Safety and Efficacy of Da Vinci Robot-Assisted Atrial Septal Defect Repair in Patients with Different Body Mass Index Levels: A Single-Center Retrospective Analysis

Safety and Efficacy of Da Vinci Robot-Assisted Atrial Septal Defect Repair in Patients with Different Body Mass Index Levels: A Single-Center Retrospective Analysis | 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 Safety and Efficacy of Da Vinci Robot-Assisted Atrial Septal Defect Repair in Patients with Different Body Mass Index Levels: A Single-Center Retrospective Analysis Qingjiang Wang, Rui Dai, Wei Wang, Haoyan Li, Xun Chi, Ziang Sun, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9161563/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Objective This study aims to investigate the impacts of various body mass index (BMI) classifications on perioperative parameters and short-term outcomes in patients undergoing Da Vinci robot-assisted atrial septal defect (ASD) repair providing evidence for personalized perioperative management. Methods A retrospective analysis was conducted on 100 patients who underwent Da Vinci robot-assisted ASD repair at Qingdao University Affiliated Hospital between November 2014 and December 2025. Based on the Chinese adult BMI classification criteria, the patients were categorized into four groups: underweight group (BMI < 18.5 kg/m², n = 9), normal weight group (18.5 ≤ BMI < 24.9 kg/m², n = 52), overweight group (25.0 ≤ BMI < 29.9 kg/m², n = 26), and obese group (BMI ≥ 30.0 kg/m², n = 13). This study compared baseline characteristics, intraoperative indicators, postoperative recovery, and short-term prognosis across these groups. Furthermore, multivariate logistic regression analyzed the independent associations of BMI classification and age with postoperative surgical site infection and hospital readmission. Results No significant differences were observed among the four groups concerning baseline echocardiographic parameters, key intraoperative metrics (e.g., operation duration, cardiopulmonary bypass time), or most postoperative recovery measures (e.g., mechanical ventilation duration, length of intensive care unit stay), with all P > 0.05. No sternotomy conversion or early mortality occurred. Univariate analysis showed the obese group had significantly higher rates of surgical site infection (15.4%) and readmission (23.1%) (all P 0.05). Conclusion Da Vinci robot-assisted ASD repair is safe and effective across different BMI levels, with its minimally invasive nature overcoming weight-related surgical challenges. Although obese patients face higher risks of postoperative infection and readmission, BMI is not an independent influencing factor. Individualized enhanced perioperative management for obese populations is recommended, and weight status should not be a contraindication for this procedure. Body mass index Da Vinci Surgical System Atrial septal defect Perioperative management Short-term prognosis 1. Introduction Atrial septal defect (ASD) represents a prevalent form of congenital heart disease, constituting approximately 13% of all such conditions [ 1 ]. In severe instances, prolonged hemodynamic abnormalities may lead to complications such as pulmonary hypertension and heart failure, necessitating surgical intervention to enhance patient prognosis [ 2 ]. The progression of minimally invasive cardiac surgery techniques has facilitated the adoption of Da Vinci robot-assisted surgery as a significant modality for ASD repair [ 3 , 4 ]. This approach capitalizes on advantages such as three-dimensional visualization and the dexterity of robotic arm manipulation [ 5 ]. Its efficacy in minimizing surgical trauma, expediting recovery, and reducing postoperative complication rates has been extensively corroborated [ 6 , 7 ]. Body mass index (BMI) serves as a fundamental indicator that elucidates the relationship between body weight and height, and it is intricately linked to metabolic status and anatomical structure [ 8 ]. Its influence on the efficacy and prognosis of cardiac surgery has been a longstanding subject of clinical investigation [ 9 ]. Prior research has suggested that both obesity and underweight conditions may impact the perioperative safety and recovery processes of cardiac surgery by modifying thoracic anatomical structures, increasing surgical complexity, and compromising postoperative wound healing and immune function [ 10 , 11 ]. Nevertheless, comprehensive clinical research examining the effects of various BMI classifications on perioperative outcomes and short-term prognosis in Da Vinci robot-assisted ASD repair remains sparse, with inconsistent findings [ 12 ]. Some studies indicate that elevated BMI is associated with prolonged operation durations and heightened complication risks, whereas others do not identify a significant correlation between BMI and surgical outcomes [ 12 , 13 ]. Furthermore, there is a pressing need for high-quality clinical evidence to inform individualized surgical strategies and perioperative management protocols for patients with atypical weight profiles, such as those who are underweight or obese. Building upon this premise, the current study conducted a retrospective analysis of clinical data from 100 patients who underwent Da Vinci robot-assisted ASD repair. The objective was to investigate the impact of varying BMI classifications (underweight, normal weight, overweight, and obese) on patients’ baseline characteristics, intraoperative indicators, postoperative recovery, and short-term outcomes. The study seeks to elucidate the relationship between BMI and the safety and efficacy of surgical procedures, thereby offering reliable insights for the development of individualized perioperative management strategies and the optimization of surgical decision-making. 2. Patients and Methods This study was conducted in compliance with the principles outlined in the Declaration of Helsinki (2013 revision) and received approval from the Institutional Ethics Committee of Qingdao University Affiliated Hospital. Due to the retrospective design of the study, the requirement for individual informed consent was waived. 2.1. Study Population A retrospective study was conducted involving 100 patients who underwent Da Vinci robot-assisted ASD repair at our hospital between November 2014 and December 2025, with comprehensive clinical data available for all patients. The inclusion criteria were as follows: (1) ASD diagnosis confirmed via echocardiography, with indications for surgical repair; (2) no history of prior cardiac surgery; and (3) availability of complete clinical data, encompassing baseline characteristics, intraoperative records, and postoperative follow-up information. The exclusion criteria were (1) presence of other complex congenital heart diseases, severe valvular heart disease, or coronary artery disease; (2) preoperative severe complications, including severe infection, liver or kidney failure, or coagulation disorders; and (3) extreme BMI values, defined as less than 15 kg/m² or greater than 50 kg/m². The patients were stratified into four categories based on the Chinese adult BMI classification criteria and clinical practice guidelines: underweight group (BMI < 18.5 kg/m²), normal weight group (18.5 ≤ BMI < 24.9 kg/m²), overweight group (25.0 ≤ BMI < 29.9 kg/m²), and obese group (BMI ≥ 30.0 kg/m²). 2.2. Surgical Methods All surgical procedures were conducted by a consistent team of experienced cardiac surgeons utilizing the Da Vinci Si or Xi robotic surgical systems. Following the successful induction of general anesthesia, a central venous catheter was inserted via percutaneous puncture of the right internal jugular vein, and a 16-Fr venous catheter was placed as the superior vena cava drainage tube. Cardiopulmonary bypass (CPB) was initiated through femoral arteriovenous cannulation. A primary operating port and surgical lens entry site were established via a 3–5 cm incision at the midclavicular line of the 4th intercostal space. Additional 5 mm incisions were made at the anterior axillary line of the 2nd and 6th intercostal spaces, as well as the parasternal region of the 5th intercostal space, to accommodate the insertion of the left and right robotic arms and the atrial retractor. Following pericardiotomy, tapes were placed around the superior and inferior vena cava for standby use. A purse-string suture was initially placed at the aortic root, followed by the insertion of a catheter for the delivery of cardioplegic solution. Subsequently, a cross-clamp was applied to the ascending aorta to obstruct blood flow, and cardioplegic solution was administered to induce cardiac arrest. Thereafter, the superior and inferior vena cava were clamped, and an incision was made in the right atrium. Closure of the ASD was performed either through direct suturing or by using a pericardial patch, contingent upon the size and condition of the defect's edges. Following the completion of suturing, a thorough evacuation of air was conducted, the cross-clamp on the ascending aorta was released, and the incision in the right atrium was sutured after the resumption of cardiac activity. In certain cases, ASD repair was conducted under beating heart conditions, depending on the patient's clinical status and anatomical features. After removing CPB catheters, thorough hemostasis was performed, followed by layered chest closure. 2.3. Statistical Methods Data analysis was conducted using SPSS version 26.0. For normally distributed continuous variables, data were represented as mean ± standard deviation, and intergroup comparisons were made using one-way analysis of variance (ANOVA). For non-normally distributed continuous variables, data were expressed as median (interquartile range) [M (Q1, Q3)], and intergroup comparisons were performed using the Kruskal-Wallis H test. Categorical variables were presented as frequencies and percentages (n [%]), with intergroup comparisons conducted using either the χ² test or Fisher's exact test. To investigate the independent associations of BMI classification and age with postoperative surgical site infection and hospital readmission rates, multivariate logistic regression analysis was employed. Variables with a P-value less than 0.05 in the univariate analysis were included in the regression model. A P-value of less than 0.05 was considered indicative of statistical significance. Potential confounding factors such as diabetes mellitus and operation duration were initially evaluated but excluded due to non-significance in univariate analysis (all P > 0.05). 