received no external funding or financial support. Authors’ contributions EGÖ : Conceptualization, patient recruitment, SWE measurements, clinical follow-up, manuscript drafting and writing YKA : Senior supervision, clinical coordination, final review and approval AGK : Methodology design, data interpretation, manuscript editing and refinement SÖ, UT, PA, MME : Participant monitoring, data collection, literature review, and supportive contributions to the study All authors read and approved the final manuscript. Acknowledgements The authors would like to thank the Department of Obstetrics and Gynecology at İzmir City Hospital for institutional support, as well as the patients who participated in the study. References American Diabetes Association. Classification and diagnosis of diabetes: standards of medical care in diabetes—2023. Diabetes Care. 2023;46(Suppl 1):S19–40. Phalle A, Gokhale D. Maternal and fetal outcomes in gestational diabetes mellitus: a narrative review of dietary interventions. Front Glob Womens Health. 2025;6:1510260. 10.3389/fgwh.2025.1510260 . Yeşilçınar İ, Kıncı MF, Ünver HC, Sivaslıoğlu AA. Pregnancy-related anxiety and prenatal attachment in pregnant women with preeclampsia and/or gestational diabetes mellitus: a cross-sectional study. J Clin Obstet Gynecol. 2023;33(1):27–35. Liu H, Zhang L, Cheng H, et al. The associations of maternal liver biomarkers in early pregnancy with the risk of gestational diabetes mellitus: a prospective cohort study and Mendelian randomization analysis. EBioMedicine. 2024;101:104659. Ribeiro MS, Hagström H, Stål P, Ajne G. Transient liver elastography in normal pregnancy: a longitudinal cohort study. Scand J Gastroenterol. 2019;54(7):869–73. Carmiel-Haggai M, Sgayer I, Bornstein J, et al. Liver stiffness and steatosis in preeclampsia as shown by transient elastography: a prospective cohort study. Am J Obstet Gynecol. 2023;227(3):e4031–9. Mandić-Marković V, Dobrijević Z, Robajac D, et al. Biochemical markers in the prediction of pregnancy outcome in gestational diabetes mellitus. Med (Kaunas). 2024;60(8):1250. 10.3390/medicina60081250 . Wu P, Wang Y, Ye Y, et al. Liver biomarkers, lipid metabolites, and risk of gestational diabetes mellitus in a prospective study among Chinese pregnant women. BMC Med. 2023;21(1):150. 10.1186/s12916-023-02818-6 . Bayraktar B, Golbasi H, Omeroglu I, et al. Evaluation of placenta and fetal lung using shear wave elastography in gestational diabetes mellitus: an innovative approach. Ultraschall Med. 2025;46(4):372–80. 10.1055/a-2323-0941 . Hassam K, Khawaja, et al. The application of transient elastography for early diagnosis of pregnancy-related complications. Am J Obstet Gynecol. 2024;230(1):104–5. European Association for the Study of the Liver. EASL clinical practice guidelines on non-invasive tests for evaluation of liver disease severity and prognosis – 2021 update. J Hepatol. 2021;75(3):659–89. 10.1016/j.jhep.2021.05.025 . 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Acar Sirinoglu H, Uysal G, Nazik H, et al. Comparison of elasticity values in normal and gestational diabetic pregnancies in the third trimester. J Obstet Gynaecol. 2022;42(5):842–7. 10.1080/01443615.2021.1945012 . Lai HW, Lyv GR, Wei YT, Zhou T. The diagnostic value of two-dimensional shear wave elastography in gestational diabetes mellitus. Placenta. 2020;101:147–53. 10.1016/j.placenta.2020.08.024 . Yuksel MA, Kilic F, Kayadibi Y, et al. Shear wave elastography of the placenta in patients with gestational diabetes mellitus. J Obstet Gynaecol. 2016;36(5):585–8. 10.3109/01443615.2015.1110120 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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. 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15:52:20","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96262,"visible":true,"origin":"","legend":"","description":"","filename":"7a096b729fd7472fabd129af0b06641d1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7706599/v1/30af9421fdd7e688feb641d3.xml"},{"id":95276950,"identity":"e51cd25c-da10-4575-85b8-f9edcbacc749","added_by":"auto","created_at":"2025-11-06 08:32:40","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107528,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7706599/v1/cfe3962719b3a448bfa19641.html"},{"id":95276943,"identity":"b78e5320-af49-47ad-be5b-d1e66b86b774","added_by":"auto","created_at":"2025-11-06 08:32:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":109317,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curve evaluating the diagnostic performance of shear wave elastography (SWE) in predicting gestational diabetes mellitus (GDM). The area under the curve (AUC) was \u003cstrong\u003e0.699,\u003c/strong\u003e indicating a moderate discriminative ability.The optimal SWE threshold was 5.79 kPa, yielding a sensitivity of 61.5%, specificity of 72.3%, positive predictive value (PPV) of 68.4%, and negative predictive value (NPV) of 64.4%.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7706599/v1/4490e80a840dd8b2a5b55717.png"},{"id":105890942,"identity":"7b3351be-cd61-485a-af72-711427d0e9ed","added_by":"auto","created_at":"2026-04-01 08:00:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":852411,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7706599/v1/b1b6040d-cd74-47b1-be82-f5ce59a6dc79.