Incidence and risk factors of heart failure in patients with varicose veins of lower extremities: a retrospective nationwide inpatient sample database study

Incidence and risk factors of heart failure in patients with varicose veins of lower extremities: a retrospective nationwide inpatient sample database study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Incidence and risk factors of heart failure in patients with varicose veins of lower extremities: a retrospective nationwide inpatient sample database study Yinglan Huang, Yangzhu Liu, Kai Dai, Fuwei Liu, Ling Wei, Li Xiao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6498400/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Objective To investigate the incidence and risk factors of (HF)in patients with varicose veins of the lower extremities (VVLEs) using a large-scale national database. Methods We conducted a retrospective analysis using data from the Nationwide Inpatient Sample (NIS) database spanning 2010 to 2019. The study population included individuals diagnosed with VVLEs. Our evaluation covered various parameters, including patient demographics, hospital characteristics, length of stay, total hospitalization charges, in-hospital mortality, comorbidities, and associated clinical complications. Results Analysis of the NIS database identified 120,748 individuals with VVLEs who met the inclusion criteria. HF developed in 16,463 cases within this cohort, resulting in an overall incidence rate of 14.4%. A temporal analysis revealed a substantial increase in HF occurrence throughout the study period, rising from 1.5% in 2010 to 29.8% in 2019. The comparative assessment showed that VVLEs patients with HF experienced more extended hospital stays, incurred higher healthcare costs, were more likely to utilize Medicare, and had higher in-hospital mortality rates than those that did not experience HF ( P < 0.001). Risk factors for HF included advanced age (≥ 65 years), Black race, comorbidities (n ≥ 1), treatment at a teaching hospital, hospitalization in the South, female sex, private insurance, elective admission, urban hospital setting, chronic pulmonary disease, fluid and electrolyte disorders, obesity, pulmonary circulation disorders, renal failure, valvular disease, weight loss, diabetes with chronic complications, and peptic ulcer disease (excluding bleeding). Moreover, HF was associated with wound infection, blood transfusion, hemorrhage/ seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg. Conclusions Studying the risk factors associated with HF in patients with VVLEs is essential for implementing preventive management strategies and optimizing patient outcomes. Heart failure varicose veins of lower extremities risk factors incidence Nationwide inpatient sample Figures Figure 1 Figure 2 Introduction Lower extremity varicose veins (VVLEs) are a highly prevalent vascular condition, affecting 14–64% of the general population [ 1 , 2 ]. This condition is characterized by symptoms such as leg pain, swelling, itching, and fatigue but can also progress to more severe manifestations, including skin pigmentation, eczema, induration, and ulceration, significantly impairing patients' quality of life [ 3 , 4 ]. While recent research has enhanced our understanding of the pathophysiology and management of VVLEs, their pathogenesis remains poorly understood [ 1 ]. Current evidence suggests that VVLEs is a complex disease with a multifactorial pathogenesis involving genetic, lifestyle, occupational, cellular, extracellular, and hemodynamic factors [ 5 – 7 ]. Of note, the fundamental characteristics of primary and secondary chronic venous disease are centered on hemodynamic abnormalities [ 8 ]. As hemodynamics are intricately linked to cardiac circulation, the bidirectional relationship between heart disease and VVLEs has garnered widespread attention [ 9 ]. Heart failure (HF) is a heterogeneous clinical syndrome resulting from the progression of various heart diseases to advanced stages [ 10 ]. HF affects an estimated 56 million individuals globally, imposing a significant health burden characterized by reduced quality of life, frequent hospitalizations, rising healthcare costs, and increased premature mortality rates [ 11 – 13 ]. With an aging population and incremental improvements in survival rates, the prevalence of HF is projected to rise by as much as 46% by 2030 [ 14 ]. Consequently, identifying and understanding factors contributing to HF risk is paramount. Previous studies have reported several risk factors for HF, including hypertension, obesity, diabetes, sex, advancing age, and a sedentary lifestyle [ 13 , 15 ]. Nevertheless, further research is warranted to identify and address modifiable risk factors influencing HF development. Recent studies have identified chronic venous insufficiency as an independent risk factor for cardiovascular and peripheral artery diseases [ 9 , 16 , 17 ]. Furthermore, common risk factors such as hypertension, diabetes, obesity, smoking, and endothelial dysfunction have been shown to independently contribute to cardiovascular diseases in patients with varicose veins [ 16 , 18 ]. To date, no study has yet comprehensively examined HF incidence and risk factors in patients with VVLEs using a large sample size. Given the above evidence, we surmise that VVLEs might be potentially associated with an increased risk of HF. Therefore, the present study aims to investigate the frequency and contributing factors of HF in patients with VVLEs using data acquired from a nationwide database. Materials and methods Data source This study utilized data from the Nationwide Inpatient Sample (NIS), the largest publicly accessible database of fully paid inpatient medical records in the United States. This database is maintained by the Healthcare Cost and Utilization Project (HCUP) and supported by the Agency for Healthcare Research and Quality (AHRQ). It includes information from over seven million hospital admissions, representing approximately 20% of annual hospitalizations [ 16 , 19 ]. Data extraction for this study included patient demographics (age, sex, race), hospital characteristics (insurance type, admission type, bed capacity, teaching status, geographic location, and region), length of stay (LOS), financial metrics, and diagnostic and procedural codes from the International Classification of Diseases, Clinical Modification (ICD-9-CM and ICD-10-CM). Ethical review board approval was not required as this study used anonymized, publicly available data. Data collection Data from 2010 to 2019 were extracted from the NIS database. VVLEs cases were identified using procedure codes from both the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) [ 6 ]. The initial diagnosis date of VVLEs served as the index date for this study. To ensure diagnostic accuracy and minimize confounding, patients were included if they had a diagnosis of VVLEs based on ICD-9-CM codes (454.0, 454.1, 454.2, 454.8, 454.9) and ICD-10-CM codes (I83.0, I83.1, I83.2, I83.8, I83.9). Patients under 18 years old and those with incomplete data were excluded from the analysis (Fig. 1). Participants were assigned to two groups: those with and without a HF diagnosis. We assessed patient demographics, hospital characteristics, and outcomes, including LOS, economic indicators, and in-hospital mortality. Comorbidities and complications were identified using ICD-9-CM and ICD-10-CM diagnostic codes (Table 1 ). Additional complications included wound infection, blood transfusion, hemorrhage/seroma/ hematoma, deep venous thrombosis, pulmonary embolism, stroke, cellulitis of the leg, noninfectious lymphatic channel disorders, seborrheic dermatitis, and arteriovenous fistulas. Table 1 Variables used in binary logistic regression analysis Variables Categories Specific Variables Patient demographics Age (≤ 64 years and ≥ 65 years), sex (male and female), race (White, Black, Hispanic, Asian or Pacific Islander, Native American and Other) Hospital characteristics Type of admission (non-elective, elective), bed size of hospital (small, medium, large), teaching status of hospital (nonteaching, teaching), location of hospital (rural, urban), type of insurance (medicare, medicaid, private insurance, self-pay, no charge, other), location of the hospital (northeast, midwest or north central, south, west) Comorbidities Acquired immune deficiency syndrome, rheumatoid arthritis, chronic blood loss anemia, chronic pulmonary disease, coagulopathy, depression, drug abuse, hypertension, hypothyroidism, liver disease, lymphoma, fluid and electrolyte disorders, other neurological disorders, obesity, peripheral vascular disorders, pulmonary circulation disorders, renal failure, solid tumor without metastasis, valvular disease, weight loss, diabetes with chronic complication, peptic ulcer disease excluding bleeding Data analysis Data analysis was conducted using the Statistical Package for the Social Sciences (SPSS) version 25.0. Differences between the two groups were evaluated using the Wilcoxon rank-sum test for continuous variables and the Chi-square test for categorical variables. Multivariate logistic regression analysis was performed using a stepwise selection method to identify independent risk factors for HF. The logistic regression model included a comprehensive set of variables from the NIS database, encompassing patient demographics, hospital attributes, and comorbid conditions (Table 1 ). Odds ratios (OR) and their corresponding 95% confidence intervals (CI) were calculated. Given the large sample size, statistical significance was defined as a P value of less than 0.001. Results HF incidence in patients with VVLEs Between 2010 and 2019, we identified 120,748 cases of VVLEs from the NIS database. After excluding ineligible patients, 126,623 individuals were included in the present study, of whom 16,463 experienced HF, resulting in an incidence rate of 14.4% (Table 2). The analysis revealed a steady annual increase in HF incidence, rising from 1.5% in 2010 to 29.8% in 2019 (Fig. 2). Table 2 Patient characteristics of VVLEs hospitalizations with and without HF (2010-2019) Characteristics Heart failure No heart failure P Total (n=count) 16463 100160 Total incidence (%) 14.40 Age (median, years) 73 (64,82) 68 (57, 78) 0.196 Age group (%) 18-44 2.47 7.89 <0.001 45-64 24.48 33.42 65-74 26.42 24.86 ≥75 46.64 33.83 Gender (%) Male 47.74 57.30 <0.001 Female 52.26 42.70 Race (%) White 73.69 72.48 <0.001 Black 12.80 8.72 Hispanic 7.02 8.59 Asian or Pacific Islander 1.04 1.22 Native American 0.37 0.47 Other 5.09 8.54 Number of Comorbidity (%) 0 0.57 6.22 <0.001 1 3.30 14.21 2 8.47 20.28 ≥3 87.66 59.28 LOS (median, d) 5 (3-9) 4 (2-6) <0.001 TOTCHG (median, $) 39956 (22091-77201) 31233 (16494-58383.75) <0.001 Type of insure (%) Medicare 77.06 61.40 <0.001 Medicaid 8.67 10.21 Private insurance 10.92 23.06 Self-pay 1.77 2.89 No charge 0.17 0.33 Other 1.42 2.11 Bed size of hospital (%) Small 20.20 20.32 0.005 Medium 29.57 28.36 Large 50.23 51.32 Elective admission (%) 8.75 28.76 <0.001 Type of hospital (teaching %) 66.94 57.26 <0.001 Continue Characteristics Heart failure No heart failure P Location of hospital (urban, %) 89.32 87.74 <0.001 Region of hospital (%) Northeast 19.52 21.18 <0.001 Midwest or North Central 28.17 26.88 South 34.09 33.63 West 18.22 18.32 Died (%) 3.20 1.39 <0.001 LOS: Length of stay, TOTCHE: Total charge, VVLEs: varicose veins of lower extremities, HF: heart failure Patient demographics between the two groups Significant differences in the incidence of HF during hospitalization were observed between sexes, with females exhibiting a higher prevalence of HF (52.26% vs. 42.70%, P < 0.001) (Table 2). Age distribution also varied between groups, with a greater proportion of patients aged over 75 years in the HF group (46.64% vs. 33.83%, P < 0.001) (Table 2). Moreover, racial differences were significant, with White and Black individuals comprising slightly higher proportions in the HF group. Hospital