Potential Utility Of The Fatty Liver Index As A Predictor Of Erectile Dysfunction And Its Severity

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Materials And Methods A group of 230 male patients with ED complaints underwent evaluation. Comprehensive routine blood serum tests were conducted to identify potential etiological factors contributing to ED. Additionally, waist circumference(WC) measurements were obtained to facilitate the calculation of the FLI. Participants were also asked to complete the validated Turkish adaptation of the 5-item International Index of Erectile Function (IIEF-5) questionnaire to assess the severity and impact of ED. Results Out of all participants, 55 were classified as non-ED, while 175 were diagnosed with ED, mostly in the mild to moderate category. According to FLI scores, 132 had hepatic steatosis(HS). Body mass index (BMI) and WC were significantly higher in the ED group. Fasting blood glucose, ALT, and triglycerides (TG) were elevated in those with ED, while AST and total testosterone levels were lower. A significant association was found between higher FLI scores and ED (p < 0.05). The FLI score was significantly higher (p < 0.05) in the severe ED group compared to the moderate, mild-moderate, and mild ED groups. Conclusion Based on the results of our study, the FLI appears to be a simple method that shows a high correlation with the severity of ED. We believe that the use of the FLI in the diagnosis and follow-up of ED is noteworthy, and further prospective studies with larger sample sizes are needed to support this conclusion. Erectile Dysfunction Fatty Liver Index Hepatosteatosis Metabolic Syndrome Figures Figure 1 INTRODUCTION Non-alcoholic fatty liver disease (NAFLD), characterized by an increase in liver fat content due to factors other than excessive alcohol consumption. It has emerged as a global public health concern, particularly affecting individuals with type 2 diabetes mellitus and morbid obesity. Epidemiological studies estimate its prevalence to range between 20% and 30% in the general population, highlighting its widespread impact and the necessity for early detection and management. ( 1 ).The etiology of NAFLD is closely associated with metabolic abnormalities, including dyslipidemia, obesity, and type 2 diabetes mellitus, which are also major contributors to the pathogenesis of metabolic syndrome and subsequent cardiovascular diseases. Given this strong association, NAFLD is widely recognized as the hepatic manifestation of metabolic syndrome(MetS)( 2 ). Ultrasonography remains the most widely utilized imaging modality for the diagnosis of NAFLD, primarily due to its cost-effectiveness, non-invasive nature, and broad accessibility. However, its diagnostic accuracy is inherently limited by operator dependency, introducing a degree of subjectivity. To address this limitation, Bedogni et al. developed the Fatty Liver Index(FLI), a simple and rapid clinical tool that has demonstrated a strong correlation with abdominal ultrasonography in population-based studies. Their findings indicate that a FLI score of ≤ 30 effectively excludes hepatosteatosis(HS), whereas a score ≥ 60 is strongly suggestive of the condition, offering a practical alternative for risk stratification in clinical and epidemiological settings. ( 3 ) FLI is a mathematical model derived from key metabolic parameters, Boddy Mass Index(BMI), waist circumference (WC), triglycerides(TG) levels, and gamma-glutamyl transferase (GGT) values. This index serves as a non-invasive tool for estimating HS. A study conducted in a European population demonstrated a significant association between FLI and metabolic dysfunctions, including insulin resistance (IR), coronary artery disease (CAD), and early atherosclerosis. These findings underscore the potential utility of FLI not only as a diagnostic marker for NAFLD but also as an indicator of cardiometabolic risk.( 4 ) Erectile dysfunction (ED), defined as the impairment of sexual function, extends beyond its impact on sexual health and is increasingly regarded as an early clinical marker of MetS( 5 ). Recent meta-analytical data indicate that the prevalence of ED is 2.6 times higher in individuals with metabolic syndrome compared to the general population( 5 ). From an etiological perspective, the pathophysiological mechanisms underlying ED closely overlap with those of NAFLD, suggesting shared metabolic risk factors such as IR, dyslipidemia, obesity, and endothelial dysfunction. This association highlights the importance of a comprehensive metabolic assessment in patients presenting with ED.( 5 ) In this study, we aimed to explore the relationship between two clinical manifestations of MetS; ED and NAFLD. Additionally, we sought to assess NAFLD status in patients diagnosed with ED. To enhance the originality of our study, we employed the FLI as a diagnostic parameter for NAFLD, given its strong correlation with ultrasonographic assessments. By utilizing FLI instead of conventional ultrasound-based evaluations, we aimed to provide a non-invasive, objective, and reproducible approach to investigating the association between ED and NAFLD. To our knowledge, this is the first study to investigate the relationship between FLI and ED and its severity. MATERIALS-METHODS 1. Ethics This study was conducted in accordance with the ethical principles set forth in the Declaration of Helsinki. All participants were fully informed about the study's purpose and provided written informed consent. Ethical approval was granted by the Local Ethics Committee of Health Science University Derince Training and Research Hospital.(approval number: 2020–107). 2. Selection of Participants A total of 230 males, aged 18 to 75, who visited the Urology Clinic of Gebze Fatih State Hospital between Semptember 1 2020, and July 1 2022 with complain of ED participated in the study. The study population was initially classified into ED(group 1) and non-ED (group 2) groups based on the 5-item International Index of Erectile Function (IIEF-5) scores, with scores of 5–21 indicating ED and scores of 22–25 indicating non-ED. The ED group was further subdivided into subgroups: severe ED (5–7 points), moderate ED (8–11 points), mild-moderate ED (12–16 points), and mild ED (17–21 points). Patients were excluded from the study if they were receiving medical treatment for hyperlipidemia or diabetes mellitus, had a weekly alcohol intake of ≥ 140 grams, or had a history of advanced cardiovascular disease. Furthermore, individuals with a history of oncological diseases, viral or autoimmune hepatitis, liver and biliary tract disorders associated with cholestasis, metabolic liver diseases, corticosteroid use, immunodeficiency, or psychiatric illnesses were also excluded. These exclusion criteria were implemented to minimize potential confounding factors and ensure a more homogenous study population for the accurate assessment of the relationship between ED and NAFLD. 3. Study Variables In this planned study, the biochemical parameters of patients diagnosed with ED, including blood triglycerides, glucose, ALT, AST, GGT, low-density lipoprotein (LDL), and total cholesterol were evaluated. Additionally, patients were classified based on their recorded BMI and WC measurements. Fasting blood samples were collected from venous blood between 08:00 and 10:00 in the morning to ensure standardized metabolic assessments and minimize diurnal variations in biochemical parameters. FLI was calculated using the following formula: FLI = (e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (ggt) + 0.053*waist circumference − 15.745) / (1 + e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (ggt) + 0.053*waist circumference − 15.745) * 100 Interpretation of FLI scores; FLI score below 30 was considered to effectively exclude hepatic steatosis, FLI score above 60 was indicative of HS, individuals with an FLI score between 30 and 60 were classified as the borderline group, requiring further evaluation.This classification allowed for a standardized, non-invasive assessment of HS, minimizing the reliance on imaging-based diagnostic methods. 