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maternal Liver Shear Wave Elastography in Pregnancies Complicated by Gestational Diabetes Mellitus: A Prospective Study","fulltext":[{"header":"Key Points","content":"\u003cp\u003e\u0026bull; Maternal liver stiffness, measured via shear wave elastography (SWE), was significantly higher in women with gestational diabetes mellitus (GDM) compared to those with normal glucose tolerance at 24\u0026ndash;28 weeks of gestation.\u003c/p\u003e\u003cp\u003e\u0026bull; SWE demonstrated moderate diagnostic performance for predicting GDM, suggesting it may serve as a supportive, non-invasive adjunct to traditional glycemic testing during routine antenatal care.\u003c/p\u003e\u003cp\u003e\u0026bull; The correlation of SWE values with metabolic parameters such as fasting glucose and HDL cholesterol highlights the potential role of liver stiffness as a surrogate marker of maternal metabolic adaptation in pregnancy.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eGestational diabetes mellitus (GDM) is a common pregnancy-specific metabolic disorder characterized by glucose intolerance with onset or first recognition during gestation. According to the American Diabetes Association (ADA), GDM affects approximately 6\u0026ndash;25% of pregnancies, depending on diagnostic criteria and population characteristics [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is associated with adverse short- and long-term outcomes for both mother and fetus, including preeclampsia, fetal overgrowth, neonatal hypoglycemia, increased lifelong risk of type 2 diabetes and metabolic syndrome, and even elevated levels of pregnancy-related anxiety [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe current diagnostic approach recommended by the ADA and the International Association of Diabetes and Pregnancy Study Groups (IADPSG) involves a one-step 75-gram oral glucose tolerance test (OGTT) performed between 24 and 28 weeks of gestation. A diagnosis of GDM is established if one or more of the following thresholds are met: fasting glucose\u0026thinsp;\u0026ge;\u0026thinsp;92 mg/dL, 1-hour\u0026thinsp;\u0026ge;\u0026thinsp;180 mg/dL, or 2-hour\u0026thinsp;\u0026ge;\u0026thinsp;153 mg/dL [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe liver plays a central role in glucose and lipid metabolism, particularly during pregnancy when physiological insulin resistance increases to support fetal demands. This adaptive process involves dynamic hepatic changes, including alterations in enzyme levels such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), and alkaline phosphatase (ALP), which have been proposed as potential indicators of maternal metabolic status [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Increasing evidence suggests that hepatic metabolic and structural changes may be associated with gestational disorders, including GDM; however, their direct contribution to GDM pathophysiology remains unclear.\u003c/p\u003e\u003cp\u003eLiver stiffness can be evaluated non-invasively using ultrasound-based techniques such as shear wave elastography (SWE), which has gained attention for its ability to detect hepatic structural changes in pregnancy. Physiological adaptations\u0026mdash;including increased plasma volume and hepatic blood flow\u0026mdash;may influence liver stiffness values, further supporting the utility of SWE in monitoring maternal hepatic and metabolic alterations during gestation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite growing interest in the hepatic involvement in pregnancy complications, research evaluating liver stiffness via quantitative imaging techniques in GDM is limited. Prior studies have largely focused on biochemical markers of liver function, while the role of SWE remains underexplored [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Given the increasing global burden of GDM and the metabolic role of the liver, assessing maternal liver stiffness may provide valuable complementary information for risk stratification of liver complications. Recent advances in shear wave elastography (SWE) have enabled non-invasive evaluation of fetal and maternal tissues in GDM. For instance, Bayraktar et al. demonstrated increased placental and fetal lung stiffness in pregnancies complicated by GDM, linking SWE findings with neonatal respiratory morbidity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBuilding on recent calls to investigate the role of liver stiffness in pregnancy complications [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], this prospective study is, to our knowledge, one of the few to assess maternal liver SWE during pregnancy. Our findings highlight the promise of SWE as a non-invasive adjunct in pregnancies complicated by GDM, particularly for enhancing risk stratification and supporting early identification of metabolic dysfunction.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Setting\u003c/h2\u003e\u003cp\u003eThis prospective observational study was conducted at the Department of Obstetrics and Gynecology, İzmir City Hospital, between January 2025 and July 2025. A total of 130 pregnant women aged 18\u0026ndash;45 years with singleton pregnancies between 24 and 28 weeks of gestation were voluntarily enrolled after undergoing a 75-gram oral glucose tolerance test (OGTT).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants and Data Collection\u003c/h3\u003e\n\u003cp\u003eEligible participants were recruited during routine antenatal visits. Inclusion criteria were: maternal age 18\u0026ndash;45 years, singleton pregnancy, completed OGTT between 24\u0026ndash;28 weeks of gestation, and provision of written informed consent. Exclusion criteria included: pre-existing type 1 or type 2 diabetes mellitus, previous GDM history, multiple pregnancy, hypertensive disorders of pregnancy (preeclampsia or gestational hypertension), obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;), and known chronic liver disease (e.g., hepatitis B/C, autoimmune liver disease).