characteristics of the two groups A higher frequency of HF in VVLEs patients was observed among those with Medicare insurance ( P < 0.001) (Table 2). Patients with HF were less likely to be admitted electively compared to those with no HF ( P < 0.001) (Table 2). Besides, HF incidence was higher in teaching and urban hospitals ( P < 0.001). Geographically, in-hospital HF was more prevalent in the South and Midwest or North Central regions and less common in the Northeast and West ( P < 0.001) (Table 2). Adverse impact of HF in patients with VVLEs Patients with HF experienced a significantly higher mortality rate, at least 2.3 times greater than those with no HF (3.2% vs. 1.39%, P < 0.001) (Table 2). HF was also associated with a one-day increase in the median length of hospital stay (5 days vs. 4 days, P < 0.001) (Table 2). These findings suggest that HF contributes to higher medical costs. Specifically, total hospital charges for blood transfusions were significantly higher in patients with HF, with an increase of $34,731 ($121,039 vs. $86,308, P < 0.001) (Table 2). HF Risk factors for patients with VVLEs To identify factors associated with HF, a logistic regression analysis was conducted. We found that advanced age (≥ 65 years) was associated with an increased risk (OR = 1.54; 95% CI = 1.459–1.627; P < 0.001), as were Black race (OR = 1.311; CI = 1.233–1.393), the presence of one comorbidity (OR = 1.929; CI = 1.543–2.411), two comorbidities (OR = 2.564; CI = 2.067–3.180), and three or more comorbidities (OR = 3.502; CI = 2.816–4.356). Additional risk factors identified included admission to a teaching hospital (OR = 1.599; CI = 1.528–1.673), hospitalization in the South (OR = 1.120; CI = 1.062–1.181) (Table 3), and specific conditions such as chronic pulmonary disease (OR = 1.555; CI = 1.492–1.620), fluid and electrolyte disorders (OR = 1.248; CI = 1.198–1.301), obesity (OR = 1.501; CI = 1.440–1.565), pulmonary circulation disorders (OR = 3.132; CI = 2.966–3.308), renal failure (OR = 2.412; CI = 2.312–2.516), valvular disease (OR = 3.081; CI = 2.927–3.243), weight loss (OR = 1.156; CI = 1.071–1.247), diabetes with chronic complications (OR = 2.126; CI = 2.033–2.225), and peptic ulcer disease (excluding bleeding) (OR = 1.497; CI = 1.200–1.868) (Table 4). Interestingly, protective factors included female sex (OR = 0.700; CI = 0.673–0.729), private insurance (OR = 0.710; CI = 0.666–0.757), elective admission (OR = 0.357; CI = 0.336–0.380), and hospitalization in an urban facility (OR = 0.813; CI = 0.760–0.871) (Table 3). Table 3 Risk factors associated with heart failure in VVLEs hospitalizations (2010-2019) Variable Multivariate Logistic Regression OR 95% CI P Age ≥65 years old 1.540 1.459-1.627 ＜0.001 Female 0.700 0.673-0.729 ＜0.001 Race White Ref —— —— Black 1.311 1.233-1.393 ＜0.001 Hispanic 0.898 0.834-0.967 0.005 Asian or Pacific Islander 0.802 0.668-0.963 0.018 Native American 0.863 0.638-1.167 0.338 Other 0.703 0.647-0.763 ＜0.001 Number of Comorbidity 0 Ref —— —— 1 1.929 1.543-2.411 ＜0.001 2 2.564 2.067-3.180 ＜0.001 ≥3 3.502 2.816-4.356 ＜0.001 Type of insurance Medicare Ref —— —— Medicaid 1.047 0.969-1.131 0.242 Private insurance 0.710 0.666-0.757 ＜0.001 Self-pay 0.867 0.755-0.995 0.042 No charge 0.880 0.581-1.334 0.548 Other 0.834 0.715-0.973 0.021 Bed size of hospital Small Ref —— —— Medium 1.026 0.972-1.084 0.349 Large 0.995 0.946-1.045 0.829 Elective admission 0.357 0.336-0.380 ＜0.001 Teaching hospital 1.599 1.528-1.673 ＜0.001 Urban hospital 0.813 0.760-0.871 ＜0.001 Region of hospital Northeast Ref —— —— Midwest or North Central 1.092 1.032-1.155 0.002 South 1.120 1.062-1.181 ＜0.001 West 1.115 1.048-1.186 0.001 OR: Odds ratio, CI: Confidence interval, VVs: varicose veins of lower extremities Table 4 Relationship between heart failure and comorbidities (2010-2019) Comorbidities Univariate Analysis Multivariate Logistic Regression Heart failure No heart failure P OR 95% CI P comorbidities Acquired immune deficiency syndrome 42 (0.3%) 317 (0.3%) 0.188 0.742 0.521-1.056 0.097 Rheumatoid arthritis 530 (3.2%) 3654(3.6%) 0.006 0.848 0.764-0.940 0.002 Chronic blood loss anemia 230 (1.4%) 1329 (1.3%) 0.467 0.755 0.643-0.886 0.001 Chronic pulmonary disease 6213 (37.7%) 22890 (22.9%) ＜0.001 1.555 1.492-1.620 ＜0.001 Coagulopathy 18,57 (11.3%) 7540 (7.5%) ＜0.001 1.109 1.041-1.182 0.001 Depression 2110 (12.8%) 13641 (13.6%) 0.005 0.921 0.871-0.975 0.004 Drug abuse 530 (3.2%) 3382 (3.4%) 0.299 0.987 0.887-1.099 0.810 Hypertension 13105 (79.6%) 66910 (66.8%) ＜0.001 1.000 0.952-1.051 0.992 Hypothyroidism 3216 (19.5%) 16761 (16.7%) ＜0.001 1.020 0.971-1.072 0.425 Liver disease 1379 (8.4%) 6916 (6.9%) ＜0.001 1.041 0.968-1.120 0.273 Lymphoma 110 (0.70%) 743 (0.70%) 0.304 0.796 0.637-0.994 0.045 Fluid and electrolyte disorders 6372 (38.7%) 23847 (23.80%) ＜0.001 1.248 1.198-1.301 ＜0.001 Other neurological disorders 1429 (8.7%) 6452 (6.4%) ＜0.001 1.019 0.952-1.092 0.585 Obesity 7087 (43.0%) 30617 (30.6%) ＜0.001 1.501 1.440-1.565 ＜0.001 Peripheral vascular disorders 3276 (19.9%) 14151 (14.1%) ＜0.001 1.088 1.036-1.143 0.001 Pulmonary circulation disorders 3766 (22.9%) 4631 (4.6%) ＜0.001 3.132 2.966-3.308 ＜0.001 Renal failure 7541 (45.8%) 15629 (15.6%) ＜0.001 2.412 2.312-2.516 ＜0.001 Solid tumor without metastasis 427 (2.6%) 2977 (3.0%) 0.007 0.786 0.699-0.883 ＜0.001 Valvular disease 4239 (25.7%) 7231(7.2%) ＜0.001 3.081 2.927-3.243 ＜0.001 Weight loss 1166 (7.1%) 4676 (4.7%) ＜0.001 1.156 1.071-1.247 ＜0.001 Diabetes with chronic complication 6250(38.0%) 12995(13.0%) ＜0.001 2.126 2.033-2.225 ＜0.001 Peptic ulcer disease excluding bleeding 140(0.9%) 434(0.4%) ＜0.001 1.497 1.200-1.868 ＜0.001 OR: Odds ratio, CI: Confidence interval Factors associated with HF in patients with VVLEs Univariate analysis showed that patients undergoing VVLEs who developed HF were more likely to experience medical complications, including wound infection, blood transfusion, hemorrhage/seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg ( P < 0.001) (Table 5). In our multivariate analysis, HF was associated with wound infection (OR = 0.270; 95% CI = 0.188–0.388), blood transfusion (OR = 0.885; CI = 0.828–0.946), hemorrhage/seroma/hematoma (OR = 0.407; CI = 0.301–0.551), deep venous thrombosis (OR = 0.408; CI = 0.365–0.457), pulmonary embolism (OR = 0.706; CI = 0.616–0.810), stroke (OR = 0.830; CI = 0.752–0.916), and cellulitis of the leg (OR = 1.318; CI = 1.269–1.369). Table 5 Relationship between heart failure and complications (2010-2019) Complications Univariate Analysis Multivariate Logistic Regression Heart failure No heart failure P OR 95% CI P Medical complications Wound infection 31 (0.20%) 699 (0.7%) ＜0.001 0.270 0.188-0.388 ＜0.001 Blood transfusion 1065 (6.5%) 7519 (7.5%) ＜0.001 0.885 0.828-0.946 ＜0.001 Hemorrhage/seroma/hematoma 45 (0.30%) 764 (0.8%) ＜0.001 0.407 0.301-0.551 ＜0.001 Deep venous thrombosis 345 (2.1%) 5243 (5.2%) ＜0.001 0.408 0.365-0.457 ＜0.001 Pulmonary embolism 240(1.5%) 2760 (2.8%) ＜0.001 0.706 0.616-0.810 ＜0.001 Stroke 464 (2.8%) 3490(3.5%) ＜0.001 0.830 0.752-0.916 ＜0.001 Cellulitis of leg 4336 (26.3%) 21197 (21.2%) ＜0.001 1.318 1.269-1.369 ＜0.001 Noninfectious lymphatic channel disorders 9 (0.1%) 24 (0.00%) 0.030 2.621 1.203-5.711 0.015 Seborrheic dermatitis 10 (0.1%) 122 (0.1%) 0.031 0.480 0.252-0.916 0.026 Arteriovenous fistulas 7 (0.0%) 18 (0%) 0.046 2.531 1.049-6.108 0.039 OR: Odds ratio, CI: Confidence interval Discussion Chronic venous dysfunction, a hallmark of VVLEs, leads to persistent retrograde venous pressure, causing capillary dilation and the accumulation of venous blood within the cutaneous microvasculature. This accumulation results in venous fluid overload, characterized by high capacitance and peripheral edema, both of which contribute to the development of HF. The current study provides a comprehensive health economic analysis of VVLEs patients who experienced HF. Herein, we observed a gradual increase in HF rates from 2010 to 2019 (from 1.5–29.8%) that is possibly driven by an aging population, endothelial dysfunction, systemic inflammatory response, hypertension, diabetes, obesity, and smoking [ 16 , 18 ]. Another plausible explanation is the existence of a bidirectional causal relationship between venous abnormalities and HF [ 20 – 22 ]. It has been reported that advanced age (≥ 65 years) is associated with an increased risk of HF in patients with VVLEs [ 14 , 16 , 18 , 20 ], consistent with the findings of this study. This may be attributed to age-related cellular and morphological alterations in the venous system, including endothelial aging, smooth muscle aging, and connective tissue aging. Indeed, old venous vessels are often accompanied by chronic inflammation, and these inflammatory factors may damage myocardial cells, impairing cardiac function and endothelial function. This could ultimately lead to decreased vasodilation and increased cardiac afterload, contributing to the development of HF [ 16 , 23 ]. Logistic regression analysis revealed that, compared to White individuals, Black individuals with VVLEs have a higher incidence of HF. These disparities in incidence might be driven by complex factors, including access to care, socioeconomic status, genetic susceptibility, social determinants of health, and implicit bias [ 24 ]. There is increasing consensus suggesting that VVLEs patients treated at teaching hospitals are more likely to develop HF [ 25 , 26 ]. This correlation may be attributed to the fact that teaching hospitals typically receive complex cases from various regions, with patients often suffering from multiple underlying conditions, such as hypertension, coronary heart disease, and diabetes. The heavier disease burden could ultimately contribute to a higher risk of heart failure [ 25 , 26 ]. Moreover, we found that hospitals in the South have a higher incidence of HF, possibly due to the higher proportion of high-risk individuals, common health risk factors, and the unequal distribution of medical resources [ 27 , 28 ]. Notably, the presence of multiple comorbidities (n ≥ 1) was associated with an increased risk of HF in patients with VVLEs. This observation is logical, given that elevated scores on predictive metrics mentioned above typically indicate a more severe health status or illness in patients, which may lead to a greater burden on their cardiovascular system, making them more prone to cardiac insufficiency [ 2 , 16 , 29 ]. In line with the literature, our study found that HF in patients with VVLEs is associated with prolonged hospital stays, elevated medical expenses, and increased mortality rates. Specifically, the median LOS increased by one day, and the total hospital charge per admission rose by $ 8,723 in VVLEs patients who experienced HF. Contributing factors include associated complications, HF management, family support, prolonged hospitalization, and intensive nursing care [ 2 , 25 , 26 , 29 ]. Importantly, numerous studies have reported a higher mortality rate among patients with HF [ 2 , 11 , 12 , 14 ]. Herein, female sex was identified as a protective factor. One potential explanation is that VVLEs can increase the risk of deep vein thrombosis (DVT), which occurs more frequently in males than in females (11.3% vs. 7.8%), thereby elevating the risk of HF [ 6 , 30 ]. Furthermore, a lower prevalence of private insurance was observed among the HF group, positioning it as a potential protective factor. These findings suggest that socioeconomic status may influence the incidence of HF. Previous studies have indicated that clinical staff may be aware of disparities in insurance coverage or income among patients and may adjust their treatment approaches accordingly [ 31 , 32 ]. Patients with VVLEs admitted electively were less likely to develop HF, possibly because elective cases typically involve healthier individuals, while emergency cases often involve more severe or complex conditions that lack thorough assessment [ 31 , 32 ]. In addition, urban hospitals were identified as protective factors against