Structural Equation Model Analysis of Hospital Stay in Patients Undergoing Single-Port Laparoscopic Surgery for Benign Gynecological Tumors

Structural Equation Model Analysis of Hospital Stay in Patients Undergoing Single-Port Laparoscopic Surgery for Benign Gynecological Tumors | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 14 November 2025 V1 Latest version Share on Structural Equation Model Analysis of Hospital Stay in Patients Undergoing Single-Port Laparoscopic Surgery for Benign Gynecological Tumors Authors : Li Li , Chenxi Zhao 0009-0004-1168-6519 , Yukun Lang , Xiaojing Zhou , Penghuan Jia , Xiangcui Guo , Xiaoming Guan , and Qianqing Wang [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176310559.98439497/v1 148 views 108 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background: Single-port laparoscopic surgery has been widely adopted for the treatment of benign gynecological tumors due to its minimally invasive advantages. However, significant individual variations exist in total length of hospital stay (TLOS) among patients. To date, few studies have evaluated the factors influencing TLOS, and existing research has only incorporated a limited number of variables as influencing factors. Objective： To identify multidimensional drivers of total length of stay (TLOS) after single-port laparoscopic surgery for benign gynecologic tumors using a comprehensive structural equation model (SEM). To determine preoperative, intraoperative, and postoperative predictors of extended hospital stay after single-port laparoscopic surgery for benign gynecological tumors and to identify potentially modifiable clinical factors that can shorten hospitalization. Methods： In this single-center retrospective cohort (n = 396; 2021-2024) we extracted pre-, intra- and postoperative variables from the electronic medical record. Clinically grounded indicators were grouped into three latent constructs and entered into an SEM to quantify direct and indirect effects on TLOS. Results： Mean TLOS was 7.3 ± 2.1 days. The final SEM (goodness-of-fit: CFI = 0.93, RMSEA = 0.06) explained 20 % of the variance in TLOS. Intra-operative factors (operative time, blood loss, fluid load, uterine size) exerted the strongest direct impact (standardized β = 0.32, p < 0.001), followed by patient characteristics (age, BMI, parity, pre-op hemoglobin; β = 0.18, p = 0.004). Postoperative recovery markers (early ambulation, diet resumption, bowel function) influenced TLOS indirectly through intra-operative pathways (β = 0.14, p = 0.02). Structural Equation Model Analysis of Hospital Stay in Patients Undergoing Single-Port Laparoscopic Surgery for Benign Gynecological Tumors Li Li 123 Chenxi Zhao 12 Yukun Lang 12 Xiaojing Zhou 12 Penghuan Jia 123 Xiangcui Guo 123 Xiaoming Guan 4 Qianqing Wang 123* 1 Henan Medical University, Xinxiang,China 2 The Fourth Clinical College of Henan Medical College, Xinxiang,China 3 Xinxiang Research Center for Natural Orifice Endoscopic Technology 4 Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas * The author is considered corresponding author. Address for Correspondence to: Qianqing Wang Department of Obstetrics and Gynecology, Xinxiang Central Hospital,The Fourth Clinical College of Xinxiang Medical College, Xinxiang,453000, Henan, China E-mail address: [email protected] Abstract Background: Single-port laparoscopic surgery has been widely adopted for the treatment of benign gynecological tumors due to its minimally invasive advantages. However, significant individual variations exist in total length of hospital stay (TLOS) among patients. To date, few studies have evaluated the factors influencing TLOS, and existing research has only incorporated a limited number of variables as influencing factors. Objective： To identify multidimensional drivers of total length of stay (TLOS) after single-port laparoscopic surgery for benign gynecologic tumors using a comprehensive structural equation model (SEM). To determine preoperative, intraoperative, and postoperative predictors of extended hospital stay after single-port laparoscopic surgery for benign gynecological tumors and to identify potentially modifiable clinical factors that can shorten hospitalization. Methods： In this single-center retrospective cohort (n = 396; 2021-2024) we extracted pre-, intra- and postoperative variables from the electronic medical record. Clinically grounded indicators were grouped into three latent constructs and entered into an SEM to quantify direct and indirect effects on TLOS. Results： Mean TLOS was 