\u003c/p\u003e\u003cp\u003eDemographic and clinical data were collected, including age, gravidity, parity, abortion history, and BMI. Laboratory parameters included OGTT results (fasting, 1-hour, and 2-hour plasma glucose levels) and biochemical markers (ALT, AST, GGT, ALP, total cholesterol, LDL, HDL, and triglycerides). Biochemical analyses were performed using a Roche Cobas 6000 analyzer (Roche Diagnostics, Mannheim, Germany) in the hospital\u0026rsquo;s central laboratory. Based on OGTT outcomes, participants were stratified into two groups: the GDM group (diagnosed with gestational diabetes mellitus) and the Non-GDM group (normal glucose tolerance).\u003c/p\u003e\n\u003ch3\u003eLiver Elastography Protocol\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eLiver Elastography Protocol\u003c/div\u003e\u003cp\u003eSWE was performed using a transabdominal ultrasound probe targeting segment 8 of the right hepatic lobe, avoiding large vessels and bile ducts. Patients were positioned in the right lateral decubitus position. For each participant, five valid SWE measurements were obtained, and the median value (in kilopascals, kPa) was recorded for analysis. All scans were performed by a single experienced obstetrician (E.G.\u0026Ouml;.), blinded to participants\u0026rsquo; GDM status, using a standardized protocol. Shear wave elastography was conducted using a GE LOGIQ P9 ultrasound system (General Electric, Bloomington, IL, USA) equipped with a convex 1\u0026ndash;6 MHz transducer and abdominal preset, with crossbeam imaging disabled during SWE acquisition.\u003c/p\u003e\u003cp\u003eLiver stiffness was categorized according to established hepatology cut-off values (EASL 2021; AASLD 2018) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]: normal (\u0026le;\u0026thinsp;6.0 kPa), mild fibrosis (6.1\u0026ndash;7.0 kPa), moderate fibrosis (7.1\u0026ndash;9.5 kPa), advanced fibrosis (9.6\u0026ndash;12.5 kPa), and cirrhosis (\u0026gt;\u0026thinsp;12.5 kPa).\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eSample size was calculated based on a two-tailed hypothesis to detect a medium effect size (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.6) with 90% power at α\u0026thinsp;=\u0026thinsp;0.05, yielding a required minimum of 59 participants per group. A total of 130 participants were included.\u003c/p\u003e\u003cp\u003e This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003c/p\u003e\u003cp\u003eStatistical analyses were conducted using SPSS version 29 (IBM Corp., Armonk, NY, USA). The distribution of continuous variables was assessed visually using histograms and analytically using the Shapiro\u0026ndash;Wilk test. For normally distributed variables, comparisons between groups were made using independent samples t-tests, while non-normally distributed data were analyzed using Mann\u0026ndash;Whitney U tests. Categorical variables were compared using chi-square tests. Pearson or Spearman correlation coefficients were calculated to assess associations between liver SWE values and biochemical parameters, depending on data distribution. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of SWE in predicting GDM, and the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were reported. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 130 pregnant women between 24 and 28 weeks of gestation were included in the study. Based on OGTT results, participants were divided into two groups: the GDM group and the Non-GDM group, consisting of those with normal glucose tolerance. Demographic characteristics of the study population are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were no significant differences between groups in terms of demographic data except BMI. BMI was significantly higher in the GDM group compared to the Non-GDM group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic Characteristics of Participants (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGDM (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-GDM (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e30.74\u0026thinsp;\u0026plusmn;\u0026thinsp;5.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e31.49\u0026thinsp;\u0026plusmn;\u0026thinsp;5.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.439\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e30.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e24.46\u0026thinsp;\u0026plusmn;\u0026thinsp;2.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGravida\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e2.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.442\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.761\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: GDM\u0026thinsp;=\u0026thinsp;Gestational Diabetes Mellitus. BMI\u0026thinsp;=\u0026thinsp;Body Mass Index. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). p-values are derived from Mann\u0026ndash;Whitney U tests comparing the GDM and Non-GDM groups.