HF, likely due to their standardized HF management protocols, extensive medical resources, advanced equipment for HF treatment, and comprehensive training programs for healthcare staff [ 33 ]. Here, logistic regression analysis revealed that chronic pulmonary disease and pulmonary circulation disorders are significant factors that increase the risk of HF. VVLEs patients often concurrently suffer from chronic inflammation and hypercoagulability, which can lead to increased right ventricular afterload, obstructed venous return, and hemodynamic changes, further increasing the burden on the heart and contributing to the development of HF [ 34 ]. Patients with fluid and electrolyte disorders were also found to be at increased risk of HF, which aligns with prior findings that also suggested that imbalances in sodium, potassium, calcium, and magnesium, disturbances in acid-base balance, and excessive or insufficient body fluids are associated with the development of HF [ 35 ]. In our investigation, obesity emerged as an independent risk factor for HF. This correlation may be attributed to the fact that obesity increases the metabolic burden and inflammatory response on the heart, while VVLEs further exacerbate the preload on the heart. Therefore, special attention should be given to weight management and the treatment of VVLEs to reduce the risk of HF [ 10 , 20 ]. Consistent findings in the literature indicate a significant correlation between HF and renal failure in VVLEs patients, likely due to the combination of VVLEs and renal failure, which significantly increases the risk of HF through mechanisms involving increased cardiac load, endothelial dysfunction, inflammation, hypertension, and shared risk factors [ 36 , 37 ]. Our study also found that valvular disease was associated with HF, likely because valvular disease can lead to significant hemodynamic changes, such as increased pressure gradients across the valves and altered blood flow patterns. These changes can further impair venous return and exacerbate the symptoms of chronic venous insufficiency, thereby increasing the burden on the heart [ 29 , 38 ]. Weight loss was also identified as a risk factor, with a reasonable explanation being that weight loss can lead to malnutrition and deficiencies in essential nutrients. This can result in systemic inflammation and further impair endothelial function, promoting a pro-inflammatory state and impairing vascular function, ultimately increasing the risk of HF [ 29 , 38 ]. Diabetes with chronic complications is likely associated with chronic inflammation and metabolic abnormalities such as dyslipidemia and insulin resistance, which may contribute to atherosclerosis and cardiovascular disease, thereby increasing the risk of HF [ 39 ]. The present study also found that peptic ulcer disease (excluding bleeding) was associated with an increased risk of HF. Similarly, a previous study found that various inflammatory mediators produced by peptic ulcers may directly damage myocardial cells, impairing the myocardium's systolic and diastolic functions. These mediators can also increase vascular resistance and promote the development of atherosclerosis, further contributing to the risk of HF [ 40 ]. Our results indicate that wound infection, blood transfusion, hemorrhage/ seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg are associated with the risk of HF. Specifically, HF in VVLEs cases was linked with wound infection and cellulitis of the leg, likely due to lower limb blood circulation disorders, which reduce the immune defense function of local tissues [ 41 ]. Patients who undergo blood transfusion and experience hemorrhage /seroma/hematoma are more prone to developing HF, possibly because these conditions are often accompanied by additional fluid load or blood volume reduction [ 42 , 43 ]. Furthermore, the inflammatory state may increase the vulnerability of the skin and soft tissues, making them more prone to ulcers and infections [ 44 ]. HF was also associated with DVT, pulmonary embolism, and stroke. DVT leads to obstructed venous return, which increases the burden on the right heart [ 6 ]. Meanwhile, pulmonary embolism may result in chronic pulmonary arterial hypertension, reducing effective ventilation and perfusion in the lungs [ 45 ]. Patients with cerebral infarction often experience slow blood circulation due to prolonged bed rest, which can easily lead to DVT and further increase the risk of pulmonary embolism and HF [ 46 ]. The use of the NIS database presents several inherent limitations. Firstly, patient data is captured only during hospital stays, meaning post-discharge complications, readmission rates, and long-term outcomes are not documented. This limitation could potentially lead to an underestimation of HF incidence [ 6 , 16 , 19 ]. Secondly, the analysis is restricted to the variables available in the NIS database. Therefore, key HF risk factors, such as body mass index, B-type natriuretic peptide levels, and ejection fraction, are notably absent [ 5 , 6 , 12 , 43 ]. Lastly, coding and documentation discrepancies or misclassifications may arise, as with any large administrative database. Conclusion VVLEs patients who experience HF face significant challenges in terms of clinical outcomes and medical costs. In the present study, several risk factors associated with HF were identified, including advanced age (≥ 65 years), being Black, comorbidities (n ≥ 1), teaching hospitals, hospitals in the South, chronic pulmonary disease, fluid and electrolyte disorders, obesity, pulmonary circulation disorders, renal failure, valvular disease, weight loss, diabetes with chronic complications, and peptic ulcer disease. Conversely, female sex, private insurance, elective admission, and urban hospitals were identified as protective factors. Furthermore, wound infection, blood transfusion, hemorrhage/seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg were all linked to HF in VVLEs patients. Additionally, an association was also found between HF, elevated hospital costs, and extended LOS. Collectively, our study could assist healthcare professionals in identifying VVLEs patients at a heightened risk of HF and implementing effective interventions to reduce adverse outcomes. Abbreviations VVLEs Varicose veins of the lower extremities HF Heart failure DVT Deep vein thrombosis HCUP Healthcare Cost and Utilization Project AHRQ Healthcare Research and Quality SPSS Statistical Package for the Social Sciences CI Confidence intervals ICD-9-CM International Classiffcation of Diseases (ninth revision) Clinical Modiffcation ICD-10-CM International Classiffcation of Diseases (tenth revision) Clinical Modiffcation LOS Length of stay NIS Nationwide Inpatient Sample OR Odds ratio Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Data availability The dataset used and analysed in the current study is a publicly available dataset (National Inpatient Sample), part of the Healthcare Cost and Utilization Project from the United States, and can be accessed at the following link: https://hcup-us.ahrq.gov/nisoverview.jsp. Acknowledgments The authors would like to thank Lei Fan from Nanfang Hospital, Southern Medical University for his invaluable assistance in reviewing the statistical methods employed in this study. Author contributions XL wrote and revised the main parts of the manuscript. HYL collected the data, performed the preliminary analysis, and drafted the manuscript. LYZ and DK completed all statistical analyses and data processing. LFW designed and produced all figures and tables. XL and HYL revised the manuscript with input from all other authors. The manuscript was approved by all authors. Funding Not applicable. Ethics approval and consent to participate Not applicable. Clinical trial number Not applicable. References Hu H, Hu L, Deng Z, Jiang Q. A prognostic nomogram for recurrence survival in post-surgical patients with varicose veins of the lower extremities. Sci Rep. 2024;14(1):5486. Zolotukhin IA, Seliverstov EI, Shevtsov YN, Avakiants IP, Nikishkov AS, Tatarintsev AM, Kirienko AI. Prevalence and Risk Factors for Chronic Venous Disease in the General Russian Population. Eur J Vasc Endovasc Surg. 2017;54(6):752–8. Du HC, Deng BY. Obesity-Related Traits Mediate the Effects of Educational Attainment on the Risk of Varicose Veins, Venous Thromboembolism, and Phlebitis. Thromb Haemost. 2024;124(10):962–70. Javaid A, Ka A, Pm S, Arora K, Mudavath SL. Innovative Approaches and Future Directions in the Management and Understanding of Varicose Veins: A Systematic Review. ACS Pharmacol Transl Sci. 2024;7(10):2971–86. Ke C, Zhou Q, Lu M, Xie R, Kong W. Association between venous leg ulcers and chronic heart failure: A Mendelian randomization study. Int Wound J. 2024;21(2):e14744. Wu NC, Chen ZC, Feng IJ, Ho CH, Chiang CY, Wang JJ, Chang WT. Severe varicose veins and the risk of mortality: a nationwide population-based cohort study. BMJ Open. 2020;10(6):e034245. Segiet OA, Brzozowa-Zasada M, Piecuch A, Dudek D, Reichman-Warmusz E, Wojnicz R. Biomolecular mechanisms in varicose veins development. Ann Vasc Surg. 2015;29(2):377–84. Bouguettaya A, Gethin G, Probst S, Sixsmith J, Team V, Weller C. How health literacy relates to venous leg ulcer healing: A scoping review. PLoS ONE. 2023;18(1):e0279368. Rusinovich Y, Rusinovich V. Association between right heart diastolic function and clinical presentation of chronic venous disease and primary varicose veins of lower extremities. Phlebology. 2020;35(7):513–9. Borlaug BA, Sharma K, Shah SJ, Ho JE. Heart Failure With Preserved Ejection Fraction: JACC Scientific Statement. J Am Coll Cardiol. 2023;81(18):1810–34. Bui AL, Horwich TB, Fonarow GC. Epidemiology and risk profile of heart failure. Nat Rev Cardiol. 2011;8(1):30–41. Yan T, Zhu S, Yin X, et al. Burden, Trends, and Inequalities of Heart Failure Globally, 1990 to 2019: A Secondary Analysis Based on the Global Burden of Disease 2019 Study. J Am Heart Assoc. 2023;12(6):e027852. Khan MS, Shahid I, Bennis A, Rakisheva A, Metra M, Butler J. Global epidemiology of heart failure. Nat Rev Cardiol. 2024;21(10):717–34. Virani SS, Alonso A, Aparicio HJ, et al. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation. 2021;143(8):e254–254743. Boorsma EM, Ter Maaten JM, Damman K, et al. Congestion in heart failure: a contemporary look at physiology, diagnosis and treatment. Nat Rev Cardiol. 2020;17(10):641–55. Choi S, Leem GH, Song TJ. Association of varicose veins with incidence risk of atrial fibrillation: a population-based cohort study. Int J Surg. 2024;110(9):5704–12. Prochaska JH, Arnold N, Falcke A, et al. Chronic venous insufficiency, cardiovascular disease, and mortality: a population study. Eur Heart J. 2021;42(40):4157–65. Lurie F, Passman M, Meisner M, et al. The 2020 update of the CEAP classification system and reporting standards. J Vasc Surg Venous Lymphat Disord. 2020;8(3):342–52. Ismail MF, Abughazaleh S, Obeidat O, et al. Racial and ethnic disparities in heart transplantation for end-stage heart failure: An analysis of the national inpatient sample (NIS) database. Curr Probl Cardiol. 2024;49(3):102399. Mäkivaara LA, Ahti TM, Luukkaala T, Hakama M, Laurikka JO. The risk of congestive heart failure is increased in persons with varicose veins. Int Angiol. 2009;28(6):452–7. Pizano A, Bequeaith B, Cifuentes S, et al. Association between cardiac conditions with venous leg ulcers in patients with chronic venous insufficiency. Phlebology. 2023;38(4):281–6. Augey F, Pinet A, Renaudier P. [Heart failure and stasis ulcer: A significant association (prospective study of 100 cases)]. Ann Dermatol Venereol. 2010;137(5):353–8. Molnár AÁ, Nádasy GL, Dörnyei G, et al. The aging venous system: from varicosities to vascular cognitive impairment. Geroscience. 