7.3 ± 2.1 days. The final SEM (goodness-of-fit: CFI = 0.93, RMSEA = 0.06) explained 20 % of the variance in TLOS. Intra-operative factors (operative time, blood loss, fluid load, uterine size) exerted the strongest direct impact (standardized β = 0.32, p < 0.001), followed by patient characteristics (age, BMI, parity, pre-op hemoglobin; β = 0.18, p = 0.004). Postoperative recovery markers (early ambulation, diet resumption, bowel function) influenced TLOS indirectly through intra-operative pathways (β = 0.14, p = 0.02). Advantages： • First study to apply a full latent-variable SEM to single-port gynecologic surgery, integrating peri-operative data rather than isolated predictors. • Reveals the dominant yet modifiable role of intra-operative efficiency, providing concrete targets (≤90 min operative time, ≤1 L fluid load) for ERAS protocols. • Offers an evidence-based template for prospective multicenter benchmarking. Conclusion： Extended hospital stay is primarily predicted by larger uterine size, longer operative time, higher intraoperative fluid use, and baseline patient factors such as age and obstetric history. These findings suggest that standardized surgical approaches and patient-tailored preoperative planning may reduce length of hospitalization.Keywords: Structural Equation Modeling; Single-Port Surgery; Length of Stay (LOS); Functional Assessment; Benign Gynecological Tumors Introduction Benign gynecological tumors (e.g., uterine fibroids, ovarian cysts) are prevalent conditions among women. Single-port laparoscopic surgery has rapidly supplanted the multi-port approach as the preferred method for treating benign gynecological tumors due to its advantages of reduced postoperative pain, accelerated recovery, and superior cosmetic outcomes [1]. However, significant variations in the total length of stay (TLOS) following such procedures not only constrain hospital efficiency but also adversely impact patient satisfaction [2]. TLOS is a complex metric influenced by multifactorial interactions. Its duration is determined not only by surgery-related elements but also by Patient Characteristics, postoperative recovery status, and non-medical factors [3]. Prolonged hospitalization leads to wastage of medical resources (e.g., bed occupancy, nursing costs, medication expenses) [4], imposes substantial financial burdens on patients [5], and strains national healthcare funds, thereby threatening the sustainability of insurance systems [6]. Conversely, reducing TLOS enhances bed turnover rates, enabling hospitals to accommodate more patients efficiently [7]. Previous studies have linked isolated factors (e.g., operative duration, patient age) to extended hospitalization [8] but typically analyzed them in segregated regression models [9–11]. Such approaches fail to capture intricate inter-variable interactions, leaving recovery mechanisms poorly elucidated and hindering the identification of actionable intervention targets within enhanced recovery after surgery (ERAS) protocols. Structural equation modeling (SEM) offers distinct advantages in deciphering multidimensional variable relationships [12]. Its core value lies in transcending the limitations of conventional regression (which handles only a single dependent variable) by simultaneously incorporating multiple independent and dependent variables, thereby precisely mapping complex interactions [13, 14]. For latent constructs central to this study—such as Patient Characteristics, Intraoperative Factors, and Postoperative Factors—which cannot be directly quantified, SEM constructs and evaluates them through observable indicators (e.g., age, operative time, time to first flatus). This approach more authentically reflects these clinically nuanced concepts [15, 16]. Given that TLOS is co-determined by multidimensional latent factors (e.g., baseline patient status, surgical trauma severity, postoperative recovery capacity) with intricate interactions, traditional regression proves inadequate for holistic mechanistic exploration. SEM’s strength resides in its ability to integrate and quantify these unobservable latent constructs. By establishing observable indicators to operationalize them, SEM concurrently evaluates their direct and indirect effect pathways on TLOS [12–14], thereby revealing multidimensional influencing mechanisms aligned with clinical realities. This study pioneers the application of a full latent-variable SEM framework to single-port gynecological surgery, integrating preoperative, intraoperative, and postoperative electronic medical