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eLogistic regression analysis was performed to identify independent biochemical predictors of GDM (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In univariate analysis, fasting glucose (OR: 1.14, 95% CI: 1.02\u0026ndash;1.28, p\u0026thinsp;=\u0026thinsp;0.021), GGT (OR: 1.07, 95% CI: 1.00\u0026ndash;1.15, p\u0026thinsp;=\u0026thinsp;0.048), LDL cholesterol (OR: 1.02, 95% CI: 1.00\u0026ndash;1.03, p\u0026thinsp;=\u0026thinsp;0.038), and HDL cholesterol (OR: 0.94, 95% CI: 0.89\u0026ndash;0.99, p\u0026thinsp;=\u0026thinsp;0.017) were significantly associated with GDM. In the multivariate model, fasting glucose (OR: 1.12, 95% CI: 1.00\u0026ndash;1.26, p\u0026thinsp;=\u0026thinsp;0.048) and HDL cholesterol (OR: 0.95, 95% CI: 0.90\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.049) remained independent predictors. GGT and LDL showed borderline significance (p\u0026thinsp;=\u0026thinsp;0.072 and p\u0026thinsp;=\u0026thinsp;0.085, respectively).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate and Multivariate Logistic Regression Analyses of Glucose and Biochemical Parameters Associated with GDM\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds Ratio (Univariate)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOdds Ratio (Multivariate)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFasting Glucose\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.02\u0026ndash;1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00\u0026ndash;1.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e1-hour Glucose\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.99\u0026ndash;1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2-hour Glucose\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.98\u0026ndash;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eALT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.98\u0026ndash;1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAST\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97\u0026ndash;1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGGT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u0026ndash;1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.99\u0026ndash;1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Cholesterol\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u0026ndash;1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLDL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u0026ndash;1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.99\u0026ndash;1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.085\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHDL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.89\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.90\u0026ndash;1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTriglyceride\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u0026ndash;1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: Odds ratios (OR) and 95% confidence intervals (CI) were calculated to assess the association between each parameter and the presence of gestational diabetes mellitus (GDM). Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analysis were considered for multivariate analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the mean SWE value was significantly elevated in the GDM group (6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87 kPa) compared to the Non-GDM group (5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61 kPa) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When liver stiffness was categorized according to fibrosis thresholds, mild and moderate fibrosis were more frequently observed in the GDM group, whereas normal SWE values were predominant in the Non-GDM group. This distribution difference was statistically significant (χ\u0026sup2; = 19.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Liver SWE Categories and Mean Values Between GDM and Non-GDM Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSWE Interpretation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGDM (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGDM SWE (kPa)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-GDM (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNon-GDM SWE (kPa)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTotal (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTotal SWE (kPa)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMild Fibrosis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e6.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModerate Fibrosis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e7.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e5.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMean SWE (kPa)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: SWE\u0026thinsp;=\u0026thinsp;Shear Wave Elastography. GDM\u0026thinsp;=\u0026thinsp;Gestational Diabetes Mellitus. Values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). A Mann\u0026ndash;Whitney U test showed a statistically significant difference in SWE values between groups (U\u0026thinsp;=\u0026thinsp;2954.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A chi-square test also demonstrated a significant difference in SWE interpretation categories between groups (χ\u0026sup2; = 19.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A Kruskal\u0026ndash;Wallis H test revealed significant differences in SWE values across stiffness categories (H\u0026thinsp;=\u0026thinsp;95.13, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the diagnostic utility of SWE in identifying GDM, a receiver operating characteristic (ROC) analysis was performed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The area under the curve (AUC) was 0.699, indicating moderate discriminative ability. The optimal SWE cut-off value was 5.79 kPa, corresponding to a sensitivity of 61.5%, specificity of 72.3%, positive predictive value (PPV) of 68.4%, and negative predictive value (NPV) of 64.4%.