3. Results 3.1. Baseline Characteristics of Patients A cohort of 100 patients diagnosed with ASD was recruited for the study, with BMI values ranging from 15.40 to 46.88 kg/m². Notable differences were identified in the age distribution across the four groups (P = 0.034), with the obese group exhibiting the highest mean age of 47 years (range: 33–59 years), whereas the underweight group demonstrated the lowest mean age of 19 years (range: 14–31 years). No statistically significant differences were observed in terms of gender distribution, New York Heart Association (NYHA) functional classification, or the presence of comorbidities, which included first-degree atrioventricular block, right bundle-branch block, atrial fibrillation, coronary heart disease, hypertension, diabetes mellitus, and cerebrovascular disease, among the four groups (all P > 0.05). Furthermore, echocardiographic assessments revealed no significant differences in ASD size, left ventricular ejection fraction (LVEF), or pulmonary artery pressure among the groups (all P > 0.05), as detailed in Table 1 . Table 1 Basement characteristics of the patients Age (years) Underweight group (n = 9) Normal weight group (n = 52) Overweight group (n = 26) Obese group (n = 13) p -value 19 (14–31) 38 (27–53) 42 (30–58) 47 (33–59) 0.034 Male gender, n (%) 7 (77.8) 36 (69.2) 15 (57.7) 9 (69.2) 0.652 NYHA class, n (%) 0.788 I 5 (55.6) 21 (40.4) 8 (30.8) 3 (23.1) II 2 (22.2) 23 (44.2) 14 (53.8) 9 (69.2) III 2 (22.2) 8 (15.4) 4 (15.4) 1 (7.7) IV 0 (0) 0 (0) 0 (0) 0 (0) Comorbidities, n (%) First - degree Atrioventricular Block or Right Bundle - Branch Block 2 (22.2) 11 (21.2) 6 (23.1) 4 (30.8) 0.915 Atrial Fibrillation 1 (11.1) 4 (7.7) 3 (11.5) 0 (0) 0.523 Coronary Heart Disease 0 (0) 1 (1.9) 1 (3.8) 1 (7.7) 0.228 Hypertension 1 (11.1) 3 (5.8) 7 (26.9) 2 (15.4) 0.086 Diabetes mellitus 0 (0) 0 (0) 2 (7.7) 0 (0) 0.328 Cerebrovascular disease 0 (0) 2 (3.8) 2 (7.7) 0 (0) 0.864 Echocardiographic data ASD size (cm) 2.42 ± 0.80 2.68 ± 0.76 2.67 ± 0.95 2.57 ± 0.97 0.836 LVEF (%) 62 (60–62) 62 (60–64) 62 (60–63) 61 (60–65) 0.705 Pulmonary artery pressure(mmHg) 52.22 ± 12.59 49.54 ± 13.19 44.73 ± 12.69 45.00 ± 9.74 0.243 BMI : body mass index; NYHA : New York Heart Association; ASD : atrial septal defect; LVEF : left ventricular ejection fraction. 3.2. Intraoperative Indicators No statistically significant differences were identified among the four groups concerning operation duration, CPB time, the proportion of cardioplegic arrest surgeries, aortic cross-clamp time, the proportion of patch closures, or red blood cell (RBC) transfusion requirements (all P > 0.05). Additionally, there were no instances of sternotomy conversion in any of the groups, as detailed in Table 2 . Table 2 Intraoperative data of the patients Operation duration (minutes) Underweight group (n = 9) Normal weight group (n = 52) Overweight group (n = 26) Obese group (n = 13) p -value 240 (200–245) 200 (180–240) 228 (195–255) 240 (200–280) 0.150 CPB time (minutes) 74 (69–95) 85 (66–105) 97 (76–122) 90 (84–110) 0.267 Cardioplegic Arrest surgery, n (%) 9 (100) 37 (71.2) 18 (69.2) 12 (92.3) 0.928 Aortic cross-clamp time (minutes) 0 (0–0) 0 (0–42) 0 (0–52) 0 (0–0) 0.138 Patch closure, n (%) 6 (66.7) 43 (82.7) 20 (76.9) 10 (76.9) 0.733 RBC transfusion (units) 0 (0–0) 0 (0–0) 0 (0–0) 0 (0–0) 0.787 Sternotomy conversion, n (%) 0 (0) 0 (0) 0 (0) 0 (0) - CPB : cardiopulmonary bypass; ASD : atrial septal defect; RBC : red blood cell. 3.3. Postoperative Indicators The analysis revealed no statistically significant differences among the four groups concerning duration of mechanical ventilation, postoperative 24-hour drainage volume, length of intensive care unit (ICU) stay, length of postoperative stay, postoperative RBC transfusion, early mortality rates, 30 - day mortality, or LVEF and pulmonary artery pressure measurements both immediately after surgery and at one month postoperatively (all P > 0.05). In terms of postoperative complications, the analysis revealed no statistically significant differences among the four groups concerning the incidence of residual ASD shunt, re-exploration for bleeding, new-onset stroke, new-onset atrial fibrillation, ventricular premature beats, pericardial effusion, second CPB, pulmonary infection, liver dysfunction, pneumothorax, or lower extremity vascular embolism (all P > 0.05). Conversely, significant differences were observed in the incidence of postoperative surgical site infection and hospital readmission rates (P = 0.009 and P = 0.001, respectively). Specifically, the obese group exhibited the highest incidence of postoperative surgical site infection at 15.4%, followed by the overweight group at 3.8%, with no cases reported in the underweight and normal weight groups. Similarly, the hospital readmission rate was highest in the obese group at 23.1%, followed by the overweight group at 7.7%, with no hospital readmission occurring in the underweight and normal weight groups, as detailed in Table 3 . Table 3 Postoperative data of the patients Duration of mechanical ventilation (hours) Underweight group (n = 9) Normal weight group (n = 52) Overweight group (n = 26) Obese group (n = 13) p -value 12 (10–13) 11 (9–15) 13(9–19) 13(10–18) 0.663 Postoperative 24-hour drainage volume (ml) 100 (55–130) 160 (80–230) 120 (70–170) 140 (90–220) 0.462 Length of ICU stay (hours) 67(49–72) 65(42–88) 71(60–96) 72 (43–87) 0.309 Length of postoperative stay (days) 10.78 ± 3.11 9.85 ± 3.23 10.19 ± 2.38 9.69 ± 2.96 0.803 RBC transfusion (units) 0 (0–0) 0 (0–0) 0 (0–0) 0 (0–0) 0.347 Early mortality, n (%) 0 (0) 0 (0) 0 (0) 0 (0) - Complications, n (%) Residual ASD shunt 0 (0) 0 (0) 0 (0) 1 (7.7) 0.058 Re-exploration for bleeding 1 (11.1) 0 (0) 1 (3.8) 0 (0) 0.460 New-onset stroke 0 (0) 1 (1.9) 0 (0) 0 (0) 0.603 New-onset atrial fibrillation 1 (11.1) 2 (3.8) 2 (7.7) 2 (15.4) 0.526 Postoperative surgical site infection 0 (0) 0 (0) 1 (3.8) 2 (15.4) 0.009 Ventricular premature beats 0 (0) 2 (3.8) 0 (0) 1 (7.7) 0.617 Pericardial effusion 0 (0) 0 (0) 0 (0) 1 (7.7) 0.058 Second cardiopulmonary bypass 0 (0) 0 (0) 1 (3.8) 0 (0) 0.491 Pulmonary infection 0 (0) 3 (5.8) 2 (7.7) 0 (0) 0.934 Liver dysfunction 0 (0) 2 (3.8) 0 (0) 0 (0) 0.460 Pneumothorax 0 (0) 2 (3.8) 0 (0) 0 (0) 0.460 Lower extremity vascular embolism 0 (0) 0 (0) 1 (3.8) 0 (0) 0.491 Hospital readmission, n (%) 0 (0) 0 (0) 2 (7.7) 3 (23.1) 0.001 30 - day mortality, n (%) 0 (0) 0 (0) 0 (0) 0 (0) Postoperative LVEF (%) 61 (60–64) 61 (60–63) 62 (60–63) 62 (60–63) 0.847 Postoperative pulmonary artery pressure (mmHg) 35.67 ± 12.47 31.25 ± 10.84 28.73 ± 4.50 29.62 ± 5.95 0.253 1-month postoperative LVEF (%) 61 (60–62) 62 (61–63) 62 (60–63) 62 (60–62) 0.338 1-month postoperative pulmonary artery pressure (mmHg) 28.33 ± 15.89 27.13 ± 9.72 27.19 ± 8.86 29.85 ± 7.81 0.834 ICU : intensive care unit; ASD : atrial septal defect; LVEF : left ventricular ejection fraction; RBC : red blood cell. 3.4. Multivariate Logistic Regression Analysis of Hospital readmission and Postoperative Surgical Site Infection 3.4.1. Hospital readmission Risk Analysis A binary logistic regression analysis was conducted, with hospital readmission serving as the dependent variable, while age and BMI classification (using the underweight group as the reference category) were included as independent variables. The analysis indicated that the model demonstrated a good overall fit, as evidenced by the Hosmer-Lemeshow test (χ²=2.781, P = 0.947), and accounted for 33.5% of the variance in hospital readmission risk (Nagelkerke R²=0.335). Furthermore, the model was found to be statistically significant (χ²=11.626, P = 0.020). However, no significant associations were identified between age or any BMI classification (normal weight, overweight, or obese groups) and the risk of hospital readmission, with all P-values exceeding 0.05 (refer to Table 4 , Table 5 , and Table 6 ). Table 4 Model summary of hospital readmission -2 Log Likelihood Cox & Snell R Square Nagelkerke R Square Chi-Square Significance ( p -value) 28.077a 0.110 0.335 11.626 0.020 Table 5 Hosmer-Lemeshow test of hospital readmission Chi-Square Significance ( p -value) 2.781 0.947 Table 6 Variable of hospital readmission B Std. Error Wald Significance ( p -value) Exp(B) 95% CI for Exp(B) Lower Bound Upper Bound Age (years) -0.008 0.031 0.071 0.790 0.992 0.934 1.053 BMI Group (Reference: Underweight group) 1.733 0.630 Normal weight group -20.162 13383.344 0.000 0.999 0.000 0.000 . Overweight group -20.058 5568.273 0.000 0.997 0.000 0.000 . Obese group -1.312 0.997 1.733 0.188 0.269 0.038 1.899 Constant -0.834 1.524 0.300 0.584 0.434 BMI: body mass index. 3.4.2. Postoperative Surgical Site Infection Risk Analysis A binary logistic regression analysis was performed with postoperative surgical site infection as the dependent variable, while age and BMI classification (using the underweight group as the reference category) served as independent variables. The findings demonstrated that the model exhibited a good fit, as evidenced by the Hosmer-Lemeshow test (χ²=2.915, P = 0.940), and accounted for 31.8% of the variance in the risk of postoperative surgical site infection, as indicated by the Nagelkerke R² value of 0.318. However, the overall statistical significance of the model was only marginally significant (χ²=7.811, P = 0.099). Furthermore, no significant associations were identified between age or any BMI classification and the risk of postoperative surgical site infection, with all P-values exceeding 0.05 (refer to Table 7 , Table 8 , and Table 9 ). Table 7 Model summary of the postoperative surgical site infection -2 Log Likelihood Cox & Snell R Square Nagelkerke R Square Chi-Square Significance ( p -value) 19.138a 0.075 0.318 7.811 0.099 Table 8 Hosmer-Lemeshow test of the postoperative surgical site infection Chi-Square Significance ( p -value) 2.915 0.940 Table 9 Variable of the postoperative surgical site infection B Std. Error Wald Significance ( p -value) Exp(B) 95% CI for Exp(B) Lower Bound Upper Bound Age (years) 0.030 0.044 0.453 0.501 1.030 0.945 1.122 BMI Group (Reference: Underweight group) 1.251 0.741 Normal weight group -18.960 13177.067 0.000 0.999 0.000 0.000 . Overweight group -19.308 5508.820 0.000 0.997 0.000 0.000 . Obese group -1.440 1.287 1.251 0.263 0.237 0.019 2.955 Constant -3.131 2.351 1.774 0.183 0.044 BMI: body mass index. 4. Discussion This study aimed to examine the influence of various BMI classifications (underweight, normal weight, overweight, and obese) on perioperative indicators and short-term prognosis in patients undergoing Da Vinci robot-assisted ASD repair. A retrospective analysis of clinical data from 100 enrolled patients indicated no significant differences in baseline characteristics, key intraoperative indicators (such as operation duration and CPB time), or most postoperative recovery indicators (including duration of mechanical ventilation and length of ICU stay) across different BMI groups (all P > 0.05). Nevertheless, the obese group exhibited significantly higher rates of postoperative surgical site infection (15.4%) and hospital readmission (23.1%) compared to other groups (P 0.05). These findings suggest that obesity may be a potential factor influencing specific postoperative complications in ASD patients and that clinical outcomes may be modulated by the interaction of multiple factors. This provides valuable clinical evidence for optimizing the perioperative management of such patients. In this study, baseline echocardiographic parameters, including ASD size, LVEF, and pulmonary artery pressure, as well as the distribution of comorbidities, were generally comparable across the four groups, with the exception of age. The obese group exhibited a higher mean age, a difference potentially attributable to the cumulative effects of obesity-related metabolic disorders [ 14 ]. Maria-Dolores et al.'s decade-long cohort study demonstrated a significant increase in BMI with advancing age among adults aged 18–60 years (P < 0.05) [ 15 ]. The underlying mechanisms may involve age-associated reductions in basal metabolic rate, alterations in lifestyle, and hormonal changes, all contributing to weight gain and increased BMI [ 16 ]. Furthermore, older individuals are more susceptible to comorbidities such