2021;43(6):2761–84. Nayak A, Hicks AJ, Morris AA. Understanding the Complexity of Heart Failure Risk and Treatment in Black Patients. Circ Heart Fail. 2020;13(8):e007264. Bekele F, Sheleme T, Tsegaye T, Parameswari SA, Syed MA, Tafese L, Gezimu W. Prevalence and risk factors of mortality among heart failure patients in low resource setting hospitals: a multicenter prospective observational study. Front Cardiovasc Med. 2024;11:1429513. Agyekum F, Folson AA, Asare BY, Doku A, Kpodonu J, Okine R, Fokuoh F, Akamah JA. Contemporary aetiology of acute heart failure in a teaching hospital in Ghana. BMC Cardiovasc Disord. 2023;23(1):82. Akwo EA, Kabagambe EK, Wang TJ, Harrell FE Jr, Blot WJ, Mumma M, Gupta DK, Lipworth L. Heart Failure Incidence and Mortality in the Southern Community Cohort Study. Circ Heart Fail. 2017;10(3):e003553. Bozkurt B, Ahmad T, Alexander K, et al. HF STATS 2024: Heart Failure Epidemiology and Outcomes Statistics An Updated 2024 Report from the Heart Failure Society of America. J Card Fail. 2025;31(1):66–116. Kim D, Park MS, Park JY, Song TJ. Association of varicose veins with the risk of heart failure: A nationwide cohort study. PLoS ONE. 2025;20(1):e0316942. Duffett L. Deep Venous Thrombosis. Ann Intern Med. 2022;175(9):ITC129–129144. Yang Q, Li J, Shi D, Xie H, Wang J, Shi Z, Zhang Y. Incidence and risk factors associated with hospital-acquired pressure ulcers following total hip arthroplasty: A retrospective nationwide inpatient sample database study. J Tissue Viability. 2022;31(2):332–8. Li X, Xie H, Liu S, et al. Analysis of the incidence and risk factors of blood transfusion in total knee revision: a retrospective nationwide inpatient sample database study. BMC Musculoskelet Disord. 2024;25(1):225. Minhas A, Sheikh AB, Ijaz SH, Mostafa A, Nazir S, Khera R, Loccoh EC, Warraich HJ. Rural-Urban Disparities in Heart Failure and Acute Myocardial Infarction Hospitalizations. Am J Cardiol. 2022;175:164–9. Turpie AG, Chin BS, Lip GY. Venous thromboembolism: pathophysiology, clinical features, and prevention. BMJ. 2002;325(7369):887–90. Bennett J, Deslippe AL, Crosby C, Belles S, Banna J. Electrolytes and Cardiovascular Disease Risk. Am J Lifestyle Med. 2020;14(4):361–5. Tsai CK, Nfor ON, Lu WY, Liaw YP. Association between varicose veins and constitution of traditional Chinese medicine plus heart-failure-like symptoms. Front Cardiovasc Med. 2024;11:1465843. Aslam MR, Muhammad Asif H, Ahmad K, et al. Global impact and contributing factors in varicose vein disease development. SAGE Open Med. 2022;10:20503121221118992. Azar J, Rao A, Oropallo A. Chronic venous insufficiency: a comprehensive review of management. J Wound Care. 2022;31(6):510–9. Theofilis P, Oikonomou E, Tsioufis K, Tousoulis D. Diabetes Mellitus and Heart Failure: Epidemiology, Pathophysiologic Mechanisms, and the Role of SGLT2 Inhibitors. Life (Basel). 2023;13(2):497. Sun J, Yao J, Olén O, et al. Risk of heart failure in inflammatory bowel disease: a Swedish population-based study. Eur Heart J. 2024;45(28):2493–504. Swoboda SJ, Schumann H, Kiritsi D. A leg ulcer with pulsating varicose veins - from the legs to the heart. Int Wound J. 2018;15(1):62–4. Gill K, Fink JC, Gilbertson DT, et al. Red blood cell transfusion, hyperkalemia, and heart failure in advanced chronic kidney disease. Pharmacoepidemiol Drug Saf. 2015;24(6):654–62. Nochioka K. Simplifying Bleeding Risk Assessment in Heart Failure. Circ J. 2021;86(1):156–7. Ito T, Kukino R, Sarayama Y, et al. Wound, Pressure Ulcer, and Burn Guidelines-5: Guidelines for the management of lower leg ulcers and varicose veins, second edition. J Dermatol. 2025;52(2):e49–4969. Di Nisio M, van Es N, Büller HR. Deep vein thrombosis and pulmonary embolism. Lancet. 2016;388(10063):3060–73. Rivas A, Lauw MN, Schnabel RB, Crowther M, Van Spall H. Stroke and Thromboembolism in Patients with Heart Failure and Sinus Rhythm: A Matter of Risk Stratification. Thromb Haemost. 2022;122(6):871–8. Additional Declarations No competing interests reported. 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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-6498400","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":462807150,"identity":"c497b20e-2a02-46d9-a654-648fec321fe2","order_by":0,"name":"Yinglan Huang","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yinglan","middleName":"","lastName":"Huang","suffix":""},{"id":462807151,"identity":"230c0802-97bf-4d71-967d-94ffd06d7ef0","order_by":1,"name":"Yangzhu Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of Gannan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yangzhu","middleName":"","lastName":"Liu","suffix":""},{"id":462807152,"identity":"c38b5b9a-d179-43a8-9381-684d0d9ed001","order_by":2,"name":"Kai Dai","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Dai","suffix":""},{"id":462807153,"identity":"7d177f92-5ee1-4c9e-ad71-b047e6c60dff","order_by":3,"name":"Fuwei Liu","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fuwei","middleName":"","lastName":"Liu","suffix":""},{"id":462807154,"identity":"b4db8906-6805-4611-801c-501caddcdfc8","order_by":4,"name":"Ling Wei","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Wei","suffix":""},{"id":462807155,"identity":"a8deadc3-e648-4eb9-94e5-3a51b64439cc","order_by":5,"name":"Li Xiao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIie3PP4rCQBTH8TcMTFh4su2TWcwVDAMiGPAqkcBUsuyyTQpZBgJusweIKB7DOiEQmxxAsPBfsW1OsCxrLUnsLOZb/Yr3KR6AzfaIEQAH8PHZ+dpWVUQ9tyXRL93vUrOkHCrPtCO5398FA/40jyaQNgh3GRfyLdIIaaAvbE0BM/x03tUQtiq0TEofmcm26n1Drw4IpaY1hNN0IDtzjZyZQC429MEMCllHxJX85ig49GVnRROTNhC8EpMjCvgfLQiRDkdYaCTE0EsKUl7c8IubhNkeZ/54fPjJjtXss+c68elSR27E7zu32Ww2243+ALDdRMNFVtRpAAAAAElFTkSuQmCC","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Li","middleName":"","lastName":"Xiao","suffix":""}],"badges":[],"createdAt":"2025-04-21 19:38:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6498400/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6498400/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83752329,"identity":"50f57b68-f421-4664-96ce-5c64888542eb","added_by":"auto","created_at":"2025-06-02 07:20:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":142866,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6498400/v1/071fe45dd45d241c279cd1f9.jpg"},{"id":83752180,"identity":"af521ba8-0d19-4631-8620-dca8d00ad12d","added_by":"auto","created_at":"2025-06-02 07:12:23","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":84304,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6498400/v1/94339cdfd99eef4f4ad698e4.jpg"},{"id":83752830,"identity":"9d5cf44f-3ad5-4e3a-8e67-6cbdeaf51380","added_by":"auto","created_at":"2025-06-02 07:28:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1646412,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6498400/v1/c0218ae2-b824-421f-aa4c-26677ed94bad.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Incidence and risk factors of heart failure in patients with varicose veins of lower extremities: a retrospective nationwide inpatient sample database study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLower extremity varicose veins (VVLEs) are a highly prevalent vascular condition, affecting 14\u0026ndash;64% of the general population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This condition is characterized by symptoms such as leg pain, swelling, itching, and fatigue but can also progress to more severe manifestations, including skin pigmentation, eczema, induration, and ulceration, significantly impairing patients' quality of life [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. While recent research has enhanced our understanding of the pathophysiology and management of VVLEs, their pathogenesis remains poorly understood [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Current evidence suggests that VVLEs is a complex disease with a multifactorial pathogenesis involving genetic, lifestyle, occupational, cellular, extracellular, and hemodynamic factors [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Of note, the fundamental characteristics of primary and secondary chronic venous disease are centered on hemodynamic abnormalities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. As hemodynamics are intricately linked to cardiac circulation, the bidirectional relationship between heart disease and VVLEs has garnered widespread attention [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Heart failure (HF) is a heterogeneous clinical syndrome resulting from the progression of various heart diseases to advanced stages [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. HF affects an estimated 56\u0026nbsp;million individuals globally, imposing a significant health burden characterized by reduced quality of life, frequent hospitalizations, rising healthcare costs, and increased premature mortality rates [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. With an aging population and incremental improvements in survival rates, the prevalence of HF is projected to rise by as much as 46% by 2030 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Consequently, identifying and understanding factors contributing to HF risk is paramount. Previous studies have reported several risk factors for HF, including hypertension, obesity, diabetes, sex, advancing age, and a sedentary lifestyle [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Nevertheless, further research is warranted to identify and address modifiable risk factors influencing HF development.\u003c/p\u003e \u003cp\u003eRecent studies have identified chronic venous insufficiency as an independent risk factor for cardiovascular and peripheral artery diseases [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, common risk factors such as hypertension, diabetes, obesity, smoking, and endothelial dysfunction have been shown to independently contribute to cardiovascular diseases in patients with varicose veins [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. To date, no study has yet comprehensively examined HF incidence and risk factors in patients with VVLEs using a large sample size. Given the above evidence, we surmise that VVLEs might be potentially associated with an increased risk of HF. Therefore, the present study aims to investigate the frequency and contributing factors of HF in patients with VVLEs using data acquired from a nationwide database.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThis study utilized data from the Nationwide Inpatient Sample (NIS), the largest publicly accessible database of fully paid inpatient medical records in the United States. This database is maintained by the Healthcare Cost and Utilization Project (HCUP) and supported by the Agency for Healthcare Research and Quality (AHRQ). It includes information from over seven million hospital admissions, representing approximately 20% of annual hospitalizations [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Data extraction for this study included patient demographics (age, sex, race), hospital characteristics (insurance type, admission type, bed capacity, teaching status, geographic location, and region), length of stay (LOS), financial metrics, and diagnostic and procedural codes from the International Classification of Diseases, Clinical Modification (ICD-9-CM and ICD-10-CM). Ethical review board approval was not required as this study used anonymized, publicly available data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eData from 2010 to 2019 were extracted from the NIS database. VVLEs cases were identified using procedure codes from both the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The initial diagnosis date of VVLEs served as the index date for this study. To ensure diagnostic accuracy and minimize confounding, patients were included if they had a diagnosis of VVLEs based on ICD-9-CM codes (454.0, 454.1, 454.2, 454.8, 454.9) and ICD-10-CM codes (I83.0, I83.1, I83.2, I83.8, I83.9). Patients under 18 years old and those with incomplete data were excluded from the analysis (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eParticipants were assigned to two groups: those with and without a HF diagnosis. We assessed patient demographics, hospital characteristics, and outcomes, including LOS, economic indicators, and in-hospital mortality. Comorbidities and complications were identified using ICD-9-CM and ICD-10-CM diagnostic codes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additional complications included wound infection, blood transfusion, hemorrhage/seroma/ hematoma, deep venous thrombosis, pulmonary embolism, stroke, cellulitis of the leg, noninfectious lymphatic channel disorders, seborrheic dermatitis, and arteriovenous fistulas.