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study demonstrated that maternal liver stiffness, as measured by shear wave elastography (SWE), was significantly higher in women with gestational diabetes mellitus (GDM) compared XXXaya i-GDM controls. The diagnostic performance of SWE was moderate (AUC: 0.699; sensitivity: 61.5%; specificity: 72.3%), suggesting that SWE may serve as a supportive, non-invasive biomarker rather than a primary diagnostic tool. To our knowledge, this is among the few prospective studies evaluating maternal hepatic SWE in pregnancies complicated by GDM, highlighting its potential utility in early detection and risk stratification.\u003c/p\u003e\u003cp\u003eThese findings align with and build upon prior research underscoring the interplay between hepatic alterations and gestational metabolic disorders. In a recent prospective cohort study, Liu et al. (2024) reported that elevated liver enzymes (ALT, AST, GGT, ALP) during early pregnancy were independently associated with increased GDM risk, with ALT showing the strongest relationship [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. While that study focused on biochemical markers, our data suggest that non-invasive imaging of liver stiffness may reflect similar underlying metabolic alterations. Moreover, studies in NAFLD and NASH populations have demonstrated that increased liver stiffness, as measured by SWE, is associated with hepatic fibrosis and adverse metabolic outcomes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], reinforcing the central role of the liver in the pathophysiology of GDM.\u003c/p\u003e\u003cp\u003eImportantly, liver stiffness naturally fluctuates during pregnancy due to physiological hemodynamic adaptations. Ribeiro et al. (2019), for instance, showed that liver stiffness and hepatic fat content increase during the third trimester and normalize postpartum, likely due to increased portal blood flow [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These reversible changes should be differentiated from pathological elevations.\u003c/p\u003e\u003cp\u003ePrevious elastography studies in GDM have largely focused on placental tissue [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], a downstream organ affected by maternal metabolic status. In contrast, our study targeted the maternal liver\u0026mdash;an upstream organ central to glucose and lipid metabolism. This distinction is clinically meaningful, as liver-based SWE may detect early alterations such as insulin resistance and hepatic steatosis, possibly before placental involvement. Supporting this organ-specific focus, Carmiel-Haggai et al. (2023) reported significantly higher liver stiffness and hepatic steatosis in women with preeclampsia compared with healthy pregnancies, with persistence into the postpartum period [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These findings suggest that while mild elevations in stiffness may reflect physiological adaptations, more pronounced increases\u0026mdash;as observed in our GDM cohort\u0026mdash;likely indicate metabolic or vascular pathology. While our study focused on maternal liver stiffness, other researchers have examined fetal and placental tissues in GDM. For example, Bayraktar et al. (2025) demonstrated increased SWE values in both central and peripheral placenta and fetal lung tissue in women with GDM, with higher fetal lung stiffness predicting neonatal respiratory complications [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Together, these studies support the systemic impact of GDM on maternal and fetal soft tissue properties, reinforcing the potential utility of SWE as a multiparametric tool in obstetric care.\u003c/p\u003e\u003cp\u003eSWE has been recognized as a reproducible and clinically applicable method for assessing hepatic metabolic changes. Given that GDM and NAFLD share common features such as hepatic fat accumulation, insulin resistance, and dyslipidemia, the higher SWE values observed in our GDM group are consistent with existing evidence linking liver stiffness to metabolic dysfunction. Thus, maternal liver SWE may serve not only as a pregnancy-specific diagnostic adjunct but also as a marker of long-term metabolic health.\u003c/p\u003e\u003cp\u003eRecent editorial commentary further supports this XXXaya i. Hassam et al. (2023) emphasized that increased liver stiffness during pregnancy may serve as an early marker of both preeclampsia and GDM, especially among women with high BMI and metabolic risk factors [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Addressing this hypothesis, our study evaluated maternal liver SWE during the critical diagnostic window (24\u0026ndash;28 weeks) and demonstrated significantly elevated values in GDM patients. Although the diagnostic performance was modest, an AUC of 0.699 supports the potential of SWE as a non-invasive adjunct to traditional glycemic markers.\u003c/p\u003e\u003cp\u003eThe main strength of this study is its prospective design and the timing of hepatic elastography performed concurrently with routine OGTT\u0026mdash;SWE was conducted during the same gestational window, enhancing its clinical relevance. Additionally, the observed correlations between SWE values and metabolic parameters such as fasting glucose and HDL cholesterol further support the role of liver stiffness as a surrogate indicator of maternal metabolic adaptation. These findings align with growing calls for integrating non-invasive elastography into obstetric care and contribute novel insights to the field.