as metabolic syndrome, diabetes mellitus, and cardiovascular diseases, underscoring the importance of considering age as a critical factor in discussions of obesity and its related health implications [ 17 ]. In terms of intraoperative indicators, no significant differences were observed in operation duration, CPB time, or aortic cross-clamp time across the four groups (all P > 0.05), thereby affirming the clinical applicability of Da Vinci robot-assisted surgery in patients with varying BMI levels. This finding contradicts the conclusion drawn by Sergio et al., which posits that "high BMI prolongs operation duration" [ 18 ]. The observed discrepancy may be attributed to the specific anatomical characteristics involved in ASD repair: the surgical field is primarily concentrated within the atrium, and the influence of thoracic fat accumulation on atrial exposure in obese patients is relatively minimal [ 19 ]. Furthermore, the three-dimensional visualization and the dexterous manipulation capabilities of the Da Vinci robotic system effectively mitigate the spatial constraints imposed by obesity, facilitating enhanced anatomical exposure, reducing the complexity of the procedure, and thereby preserving surgical efficiency [ 5 ]. Individualized technical adjustments and perioperative management strategies are essential for patients with varying BMI levels. For obese patients, it is recommended to conduct preoperative chest CT scans to evaluate chest wall fat thickness and to tailor the positioning of operating ports accordingly [ 6 ]. During surgery, the use of adaptive instruments, such as lengthened trocars, is advised, along with the prioritization of beating heart surgery to minimize the risk of aortic injury [ 20 ]. Postoperatively, enhanced blood glucose control and meticulous incision care are crucial to reduce the risk of infection [ 21 ]. Conversely, for young and underweight patients, who possess slender blood vessels with high wall elasticity and are susceptible to vasospasm, a detailed preoperative vascular assessment is imperative [ 22 ]. Intraoperatively, real-time ultrasound should be employed to localize vascular pathways, and local application of nitroglycerin prior to puncture is recommended to prevent spasm [ 23 ]. The use of small-caliber, thin-walled puncture needles and adaptive cannulas, along with gentle handling to avoid repeated puncture or aggressive dilation, is advised [ 24 ]. If vasospasm occurs, the operation should be paused and spasmolytic drugs administered; open intubation under direct vision may be necessary [ 25 ]. Additionally, CPB should be conducted using a low-flow and low-pressure perfusion mode [ 21 ]. In terms of short-term postoperative recovery, no significant differences were observed among the four groups in duration of mechanical ventilation, length of ICU stay, length of postoperative stay, or cardiac function recovery, including LVEF and pulmonary artery pressure immediately after surgery and one month postoperatively (all P > 0.05). Notably, there were no instances of sternotomy conversion, early mortality, or 30-day mortality within the entire cohort. These findings further substantiate the efficacy of Da Vinci robot-assisted surgery in mitigating the impact of BMI-related physiological variations on postoperative recovery. The study by Li et al. corroborates these results, demonstrating that, compared to traditional thoracotomy, Da Vinci robot-assisted surgery is associated with smaller incisions, reduced trauma to chest wall muscles and bones, and less postoperative pain, facilitating earlier mobilization and consequently reducing mechanical ventilation time and hospital stay [ 26 ]. Remarkably, both underweight and obese patients exhibited comparable short-term recovery outcomes to those of normal-weight patients, thereby challenging the conventional notion that "obese patients experience delayed postoperative recovery" following traditional thoracotomy [ 12 ]. While univariate analysis revealed statistically significant associations between BMI classification and both postoperative surgical site infection and hospital readmission rate (all P 0.05). Several factors may account for this discrepancy: firstly, the relatively small sample size of the study, particularly within the underweight (n = 9) and obese (n = 13) groups, may have resulted in insufficient statistical power to detect potential independent associations between BMI and the outcomes. Secondly, the regression model was limited to age and BMI classification as independent variables, whereas postoperative infection and hospital readmission are likely influenced by numerous confounding factors, such as perioperative antibiotic use, quality of incision care, postoperative activity level, and management of comorbid metabolic diseases [ 27 ]. The exclusion of these variables may obscure the independent effect of BMI. Thirdly, the Da Vinci robot-assisted surgery is characterized by an extensive learning curve, with increased surgical complexity observed in obese patients [ 28 , 29 ]. These procedures are typically conducted once surgeons have surpassed the learning curve, and the implementation of standardized operating procedures may mitigate outcome disparities among patients with varying BMI levels. Consequently, it becomes challenging for BMI alone to exhibit an independent risk contribution. Fourth, the presence of exceedingly large standard errors in certain BMI categories (specifically, the normal weight and overweight groups) within the regression model indicates potential issues of multicollinearity or uneven sample distribution, which could compromise the reliability of parameter estimation. From a clinical standpoint, the regression results do not dismiss the potential risks associated with obesity but rather highlight the complexity of clinical outcomes. The influence of obesity on postoperative infection and hospital readmission may not be a direct, independent effect; instead, it may occur through synergistic interactions with factors such as blood glucose control, immune function, and the quality of incision care [ 14 , 16 ]. Consequently, it is imperative to optimize perioperative management strategies based on BMI characteristics. For obese patients, this includes preoperative regulation of metabolic indicators such as blood glucose and lipids to improve insulin resistance; precise intraoperative puncture positioning to avoid areas with significant fat accumulation; optimization of incision location; enhanced hemostasis and sterile techniques to reduce infection risks; and postoperative measures such as improved incision care (e.g., maintaining a dry and clean incision, regular dressing changes), early rehabilitation exercises (to promote local blood circulation and accelerate wound healing), and the judicious use of antibiotics, while developing a comprehensive long-term follow-up mechanism designed to promptly identify signs of infection and implement targeted interventions aimed at reducing the risk of hospital readmission [ 9 , 12 , 13 ]. This study is subject to several limitations. Firstly, the relatively small sample size, particularly within the underweight and obese cohorts, may compromise the stability and external validity of the statistical findings. Secondly, the single-center retrospective design inherently introduces selection bias, and the absence of long-term prognostic data hinders a comprehensive assessment of the impact of BMI on patients' long-term outcomes. Thirdly, the regression model incorporated only age and BMI classification as independent variables, neglecting potential confounding factors such as blood glucose levels, lipid profiles, metabolic indicators, immune function, and quality of care, which could introduce bias into the results. Fourthly, instability in parameter estimation was observed in certain BMI groups within the regression model, potentially attributable to sample distribution characteristics or model specifications. Lastly, the absence of a traditional thoracotomy control group precludes direct comparison of the clinical advantages associated with different surgical approaches across varying BMI levels. Future research should aim to increase the sample size and employ a multicenter prospective design. It is essential to include a control cohort comprising both Da Vinci robot-assisted surgery and traditional thoracotomy to rigorously assess the long-term clinical benefits of minimally invasive techniques in patients with ASD across various BMI categories. Additionally, refining observational indicators and meticulously documenting surgical procedures and postoperative rehabilitation interventions will aid in developing a more comprehensive prognostic prediction model. Extending the follow-up period to at least one year is recommended to thoroughly evaluate the impact of BMI on long-term cardiac function, metabolism-related complications, and quality of life. This approach will provide robust clinical evidence to support the personalized application of Da Vinci robot-assisted surgery. 5. Conclusion In conclusion, Da Vinci robot-assisted ASD repair exhibits favorable safety and efficacy across patients with varying BMI levels. The minimally invasive nature of this technique effectively addresses surgical challenges associated with weight-related factors, ensuring consistent short-term clinical recovery outcomes for all patients. Although multivariate analysis did not reveal independent associations between BMI and the risk of postoperative surgical site infections or hospital readmission (all P > 0.05), obese patients remain at a significantly higher risk for these adverse outcomes (all P < 0.05). Clinical practice should incorporate individualized and enhanced perioperative management strategies for obese populations. Importantly, weight status should not serve as a contraindication for ASD patients considering Da Vinci robot-assisted repair. The focus should be on optimizing surgical processes and postoperative care plans tailored to BMI characteristics to maximize the clinical benefits of this minimally invasive approach. Abbreviations ASD Atrial Septal Defect BMI Body Mass Index CPB Cardiopulmonary Bypass ICU Intensive Care Unit LVEF Left Ventricular Ejection Fraction NYHA New York Heart Association RBC Red Blood Cell ANOVA Analysis of Variance BMI : body mass index; NYHA : New York Heart Association; ASD : atrial septal defect; LVEF : left ventricular ejection fraction. CPB : cardiopulmonary bypass; ASD : atrial septal defect; RBC : red blood cell. ICU : intensive care unit; ASD : atrial septal defect; LVEF : left ventricular ejection fraction; RBC : red blood cell. Declarations Ethics Approval and Consent to Participate This study was approved by the institutional review board of The Affiliated Hospital of Qingdao University (Approval number QYFY WZLL 42136). Since the study was a retrospective study, informed consent was waived by the Ethics Committee. This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Consent for Publication Not applicable. Availability of data and materials The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests Funding This work received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions Sumin Yang, Wei Wang, and Qingjiang Wang participated in the surgery. Haoyan Li, Xun Chi, and Ziang Sun participated in data collection. Qingjiang Wang and Rui Dai contributed to revising and drafting the manuscript. All authors read and approved the final manuscript. Acknowledgements We would like to thank Lianbao Chi for his valuable assistance in the translation and polishing of this manuscript. References Nashat H, Montanaro C, Li W, Kempny A, Wort SJ, Dimopoulos K, et al. Atrial septal defects and pulmonary arterial hypertension. J Thorac Dis. 2018;10:S2953–65. https://doi.org/10.21037/jtd.2018.08.92 . Brida M, Chessa M, Celermajer D, Li W, Geva T, Khairy P, et al. Atrial septal defect in adulthood: a new paradigm for congenital heart disease. Eur Heart J. 2022;43:2660–71. https://doi.org/10.1093/eurheartj/ehab646 . Yun T, Kim H, Sohn B, Chang HW, Lim C, Park K-H. Robot-Assisted Repair of Atrial Septal Defect: A Comparison of Beating and Non-Beating Heart Surgery. J Chest Surg. 2022;55:55–60. https://doi.org/10.5090/jcs.21.111 . Li X, Liu Z, Kong R, Zhang C, Ge S. Robot-assisted beating‐heart surgery for atrial septal defect repair in a case of situs inversus totalis with dextrocardia. Int J Med Robot. 