4. Statistical Analysis: The Kolmogorov Smirnov test was used to check the normality of data for quantitative variables. Descriptive data were expressed in median and interquartile range, and frequency. The Pearson chi-square,and Mann-Whitney-U tests were used wherever possible. ROC curve analysis was conducted to determine effect size and cutoff values, and both univariate and multivariate logistic regression analyses were performed to assess the strength of associations. All statistical analyses were performed using SPSS version 27.0 software. Furthermore, a separate Receiver Operating Characteristic (ROC) analysis was conducted to calculate the area under the curve (AUC), and the relevance of the cut-off value for significant efficacy of FLI in differentiating control and case group patients. RESULTS After applying the exclusion criteria, the demographic and biochemical parameters of the remaining 230 patients are summarized in Table 1 . Based on the IIEF-5 scoring, 55 patients were classified as non-ED(group 1), while 175 patients were diagnosed with ED(group 2). Among the patients with ED, the majority were categorized within the mild to moderate ED group. Furthermore, according to FLI scores, 132 patients were classified as having HS, representing the majority of the study population. Table 1 Demographic and baseline clinical characteristics of study patients Median (IQR) Age (year) 50 (41–57) BMI (kg/m 2 ) 28,18 (25,38–31,10) WS (cm) 101 (94–110) Smoking(n, %) No 158 (%68,7) Yes 72 (%31,3) Glucose (mg/dL) 97 (90–108) AST (U/L) 20 (18–24) ALT (U/L) 23 (16–30) Total Cholesterol (mg/dL) 192 (163–220) LDL Cholesterol (mg/dL) 124 (102–148) Triglyceride (mg/dL) 135 (100–205) GGT (U/L) 26 (20–37) Total Testosteron (ng/mL) 3,59 (2,77–4,50) FLI Score 68,66 (39,32–84,40) FLI Subgroup (n, %) HS (-) 32 (%13,9) HS (Borderline) 66 (%28,7) HS (+) 132 (%57,4) IIEF Score 14 ( 10 – 20 ) IIEF Subgorup (n, %) Severe 28 (%12,2) Moderate 57 (%24,8) Mild-Moderate 61 (%26,5) Mild 29 (%12,6) Non – ED 55 (%23,9) IQR:interquartile range, BMI:bodd mass index, WS:waist circumfrance, AST:aspartate aminotransferase ALT:alanine aminotransferase,, LDL:low-density lipoprotein, GGT: gamma-glutamyl transferase, FLI:fatty liver index, HS:hepatosteatosis, IIEF:International Index of Erectile Function, ED:erectile dysfunction Comparison of demographic characteristics and biochemical parameters of groups are summarized in Table 2 . The analysis revealed that the age of the patients did not differ significantly between the groups (p > 0.05). However, BMI and WC were significantly higher in the group 1(p 0.05). In contrast, fasting blood glucose, ALT, and TG levels were significantly higher in the group 1 (p 0.05). However, AST and total testosterone levels were significantly lower in the group 1 (p < 0.05).Furthermore, FLI score was significantly higher in the group 1 (p < 0.05), suggesting a stronger association between HS and the ED. Table 2 Comparison of Demographic Characteristics and Biochemical Parameters Between Groups Groups Group 1(ED +) (n = 175, %76,1) Group 2 (ED -) (n = 55, %23,9) Median (IQR) n, % Median (IQR) n, % p -value Age (year) 49 (41–55) 50 (32–63) a 0,763 BMI (kg/m 2 ) 29,09 (26,29–32,07) 24,92 (23,40–28,39) a <0,001 * WC (cm) 104 (95–110) 92 (87–100) a <0,001 * Smoking (yes) 54 (%30,9) 18 (%32,7) b 0,794 Glucose (mg/dL) 101 (91–109) 93 (87–102) a 0,006 * AST (U/L) 20 (17–24) 22 (19–29) a 0,011 * ALT (U/L) 23 (17–31) 17 (14–29) a 0,008 * Total Cholesterole (mg/dL) 191 (163–224) 192 (172–211) a 0,479 LDL Cholesterole (mg/dL) 124 (105–148) 124 (100–150) a 0,693 Triglyceride (mg/dL) 151 (105–220) 104 (68–155) a <0,001 * GGT (U/L) 26 (20–36) 27 (20–38) a 0,869 Total Testosteron (ng/mL) 3,44 (2,61–4,45) 3,94 (3,38–4,83) a 0,004 * FLI Score 73,69 (50,03–86,26) 36,12 (22,45–71,48) a <0,001 * FLI Subgroup HS (-) 11 (%6,3) 21 (%38,2) b <0,001 * HS (Borderline) 51 (%29,1) 15 (%27,3) HS (+) 113 (%64,6) 19 (%34,5) a Mann-Whitney U test , b Pearson Chi-Square test , * p < 0,05 IQR:interquartile range, BMI:bodd mass index, WS:waist circumfrance, AST:aspartate aminotransferase ALT:alanine aminotransferase,, LDL:low-density lipoprotein, GGT: gamma-glutamyl transferase, FLI:fatty liver index, HS:hepatosteatosis, IIEF:International Index of Erectile Function, ED:erectile dysfunction In the univariate analysis, several factors demonstrated a significant impact (p 0.05) was observed for the ALT levels in distinguishing between the groups.In the multivariate analysis, WC, FLI score, and AST levels were identified as significant independent factors (p < 0.05) in the discrimination of patients between the groups ( Table 3 ). Table 3 Outcomes of the univariate and multivarete logistic regression analyses assesing the association between clinical variables and ED Univariate Model Multivariate Model OR %95 CI p OR %95 CI p BMI 1.308 1.181 - 1.448 < 0.001 WC(cm) 1.113 1.072 - 1.156 < 0.001 1.063 1.001 - 1.129 0.046 FLI Score 1.039 1.025 - 1.053 < 0.001 1.028 1.004 - 1.053 0.022 Fasting Blood Sugar 1.017 1.001 - 1.033 0.033 AST 0.954 0.921 - 0.988 0.008 0.919 0.878 - 0.963 < 0.001 ALT 1.009 0.988 - 1.029 0.410 TG 1.008 1.003 - 1.012 < 0.001 Total Testosterone(ng/ml) 0.791 0.638 - 0.980 0.032 Lojistik Regresyon (Forward LR) BMI:bodd mass index, WS:waist circumfrance, FLI:fatty liver index, AST:aspartate aminotransferase ALT:alanine aminotransferase,, GGT: gamma-glutamyl transferase , A significant efficiency was observed in using the FLI for discriminating between the groups patients, with an AUC of 0.756 (95% CI: 0.681–0.831). Additionally, the FLI with a cutoff value of 51 demonstrated significant efficiency in distinguishing between the groups, with an AUC of 0.715 (95% CI: 0.629–0.800). At a cut-off value of 51, the FLI had a sensitivity of 74.3%, a positive predictive value of 87.2%, a specificity of 66.5%, and a negative predictive value of 44.4% in distinguishing between patients with and without ED (Fig. 1 ). Association between ED severity and FLI scores is summarized in Table 4 . The analysis demonstrated a significant corelation between the severity of ED and the FLI score. The FLI score was significantly higher (p < 0.05) in the severe ED group compared to the moderate, mild-moderate, and mild ED groups. Similarly, the moderate ED group exhibited significantly higher (p < 0.05) FLI scores than the mild-moderate and mild ED groups.These findings indicate a progressive increase in FLI scores with increasing severity of erectile dysfunction, suggesting a potential association between HS and ED severity. Table-4: Association Between ED Severity and Fatty FLI Fatty Liver Index p Min-Max Median Mean ± sd IIEF Score ¹Severe ED 15.7 - 99.5 90.3 84.5 ± 17.6 < 0.001 K ²Moderate ED 17.0 - 99.0 82.8¹ 79.6 ± 15.4 ³Mild-Moderate ED 16.7 - 96.9 56.9¹² 58.5 ± 20.5 ⁴Mild ED 26.8 - 87.9 43.1¹²³ 49.1 ± 18.7 K Kruskal-wallis test ¹Difference with severe ED , ² Difference with moderate ED, ³ Difference with mild-moderate ED DISCUSSION In the present study, we investigated the relationship between NAFLD and ED and its severity using the FLI as a diagnostic parameter of HS. Our study results demonstrated that men diagnosed with ED had higher FLI scores. Additionally, subgroup analysis revealed a positive correlation between ED severity and FLI scores, suggesting a potential association between the progression of ED and the degree of HS. In this study, we tried to reveal the relationship between NAFLD, one of the early findings of MetS, and ED. Recent evidence suggests that endothelial dysfunction may represent one of the earliest contributors to hepatic fat accumulation and subsequent liver injury( 6 ). Liver sinusoidal endothelial cells function similarly to vascular endothelial cells and play a pivotal role in anti-inflammatory and antifibrotic processes ( 7 , 8 ). Moreover, impaired nitric oxide (NO) production has been implicated in the initiation and progression of hepatic inflammation, ultimately leading to the development of NAFLD and its potential progression to advanced liver disease ( 9 ). Recent human studies have demonstrated significant endothelial NO synthase (eNOS) dysfunction in patients with NAFLD, while animal models indicate that eNOS deficiency exacerbates the early stages of the disease ( 9 , 10 ). Notably, vascular endothelial dysfunction is also a well-established factor in the pathogenesis of ED ( 11 ). A hallmark of endothelial dysfunction is the reduced bioavailability of NO, which impairs the regulation of vascular tone, hindering the balance between vasodilation and vasoconstriction is one of the key mechanisms underlying ED development ( 12 ).NAFLD is recognized as one of the mixed pathophysiological pathways contributing to the development of ED( 13 ). Duman et al. were the first to prospectively investigate the relationship between NAFLD and ED in a cohort of 40 