\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\u003eVariables used in binary logistic regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables Categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecific Variables\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient demographics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge (\u0026le;\u0026thinsp;64 years and \u0026ge;\u0026thinsp;65 years), sex (male and female), race (White, Black, Hispanic, Asian or Pacific Islander, Native American and Other)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of admission (non-elective, elective), bed size of hospital (small, medium, large), teaching status of hospital (nonteaching, teaching), location of hospital (rural, urban), type of insurance (medicare, medicaid, private insurance, self-pay, no charge, other), location of the hospital (northeast, midwest or north central, south, west)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcquired immune deficiency syndrome, rheumatoid arthritis, chronic blood loss anemia, chronic pulmonary disease, coagulopathy, depression, drug abuse, hypertension, hypothyroidism, liver disease, lymphoma, fluid and electrolyte disorders, other neurological disorders, obesity, peripheral vascular disorders, pulmonary circulation disorders, renal failure, solid tumor without metastasis, valvular disease, weight loss, diabetes with chronic complication, peptic ulcer disease excluding bleeding\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eData analysis was conducted using the Statistical Package for the Social Sciences (SPSS) version 25.0. Differences between the two groups were evaluated using the Wilcoxon rank-sum test for continuous variables and the Chi-square test for categorical variables. Multivariate logistic regression analysis was performed using a stepwise selection method to identify independent risk factors for HF. The logistic regression model included a comprehensive set of variables from the NIS database, encompassing patient demographics, hospital attributes, and comorbid conditions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Odds ratios (OR) and their corresponding 95% confidence intervals (CI) were calculated. Given the large sample size, statistical significance was defined as a \u003cem\u003eP\u003c/em\u003e value of less than 0.001.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eHF incidence in patients with VVLEs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween 2010 and 2019, we identified 120,748 cases of VVLEs from the NIS database. After excluding ineligible patients, 126,623 individuals were included in the present study, of whom 16,463 experienced HF, resulting in an incidence rate of 14.4% (Table 2). The analysis revealed a steady annual increase in HF incidence, rising from 1.5% in 2010 to 29.8% in 2019 (Fig. 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003ePatient characteristics of VVLEs hospitalizations with and without HF (2010-2019)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo heart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n=count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e16463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e100160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal incidence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 265px;\"\u003e\n \u003cp\u003e14.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (median, years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e73 (64,82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e68 (57, 78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e18-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e7.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e45-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e24.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e33.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e65-74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e26.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e24.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026ge;75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e46.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e33.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e47.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e57.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e52.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e42.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e73.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e72.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e12.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e8.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e7.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e8.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e5.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e8.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Comorbidity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e14.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e8.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e20.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e87.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e59.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS (median, d)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e5 (3-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e4 (2-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTCHG (median, $)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e39956\u003c/p\u003e\n \u003cp\u003e(22091-77201)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e31233\u003c/p\u003e\n \u003cp\u003e(16494-58383.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of insure (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e77.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e61.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e8.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e10.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e23.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eNo charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed size of hospital\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eSmall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e20.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e20.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e29.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e28.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e50.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e51.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElective admission (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e8.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e28.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of hospital (teaching %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e66.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e57.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eContinue\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo heart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation of hospital (urban, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e89.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e87.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion of hospital (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e19.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e21.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eMidwest or North Central\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e28.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e26.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e34.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e33.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e18.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e18.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDied (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLOS: Length of stay, TOTCHE: Total charge, VVLEs: varicose veins of lower extremities, HF: heart failure\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient demographics between the two groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificant differences in the incidence of HF during hospitalization were observed between sexes, with females exhibiting a higher prevalence of HF (52.26% vs. 42.70%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2). Age distribution also varied between groups, with a greater proportion of patients aged over 75 years in the HF group (46.64% vs. 33.83%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2). Moreover, racial differences were significant, with White and Black individuals comprising slightly higher proportions in the HF group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHospital characteristics of the two groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA higher frequency of HF in VVLEs patients was observed among those with Medicare insurance (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2). Patients with HF were less likely to be admitted electively compared to those with no HF (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2). Besides, HF incidence was higher in teaching and urban hospitals (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Geographically, in-hospital HF was more prevalent in the South and Midwest or North Central regions and less common in the Northeast and West (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdverse impact of HF in patients with VVLEs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients with HF experienced a significantly higher mortality rate, at least 2.3 times greater than those with no HF (3.2% vs. 1.39%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2). HF was also associated with a one-day increase in the median length of hospital stay (5 days vs. 4 days, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2). These findings suggest that HF contributes to higher medical costs. Specifically, total hospital charges for blood transfusions were significantly higher in patients with HF, with an increase of $34,731 ($121,039 vs. $86,308, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHF Risk factors for patients with VVLEs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify factors associated with HF, a logistic regression analysis was conducted. We found that advanced age (\u0026ge; 65 years) was associated with an increased risk (OR = 1.54; 95% CI = 1.459\u0026ndash;1.627; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), as were Black race (OR = 1.311; CI = 1.233\u0026ndash;1.393), the presence of one comorbidity (OR = 1.929; CI = 1.543\u0026ndash;2.411), two comorbidities (OR = 2.564; CI = 2.067\u0026ndash;3.180), and three or more comorbidities (OR = 3.502; CI = 2.816\u0026ndash;4.356). Additional risk factors identified included admission to a teaching hospital (OR = 1.599; CI = 1.528\u0026ndash;1.673), hospitalization in the South (OR = 1.120; CI = 1.062\u0026ndash;1.181) (Table 3), and specific conditions such as chronic pulmonary disease (OR = 1.555; CI = 1.492\u0026ndash;1.620), fluid and electrolyte disorders (OR = 1.248; CI = 1.198\u0026ndash;1.301), obesity (OR = 1.501; CI = 1.440\u0026ndash;1.565), pulmonary circulation disorders (OR = 3.132; CI = 2.966\u0026ndash;3.308), renal failure (OR = 2.412; CI = 2.312\u0026ndash;2.516), valvular disease (OR = 3.081; CI = 2.927\u0026ndash;3.243), weight loss (OR = 1.156; CI = 1.071\u0026ndash;1.247), diabetes with chronic complications (OR = 2.126; CI = 2.033\u0026ndash;2.225), and peptic ulcer disease (excluding bleeding) (OR = 1.497; CI = 1.200\u0026ndash;1.868) (Table 4). Interestingly, protective factors included female sex (OR = 0.700; CI = 0.673\u0026ndash;0.729), private insurance (OR = 0.710; CI = 0.666\u0026ndash;0.757), elective admission (OR = 0.357; CI = 0.336\u0026ndash;0.380), and hospitalization in an urban facility (OR = 0.813; CI = 0.760\u0026ndash;0.871) (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eRisk factors associated with heart failure in VVLEs hospitalizations (2010-2019)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge \u0026ge;65 years old\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.459-1.