2021;17:e2304. https://doi.org/10.1002/rcs.2304 . Woo YJ. Robotic cardiac surgery. Int J Med Robot. 2006;2:225–32. https://doi.org/10.1002/rcs.98 . Kadan M, Erol G, Kubat E, İnce ME, Akyol FB, Karabacak K, et al. Robotic repair of atrial septal defect with partial pulmonary venous return anomaly: Our 5 year experience. Int J Med Robot. 2022;18:e2395. https://doi.org/10.1002/rcs.2395 . Kim K, Kim YS, Kim HR, Kim HJ, Yoo JS, Kim JB, et al. Robotic repair of atrial septal defect: Pre-groove vertical right atriotomy approach. JTCVS Tech. 2024;28:73–81. https://doi.org/10.1016/j.xjtc.2024.05.022 . James WPT. The epidemiology of obesity: the size of the problem. J Intern Med. 2008;263:336–52. https://doi.org/10.1111/j.1365-2796.2008.01922.x . Rosengren A. Obesity and cardiovascular health: the size of the problem. Eur Heart J. 2021;42:3404–6. https://doi.org/10.1093/eurheartj/ehab518 . Bai Y-X, Wang Z-H, Lv Y, Liu J, Xu Z-Z, Feng Y-Q, et al. Association between frailty and acute kidney injury after cardiac surgery: unraveling the moderation effect of body fat through an international, retrospective, multicohort study. Int J Surg. 2025;111:761–70. https://doi.org/10.1097/JS9.0000000000001861 . Ghanta RK, LaPar DJ, Zhang Q, Devarkonda V, Isbell JM, Yarboro LT, et al. Obesity Increases Risk-Adjusted Morbidity, Mortality, and Cost Following Cardiac Surgery. J Am Heart Assoc. 2017;6:e003831. https://doi.org/10.1161/JAHA.116.003831 . Wu W, Ding R, Chen J, Yuan Y, Song Y, Yan M, et al. Effect of body mass index on clinical outcomes after robotic cardiac surgery: is there an obesity paradox? BMC Cardiovasc Disord. 2023;23:271. https://doi.org/10.1186/s12872-023-03277-w . Senay S, Cacur O, Bastopcu M, Gullu AU, Kocyigit M, Alhan C. Robotic mitral valve operations can be safely performed in obese patients. J Card Surg. 2021;36:3126–30. https://doi.org/10.1111/jocs.15758 . Salas-Salvadó J, Díaz-López A, Ruiz-Canela M, Basora J, Fitó M, Corella D, et al. Effect of a Lifestyle Intervention Program With Energy-Restricted Mediterranean Diet and Exercise on Weight Loss and Cardiovascular Risk Factors: One-Year Results of the PREDIMED-Plus Trial. Diabetes Care. 2019;42:777–88. https://doi.org/10.2337/dc18-0836 . Santos M-D, Buti M, López-Cano C, Sánchez E, Vidal A, Hernández M, et al. Dynamics of Anthropometric Indices in a Large Paired Cohort With 10 Years of Follow-Up: Paving the Way to Sarcopenic Obesity. Front Endocrinol. 2020;11:209. https://doi.org/10.3389/fendo.2020.00209 . Inoue Y, Qin B, Poti J, Sokol R, Gordon-Larsen P. Epidemiology of Obesity in Adults: Latest Trends. Curr Obes Rep. 2018;7:276–88. https://doi.org/10.1007/s13679-018-0317-8 . Gutiérrez-Fisac JL, Guallar‐Castillón P, León‐Muñoz LM, Graciani A, Banegas JR, Rodríguez‐Artalejo F. Prevalence of general and abdominal obesity in the adult population of Spain, 2008–2010: the ENRICA study. Obes Rev. 2012;13:388–92. https://doi.org/10.1111/j.1467-789X.2011.00964.x . Fernandez-Pello S, Verma N, Kuusk T, Berezowska A, Mumtaz F, Patki P, et al. Perioperative impact of body mass index on upper urinary tract and renal robot-assisted surgery: a single high-volume centre experience. J Robot Surg. 2022;16:611–9. https://doi.org/10.1007/s11701-021-01285-6 . Senay S, Gullu AU, Kocyigit M, Degirmencioglu A, Karabulut H, Alhan C. Robotic atrial septal defect closure. Multimed Man Cardio-Thorac Surg. 2014;2014:mmu014–014. https://doi.org/10.1093/mmcts/mmu014 . Ishikawa N, Watanabe G. Robot-Assisted Cardiac Surgery. Ann Thorac Cardiovasc Surg. 2015;21:322–8. https://doi.org/10.5761/atcs.ra.15-00145 . Yun T, Kim H, Sohn B, Chang HW, Lim C, Park K-H. Robot-Assisted Repair of Atrial Septal Defect: A Comparison of Beating and Non-Beating Heart Surgery. J Chest Surg. 2022;55:55–60. https://doi.org/10.5090/jcs.21.111 . Ceresa F, Sansone F, Patanè F. Role of Preoperative Femoral Artery Color Doppler Echocardiography in Minimally Invasive Cardiac Surgery. Innov Technol Tech Cardiothorac Vasc Surg. 2012;7:441–4. https://doi.org/10.1177/155698451200700612 . Sen O, Aydin U, Kadirogullari E, Bayram M, Karacalilar M, Kutluk E, et al. Mid-Term Results of Peripheral Cannulation After Robotic Cardiac Surgery. Braz J Cardiovasc Surg [Internet]. 2018. https://doi.org/10.21470/1678-9741-2018-0061 . [cited 2026 Mar 2];33. Nakajima H, Takazawa A, Tounaga C, Yoshitake A, Tochii M, Hayashi J, et al. Comparison of the Efficacy of Transthoracic Cannulation into the Ascending Aorta Versus Femoral Artery Cannulation in Minimally Invasive Cardiac Surgery. Innov Technol Tech Cardiothorac Vasc Surg. 2019;14:537–44. https://doi.org/10.1177/1556984519879123 . Von Segesser LK. Peripheral cannulation for cardiopulmonary bypass. Multimed Man Cardio-Thorac Surg. 2006;2006. https://doi.org/10.1510/mmcts.2005.001610 . mmcts.2005.001610. Li C, Zhang T, Wang H, Hou Z, Zhang Y, Chen W. Advanced surgical tool: Progress in clinical application of intelligent surgical robot. Smart Med. 2022;1:e20220021. https://doi.org/10.1002/SMMD.20220021 . Maniar HS, Bell JM, Moon MR, Meyers BF, Marsala J, Lawton JS, et al. Prospective evaluation of patients readmitted after cardiac surgery: Analysis of outcomes and identification of risk factors. J Thorac Cardiovasc Surg. 2014;147:1013–20. https://doi.org/10.1016/j.jtcvs.2013.10.066 . Tatooles AJ, Pappas PS, Gordon PJ, Slaughter MS. Minimally invasive mitral valve repair using the da Vinci robotic system. Ann Thorac Surg. 2004;77:1978–84. https://doi.org/10.1016/j.athoracsur.2003.11.024 . Balkhy HH. Robotic totally endoscopic coronary artery bypass grafting: It’s now or never! JTCVS Tech. 2021;10:153–7. https://doi.org/10.1016/j.xjtc.2021.03.037 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 06 Apr, 2026 Reviews received at journal 02 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviewers invited by journal 02 Apr, 2026 Editor assigned by journal 21 Mar, 2026 Submission checks completed at journal 21 Mar, 2026 First submitted to journal 18 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-9161563","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618136178,"identity":"5634d598-2f9c-492d-b66b-02712419b30b","order_by":0,"name":"Qingjiang Wang","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Qingjiang","middleName":"","lastName":"Wang","suffix":""},{"id":618136179,"identity":"520cb267-49ed-484d-9c8f-8542140235af","order_by":1,"name":"Rui Dai","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Dai","suffix":""},{"id":618136180,"identity":"8280f286-5baf-439c-bf30-d710b4182735","order_by":2,"name":"Wei Wang","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Wang","suffix":""},{"id":618136181,"identity":"6e33772b-ee80-4890-b241-a18d2bd15c95","order_by":3,"name":"Haoyan Li","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Haoyan","middleName":"","lastName":"Li","suffix":""},{"id":618136182,"identity":"c7c65503-9894-4de8-82a8-40835bbde994","order_by":4,"name":"Xun Chi","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Xun","middleName":"","lastName":"Chi","suffix":""},{"id":618136183,"identity":"a66b2665-9382-416b-b571-29e79cfd4b40","order_by":5,"name":"Ziang Sun","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Ziang","middleName":"","lastName":"Sun","suffix":""},{"id":618136184,"identity":"e5c68c6d-27f9-4186-8f42-fad6ed1f7f2e","order_by":6,"name":"Sumin Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYBACNvbmgw8SKiTs+CGMGsJa+HiOJRs8OGOTLNkDZhwjrEVOIkdN8GFbGuOGGzlqkg9bmIlwGM8ZNoaEM4eZDW7ksFUkNrAx8Ld3JxDwS+8xoBcO80meeXvsRuIOGQaJM2c3ELDlXLoByBa+43lpNxKBVhpI5BLQIpFjJpHYdpix4UCOWUFiGzPRWtIYJ5zIMWMgTgsokBOggSyRcOYYD0G/yLc3H3z4AxqVH39U1Mjxt/fi14IBeEhTPgpGwSgYBaMAKwAAtFlR0i/0IJwAAAAASUVORK5CYII=","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":true,"prefix":"","firstName":"Sumin","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2026-03-18 16:24:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9161563/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9161563/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106410989,"identity":"7ffdd86e-af09-4900-8cab-5f2c51e4480f","added_by":"auto","created_at":"2026-04-08 09:52:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1440207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9161563/v1/aae18b62-2718-4156-aa2d-54810ecfc1d2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Safety and Efficacy of Da Vinci Robot-Assisted Atrial Septal Defect Repair in Patients with Different Body Mass Index Levels: A Single-Center Retrospective Analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAtrial septal defect (ASD) represents a prevalent form of congenital heart disease, constituting approximately 13% of all such conditions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In severe instances, prolonged hemodynamic abnormalities may lead to complications such as pulmonary hypertension and heart failure, necessitating surgical intervention to enhance patient prognosis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The progression of minimally invasive cardiac surgery techniques has facilitated the adoption of Da Vinci robot-assisted surgery as a significant modality for ASD repair [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This approach capitalizes on advantages such as three-dimensional visualization and the dexterity of robotic arm manipulation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Its efficacy in minimizing surgical trauma, expediting recovery, and reducing postoperative complication rates has been extensively corroborated [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBody mass index (BMI) serves as a fundamental indicator that elucidates the relationship between body weight and height, and it is intricately linked to metabolic status and anatomical structure [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Its influence on the efficacy and prognosis of cardiac surgery has been a longstanding subject of clinical investigation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Prior research has suggested that both obesity and underweight conditions may impact the perioperative safety and recovery processes of cardiac surgery by modifying thoracic anatomical structures, increasing surgical complexity, and compromising postoperative wound healing and immune function [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Nevertheless, comprehensive clinical research examining the effects of various BMI classifications on perioperative outcomes and short-term prognosis in Da Vinci robot-assisted ASD repair remains sparse, with inconsistent findings [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Some studies indicate that elevated BMI is associated with prolonged operation durations and heightened complication risks, whereas others do not identify a significant correlation between BMI and surgical outcomes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Furthermore, there is a pressing need for high-quality clinical evidence to inform individualized surgical strategies and perioperative management protocols for patients with atypical weight profiles, such as those who are underweight or obese.