individuals. Their study demonstrated that patients with ED had significantly higher NAFLD scores compared to those without ED. Furthermore, histological analysis revealed that the severity of ED worsened as NAFLD-related liver damage progressed, suggesting a potential link between hepatic dysfunction and erectile impairment( 14 ). The findings of the present study indicate that the FLI score was significantly higher in the ED group compared to the non-ED group (p < 0.05). This finding reinforces the potential association between NAFLD and ED. Hasanain et al. found that older age, obesity, and hypertension were significantly more frequent in patients with NAFLD and ED, but multivariate analysis yielded only age as a variable associated with ED( 15 ). In the present study, similar to previous findings, BMI and WC values were significantly higher in the group with ED. When ED was evaluated in general, it was found to be more common in older men, and therefore, the higher the average age of the population analysed, the higher the prevalence of ED was found( 16 ). In contrast to previous literature, no age difference was observed between the groups in our study. This result could be due to the smaller sample size in the non-ED group. Previous studies have reported varying degrees of association between ED and different components of MetS, including obesity, hypertension, hyperglycemia, dyslipidemia, BMI, and elevated levels of cholesterol and high-density lipoprotein cholesterol( 17 , 18 ). Consistent with the existing literature, our study revealed that, in the univariate analysis, factors such as BMI, WC, fasting blood glucose, AST, TG, total testosterone, and the FLI significantly differentiated between patients with and without ED. Moreover, in the multivariate analysis, WC, AST, and the FLI exhibited significant and independent associations in distinguishing ED patients from those without the condition. In addition to these studies, it has been reported that NAFLD, another component of MetS, is an independent factor influencing ED. NAFLD is considered a hepatic manifestation of MetS, and recent animal and human studies have focused on evaluating the relationship between NAFLD and ED( 15 , 19 , 20 ). Our present study is the first study in the literature to examine the relationship between FLI and ED. The FLI is recognized as a surrogate marker for histological fatty liver. Previous studies have indicated that FLI is effective in identifying NAFLD when compared to ultrasound and in detecting the presence of hepatic fat infiltration in contrast to magnetic resonance spectroscopy ( 21 , 22 ). The advantage of using FLI lies in its ability to indicate a higher degree of hepatic steatosis with a higher score. An FLI score of < 30 is typically used to rule out HS, while an FLI of ≥ 60 suggests the presence of the disease in Caucasian populations ( 3 ). However, the optimal cutoff value of FLI for predicting NAFLD may vary for some populations. A study conducted in China suggested that FLI accurately detected NAFLD, with an optimal cutoff value of 30 in middle-aged and elderly Chinese individuals ( 22 ). In our ROC analysis, an FLI cutoff value of 51 predicted the presence of ED with a sensitivity of 74.3%, a PPV of 87.2%, and a specificity of 65.5%. In this study, we also examined the subgroups of ED based on the IIEF-5 scores in relation to the FLI. Our findings demonstrated that patients with ED exhibited significantly higher FLI values, which were positively correlated with the severity of ED. Although this study represents the first investigation into the relationship between ED severity and FLI, various markers of MetS have previously been explored in connection with ED severity. In accordance with the findings of Sambel et al., when assessing all ED subgroups, a significant difference was observed only between the mild and severe ED groups with respect to the triglyceride-glucose (TyG) index( 23 ). Our analyses further revealed that the FLI was notably effective in distinguishing severe ED from other ED subgroups. Likewise, the moderate ED group exhibited significantly higher FLI scores compared to the mild-moderate and mild ED groups. Additionally, the FLI score in the mild-moderate ED group was significantly elevated relative to the mild ED group. Given that ED may serve as an early indicator of underlying cardiovascular disease (CVD), assessing its severity could facilitate the identification of patients who may benefit from targeted interventions, including lifestyle modifications aimed at reducing both morbidity and mortality. This study has several limitations that should be considered. Firstly, the relatively small sample size, particularly in the control group, may restrict the generalizability and accuracy of the results. Secondly, while a thorough biochemical analysis was conducted for all participants, the lack of measurements for sex hormone-binding globulin (SHBG) and free testosterone levels represents a notable limitation. Thirdly, the diagnosis of ED was solely based on the IIEF-5 questionnaire, which provides a less objective assessment compared to more precise diagnostic methods, such as penile Doppler ultrasound. Furthermore, patients receiving treatment for ED were excluded from the study, thereby preventing the assessment of treatment effects and associated biomarkers within the scope of this research. Regarding the strengths of our study, it is the first study in the literature to explore the relationship between the FLI and ED. While FLI is not considered the gold standard for diagnosing fatty liver disease, as is the case with pathological results, it offers a practical and easily applicable method. In addition to the blood analyses recommended by the European Association of Urology (EAU) guidelines, anthropometric measurements, which can be conveniently performed in outpatient settings, may provide valuable insights into the potential metabolic syndrome status of patients presenting with ED. CONCLUSION This study reveals that FLI was significantly positively correlated with ED. Despite some limitations, the FLI proves to be a cost-free and practical marker for estimating the severity of organic ED. We believe that this index has the potential to be valuable in both diagnosing and assessing the severity of ED. However, additional studies are needed to confirm these findings and investigate the potential use of the FLI in shaping treatment strategies for ED. Declarations Conflict of Interest : The authors have nothing to disclose. Funding : None. Acknowledgments: None Authors’ Contributions: Research conception and design: Huseyin Aytac Ates Data acquisition: Huseyin Aytac Ates,Yusuf Sahin, Emrah Okucu Statistical analysis: Nejdet Karsiyakali Data analysis and interpretation: Huseyin Aytac Ates , Emre Karabay Drafting of the manuscript: Huseyin Aytac Ates, Yusuf Sahin, Emrah Okucu Supervision: All authors Approval of the final manuscript: All authors Ethics approval and consent to participate : This study has been performed in accordance with the Declaration of Helsinki and the protocol was reviewed and approved by Health Sciences University Derince Training and Research Hospital Local Ethics Committee (approval number:2020/107). Consent for publication : Not applicable. References Lazo M, Hernaez R, Eberhardt MS, Bonekamp S, Kamel I, Guallar E, Koteish A, Brancati FL, Clark JM. Prevalence of nonalcoholic fatty liver disease in the United States: the Third National Health and Nutrition Examination Survey, 1988–1994. 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Heart disease risk factors predict erectile dysfunction 25 years later: the Rancho Bernardo Study. J Am Coll Cardiol. 2004;43(8):1405–11. 10.1016/j.jacc.2003.11.041 . Raheem OA, Su JJ, Wilson JR, Hsieh TC. The Association of Erectile Dysfunction and Cardiovascular Disease: A Systematic Critical Review. Am J Mens Health. 2017;11(3):552–63. 10.1177/1557988316630305 . Marchesini G, Bugianesi E, Forlani G, Cerrelli F, Lenzi M, Manini R, Natale S, Vanni E, Villanova N, Melchionda N, Rizzetto M. Nonalcoholic fatty liver, steatohepatitis, and the metabolic syndrome. Hepatology. 2003;37(4):917–23. 10.1053/jhep.2003.50161 . Vignozzi L, Filippi S, Comeglio P, Cellai I, Sarchielli E, Morelli A, Rastrelli G, Maneschi E, Galli A, Vannelli GB, Saad F, Mannucci E, Adorini L, Maggi M. Nonalcoholic steatohepatitis as a novel player in metabolic syndrome-induced erectile dysfunction: an experimental study in the rabbit. Mol Cell Endocrinol. 