record data. The model simultaneously quantifies the direct/indirect effects of each factor on TLOS and identifies the most modifiable key drivers [18]. Results highlight the dominance of intraoperative efficiency. Accordingly, we propose concrete, actionable benchmarks: operative time ≤90 minutes and intraoperative fluid administration <1 liter. These findings provide an evidence-informed blueprint for implementing prospective, multicenter ERAS initiatives and performance benchmarking. In light of the current absence of multidimensional mechanistic studies on TLOS for single-port laparoscopy, this research employs SEM to dissect its determinants for the first time. It aims to establish foundational data and hypotheses for this field, guiding future controlled studies. Data Source Data for this study were extracted from the Electronic Medical Record (EMR) system of Xinxiang Central Hospital. All patient data underwent de-identification procedures to ensure privacy protection. The study protocol received approval from the hospital’s Ethics Committee (Approval No.: 2025-154-01（K）). Study Cohort We retrospectively reviewed the records of patients who underwent gynecological Laparo-Endoscopic Single-Site Surgery (LESS) at Xinxiang Central Hospital between January 2021 and December 2024. Patients meeting the inclusion criteria were identified through the hospital’s EMR system. Inclusion criteria comprised: (1) diagnosis of benign gynecological tumors (e.g., uterine fibroids, ovarian cysts); (2) treatment with LESS; and (3) postoperative pathological confirmation of benign disease. Medical records with complete Total Length of Stay (TLOS) data, sourced from hospital billing records and postoperative rehabilitation assessment reports, were included. Exclusion criteria were: (1) concurrent malignant disease; (2) severe underlying medical comorbidities; (3) conversion to laparotomy; and (4) incomplete clinical data. Based on these criteria, a final cohort of 396 patient records was established for analysis. Covariate Selection A comprehensive set of covariates was selected using the hospital EMR query and analysis tools. Selection was informed by prior studies examining TLOS following gynecological LESS, predictors of other postoperative outcomes in LESS, and established predictors of TLOS after gynecological surgery. Sociodemographic data were extracted directly from the EMR. The surgery date served as the reference point for defining preoperative and postoperative timeframes. Diagnostic and surgical details were obtained from physician documentation. The most recent complete blood count (CBC) laboratory test prior to surgery (within 1 week maximum) was selected to indicate preoperative hemoglobin levels. A CBC test measured on postoperative day 1 was used to indicate postoperative hemoglobin levels. The total volume of fluid resuscitation was calculated as the sum of intraoperative fluid administration and postoperative fluid supplementation administered during the hospital stay. Postoperative functional dependency was assessed using the following metrics: time to first ambulation, time to first flatus, time to first defecation, and time to first oral intake [18]. Data on TLOS, complications, and hospitalization details were retrieved from the hospital record system. The All Patient Refined Diagnosis-Related Group (APR-DRG) severity of illness level was calculated for all patients based on primary and secondary discharge diagnoses, age, and pre-existing medical conditions. Through the methods described above, we ensured the scientific rationale and clinical relevance of the covariate selection, enabling a comprehensive representation of the multidimensional factors influencing TLOS in gynecological LESS Statistical Analysis Descriptive statistics and correlation analyses were performed using SPSS software, version 27.0 (SPSS Inc., Chicago, IL, USA). Structural Equation Modeling (SEM) was conducted using SPSS Amos, version 29.0 (SPSS Inc.). Within the SEM framework, Total Length of Stay (TLOS) was modeled as the dependent variable, regressed on three latent factors. Each latent factor was constructed from multiple observed indicator variables. To ensure conceptual validity, the assignment of observed indicators to their respective latent factors (e.g., which specific indicators constitute ”Patient Characteristics”) was confirmed via an expert Delphi method. As shown in the table 1 : Table 1 Demographic Characteristics and Perioperative Indicators of the Study Subjects Age(y) 35.28 10.48 BMI(kg/m2) 