\u003c/p\u003e \u003cp\u003eBuilding upon this premise, the current study conducted a retrospective analysis of clinical data from 100 patients who underwent Da Vinci robot-assisted ASD repair. The objective was to investigate the impact of varying BMI classifications (underweight, normal weight, overweight, and obese) on patients\u0026rsquo; baseline characteristics, intraoperative indicators, postoperative recovery, and short-term outcomes. The study seeks to elucidate the relationship between BMI and the safety and efficacy of surgical procedures, thereby offering reliable insights for the development of individualized perioperative management strategies and the optimization of surgical decision-making.\u003c/p\u003e"},{"header":"2. Patients and Methods","content":"\u003cp\u003e This study was conducted in compliance with the principles outlined in the Declaration of Helsinki (2013 revision) and received approval from the Institutional Ethics Committee of Qingdao University Affiliated Hospital. Due to the retrospective design of the study, the requirement for individual informed consent was waived.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Population\u003c/h2\u003e \u003cp\u003eA retrospective study was conducted involving 100 patients who underwent Da Vinci robot-assisted ASD repair at our hospital between November 2014 and December 2025, with comprehensive clinical data available for all patients. The inclusion criteria were as follows: (1) ASD diagnosis confirmed via echocardiography, with indications for surgical repair; (2) no history of prior cardiac surgery; and (3) availability of complete clinical data, encompassing baseline characteristics, intraoperative records, and postoperative follow-up information. The exclusion criteria were (1) presence of other complex congenital heart diseases, severe valvular heart disease, or coronary artery disease; (2) preoperative severe complications, including severe infection, liver or kidney failure, or coagulation disorders; and (3) extreme BMI values, defined as less than 15 kg/m\u0026sup2; or greater than 50 kg/m\u0026sup2;.\u003c/p\u003e \u003cp\u003eThe patients were stratified into four categories based on the Chinese adult BMI classification criteria and clinical practice guidelines: underweight group (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;), normal weight group (18.5\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;24.9 kg/m\u0026sup2;), overweight group (25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;29.9 kg/m\u0026sup2;), and obese group (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30.0 kg/m\u0026sup2;).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Surgical Methods\u003c/h2\u003e \u003cp\u003eAll surgical procedures were conducted by a consistent team of experienced cardiac surgeons utilizing the Da Vinci Si or Xi robotic surgical systems. Following the successful induction of general anesthesia, a central venous catheter was inserted via percutaneous puncture of the right internal jugular vein, and a 16-Fr venous catheter was placed as the superior vena cava drainage tube. Cardiopulmonary bypass (CPB) was initiated through femoral arteriovenous cannulation. A primary operating port and surgical lens entry site were established via a 3\u0026ndash;5 cm incision at the midclavicular line of the 4th intercostal space. Additional 5 mm incisions were made at the anterior axillary line of the 2nd and 6th intercostal spaces, as well as the parasternal region of the 5th intercostal space, to accommodate the insertion of the left and right robotic arms and the atrial retractor. Following pericardiotomy, tapes were placed around the superior and inferior vena cava for standby use.\u003c/p\u003e \u003cp\u003eA purse-string suture was initially placed at the aortic root, followed by the insertion of a catheter for the delivery of cardioplegic solution. Subsequently, a cross-clamp was applied to the ascending aorta to obstruct blood flow, and cardioplegic solution was administered to induce cardiac arrest. Thereafter, the superior and inferior vena cava were clamped, and an incision was made in the right atrium. Closure of the ASD was performed either through direct suturing or by using a pericardial patch, contingent upon the size and condition of the defect's edges. Following the completion of suturing, a thorough evacuation of air was conducted, the cross-clamp on the ascending aorta was released, and the incision in the right atrium was sutured after the resumption of cardiac activity. In certain cases, ASD repair was conducted under beating heart conditions, depending on the patient's clinical status and anatomical features.\u003c/p\u003e \u003cp\u003eAfter removing CPB catheters, thorough hemostasis was performed, followed by layered chest closure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical Methods\u003c/h2\u003e \u003cp\u003eData analysis was conducted using SPSS version 26.0. For normally distributed continuous variables, data were represented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and intergroup comparisons were made using one-way analysis of variance (ANOVA). For non-normally distributed continuous variables, data were expressed as median (interquartile range) [M (Q1, Q3)], and intergroup comparisons were performed using the Kruskal-Wallis H test. Categorical variables were presented as frequencies and percentages (n [%]), with intergroup comparisons conducted using either the χ\u0026sup2; test or Fisher's exact test. To investigate the independent associations of BMI classification and age with postoperative surgical site infection and hospital readmission rates, multivariate logistic regression analysis was employed. Variables with a P-value less than 0.05 in the univariate analysis were included in the regression model. A P-value of less than 0.05 was considered indicative of statistical significance. Potential confounding factors such as diabetes mellitus and operation duration were initially evaluated but excluded due to non-significance in univariate analysis (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Baseline Characteristics of Patients\u003c/h2\u003e \u003cp\u003eA cohort of 100 patients diagnosed with ASD was recruited for the study, with BMI values ranging from 15.40 to 46.88 kg/m\u0026sup2;. Notable differences were identified in the age distribution across the four groups (P\u0026thinsp;=\u0026thinsp;0.034), with the obese group exhibiting the highest mean age of 47 years (range: 33\u0026ndash;59 years), whereas the underweight group demonstrated the lowest mean age of 19 years (range: 14\u0026ndash;31 years).\u003c/p\u003e \u003cp\u003eNo statistically significant differences were observed in terms of gender distribution, New York Heart Association (NYHA) functional classification, or the presence of comorbidities, which included first-degree atrioventricular block, right bundle-branch block, atrial fibrillation, coronary heart disease, hypertension, diabetes mellitus, and cerebrovascular disease, among the four groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Furthermore, echocardiographic assessments revealed no significant differences in ASD size, left ventricular ejection fraction (LVEF), or pulmonary artery pressure among the groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eBasement characteristics of the patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderweight group (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal weight group (n\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight group (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObese group (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (14\u0026ndash;31)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (27\u0026ndash;53)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (30\u0026ndash;58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47 (33\u0026ndash;59)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale gender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA class, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst - degree Atrioventricular Block or Right Bundle - Branch Block\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial Fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary Heart Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.328\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.864\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEchocardiographic data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASD size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (60\u0026ndash;62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (60\u0026ndash;64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (60\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61 (60\u0026ndash;65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary artery pressure(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.22\u0026thinsp;\u0026plusmn;\u0026thinsp;12.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.54\u0026thinsp;\u0026plusmn;\u0026thinsp;13.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.73\u0026thinsp;\u0026plusmn;\u0026thinsp;12.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.00\u0026thinsp;\u0026plusmn;\u0026thinsp;9.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eBMI\u003c/b\u003e: body mass index; \u003cb\u003eNYHA\u003c/b\u003e: New York Heart Association; \u003cb\u003eASD\u003c/b\u003e: atrial septal defect; \u003cb\u003eLVEF\u003c/b\u003e: left ventricular ejection fraction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Intraoperative Indicators\u003c/h2\u003e \u003cp\u003eNo statistically significant differences were identified among the four groups concerning operation duration, CPB time, the proportion of cardioplegic arrest surgeries, aortic cross-clamp time, the proportion of patch closures, or red blood cell (RBC) transfusion requirements (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Additionally, there were no instances of sternotomy conversion in any of the groups, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIntraoperative data of the patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOperation duration (minutes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderweight group (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal weight group (n\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight group (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObese group (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240 (200\u0026ndash;245)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200 (180\u0026ndash;240)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e228 (195\u0026ndash;255)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e240 (200\u0026ndash;280)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCPB time (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (69\u0026ndash;95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85 (66\u0026ndash;105)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97 (76\u0026ndash;122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90 (84\u0026ndash;110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardioplegic Arrest surgery, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic cross-clamp time (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0\u0026ndash;42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0\u0026ndash;52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatch closure, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (82.