2014;384(1–2):143–54. 10.1016/j.mce.2014.01.014 . Gastaldelli A, Kozakova M, Højlund K, Flyvbjerg A, Favuzzi A, Mitrakou A, Balkau B. RISC Investigators. Fatty liver is associated with insulin resistance, risk of coronary heart disease, and early atherosclerosis in a large European population. Hepatology. 2009;49(5):1537–44. 10.1002/hep.22845 . Huang X, Xu M, Chen Y, Peng K, Huang Y, Wang P, Ding L, Lin L, Xu Y, Chen Y, Lu J, Wang W, Bi Y, Ning G. Validation of the Fatty Liver Index for Nonalcoholic Fatty Liver Disease in Middle-Aged and Elderly Chinese. Med (Baltim). 2015;94(40):e1682. 10.1097/MD.0000000000001682 . Sambel M, Erdogan A, Caglayan V, Avci S, Kilic S, Yildiz HE, Keskin E. Can atherogenic indices and the triglyceride-glucose index be used to predict erectile dysfunction? Sex Med. 2024;11(6):qfad069. 10.1093/sexmed/qfad069 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 25 Jul, 2025 Read the published version in BMC Urology → Version 1 posted Editorial decision: Revision requested 14 May, 2025 Reviewers agreed at journal 13 May, 2025 Reviews received at journal 09 May, 2025 Reviewers agreed at journal 09 May, 2025 Reviewers agreed at journal 08 May, 2025 Reviews received at journal 08 May, 2025 Reviewers agreed at journal 08 May, 2025 Reviewers agreed at journal 08 May, 2025 Reviewers agreed at journal 08 May, 2025 Reviewers invited by journal 08 May, 2025 Editor invited by journal 08 May, 2025 Editor assigned by journal 05 May, 2025 Submission checks completed at journal 05 May, 2025 First submitted to journal 29 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies 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-6553567","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":454887052,"identity":"25914cda-6ded-499b-8d73-e16975a58bc5","order_by":0,"name":"Huseyin Aytac Ates","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYBACAyQ24wMgwcNHlJYDIKUMDMwgDg8bKVrYJEAcglrMGZifSX+osZO3Z29/Vvk1x06GjYH54aMbeLRYNrCZSRw4lmzYw3PG7LbstmSgw9iMjXPwOewAA1AL2wHGHokcttuS25iBWnjYpPFrYf8mceDfAfse+efPiiW31ROjhcdM4mDbgcQeCQYzxo/bDhOh5TBPscXZvuTknjM5xtKM247zsDET8svx9o03Kr7Z2ba3H3/48ee2ant+9uaHj/FpYWBmYJGAs3kgIgQB8wcYi/EHYdWjYBSMglEwAgEAUFpEgU2nwcAAAAAASUVORK5CYII=","orcid":"","institution":"İstanbul Eğitim ve Araştırma Hastanesi","correspondingAuthor":true,"prefix":"","firstName":"Huseyin","middleName":"Aytac","lastName":"Ates","suffix":""},{"id":454887053,"identity":"93711203-1445-4328-b241-fda4ae448cdd","order_by":1,"name":"Emrah Okucu","email":"","orcid":"","institution":"İstanbul Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Emrah","middleName":"","lastName":"Okucu","suffix":""},{"id":454887054,"identity":"4a85079a-c23f-4206-be90-e48ae20d83a3","order_by":2,"name":"Yusuf Sahin","email":"","orcid":"","institution":"İstanbul Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Yusuf","middleName":"","lastName":"Sahin","suffix":""},{"id":454887055,"identity":"b68037d6-8a15-405b-8e3b-86f94ab06157","order_by":3,"name":"Nejdet Karsiyakali","email":"","orcid":"","institution":"Acıbadem University","correspondingAuthor":false,"prefix":"","firstName":"Nejdet","middleName":"","lastName":"Karsiyakali","suffix":""},{"id":454887056,"identity":"fb6d08b4-ac6e-42e0-b275-d7da0d46929b","order_by":4,"name":"Emre Karabay","email":"","orcid":"","institution":"Acıbadem University","correspondingAuthor":false,"prefix":"","firstName":"Emre","middleName":"","lastName":"Karabay","suffix":""}],"badges":[],"createdAt":"2025-04-29 07:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6553567/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6553567/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12894-025-01865-w","type":"published","date":"2025-07-25T15:57:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82713425,"identity":"7a91d2bc-4750-4d2e-8ee0-2f7f205c7ffb","added_by":"auto","created_at":"2025-05-14 11:52:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36632,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe TyG index was found to have a significant effectiveness in distinguishing between patients with and without erectile dysfunction [Area under the curve 0.706 (0.626-0.786)]. The TyG index with a cut-off value of 4.678 was also found to have significant effectiveness in distinguishing between patients with and without erectile dysfunction [Area under the curve 0.649 (0.565-0.734)].\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6553567/v1/1c8f75ea19fefdff4211b0df.png"},{"id":88506164,"identity":"982d4742-aca0-4c73-aa57-8d29c4d62780","added_by":"auto","created_at":"2025-08-07 07:32:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":898294,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6553567/v1/4e51159a-2983-41b0-a70e-7531e1837ba2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Potential Utility Of The Fatty Liver Index As A Predictor Of Erectile Dysfunction And Its Severity","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eNon-alcoholic fatty liver disease (NAFLD), characterized by an increase in liver fat content due to factors other than excessive alcohol consumption. It has emerged as a global public health concern, particularly affecting individuals with type 2 diabetes mellitus and morbid obesity. Epidemiological studies estimate its prevalence to range between 20% and 30% in the general population, highlighting its widespread impact and the necessity for early detection and management. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).The etiology of NAFLD is closely associated with metabolic abnormalities, including dyslipidemia, obesity, and type 2 diabetes mellitus, which are also major contributors to the pathogenesis of metabolic syndrome and subsequent cardiovascular diseases. Given this strong association, NAFLD is widely recognized as the hepatic manifestation of metabolic syndrome(MetS)(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUltrasonography remains the most widely utilized imaging modality for the diagnosis of NAFLD, primarily due to its cost-effectiveness, non-invasive nature, and broad accessibility. However, its diagnostic accuracy is inherently limited by operator dependency, introducing a degree of subjectivity. To address this limitation, Bedogni et al. developed the Fatty Liver Index(FLI), a simple and rapid clinical tool that has demonstrated a strong correlation with abdominal ultrasonography in population-based studies. Their findings indicate that a FLI score of ≤ 30 effectively excludes hepatosteatosis(HS), whereas a score ≥ 60 is strongly suggestive of the condition, offering a practical alternative for risk stratification in clinical and epidemiological settings. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eFLI is a mathematical model derived from key metabolic parameters, Boddy Mass Index(BMI), waist circumference (WC), triglycerides(TG) levels, and gamma-glutamyl transferase (GGT) values. This index serves as a non-invasive tool for estimating HS. A study conducted in a European population demonstrated a significant association between FLI and metabolic dysfunctions, including insulin resistance (IR), coronary artery disease (CAD), and early atherosclerosis. These findings underscore the potential utility of FLI not only as a diagnostic marker for NAFLD but also as an indicator of cardiometabolic risk.(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eErectile dysfunction (ED), defined as the impairment of sexual function, extends beyond its impact on sexual health and is increasingly regarded as an early clinical marker of MetS(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Recent meta-analytical data indicate that the prevalence of ED is 2.6 times higher in individuals with metabolic syndrome compared to the general population(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). From an etiological perspective, the pathophysiological mechanisms underlying ED closely overlap with those of NAFLD, suggesting shared metabolic risk factors such as IR, dyslipidemia, obesity, and endothelial dysfunction. This association highlights the importance of a comprehensive metabolic assessment in patients presenting with ED.