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.673-0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.233-1.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.834-0.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.668-0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.638-1.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.338\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.647-0.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Comorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.543-2.411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e2.067-3.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e3.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e2.816-4.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.969-1.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.666-0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.755-0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eNo charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.581-1.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.548\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.715-0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed size of hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eSmall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.972-1.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.946-1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElective admission\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.336-0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTeaching hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.528-1.673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.760-0.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion of hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMidwest or North Central\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.032-1.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.062-1.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.048-1.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR: Odds ratio, CI: Confidence interval, VVs: varicose veins of lower extremities\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eRelationship between heart failure and\u0026nbsp;comorbidities (2010-2019)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"749\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 298px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo heart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ecomorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eAcquired immune deficiency syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e42 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e317 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.521-1.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eRheumatoid arthritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e530 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e3654(3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.764-0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eChronic blood loss anemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e230 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1329 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.643-0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eChronic pulmonary disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e6213 (37.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e22890 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.492-1.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eCoagulopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e18,57 (11.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e7540 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.041-1.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e2110 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e13641 (13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.871-0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDrug abuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e530 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e3382 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.887-1.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e13105 (79.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e66910 (66.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.952-1.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e3216 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e16761 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.971-1.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eLiver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e1379 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e6916 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.968-1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eLymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e110 (0.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e743 (0.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.637-0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eFluid and electrolyte disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e6372 (38.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e23847 (23.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.198-1.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eOther neurological disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e1429 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e6452 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.952-1.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e7087 (43.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e30617 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.440-1.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003ePeripheral vascular disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e3276 (19.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e14151 (14.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.036-1.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003ePulmonary circulation disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e3766 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e4631 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e3.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e2.966-3.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eRenal failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e7541 (45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e15629 (15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.312-2.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eSolid tumor without metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e427 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e2977 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.699-0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eValvular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e4239 (25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e7231(7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.927-3.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eWeight loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1166 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e4676 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.071-1.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eDiabetes with chronic complication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e6250(38.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e12995(13.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.033-2.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003ePeptic ulcer disease excluding bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e140(0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e434(0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.200-1.868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR: Odds ratio, CI: Confidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with HF in patients with VVLEs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnivariate analysis showed that patients undergoing VVLEs who developed HF were more likely to experience medical complications, including wound infection, blood transfusion, hemorrhage/seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Table 5). In our multivariate analysis, HF was associated with wound infection (OR = 0.270; 95% CI = 0.188\u0026ndash;0.388), blood transfusion (OR = 0.885; CI = 0.828\u0026ndash;0.946), hemorrhage/seroma/hematoma (OR = 0.407; CI = 0.301\u0026ndash;0.551), deep venous thrombosis (OR = 0.408; CI = 0.365\u0026ndash;0.457), pulmonary embolism (OR = 0.706; CI = 0.616\u0026ndash;0.810), stroke (OR = 0.830; CI = 0.752\u0026ndash;0.916), and cellulitis of the leg (OR = 1.318; CI = 1.269\u0026ndash;1.369).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003eRelationship between heart failure and complications (2010-2019)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"738\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 303px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 250px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo heart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical complications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eWound infection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e31 (0.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e699 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.188-0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eBlood transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e1065 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e7519 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.828-0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eHemorrhage/seroma/hematoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e45 (0.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e764 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.301-0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eDeep venous thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e345 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e5243 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.365-0.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003ePulmonary embolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e240(1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e2760 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.616-0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e464 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e3490(3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.752-0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eCellulitis of leg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e4336 (26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e21197 (21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e1.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.269-1.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eNoninfectious lymphatic channel disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e9 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e24 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e2.