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC transfusion (units)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSternotomy conversion, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eCPB\u003c/b\u003e: cardiopulmonary bypass; \u003cb\u003eASD\u003c/b\u003e: atrial septal defect; \u003cb\u003eRBC\u003c/b\u003e: red blood cell.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Postoperative Indicators\u003c/h2\u003e \u003cp\u003eThe analysis revealed no statistically significant differences among the four groups concerning duration of mechanical ventilation, postoperative 24-hour drainage volume, length of intensive care unit (ICU) stay, length of postoperative stay, postoperative RBC transfusion, early mortality rates, 30 - day mortality, or LVEF and pulmonary artery pressure measurements both immediately after surgery and at one month postoperatively (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eIn terms of postoperative complications, the analysis revealed no statistically significant differences among the four groups concerning the incidence of residual ASD shunt, re-exploration for bleeding, new-onset stroke, new-onset atrial fibrillation, ventricular premature beats, pericardial effusion, second CPB, pulmonary infection, liver dysfunction, pneumothorax, or lower extremity vascular embolism (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Conversely, significant differences were observed in the incidence of postoperative surgical site infection and hospital readmission rates (P\u0026thinsp;=\u0026thinsp;0.009 and P\u0026thinsp;=\u0026thinsp;0.001, respectively). Specifically, the obese group exhibited the highest incidence of postoperative surgical site infection at 15.4%, followed by the overweight group at 3.8%, with no cases reported in the underweight and normal weight groups. Similarly, the hospital readmission rate was highest in the obese group at 23.1%, followed by the overweight group at 7.7%, with no hospital readmission occurring in the underweight and normal weight groups, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePostoperative data of the patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDuration of mechanical ventilation (hours)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderweight group (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal weight group (n\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight group (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObese group (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (10\u0026ndash;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (9\u0026ndash;15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(9\u0026ndash;19)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(10\u0026ndash;18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.663\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative 24-hour drainage volume (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (55\u0026ndash;130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (80\u0026ndash;230)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120 (70\u0026ndash;170)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140 (90\u0026ndash;220)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of ICU stay (hours)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67(49\u0026ndash;72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65(42\u0026ndash;88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71(60\u0026ndash;96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72 (43\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of postoperative stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.85\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC transfusion (units)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly mortality, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplications, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual ASD shunt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRe-exploration for bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew-onset stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew-onset atrial fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative surgical site infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVentricular premature beats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.617\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePericardial effusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond cardiopulmonary bypass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.934\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePneumothorax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower extremity vascular embolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital readmission, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30 - day mortality, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative LVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (60\u0026ndash;64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (60\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (60\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 (60\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative pulmonary artery pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.67\u0026thinsp;\u0026plusmn;\u0026thinsp;12.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;10.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.62\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-month postoperative LVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (60\u0026ndash;62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (61\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (60\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 (60\u0026ndash;62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-month postoperative pulmonary artery pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.33\u0026thinsp;\u0026plusmn;\u0026thinsp;15.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.13\u0026thinsp;\u0026plusmn;\u0026thinsp;9.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.19\u0026thinsp;\u0026plusmn;\u0026thinsp;8.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.85\u0026thinsp;\u0026plusmn;\u0026thinsp;7.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eICU\u003c/b\u003e: intensive care unit; \u003cb\u003eASD\u003c/b\u003e: atrial septal defect; \u003cb\u003eLVEF\u003c/b\u003e: left ventricular ejection fraction; \u003cb\u003eRBC\u003c/b\u003e: red blood cell.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Multivariate Logistic Regression Analysis of Hospital readmission and Postoperative Surgical Site Infection\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1. Hospital readmission Risk Analysis\u003c/h2\u003e \u003cp\u003eA binary logistic regression analysis was conducted, with hospital readmission serving as the dependent variable, while age and BMI classification (using the underweight group as the reference category) were included as independent variables. The analysis indicated that the model demonstrated a good overall fit, as evidenced by the Hosmer-Lemeshow test (χ\u0026sup2;=2.781, P\u0026thinsp;=\u0026thinsp;0.947), and accounted for 33.5% of the variance in hospital readmission risk (Nagelkerke R\u0026sup2;=0.335). Furthermore, the model was found to be statistically significant (χ\u0026sup2;=11.626, P\u0026thinsp;=\u0026thinsp;0.020). However, no significant associations were identified between age or any BMI classification (normal weight, overweight, or obese groups) and the risk of hospital readmission, with all P-values exceeding 0.05 (refer to Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, and Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel summary of hospital readmission\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-2 Log Likelihood\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCox \u0026amp; Snell R Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNagelkerke R Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificance (\u003cem\u003ep\u003c/em\u003e-value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28.077a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHosmer-Lemeshow test of hospital readmission\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\u003eChi-Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignificance (\u003cem\u003ep\u003c/em\u003e-value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariable of hospital readmission\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificance (\u003cem\u003ep\u003c/em\u003e-value)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eExp(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% CI for Exp(B)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower Bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper Bound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI Group\u003c/p\u003e \u003cp\u003e(Reference: Underweight group)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-20.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13383.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-20.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5568.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObese group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.899\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eBMI:\u0026nbsp;\u003c/strong\u003ebody mass index.