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn this study, we aimed to explore the relationship between two clinical manifestations of MetS; ED and NAFLD. Additionally, we sought to assess NAFLD status in patients diagnosed with ED. To enhance the originality of our study, we employed the FLI as a diagnostic parameter for NAFLD, given its strong correlation with ultrasonographic assessments. By utilizing FLI instead of conventional ultrasound-based evaluations, we aimed to provide a non-invasive, objective, and reproducible approach to investigating the association between ED and NAFLD. To our knowledge, this is the first study to investigate the relationship between FLI and ED and its severity.\u003c/p\u003e"},{"header":"MATERIALS-METHODS","content":"\u003ch3\u003e1. Ethics\u003c/h3\u003e\u003cp\u003e This study was conducted in accordance with the ethical principles set forth in the Declaration of Helsinki. All participants were fully informed about the study's purpose and provided written informed consent. Ethical approval was granted by the Local Ethics Committee of Health Science University Derince Training and Research Hospital.(approval number: 2020–107).\u003c/p\u003e\u003ch2\u003e2. Selection of Participants\u003c/h2\u003e\u003cp\u003e A total of 230 males, aged 18 to 75, who visited the Urology Clinic of Gebze Fatih State Hospital between Semptember 1 2020, and July 1 2022 with complain of ED participated in the study. The study population was initially classified into ED(group 1) and non-ED (group 2) groups based on the 5-item International Index of Erectile Function (IIEF-5) scores, with scores of 5–21 indicating ED and scores of 22–25 indicating non-ED. The ED group was further subdivided into subgroups: severe ED (5–7 points), moderate ED (8–11 points), mild-moderate ED (12–16 points), and mild ED (17–21 points).\u003c/p\u003e\u003cp\u003ePatients were excluded from the study if they were receiving medical treatment for hyperlipidemia or diabetes mellitus, had a weekly alcohol intake of ≥ 140 grams, or had a history of advanced cardiovascular disease. Furthermore, individuals with a history of oncological diseases, viral or autoimmune hepatitis, liver and biliary tract disorders associated with cholestasis, metabolic liver diseases, corticosteroid use, immunodeficiency, or psychiatric illnesses were also excluded. These exclusion criteria were implemented to minimize potential confounding factors and ensure a more homogenous study population for the accurate assessment of the relationship between ED and NAFLD.\u003c/p\u003e\u003ch3\u003e3. Study Variables\u003c/h3\u003e\u003cp\u003eIn this planned study, the biochemical parameters of patients diagnosed with ED, including blood triglycerides, glucose, ALT, AST, GGT, low-density lipoprotein (LDL), and total cholesterol were evaluated. Additionally, patients were classified based on their recorded BMI and WC measurements. Fasting blood samples were collected from venous blood between 08:00 and 10:00 in the morning to ensure standardized metabolic assessments and minimize diurnal variations in biochemical parameters.\u003c/p\u003e\u003cp\u003eFLI was calculated using the following formula:\u003c/p\u003e\u003cp\u003eFLI = (e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (ggt) + 0.053*waist circumference − 15.745) / (1 + e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (ggt) + 0.053*waist circumference − 15.745) * 100\u003c/p\u003e\u003cp\u003eInterpretation of FLI scores; FLI score below 30 was considered to effectively exclude hepatic steatosis, FLI score above 60 was indicative of HS, individuals with an FLI score between 30 and 60 were classified as the borderline group, requiring further evaluation.This classification allowed for a standardized, non-invasive assessment of HS, minimizing the reliance on imaging-based diagnostic methods.\u003c/p\u003e\u003ch2\u003e4. Statistical Analysis:\u003c/h2\u003e\u003cp\u003eThe Kolmogorov Smirnov test was used to check the normality of data for quantitative variables. Descriptive data were expressed in median and interquartile range, and frequency. The Pearson chi-square,and Mann-Whitney-U tests were used wherever possible. ROC curve analysis was conducted to determine effect size and cutoff values, and both univariate and multivariate logistic regression analyses were performed to assess the strength of associations. All statistical analyses were performed using SPSS version 27.0 software. Furthermore, a separate Receiver Operating Characteristic (ROC) analysis was conducted to calculate the area under the curve (AUC), and the relevance of the cut-off value for significant efficacy of FLI in differentiating control and case group patients.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eAfter applying the exclusion criteria, the demographic and biochemical parameters of the remaining 230 patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Based on the IIEF-5 scoring, 55 patients were classified as non-ED(group 1), while 175 patients were diagnosed with ED(group 2). Among the patients with ED, the majority were categorized within the mild to moderate ED group. Furthermore, according to FLI scores, 132 patients were classified as having HS, representing the majority of the study population.\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 and baseline clinical characteristics of study patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (41\u0026ndash;57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28,18 (25,38\u0026ndash;31,10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWS (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 (94\u0026ndash;110)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoking(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158 (%68,7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (%31,3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97 (90\u0026ndash;108)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (18\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (16\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal\u0026nbsp;Cholesterol\u0026nbsp; (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192 (163\u0026ndash;220)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLDL Cholesterol\u0026nbsp; (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 (102\u0026ndash;148)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTriglyceride (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (100\u0026ndash;205)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGGT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (20\u0026ndash;37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Testosteron (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,59 (2,77\u0026ndash;4,50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFLI Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68,66 (39,32\u0026ndash;84,40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFLI Subgroup (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHS (-)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (%13,9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHS (Borderline)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (%28,7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHS (+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132 (%57,4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIIEF Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eIIEF Subgorup (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (%12,2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (%24,8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild-Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (%26,5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (%12,6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon \u0026ndash; ED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (%23,9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIQR:interquartile range, BMI:bodd mass index, WS:waist circumfrance, AST:aspartate aminotransferase ALT:alanine aminotransferase,, LDL:low-density lipoprotein, GGT: gamma-glutamyl transferase, FLI:fatty liver index, HS:hepatosteatosis, IIEF:International Index of Erectile Function, ED:erectile dysfunction\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eComparison of demographic characteristics and biochemical parameters of groups are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The analysis revealed that the age of the patients did not differ significantly between the groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, BMI and WC were significantly higher in the group 1(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).The smoking rate did not show a significant difference between the groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In contrast, fasting blood glucose, ALT, and TG levels were significantly higher in the group 1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).Total cholesterol, LDL cholesterol, and GGT levels did not differ significantly between the groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, AST and total testosterone levels were significantly lower in the group 1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).Furthermore, FLI score was significantly higher in the group 1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting a stronger association between HS and the ED.