23.71 3.83 Menopause status Not menopausal 388 98% Menopausal 8 2% Vaginal delivery times 0.93 0.97 Cesarean section times 0.32 0.67 Abortion times 0.80 1.03 Pelvic surgery history No 280 70.7% Yes 116 29.3% Chronic disease No 353 89.1% Yes 43 10.9% Preoperative hemoglobin Normal 352 88.9% Mild anemia 30 7.6% Severe anemia with transfusion before surgery 14 3.5% Tumor size(cm) 6.38 2.45 Uterine size Normal 290 73.2% 1 month of pregnancy 42 10.6% 2 months of pregnancy 31 7.8% ≥3 months of pregnancy 33 8.3% Surgery time(h) 1.55 0.63 Intraoperative fluid replacement(L) 1.08 0.35 Postoperative fluid replacement(L) 7.31 2.27 Urinary catheter removal time ≤24h 294 74.2% ≤48h 92 23.2% ≤72h 10 2.5% Flatus time ≤24h 227 57.3% ≤48h 155 39.1% ≤72h 14 3.5% Defecation time ≤24h 13 3.3% ≤48h 234 59.1% ≤72h 149 37.6% Feeding time ≤24h 241 60.9% ≤48h 129 32.6% ≤72h 26 6.6% Out-of-bed time ≤24h 284 71.7% ≤72h 112 28.3% Postoperative electrolytes Normal 312 78.8% Electrolyte disorder 84 21.2% Preoperative and postoperative hemoglobin difference (g/L) 12.31 9.87 TLOS(d) 7.33 1.79 LOS(d) 4.21 1.05 Note : BMI, body mass index; TLOS, total length of stay; LOS, length of postoperative stay; SD, standard deviation Patient Characteristics: Age, Body Mass Index (BMI), menstrual status, history of prior pelvic surgery, preoperative hemoglobin level, number of cesarean deliveries, number of vaginal deliveries, number of abortions, history of chronic disease. Operative Factors: Operative time, tumor size, uterine size, volume of intraoperative fluid administration. Postoperative Factors: Volume of postoperative fluid administration, time to urinary catheter removal, time to first flatus, time to first defecation, time to first oral intake, time to first ambulation, postoperative electrolyte levels, the difference between preoperative and postoperative hemoglobin levels. Prior to final SEM testing, model parameters (factor loadings/regression weights) and modification indices were estimated. This process facilitated the selection of the best-fitting indicators for each factor based on their contribution to the overall model fit. Indicators deemed unsuitable were subsequently removed. Following this refinement process, the final set of observed variables retained in the model were: Patient Characteristics: Age, number of vaginal deliveries, number of abortions. Operative Factors: Preoperative hemoglobin level, uterine size, operative time, volume of intraoperative fluid administration, and history of prior pelvic surgery. Postoperative Factors: Time to first flatus, time to first oral intake, time to first ambulation. Results This study enrolled 396 patients undergoing laparo-endoscopic single-site surgery (LESS) for benign gynecological tumors. Correlation analysis initially identified variables associated with total length of stay (TLOS), followed by structural equation modeling (SEM) to delineate multidimensional pathways influencing TLOS. Correlation Analysis Correlation analysis revealed statistically significant associations with TLOS. :The results are presented in the table 2. Table 2 Correlation Matrix of Variables Included in the Final Structural Equation Model (SEM) Surgery history 1 — — — — — — — — — — — Preoperative hemoglobin 0.16 1 — — — — — — — — — — Age 0.36 0.25 1 — — — — — — — — — TLOS 0.16 0.19 0.38 1 — — — — — — — — Out-bed time 0.03 0.15 0.24 0.18 1 — — — — — — — Feeding time 0.07 0.15 0.23 0.12 0.68 1 — — — — — — Flatus time 0.06 0.11 0.20 0.11 0.64 0.81 1 — — — — — Intraoperative fluid 0.12 0.15 0.20 0.16 0.15 0.14 0.08 1 — — — — Surgery time 0.18 0.17 0.25 0.26 0.23 0.21 0.16 0.49 1 — — — Uterine size 0.20 0.34 0.53 0.31 0.31 0.32 0.25 0.30 0.41 1 — — Abortion times 0.15 0.05 0.43 0.25 0.17 0.11 0.13 0.11 0.09 0.29 1 — Vaginal delivery -0.14 0.13 0.52 0.26 0.18 0.15 0.16 -0.01 0.00 0.24 0.39 1 Note : LOS, length of stay; SEM, structural equation model. All correlation coefficients are statistically significant at P < 0.05 unless otherwise specified. Among patient characteristics, age demonstrated moderate positive correlation (r=0.38, P<0.05), uterine size showed positive correlation (r=0.31, P<0.05), while both vaginal delivery count (r=0.26, P<0.05) and abortion history (r=0.25, P<0.05) were positively correlated. For intraoperative factors, operative time correlated positively (r=0.26, P<0.05) and intraoperative fluid volume exhibited weak positive correlation (r=0.16, P<0.05). Postoperatively, time to ambulation (r=0.18, P<0.05), first oral intake (r=0.12, P<0.05), and first flatus (r=0.11, P<0.05) all