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2. Postoperative Surgical Site Infection Risk Analysis\u003c/h2\u003e \u003cp\u003eA binary logistic regression analysis was performed with postoperative surgical site infection as the dependent variable, while age and BMI classification (using the underweight group as the reference category) served as independent variables. The findings demonstrated that the model exhibited a good fit, as evidenced by the Hosmer-Lemeshow test (χ\u0026sup2;=2.915, P\u0026thinsp;=\u0026thinsp;0.940), and accounted for 31.8% of the variance in the risk of postoperative surgical site infection, as indicated by the Nagelkerke R\u0026sup2; value of 0.318. However, the overall statistical significance of the model was only marginally significant (χ\u0026sup2;=7.811, P\u0026thinsp;=\u0026thinsp;0.099). Furthermore, no significant associations were identified between age or any BMI classification and the risk of postoperative surgical site infection, with all P-values exceeding 0.05 (refer to Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, and Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel summary of the postoperative surgical site infection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-2 Log Likelihood\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCox \u0026amp; Snell R Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNagelkerke R Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificance (\u003cem\u003ep\u003c/em\u003e-value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19.138a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHosmer-Lemeshow test of the postoperative surgical site infection\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\u003eChi-Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignificance (\u003cem\u003ep\u003c/em\u003e-value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariable of the postoperative surgical site infection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificance (\u003cem\u003ep\u003c/em\u003e-value)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eExp(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% CI for Exp(B)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower Bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper Bound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI Group\u003c/p\u003e \u003cp\u003e(Reference: Underweight group)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-18.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13177.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-19.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5508.820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObese group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eBMI:\u0026nbsp;\u003c/strong\u003ebody mass index.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study aimed to examine the influence of various BMI classifications (underweight, normal weight, overweight, and obese) on perioperative indicators and short-term prognosis in patients undergoing Da Vinci robot-assisted ASD repair. A retrospective analysis of clinical data from 100 enrolled patients indicated no significant differences in baseline characteristics, key intraoperative indicators (such as operation duration and CPB time), or most postoperative recovery indicators (including duration of mechanical ventilation and length of ICU stay) across different BMI groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Nevertheless, the obese group exhibited significantly higher rates of postoperative surgical site infection (15.4%) and hospital readmission (23.1%) compared to other groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multivariate logistic regression analysis did not identify BMI classification or age as independent predictors of these adverse outcomes (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). These findings suggest that obesity may be a potential factor influencing specific postoperative complications in ASD patients and that clinical outcomes may be modulated by the interaction of multiple factors. This provides valuable clinical evidence for optimizing the perioperative management of such patients.\u003c/p\u003e \u003cp\u003eIn this study, baseline echocardiographic parameters, including ASD size, LVEF, and pulmonary artery pressure, as well as the distribution of comorbidities, were generally comparable across the four groups, with the exception of age. The obese group exhibited a higher mean age, a difference potentially attributable to the cumulative effects of obesity-related metabolic disorders [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Maria-Dolores et al.'s decade-long cohort study demonstrated a significant increase in BMI with advancing age among adults aged 18\u0026ndash;60 years (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The underlying mechanisms may involve age-associated reductions in basal metabolic rate, alterations in lifestyle, and hormonal changes, all contributing to weight gain and increased BMI [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, older individuals are more susceptible to comorbidities such as metabolic syndrome, diabetes mellitus, and cardiovascular diseases, underscoring the importance of considering age as a critical factor in discussions of obesity and its related health implications [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn terms of intraoperative indicators, no significant differences were observed in operation duration, CPB time, or aortic cross-clamp time across the four groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), thereby affirming the clinical applicability of Da Vinci robot-assisted surgery in patients with varying BMI levels. This finding contradicts the conclusion drawn by Sergio et al., which posits that \"high BMI prolongs operation duration\" [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The observed discrepancy may be attributed to the specific anatomical characteristics involved in ASD repair: the surgical field is primarily concentrated within the atrium, and the influence of thoracic fat accumulation on atrial exposure in obese patients is relatively minimal [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Furthermore, the three-dimensional visualization and the dexterous manipulation capabilities of the Da Vinci robotic system effectively mitigate the spatial constraints imposed by obesity, facilitating enhanced anatomical exposure, reducing the complexity of the procedure, and thereby preserving surgical efficiency [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Individualized technical adjustments and perioperative management strategies are essential for patients with varying BMI levels. For obese patients, it is recommended to conduct preoperative chest CT scans to evaluate chest wall fat thickness and to tailor the positioning of operating ports accordingly [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. During surgery, the use of adaptive instruments, such as lengthened trocars, is advised, along with the prioritization of beating heart surgery to minimize the risk of aortic injury [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Postoperatively, enhanced blood glucose control and meticulous incision care are crucial to reduce the risk of infection [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Conversely, for young and underweight patients, who possess slender blood vessels with high wall elasticity and are susceptible to vasospasm, a detailed preoperative vascular assessment is imperative [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Intraoperatively, real-time ultrasound should be employed to localize vascular pathways, and local application of nitroglycerin prior to puncture is recommended to prevent spasm [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The use of small-caliber, thin-walled puncture needles and adaptive cannulas, along with gentle handling to avoid repeated puncture or aggressive dilation, is advised [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. If vasospasm occurs, the operation should be paused and spasmolytic drugs administered; open intubation under direct vision may be necessary [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Additionally, CPB should be conducted using a low-flow and low-pressure perfusion mode [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn terms of short-term postoperative recovery, no significant differences were observed among the four groups in duration of mechanical ventilation, length of ICU stay, length of postoperative stay, or cardiac function recovery, including LVEF and pulmonary artery pressure immediately after surgery and one month postoperatively (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Notably, there were no instances of sternotomy conversion, early mortality, or 30-day mortality within the entire cohort. These findings further substantiate the efficacy of Da Vinci robot-assisted surgery in mitigating the impact of BMI-related physiological variations on postoperative recovery. The study by Li et al. corroborates these results, demonstrating that, compared to traditional thoracotomy, Da Vinci robot-assisted surgery is associated with smaller incisions, reduced trauma to chest wall muscles and bones, and less postoperative pain, facilitating earlier mobilization and consequently reducing mechanical ventilation time and hospital stay [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Remarkably, both underweight and obese patients exhibited comparable short-term recovery outcomes to those of normal-weight patients, thereby challenging the conventional notion that \"obese patients experience delayed postoperative recovery\" following traditional thoracotomy [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile univariate analysis revealed statistically significant associations between BMI classification and both postoperative surgical site infection and hospital readmission rate (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), multivariate logistic regression analysis did not identify BMI classification or age as independent predictors of these adverse outcomes (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Several factors may account for this discrepancy: firstly, the relatively small sample size of the study, particularly within the underweight (n\u0026thinsp;=\u0026thinsp;9) and obese (n\u0026thinsp;=\u0026thinsp;13) groups, may have resulted in insufficient statistical power to detect potential independent associations between BMI and the outcomes. Secondly, the regression model was limited to age and BMI classification as independent variables, whereas postoperative infection and hospital readmission are likely influenced by numerous confounding factors, such as perioperative antibiotic use, quality of incision care, postoperative activity level, and management of comorbid metabolic diseases [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The exclusion of these variables may obscure the independent effect of BMI. Thirdly, the Da Vinci robot-assisted surgery is characterized by an extensive learning curve, with increased surgical complexity observed in obese patients [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These procedures are typically conducted once surgeons have surpassed the learning curve, and the implementation of standardized operating procedures may mitigate outcome disparities among patients with varying BMI levels. Consequently, it becomes challenging for BMI alone to exhibit an independent risk contribution. Fourth, the presence of exceedingly large standard errors in certain BMI categories (specifically, the normal weight and overweight groups) within the regression model indicates potential issues of multicollinearity or uneven sample distribution, which could compromise the reliability of parameter estimation.