\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\u003eComparison of Demographic Characteristics and Biochemical Parameters Between 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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eGroup 1(ED +)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;175, %76,1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eGroup 2 (ED -)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;55, %23,9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (41\u0026ndash;55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50 (32\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,763\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29,09 (26,29\u0026ndash;32,07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24,92 (23,40\u0026ndash;28,39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u0026lt;0,001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWC (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (95\u0026ndash;110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92 (87\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u0026lt;0,001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking (yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (%30,9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (%32,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e0,794\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 (91\u0026ndash;109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93 (87\u0026ndash;102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,006\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (17\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (19\u0026ndash;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,011\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (17\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (14\u0026ndash;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,008\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Cholesterole (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191 (163\u0026ndash;224)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e192 (172\u0026ndash;211)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLDL Cholesterole (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 (105\u0026ndash;148)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124 (100\u0026ndash;150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,693\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTriglyceride (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151 (105\u0026ndash;220)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104 (68\u0026ndash;155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u0026lt;0,001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGGT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (20\u0026ndash;36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (20\u0026ndash;38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Testosteron (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,44 (2,61\u0026ndash;4,45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,94 (3,38\u0026ndash;4,83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e0,004\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFLI Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73,69 (50,03\u0026ndash;86,26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36,12 (22,45\u0026ndash;71,48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u0026lt;0,001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFLI Subgroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHS (-)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (%6,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21 (%38,2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u0026lt;0,001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHS (Borderline)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (%29,1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 (%27,3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHS (+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113 (%64,6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (%34,5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eMann-Whitney U test\u003c/em\u003e, \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003cem\u003ePearson Chi-Square test\u003c/em\u003e, \u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0,05\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eIQR:interquartile range, BMI:bodd mass index, WS:waist circumfrance, AST:aspartate aminotransferase ALT:alanine aminotransferase,, LDL:low-density lipoprotein, GGT: gamma-glutamyl transferase, FLI:fatty liver index, HS:hepatosteatosis, IIEF:International Index of Erectile Function, ED:erectile dysfunction\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the univariate analysis, several factors demonstrated a significant impact (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on the discrimination between the groups, including BMI, WC, FLI score, fasting blood glucose, AST, TG, and total testosterone levels. However, no significant effect (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) was observed for the ALT levels in distinguishing between the groups.In the multivariate analysis, WC, FLI score, and AST levels were identified as significant independent factors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the discrimination of patients between the groups \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\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\u003eOutcomes of the univariate and multivarete logistic regression analyses assesing the association between clinical variables and ED\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eUnivariate Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eMultivariate Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e%95 CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003e%95 CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWC(cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLI Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting Blood Sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Testosterone(ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLojistik Regresyon (Forward LR)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eBMI:bodd mass index, WS:waist circumfrance, FLI:fatty liver index, AST:aspartate aminotransferase ALT:alanine aminotransferase,, GGT: gamma-glutamyl transferase\u003c/em\u003e,\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA significant efficiency was observed in using the FLI for discriminating between the groups patients, with an AUC of 0.756 (95% CI: 0.681\u0026ndash;0.831). Additionally, the FLI with a cutoff value of 51 demonstrated significant efficiency in distinguishing between the groups, with an AUC of 0.715 (95% CI: 0.629\u0026ndash;0.800). At a cut-off value of 51, the FLI had a sensitivity of 74.3%, a positive predictive value of 87.2%, a specificity of 66.5%, and a negative predictive value of 44.4% in distinguishing between patients with and without ED (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAssociation between ED severity and FLI scores is summarized in \u003cb\u003eTable\u0026nbsp;4\u003c/b\u003e. The analysis demonstrated a significant corelation between the severity of ED and the FLI score. The FLI score was significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the severe ED group compared to the moderate, mild-moderate, and mild ED groups. Similarly, the moderate ED group exhibited significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) FLI scores than the mild-moderate and mild ED groups.These findings indicate a progressive increase in FLI scores with increasing severity of erectile dysfunction, suggesting a potential association between HS and ED severity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eTable-4: Association Between ED Severity and Fatty