displayed weak positive correlations with TLOS. Notably, strong internal correlations existed among recovery indicators: first oral intake and first flatus demonstrated marked synergy (r=0.81, P<0.001), as did ambulation and oral intake times (r=0.68, P<0.001), indicating coordinated functional recovery processes. SEM Results Based on the correlation analysis results, a structural equation model (SEM) incorporating three latent variables—Patient Characteristics, Intraoperative Factors, and Postoperative Factors—was constructed. The results are shown in the figure 1: Figure1: Structural Equation Model Path Diagram of Factors Influencing Total Length of Stay (TLOS) in Patients Undergoing Single-Port Laparoscopic Surgery for Benign Gynecological Tumors Note : A structural equation model (SEM) of total length of stay (TLOS) was constructed using Amos software. The values along the paths represent standardized loadings, while those adjacent to the variables denote squared multiple correlations (SMC), indicating the proportion of variance explained by the model. TLOS was specified as the dependent variable. Variables represented by ellipses are latent constructs, including Patient Characteristics, Intraoperative Factors, and Postoperative Factors. The model fit indices demonstrated acceptable performance: χ²=182.758, χ²/df=3.730 (approaching ideal 1-4 range), GFI=0.937, AGFI=0.900 (both Collectively, these indices confirm the model’s capacity to systematically elucidate direct/indirect effect pathways between latent constructs, observed variables, and TLOS. The effects of various factors on TLOS are presented in the table 3 : Table 3 Loadings of Observed Variables on Latent Variables and Their Direct Effects on Total Length of Stay (TLOS) in the Structural Equation Model Patient Characteristics Age 1 Vaginal delivery 0.055 0.006 9.307 0.001 Abortion times 0.05 0.007 7.376 0.001 Intraoperative Factors Uterine size 1 Surgery time 0.391 0.049 8.058 0.001 In-fluid 0.161 0.027 6.029 0.001 Pre-hemoglobin 0.236 0.034 6.908 0.001 Pelvic surgery 0.19 0.039 4.894 0.001 Postoperative Factors Flatus time 1 Feeding time 1.175 0.054 21.847 0.001 Out-of-bed time 0.678 0.04 17.1 0.001 Tlos Patient Characteristics 0.047 0.017 2.712 0.007 Intraoperative Factors 0.545 0.227 2.396 0.017 Note : S.E. = Standard Error; C.R. = Critical Ratio; P = Probability value. Factor loadings analysis revealed: For Patient Characteristics (age-referenced), both vaginal deliveries (Estimate=0.055, CR=9.307, P<0.001) and abortions (Estimate=0.050, CR=7.376, P<0.001) carried significant positive loadings, establishing obstetric history as a key component. Regarding Intraoperative Factors (uterine size-referenced), operative time (Estimate=0.391, CR=8.058, P<0.001; highest standardized loading), preoperative hemoglobin (Estimate=0.236, CR=6.908, P<0.001), prior pelvic surgery (Estimate=0.190, CR=4.894, P<0.001), and intraoperative fluids (Estimate=0.161, CR=6.029, P<0.001) all contributed significantly. For Postoperative Factors (first flatus-referenced), first oral intake (Estimate=1.175, CR=21.847, P<0.001) and ambulation time (Estimate=0.678, CR=17.100, P<0.001) loaded strongly, confirming gastrointestinal recovery and early mobilization as core dimensions. Path analysis demonstrated: Patient Characteristics exerted significant direct positive effects on TLOS (Estimate=0.047, CR=2.712, P=0.007), as did Intraoperative Factors (Estimate=0.545, CR=2.396, P=0.017) with greater effect magnitude. Postoperative Factors influenced TLOS exclusively through indirect pathways via associations with preoperative/intraoperative constructs, with statistically validated mediation effects. These two direct-effect dimensions constituted primary determinants of TLOS, supported by the model’s acceptable explanatory power in reflecting multidimensional TLOS mechanisms. Discussion This study employed Structural Equation Modeling (SEM) to systematically investigate the factors influencing Total Length of Stay (TLOS) following Laparo-Endoscopic Single-Site Surgery (LESS) for benign gynecological tumors. The core findings reveal that preoperative factors (Patient Characteristics) and intraoperative factors exert a direct influence on TLOS, while postoperative factors act indirectly through their associations with the former two. Crucially, the direct impact of intraoperative factors on TLOS was stronger than that of preoperative factors. The pivotal contribution of this work lies in being the first to delineate the specific pathways and magnitudes