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.203-5.711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003eSeborrheic dermatitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e10 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e122 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.252-0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eArteriovenous fistulas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e7 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e18 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e2.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.049-6.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR: Odds ratio, CI: Confidence interval\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eChronic venous dysfunction, a hallmark of VVLEs, leads to persistent retrograde venous pressure, causing capillary dilation and the accumulation of venous blood within the cutaneous microvasculature. This accumulation results in venous fluid overload, characterized by high capacitance and peripheral edema, both of which contribute to the development of HF. The current study provides a comprehensive health economic analysis of VVLEs patients who experienced HF.\u003c/p\u003e \u003cp\u003eHerein, we observed a gradual increase in HF rates from 2010 to 2019 (from 1.5\u0026ndash;29.8%) that is possibly driven by an aging population, endothelial dysfunction, systemic inflammatory response, hypertension, diabetes, obesity, and smoking [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Another plausible explanation is the existence of a bidirectional causal relationship between venous abnormalities and HF [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It has been reported that advanced age (\u0026ge;\u0026thinsp;65 years) is associated with an increased risk of HF in patients with VVLEs [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], consistent with the findings of this study. This may be attributed to age-related cellular and morphological alterations in the venous system, including endothelial aging, smooth muscle aging, and connective tissue aging. Indeed, old venous vessels are often accompanied by chronic inflammation, and these inflammatory factors may damage myocardial cells, impairing cardiac function and endothelial function. This could ultimately lead to decreased vasodilation and increased cardiac afterload, contributing to the development of HF [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Logistic regression analysis revealed that, compared to White individuals, Black individuals with VVLEs have a higher incidence of HF. These disparities in incidence might be driven by complex factors, including access to care, socioeconomic status, genetic susceptibility, social determinants of health, and implicit bias [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is increasing consensus suggesting that VVLEs patients treated at teaching hospitals are more likely to develop HF [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This correlation may be attributed to the fact that teaching hospitals typically receive complex cases from various regions, with patients often suffering from multiple underlying conditions, such as hypertension, coronary heart disease, and diabetes. The heavier disease burden could ultimately contribute to a higher risk of heart failure [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, we found that hospitals in the South have a higher incidence of HF, possibly due to the higher proportion of high-risk individuals, common health risk factors, and the unequal distribution of medical resources [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Notably, the presence of multiple comorbidities (n\u0026thinsp;\u0026ge;\u0026thinsp;1) was associated with an increased risk of HF in patients with VVLEs. This observation is logical, given that elevated scores on predictive metrics mentioned above typically indicate a more severe health status or illness in patients, which may lead to a greater burden on their cardiovascular system, making them more prone to cardiac insufficiency [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In line with the literature, our study found that HF in patients with VVLEs is associated with prolonged hospital stays, elevated medical expenses, and increased mortality rates. Specifically, the median LOS increased by one day, and the total hospital charge per admission rose by \u003cspan\u003e$\u003c/span\u003e8,723 in VVLEs patients who experienced HF. Contributing factors include associated complications, HF management, family support, prolonged hospitalization, and intensive nursing care [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Importantly, numerous studies have reported a higher mortality rate among patients with HF [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHerein, female sex was identified as a protective factor. One potential explanation is that VVLEs can increase the risk of deep vein thrombosis (DVT), which occurs more frequently in males than in females (11.3% vs. 7.8%), thereby elevating the risk of HF [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, a lower prevalence of private insurance was observed among the HF group, positioning it as a potential protective factor. These findings suggest that socioeconomic status may influence the incidence of HF. Previous studies have indicated that clinical staff may be aware of disparities in insurance coverage or income among patients and may adjust their treatment approaches accordingly [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Patients with VVLEs admitted electively were less likely to develop HF, possibly because elective cases typically involve healthier individuals, while emergency cases often involve more severe or complex conditions that lack thorough assessment [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In addition, urban hospitals were identified as protective factors against HF, likely due to their standardized HF management protocols, extensive medical resources, advanced equipment for HF treatment, and comprehensive training programs for healthcare staff [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHere, logistic regression analysis revealed that chronic pulmonary disease and pulmonary circulation disorders are significant factors that increase the risk of HF. VVLEs patients often concurrently suffer from chronic inflammation and hypercoagulability, which can lead to increased right ventricular afterload, obstructed venous return, and hemodynamic changes, further increasing the burden on the heart and contributing to the development of HF [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Patients with fluid and electrolyte disorders were also found to be at increased risk of HF, which aligns with prior findings that also suggested that imbalances in sodium, potassium, calcium, and magnesium, disturbances in acid-base balance, and excessive or insufficient body fluids are associated with the development of HF [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In our investigation, obesity emerged as an independent risk factor for HF. This correlation may be attributed to the fact that obesity increases the metabolic burden and inflammatory response on the heart, while VVLEs further exacerbate the preload on the heart. Therefore, special attention should be given to weight management and the treatment of VVLEs to reduce the risk of HF [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistent findings in the literature indicate a significant correlation between HF and renal failure in VVLEs patients, likely due to the combination of VVLEs and renal failure, which significantly increases the risk of HF through mechanisms involving increased cardiac load, endothelial dysfunction, inflammation, hypertension, and shared risk factors [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Our study also found that valvular disease was associated with HF, likely because valvular disease can lead to significant hemodynamic changes, such as increased pressure gradients across the valves and altered blood flow patterns. These changes can further impair venous return and exacerbate the symptoms of chronic venous insufficiency, thereby increasing the burden on the heart [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Weight loss was also identified as a risk factor, with a reasonable explanation being that weight loss can lead to malnutrition and deficiencies in essential nutrients. This can result in systemic inflammation and further impair endothelial function, promoting a pro-inflammatory state and impairing vascular function, ultimately increasing the risk of HF [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiabetes with chronic complications is likely associated with chronic inflammation and metabolic abnormalities such as dyslipidemia and insulin resistance, which may contribute to atherosclerosis and cardiovascular disease, thereby increasing the risk of HF [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The present study also found that peptic ulcer disease (excluding bleeding) was associated with an increased risk of HF. Similarly, a previous study found that various inflammatory mediators produced by peptic ulcers may directly damage myocardial cells, impairing the myocardium's systolic and diastolic functions. These mediators can also increase vascular resistance and promote the development of atherosclerosis, further contributing to the risk of HF [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur results indicate that wound infection, blood transfusion, hemorrhage/ seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg are associated with the risk of HF. Specifically, HF in VVLEs cases was linked with wound infection and cellulitis of the leg, likely due to lower limb blood circulation disorders, which reduce the immune defense function of local tissues [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Patients who undergo blood transfusion and experience hemorrhage /seroma/hematoma are more prone to developing HF, possibly because these conditions are often accompanied by additional fluid load or blood volume reduction [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Furthermore, the inflammatory state may increase the vulnerability of the skin and soft tissues, making them more prone to ulcers and infections [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. HF was also associated with DVT, pulmonary embolism, and stroke. DVT leads to obstructed venous return, which increases the burden on the right heart [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Meanwhile, pulmonary embolism may result in chronic pulmonary arterial hypertension, reducing effective ventilation and perfusion in the lungs [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Patients with cerebral infarction often experience slow blood circulation due to prolonged bed rest, which can easily lead to DVT and further increase the risk of pulmonary embolism and HF [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe use of the NIS database presents several inherent limitations. Firstly, patient data is captured only during hospital stays, meaning post-discharge complications, readmission rates, and long-term outcomes are not documented. This limitation could potentially lead to an underestimation of HF incidence [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Secondly, the analysis is restricted to the variables available in the NIS database. Therefore, key HF risk factors, such as body mass index, B-type natriuretic peptide levels, and ejection fraction, are notably absent [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Lastly, coding and documentation discrepancies or misclassifications may arise, as with any large administrative database.