FLI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e \u003cp\u003eFatty Liver Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eIIEF Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026sup1;Severe ED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003csup\u003eK\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026sup2;Moderate ED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.8\u0026sup1;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026sup3;Mild-Moderate ED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.9\u0026sup1;\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e⁴Mild ED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.1\u0026sup1;\u0026sup2;\u0026sup3;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003eK\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eKruskal-wallis test \u0026sup1;Difference with severe ED\u003c/em\u003e,\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003e\u0026sup2; Difference with moderate ED, \u0026sup3; Difference with mild-moderate ED\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn the present study, we investigated the relationship between NAFLD and ED and its severity using the FLI as a diagnostic parameter of HS. Our study results demonstrated that men diagnosed with ED had higher FLI scores. Additionally, subgroup analysis revealed a positive correlation between ED severity and FLI scores, suggesting a potential association between the progression of ED and the degree of HS.\u003c/p\u003e \u003cp\u003eIn this study, we tried to reveal the relationship between NAFLD, one of the early findings of MetS, and ED. Recent evidence suggests that endothelial dysfunction may represent one of the earliest contributors to hepatic fat accumulation and subsequent liver injury(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Liver sinusoidal endothelial cells function similarly to vascular endothelial cells and play a pivotal role in anti-inflammatory and antifibrotic processes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Moreover, impaired nitric oxide (NO) production has been implicated in the initiation and progression of hepatic inflammation, ultimately leading to the development of NAFLD and its potential progression to advanced liver disease (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Recent human studies have demonstrated significant endothelial NO synthase (eNOS) dysfunction in patients with NAFLD, while animal models indicate that eNOS deficiency exacerbates the early stages of the disease (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Notably, vascular endothelial dysfunction is also a well-established factor in the pathogenesis of ED (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). A hallmark of endothelial dysfunction is the reduced bioavailability of NO, which impairs the regulation of vascular tone, hindering the balance between vasodilation and vasoconstriction is one of the key mechanisms underlying ED development (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).NAFLD is recognized as one of the mixed pathophysiological pathways contributing to the development of ED(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Duman et al. were the first to prospectively investigate the relationship between NAFLD and ED in a cohort of 40 individuals. Their study demonstrated that patients with ED had significantly higher NAFLD scores compared to those without ED. Furthermore, histological analysis revealed that the severity of ED worsened as NAFLD-related liver damage progressed, suggesting a potential link between hepatic dysfunction and erectile impairment(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The findings of the present study indicate that the FLI score was significantly higher in the ED group compared to the non-ED group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This finding reinforces the potential association between NAFLD and ED. Hasanain et al. found that older age, obesity, and hypertension were significantly more frequent in patients with NAFLD and ED, but multivariate analysis yielded only age as a variable associated with ED(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In the present study, similar to previous findings, BMI and WC values were significantly higher in the group with ED. When ED was evaluated in general, it was found to be more common in older men, and therefore, the higher the average age of the population analysed, the higher the prevalence of ED was found(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In contrast to previous literature, no age difference was observed between the groups in our study. This result could be due to the smaller sample size in the non-ED group.\u003c/p\u003e \u003cp\u003ePrevious studies have reported varying degrees of association between ED and different components of MetS, including obesity, hypertension, hyperglycemia, dyslipidemia, BMI, and elevated levels of cholesterol and high-density lipoprotein cholesterol(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Consistent with the existing literature, our study revealed that, in the univariate analysis, factors such as BMI, WC, fasting blood glucose, AST, TG, total testosterone, and the FLI significantly differentiated between patients with and without ED. Moreover, in the multivariate analysis, WC, AST, and the FLI exhibited significant and independent associations in distinguishing ED patients from those without the condition. In addition to these studies, it has been reported that NAFLD, another component of MetS, is an independent factor influencing ED. NAFLD is considered a hepatic manifestation of MetS, and recent animal and human studies have focused on evaluating the relationship between NAFLD and ED(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Our present study is the first study in the literature to examine the relationship between FLI and ED. The FLI is recognized as a surrogate marker for histological fatty liver. Previous studies have indicated that FLI is effective in identifying NAFLD when compared to ultrasound and in detecting the presence of hepatic fat infiltration in contrast to magnetic resonance spectroscopy (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The advantage of using FLI lies in its ability to indicate a higher degree of hepatic steatosis with a higher score. An FLI score of \u0026lt;\u0026thinsp;30 is typically used to rule out HS, while an FLI of \u0026ge;\u0026thinsp;60 suggests the presence of the disease in Caucasian populations (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, the optimal cutoff value of FLI for predicting NAFLD may vary for some populations. A study conducted in China suggested that FLI accurately detected NAFLD, with an optimal cutoff value of 30 in middle-aged and elderly Chinese individuals (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In our ROC analysis, an FLI cutoff value of 51 predicted the presence of ED with a sensitivity of 74.3%, a PPV of 87.2%, and a specificity of 65.5%.\u003c/p\u003e \u003cp\u003eIn this study, we also examined the subgroups of ED based on the IIEF-5 scores in relation to the FLI. Our findings demonstrated that patients with ED exhibited significantly higher FLI values, which were positively correlated with the severity of ED. Although this study represents the first investigation into the relationship between ED severity and FLI, various markers of MetS have previously been explored in connection with ED severity. In accordance with the findings of Sambel et al., when assessing all ED subgroups, a significant difference was observed only between the mild and severe ED groups with respect to the triglyceride-glucose (TyG) index(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Our analyses further revealed that the FLI was notably effective in distinguishing severe ED from other ED subgroups. Likewise, the moderate ED group exhibited significantly higher FLI scores compared to the mild-moderate and mild ED groups. Additionally, the FLI score in the mild-moderate ED group was significantly elevated relative to the mild ED group. Given that ED may serve as an early indicator of underlying cardiovascular disease (CVD), assessing its severity could facilitate the identification of patients who may benefit from targeted interventions, including lifestyle modifications aimed at reducing both morbidity and mortality.