\u003c/p\u003e \u003cp\u003eFrom a clinical standpoint, the regression results do not dismiss the potential risks associated with obesity but rather highlight the complexity of clinical outcomes. The influence of obesity on postoperative infection and hospital readmission may not be a direct, independent effect; instead, it may occur through synergistic interactions with factors such as blood glucose control, immune function, and the quality of incision care [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Consequently, it is imperative to optimize perioperative management strategies based on BMI characteristics. For obese patients, this includes preoperative regulation of metabolic indicators such as blood glucose and lipids to improve insulin resistance; precise intraoperative puncture positioning to avoid areas with significant fat accumulation; optimization of incision location; enhanced hemostasis and sterile techniques to reduce infection risks; and postoperative measures such as improved incision care (e.g., maintaining a dry and clean incision, regular dressing changes), early rehabilitation exercises (to promote local blood circulation and accelerate wound healing), and the judicious use of antibiotics, while developing a comprehensive long-term follow-up mechanism designed to promptly identify signs of infection and implement targeted interventions aimed at reducing the risk of hospital readmission [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study is subject to several limitations. Firstly, the relatively small sample size, particularly within the underweight and obese cohorts, may compromise the stability and external validity of the statistical findings. Secondly, the single-center retrospective design inherently introduces selection bias, and the absence of long-term prognostic data hinders a comprehensive assessment of the impact of BMI on patients' long-term outcomes. Thirdly, the regression model incorporated only age and BMI classification as independent variables, neglecting potential confounding factors such as blood glucose levels, lipid profiles, metabolic indicators, immune function, and quality of care, which could introduce bias into the results. Fourthly, instability in parameter estimation was observed in certain BMI groups within the regression model, potentially attributable to sample distribution characteristics or model specifications. Lastly, the absence of a traditional thoracotomy control group precludes direct comparison of the clinical advantages associated with different surgical approaches across varying BMI levels.\u003c/p\u003e \u003cp\u003eFuture research should aim to increase the sample size and employ a multicenter prospective design. It is essential to include a control cohort comprising both Da Vinci robot-assisted surgery and traditional thoracotomy to rigorously assess the long-term clinical benefits of minimally invasive techniques in patients with ASD across various BMI categories. Additionally, refining observational indicators and meticulously documenting surgical procedures and postoperative rehabilitation interventions will aid in developing a more comprehensive prognostic prediction model. Extending the follow-up period to at least one year is recommended to thoroughly evaluate the impact of BMI on long-term cardiac function, metabolism-related complications, and quality of life. This approach will provide robust clinical evidence to support the personalized application of Da Vinci robot-assisted surgery.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, Da Vinci robot-assisted ASD repair exhibits favorable safety and efficacy across patients with varying BMI levels. The minimally invasive nature of this technique effectively addresses surgical challenges associated with weight-related factors, ensuring consistent short-term clinical recovery outcomes for all patients. Although multivariate analysis did not reveal independent associations between BMI and the risk of postoperative surgical site infections or hospital readmission (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), obese patients remain at a significantly higher risk for these adverse outcomes (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Clinical practice should incorporate individualized and enhanced perioperative management strategies for obese populations. Importantly, weight status should not serve as a contraindication for ASD patients considering Da Vinci robot-assisted repair. The focus should be on optimizing surgical processes and postoperative care plans tailored to BMI characteristics to maximize the clinical benefits of this minimally invasive approach.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eASD\u003c/strong\u003e Atrial Septal Defect\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e Body Mass Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCPB\u003c/strong\u003e Cardiopulmonary Bypass\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICU\u003c/strong\u003e Intensive Care Unit\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLVEF\u003c/strong\u003e Left Ventricular Ejection Fraction\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNYHA\u003c/strong\u003e New York Heart Association\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBC\u003c/strong\u003e Red Blood Cell\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eANOVA\u003c/strong\u003e Analysis of Variance\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e: body mass index;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNYHA\u003c/strong\u003e: New York Heart Association;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eASD\u003c/strong\u003e: atrial septal defect;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLVEF\u003c/strong\u003e: left ventricular ejection fraction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCPB\u003c/strong\u003e: cardiopulmonary bypass;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eASD\u003c/strong\u003e: atrial septal defect;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBC\u003c/strong\u003e: red blood cell.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICU\u003c/strong\u003e: intensive care unit;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eASD\u003c/strong\u003e: atrial septal defect;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLVEF\u003c/strong\u003e: left ventricular ejection fraction;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBC\u003c/strong\u003e: red blood cell.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the institutional review board of The Affiliated Hospital of Qingdao University (Approval number\u0026nbsp;QYFY WZLL 42136). Since the study was a retrospective study, informed consent was waived by the Ethics Committee. This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.\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\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSumin Yang, Wei Wang, and Qingjiang Wang participated in the surgery. Haoyan Li, Xun Chi, and Ziang Sun participated in data collection. Qingjiang Wang and Rui Dai contributed to revising and drafting the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Lianbao Chi for his valuable assistance in the translation and polishing of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNashat H, Montanaro C, Li W, Kempny A, Wort SJ, Dimopoulos K, et al. Atrial septal defects and pulmonary arterial hypertension. 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JTCVS Tech. 2021;10:153\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.xjtc.2021.03.037\u003c/span\u003e\u003cspan address=\"10.1016/j.xjtc.2021.03.037\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Body mass index, Da Vinci Surgical System, Atrial septal defect, Perioperative management, Short-term prognosis","lastPublishedDoi":"10.21203/rs.3.rs-9161563/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9161563/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aims to investigate the impacts of various body mass index (BMI) classifications on perioperative parameters and short-term outcomes in patients undergoing Da Vinci robot-assisted atrial septal defect (ASD) repair providing evidence for personalized perioperative management.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective analysis was conducted on 100 patients who underwent Da Vinci robot-assisted ASD repair at Qingdao University Affiliated Hospital between November 2014 and December 2025. Based on the Chinese adult BMI classification criteria, the patients were categorized into four groups: underweight group (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;, n\u0026thinsp;=\u0026thinsp;9), normal weight group (18.5\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;24.9 kg/m\u0026sup2;, n\u0026thinsp;=\u0026thinsp;52), overweight group (25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;29.9 kg/m\u0026sup2;, n\u0026thinsp;=\u0026thinsp;26), and obese group (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30.0 kg/m\u0026sup2;, n\u0026thinsp;=\u0026thinsp;13). This study compared baseline characteristics, intraoperative indicators, postoperative recovery, and short-term prognosis across these groups. Furthermore, multivariate logistic regression analyzed the independent associations of BMI classification and age with postoperative surgical site infection and hospital readmission.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eNo significant differences were observed among the four groups concerning baseline echocardiographic parameters, key intraoperative metrics (e.g., operation duration, cardiopulmonary bypass time), or most postoperative recovery measures (e.g., mechanical ventilation duration, length of intensive care unit stay), with all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05. No sternotomy conversion or early mortality occurred. Univariate analysis showed the obese group had significantly higher rates of surgical site infection (15.4%) and readmission (23.1%) (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but multivariate regression did not identify BMI classification or age as independent predictors (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDa Vinci robot-assisted ASD repair is safe and effective across different BMI levels, with its minimally invasive nature overcoming weight-related surgical challenges. Although obese patients face higher risks of postoperative infection and readmission, BMI is not an independent influencing factor. Individualized enhanced perioperative management for obese populations is recommended, and weight status should not be a contraindication for this procedure.\u003c/p\u003e","manuscriptTitle":"Safety and Efficacy of Da Vinci Robot-Assisted Atrial Septal Defect Repair in Patients with Different Body Mass Index Levels: A Single-Center Retrospective Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-08 09:28:16","doi":"10.21203/rs.3.rs-9161563/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-06T09:14:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T00:46:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16822435698400274596300270700399399624","date":"2026-04-02T14:19:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283651936140331022936972103594004331517","date":"2026-04-02T13:34:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T13:27:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-21T05:35:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-21T05:35:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cardiothoracic Surgery","date":"2026-03-18T16:07:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f818d75d-0bb3-4a43-837e-0de19f635b8d","owner":[],"postedDate":"April 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T16:38:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-08 09:28:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9161563","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9161563","identity":"rs-9161563","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}