\u003c/p\u003e\u003cp\u003eHowever, our study has limitations. It was conducted at a single center with a modest sample size, potentially limiting generalizability. Moreover, maternal and neonatal outcomes (e.g., insulin use, fetal growth, delivery complications) were not analyzed, precluding assessment of the prognostic utility of SWE. Future multicenter studies with larger cohorts and longitudinal follow-up are warranted to address these gaps and to explore the potential value of serial SWE measurements throughout pregnancy.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eMaternal liver stiffness, as measured by shear wave elastography (SWE), was significantly higher in women with GDM compared XXXaya i-GDM controls at 24\u0026ndash;28 weeks of gestation, supporting its potential role as a non-invasive adjunctive tool in GDM risk assessment. SWE offers a bedside, radiation-free, and clinically feasible method for enhancing metabolic risk stratification in pregnancy. While the diagnostic performance of SWE was modest, its ability to differentiate GDM from non-GDM suggests that it may complement, rather than replace, OGTT. Larger multicenter studies are needed to validate these findings and assess whether liver stiffness measurements can help predict adverse pregnancy outcomes or guide individualized management strategies. Additionally, future research should investigate whether SWE performed earlier in gestation (e.g., 11\u0026ndash;14 weeks) XXXaya id in the early prediction of GDM.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eADA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAmerican Diabetes Association\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eAUC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eArea Under the Curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eALP\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlkaline Phosphatase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eALT\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlanine Aminotransferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eAST\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAspartate Aminotransferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody Mass Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eGDM\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGestational Diabetes Mellitus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eGGT\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGamma\u0026ndash;Glutamyl Transferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eHDL\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHigh\u0026ndash;Density Lipoprotein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eIADPSG\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInternational Association of Diabetes and Pregnancy Study Groups\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003ekPa\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eKilopascal\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eLDL\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLow\u0026ndash;Density Lipoprotein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eNAFLD\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNon\u0026ndash;Alcoholic Fatty Liver Disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eNASH\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNon\u0026ndash;Alcoholic Steatohepatitis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eNPV\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNegative Predictive Value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eOGTT\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOral Glucose Tolerance Test\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eOR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003ePPV\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePositive Predictive Value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eROC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eReceiver Operating Characteristic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; \u003cb\u003eSWE\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eShear Wave Elastography\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch4\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThe study protocol was approved by the Institutional Ethics Committee of İzmir City Hospital (Approval No: 2025/170). Written informed consent was obtained from all participants. All procedures were conducted in accordance with the Declaration of Helsinki. SWE is a non-invasive, radiation-free imaging modality, and no intervention posing risk to maternal or fetal health was performed.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eNot applicable. This manuscript does not include identifiable individual data.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThis study received no external funding or financial support.