\u003c/p\u003e \u003cp\u003eThis study has several limitations that should be considered. Firstly, the relatively small sample size, particularly in the control group, may restrict the generalizability and accuracy of the results. Secondly, while a thorough biochemical analysis was conducted for all participants, the lack of measurements for sex hormone-binding globulin (SHBG) and free testosterone levels represents a notable limitation. Thirdly, the diagnosis of ED was solely based on the IIEF-5 questionnaire, which provides a less objective assessment compared to more precise diagnostic methods, such as penile Doppler ultrasound. Furthermore, patients receiving treatment for ED were excluded from the study, thereby preventing the assessment of treatment effects and associated biomarkers within the scope of this research.\u003c/p\u003e \u003cp\u003eRegarding the strengths of our study, it is the first study in the literature to explore the relationship between the FLI and ED. While FLI is not considered the gold standard for diagnosing fatty liver disease, as is the case with pathological results, it offers a practical and easily applicable method. In addition to the blood analyses recommended by the European Association of Urology (EAU) guidelines, anthropometric measurements, which can be conveniently performed in outpatient settings, may provide valuable insights into the potential metabolic syndrome status of patients presenting with ED.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study reveals that FLI was significantly positively correlated with ED. Despite some limitations, the FLI proves to be a cost-free and practical marker for estimating the severity of organic ED. We believe that this index has the potential to be valuable in both diagnosing and assessing the severity of ED. However, additional studies are needed to confirm these findings and investigate the potential use of the FLI in shaping treatment strategies for ED.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The authors have nothing to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e None.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch conception and design:\u003c/strong\u003e Huseyin Aytac Ates\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData acquisition:\u003c/strong\u003e Huseyin Aytac Ates,Yusuf Sahin, Emrah Okucu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e Nejdet Karsiyakali\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis and interpretation:\u003c/strong\u003e Huseyin Aytac Ates , Emre Karabay\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDrafting of the manuscript:\u003c/strong\u003e Huseyin Aytac Ates, Yusuf Sahin, Emrah Okucu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupervision:\u003c/strong\u003e All authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eApproval of the final manuscript:\u003c/strong\u003e All authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e :\u003c/p\u003e\n\u003cp\u003eThis study has been performed in accordance with the Declaration of Helsinki and the protocol was reviewed and approved by Health Sciences University Derince Training and Research Hospital Local Ethics Committee (approval number:2020/107).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLazo M, Hernaez R, Eberhardt MS, Bonekamp S, Kamel I, Guallar E, Koteish A, Brancati FL, Clark JM. 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Can atherogenic indices and the triglyceride-glucose index be used to predict erectile dysfunction? Sex Med. 2024;11(6):qfad069. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/sexmed/qfad069\u003c/span\u003e\u003cspan address=\"10.1093/sexmed/qfad069\" 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":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-urology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"buro","sideBox":"Learn more about [BMC Urology](http://bmcurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/buro/default.aspx","title":"BMC Urology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Erectile Dysfunction, Fatty Liver Index, Hepatosteatosis, Metabolic Syndrome","lastPublishedDoi":"10.21203/rs.3.rs-6553567/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6553567/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThe aim of this study was to evaluate the relationship between Fatty Liver Index(FLI) and Erectile Dysfunction(ED) and its severity.\u003c/p\u003e\u003ch2\u003eMaterials And Methods\u003c/h2\u003e \u003cp\u003eA group of 230 male patients with ED complaints underwent evaluation. Comprehensive routine blood serum tests were conducted to identify potential etiological factors contributing to ED. Additionally, waist circumference(WC) measurements were obtained to facilitate the calculation of the FLI. Participants were also asked to complete the validated Turkish adaptation of the 5-item International Index of Erectile Function (IIEF-5) questionnaire to assess the severity and impact of ED.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOut of all participants, 55 were classified as non-ED, while 175 were diagnosed with ED, mostly in the mild to moderate category. According to FLI scores, 132 had hepatic steatosis(HS). Body mass index (BMI) and WC were significantly higher in the ED group. Fasting blood glucose, ALT, and triglycerides (TG) were elevated in those with ED, while AST and total testosterone levels were lower. A significant association was found between higher FLI scores and ED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The FLI score was significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the severe ED group compared to the moderate, mild-moderate, and mild ED groups.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBased on the results of our study, the FLI appears to be a simple method that shows a high correlation with the severity of ED. We believe that the use of the FLI in the diagnosis and follow-up of ED is noteworthy, and further prospective studies with larger sample sizes are needed to support this conclusion.\u003c/p\u003e","manuscriptTitle":"Potential Utility Of The Fatty Liver Index As A Predictor Of Erectile Dysfunction And Its Severity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-14 11:52:28","doi":"10.21203/rs.3.rs-6553567/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-14T19:57:43+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"83173244558325253821279322633403895138","date":"2025-05-13T12:32:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-09T20:39:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244985234622441823902774933128721650389","date":"2025-05-09T20:33:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"85465267424005255975703904561100734147","date":"2025-05-09T02:29:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-09T01:58:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60014105902306950440778670662073303246","date":"2025-05-09T00:47:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188200376611577704009633478985097902176","date":"2025-05-08T20:46:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214849926984588772151681318801809574807","date":"2025-05-08T20:21:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-08T20:04:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-08T18:10:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-05T14:15:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-05T14:14:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Urology","date":"2025-04-29T07:13:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-urology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"buro","sideBox":"Learn more about [BMC Urology](http://bmcurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/buro/default.aspx","title":"BMC Urology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6e0a481a-74cc-4665-b8c1-91edbaa91edc","owner":[],"postedDate":"May 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-07T07:19:30+00:00","versionOfRecord":{"articleIdentity":"rs-6553567","link":"https://doi.org/10.1186/s12894-025-01865-w","journal":{"identity":"bmc-urology","isVorOnly":false,"title":"BMC Urology"},"publishedOn":"2025-07-25 15:57:34","publishedOnDateReadable":"July 25th, 2025"},"versionCreatedAt":"2025-05-14 11:52:28","video":"","vorDoi":"10.1186/s12894-025-01865-w","vorDoiUrl":"https://doi.org/10.1186/s12894-025-01865-w","workflowStages":[]},"version":"v1","identity":"rs-6553567","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6553567","identity":"rs-6553567","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}