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eVVLEs patients who experience HF face significant challenges in terms of clinical outcomes and medical costs. In the present study, several risk factors associated with HF were identified, including advanced age (\u0026ge;\u0026thinsp;65 years), being Black, comorbidities (n\u0026thinsp;\u0026ge;\u0026thinsp;1), teaching hospitals, hospitals in the South, chronic pulmonary disease, fluid and electrolyte disorders, obesity, pulmonary circulation disorders, renal failure, valvular disease, weight loss, diabetes with chronic complications, and peptic ulcer disease. Conversely, female sex, private insurance, elective admission, and urban hospitals were identified as protective factors. Furthermore, wound infection, blood transfusion, hemorrhage/seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg were all linked to HF in VVLEs patients. Additionally, an association was also found between HF, elevated hospital costs, and extended LOS. Collectively, our study could assist healthcare professionals in identifying VVLEs patients at a heightened risk of HF and implementing effective interventions to reduce adverse outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"765\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eVVLEs \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eVaricose veins of the lower extremities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eHF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eHeart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eDVT \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eDeep vein thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eHCUP \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eHealthcare Cost and Utilization Project\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eAHRQ \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eHealthcare Research and Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eSPSS \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eCI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eConfidence intervals\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eICD-9-CM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eInternational Classiffcation of Diseases (ninth revision) Clinical Modiffcation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eICD-10-CM\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eInternational Classiffcation of Diseases (tenth revision) Clinical Modiffcation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eLOS \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eNIS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eNationwide Inpatient Sample\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eOR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 650px;\"\u003e\n \u003cp\u003eOdds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used and analysed in the current study is a publicly available dataset (National Inpatient Sample), part of the Healthcare Cost and Utilization Project from the United States, and can be accessed at the following link: https://hcup-us.ahrq.gov/nisoverview.jsp.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Lei Fan from Nanfang Hospital, Southern Medical University for his invaluable assistance in reviewing the statistical methods employed in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXL wrote and revised the main parts of the manuscript. HYL collected the data, performed the preliminary analysis, and drafted the manuscript. LYZ and DK completed all statistical analyses and data processing. LFW designed and produced all figures and tables. XL and HYL revised the manuscript with input from all other authors. The manuscript was approved by all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHu H, Hu L, Deng Z, Jiang Q. A prognostic nomogram for recurrence survival in post-surgical patients with varicose veins of the lower extremities. 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J Am Heart Assoc. 2023;12(6):e027852.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan MS, Shahid I, Bennis A, Rakisheva A, Metra M, Butler J. Global epidemiology of heart failure. Nat Rev Cardiol. 2024;21(10):717\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVirani SS, Alonso A, Aparicio HJ, et al. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation. 2021;143(8):e254\u0026ndash;254743.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoorsma EM, Ter Maaten JM, Damman K, et al. Congestion in heart failure: a contemporary look at physiology, diagnosis and treatment. Nat Rev Cardiol. 2020;17(10):641\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi S, Leem GH, Song TJ. Association of varicose veins with incidence risk of atrial fibrillation: a population-based cohort study. 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The risk of congestive heart failure is increased in persons with varicose veins. Int Angiol. 2009;28(6):452\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePizano A, Bequeaith B, Cifuentes S, et al. Association between cardiac conditions with venous leg ulcers in patients with chronic venous insufficiency. Phlebology. 2023;38(4):281\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAugey F, Pinet A, Renaudier P. [Heart failure and stasis ulcer: A significant association (prospective study of 100 cases)]. Ann Dermatol Venereol. 2010;137(5):353\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoln\u0026aacute;r A\u0026Aacute;, N\u0026aacute;dasy GL, D\u0026ouml;rnyei G, et al. The aging venous system: from varicosities to vascular cognitive impairment. Geroscience. 2021;43(6):2761\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNayak A, Hicks AJ, Morris AA. 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Am J Lifestyle Med. 2020;14(4):361\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsai CK, Nfor ON, Lu WY, Liaw YP. Association between varicose veins and constitution of traditional Chinese medicine plus heart-failure-like symptoms. Front Cardiovasc Med. 2024;11:1465843.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAslam MR, Muhammad Asif H, Ahmad K, et al. Global impact and contributing factors in varicose vein disease development. SAGE Open Med. 2022;10:20503121221118992.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzar J, Rao A, Oropallo A. Chronic venous insufficiency: a comprehensive review of management. J Wound Care. 2022;31(6):510\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTheofilis P, Oikonomou E, Tsioufis K, Tousoulis D. Diabetes Mellitus and Heart Failure: Epidemiology, Pathophysiologic Mechanisms, and the Role of SGLT2 Inhibitors. Life (Basel). 2023;13(2):497.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun J, Yao J, Ol\u0026eacute;n O, et al. Risk of heart failure in inflammatory bowel disease: a Swedish population-based study. Eur Heart J. 2024;45(28):2493\u0026ndash;504.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwoboda SJ, Schumann H, Kiritsi D. A leg ulcer with pulsating varicose veins - from the legs to the heart. Int Wound J. 2018;15(1):62\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGill K, Fink JC, Gilbertson DT, et al. Red blood cell transfusion, hyperkalemia, and heart failure in advanced chronic kidney disease. Pharmacoepidemiol Drug Saf. 2015;24(6):654\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNochioka K. Simplifying Bleeding Risk Assessment in Heart Failure. Circ J. 2021;86(1):156\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIto T, Kukino R, Sarayama Y, et al. Wound, Pressure Ulcer, and Burn Guidelines-5: Guidelines for the management of lower leg ulcers and varicose veins, second edition. J Dermatol. 2025;52(2):e49\u0026ndash;4969.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Nisio M, van Es N, B\u0026uuml;ller HR. Deep vein thrombosis and pulmonary embolism. Lancet. 2016;388(10063):3060\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRivas A, Lauw MN, Schnabel RB, Crowther M, Van Spall H. Stroke and Thromboembolism in Patients with Heart Failure and Sinus Rhythm: A Matter of Risk Stratification. Thromb Haemost. 2022;122(6):871\u0026ndash;8.\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Heart failure, varicose veins of lower extremities, risk factors, incidence, Nationwide inpatient sample","lastPublishedDoi":"10.21203/rs.3.rs-6498400/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6498400/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo investigate the incidence and risk factors of (HF)in patients with varicose veins of the lower extremities (VVLEs) using a large-scale national database.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective analysis using data from the Nationwide Inpatient Sample (NIS) database spanning 2010 to 2019. The study population included individuals diagnosed with VVLEs. Our evaluation covered various parameters, including patient demographics, hospital characteristics, length of stay, total hospitalization charges, in-hospital mortality, comorbidities, and associated clinical complications.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAnalysis of the NIS database identified 120,748 individuals with VVLEs who met the inclusion criteria. HF developed in 16,463 cases within this cohort, resulting in an overall incidence rate of 14.4%. A temporal analysis revealed a substantial increase in HF occurrence throughout the study period, rising from 1.5% in 2010 to 29.8% in 2019. The comparative assessment showed that VVLEs patients with HF experienced more extended hospital stays, incurred higher healthcare costs, were more likely to utilize Medicare, and had higher in-hospital mortality rates than those that did not experience HF (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Risk factors for HF included advanced age (\u0026ge;\u0026thinsp;65 years), Black race, comorbidities (n\u0026thinsp;\u0026ge;\u0026thinsp;1), treatment at a teaching hospital, hospitalization in the South, female sex, private insurance, elective admission, urban hospital setting, chronic pulmonary disease, fluid and electrolyte disorders, obesity, pulmonary circulation disorders, renal failure, valvular disease, weight loss, diabetes with chronic complications, and peptic ulcer disease (excluding bleeding). Moreover, HF was associated with wound infection, blood transfusion, hemorrhage/ seroma/hematoma, deep venous thrombosis, pulmonary embolism, stroke, and cellulitis of the leg.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eStudying the risk factors associated with HF in patients with VVLEs is essential for implementing preventive management strategies and optimizing patient outcomes.\u003c/p\u003e","manuscriptTitle":"Incidence and risk factors of heart failure in patients with varicose veins of lower extremities: a retrospective nationwide inpatient sample database study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-02 07:12:19","doi":"10.21203/rs.3.rs-6498400/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-15T06:49:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T15:54:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138328010927810413266686007294799028636","date":"2026-04-29T14:09:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-13T17:32:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132349282128105245604421487311386240256","date":"2025-06-10T11:36:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-28T03:08:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-27T06:41:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-07T20:24:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-07T13:12:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-05-07T13:11:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dde4d4bf-0314-465d-ae55-d39ca5c5a472","owner":[],"postedDate":"June 2nd, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-15T06:49:35+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T06:54:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-02 07:12:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6498400","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6498400","identity":"rs-6498400","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}