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/h4\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eEG\u0026Ouml;\u003c/strong\u003e: Conceptualization, patient recruitment, SWE measurements, clinical follow-up, manuscript drafting and writing\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eYKA\u003c/strong\u003e: Senior supervision, clinical coordination, final review and approval\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAGK\u003c/strong\u003e: Methodology design, data interpretation, manuscript editing and refinement\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eS\u0026Ouml;, UT, PA, MME\u003c/strong\u003e: Participant monitoring, data collection, literature review, and supportive contributions to the study\u003cbr\u003e\u0026nbsp;All authors read and approved the final manuscript.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch4\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThe authors would like to thank the Department of Obstetrics and Gynecology at İzmir City Hospital for institutional support, as well as the patients who participated in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmerican Diabetes Association. Classification and diagnosis of diabetes: standards of medical care in diabetes\u0026mdash;2023. Diabetes Care. 2023;46(Suppl 1):S19\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhalle A, Gokhale D. Maternal and fetal outcomes in gestational diabetes mellitus: a narrative review of dietary interventions. Front Glob Womens Health. 2025;6:1510260. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fgwh.2025.1510260\u003c/span\u003e\u003cspan address=\"10.3389/fgwh.2025.1510260\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYeşil\u0026ccedil;ınar İ, Kıncı MF, \u0026Uuml;nver HC, Sivaslıoğlu AA. Pregnancy-related anxiety and prenatal attachment in pregnant women with preeclampsia and/or gestational diabetes mellitus: a cross-sectional study. 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Shear wave elastography of the placenta in patients with gestational diabetes mellitus. J Obstet Gynaecol. 2016;36(5):585\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/01443615.2015.1110120\u003c/span\u003e\u003cspan address=\"10.3109/01443615.2015.1110120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diabetes, Gestational, Elastography, Shear Wave, Liver, Pregnancy, Ultrasonography","lastPublishedDoi":"10.21203/rs.3.rs-7706599/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7706599/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eGestational diabetes mellitus (GDM) is associated with adverse maternal and fetal outcomes. Recent advances in imaging have introduced shear wave elastography (SWE) as a non-invasive method for evaluating soft tissue stiffness. This study aimed to assess maternal liver stiffness using SWE in pregnancies with and without GDM and evaluate its potential utility in GDM risk stratification.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eThis prospective observational study included 130 women with singleton pregnancies between 24 and 28 weeks\u0026rsquo; gestation. All participants underwent a 75 g oral glucose tolerance test (OGTT) and were categorized into GDM (n\u0026thinsp;=\u0026thinsp;65) or non-GDM (n\u0026thinsp;=\u0026thinsp;65) groups based on ADA/IADPSG criteria. Liver stiffness was measured transabdominally using SWE targeting segment 8 of the right hepatic lobe. Five measurements were obtained per participant, and the median value was used for analysis. Liver stiffness values were classified based on established hepatology thresholds. Demographic, biochemical, and elastographic variables were compared between groups. Correlation and receiver operating characteristic (ROC) analyses were performed to assess associations and diagnostic performance.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eMean body mass index was significantly higher in the GDM group (30.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 kg/m\u0026sup2;) than in the non-GDM group (24.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 kg/m\u0026sup2;) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Liver stiffness was also significantly elevated in women with GDM (6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87 kPa vs. 5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61 kPa, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Stiffness values\u0026thinsp;\u0026ge;\u0026thinsp;6.1 kPa (suggestive of fibrosis) were observed in 61.5% of GDM and 23.1% of non-GDM cases (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). SWE values correlated positively with fasting glucose (r\u0026thinsp;=\u0026thinsp;0.173) and LDL cholesterol (r\u0026thinsp;=\u0026thinsp;0.199), and inversely with HDL cholesterol (r = \u0026minus;\u0026thinsp;0.226). ROC analysis identified a cut-off value of 5.79 kPa (AUC: 0.699), with 61.5% sensitivity and 72.3% specificity for predicting GDM.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e\u003cp\u003eMaternal liver stiffness is significantly increased in GDM and shows moderate discriminative power during OGTT screening. SWE may serve as a useful adjunct for non-invasive metabolic assessment in pregnancy.\u003c/p\u003e","manuscriptTitle":"Maternal Liver Shear Wave Elastography in Pregnancies Complicated by Gestational Diabetes Mellitus: A Prospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 08:32:36","doi":"10.21203/rs.3.rs-7706599/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d718b6b4-ddde-4ed8-8207-b7eee426aa08","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T07:58:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 08:32:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7706599","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7706599","identity":"rs-7706599","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}