through which these factors affect hospitalization duration in the context of LESS. This provides a quantifiable foundation for clinical interventions targeting key modifiable elements (e.g., optimizing preoperative assessment and standardizing intraoperative procedures) to reduce TLOS. Importantly, it offers theoretical underpinnings for developing Enhanced Recovery After Surgery (ERAS) protocols specifically for gynecological minimally invasive surgery. The observed results align with established clinical mechanisms and prior research. The significant impact of Patient Characteristics (e.g., age, number of vaginal deliveries, number of abortions) on TLOS fundamentally relates to the influence of baseline patient status on surgical tolerance. Advanced age may be associated with decreased pelvic tissue elasticity and increased vascular fragility [19], while a history of multiple deliveries can elevate the risk of pelvic adhesions [20]. These factors potentially increase surgical difficulty and introduce uncertainty into postoperative recovery, consequently prolonging hospitalization. The direct effect of Intraoperative Factors (e.g., uterine size, operative time) is closely tied to the degree of surgical trauma. Larger uterine volume [21] impedes optimal surgical field exposure [22], and prolonged operative time may heighten risks of intraoperative bleeding and tissue injury, necessitating extended postoperative observation and recovery periods. This mechanism is consistent with the fundamental surgical principle linking ”trauma burden” to ”recovery duration” [23]. Our secondary results further enrich the understanding of TLOS. The strong internal correlations among postoperative recovery indicators (e.g., r=0.81 between time to first oral intake and time to first flatus) suggest significant synergy in the recovery of gastrointestinal function and ambulatory capacity. Delays in one aspect may consequently prolong the overall recovery trajectory. This study represents the first application of SEM to investigate the mechanisms influencing TLOS specifically within the domain of gynecological LESS. Globally, SEM has gained traction in gynecologic oncology research. For instance, studies on ovarian cancer have utilized SEM to construct prognostic models, integrating latent constructs such as residual tumor size after primary surgery, platinum-free interval, and CA125 levels at recurrence. These models clearly delineate the direct and indirect effects of these factors on progression-free survival and overall survival, offering a multidimensional basis for clinical decision-making [24]. Similarly, research focusing on patients after surgery for gynecologic malignancies employed SEM to analyze latent variables related to postoperative recovery (e.g., age, BMI), primarily assessing frailty status. This work exemplifies the methodology’s strength in elucidating complex interrelationships among multiple factors through path analysis [25]. These applications highlight the core strength of SEM: its capacity to integrate unobservable latent constructs (e.g., ”patient baseline status,” ”disease characteristics,” ”treatment-related factors”) [26] and precisely quantify the direct and indirect effects between variables via path coefficients. This provides a holistic perspective on variable associations that traditional regression or univariate analyses cannot achieve [27], corroborating the advantages of SEM outlined in our Introduction. Compared to other SEM applications in gynecologic oncology, the uniqueness of this study lies in its novel focus on the minimally invasive nature of LESS. We utilized SEM to capture the chain of relationships spanning ”Patient Characteristics → Intraoperative Procedures → Postoperative Recovery.” This approach not only quantified the dominant direct role of intraoperative factors (e.g., operative time) on TLOS but also elucidated the indirect influence of postoperative factors (e.g., time to flatus/oral intake) mediated through their synergy with preoperative and intraoperative factors. This analytical framework overcomes a key limitation of previous ERAS studies in gynecologic oncology, which often relied on single-factor analyses. For example, while the Nelson 2023 ERAS-GY guidelines list predictors of hospital stay [18], they do not clarify the interactive pathways between these factors. SEM, with its inherent capability to handle multiple latent variables and quantify complex relationships [28], effectively addresses this gap, thereby providing a more systematic theoretical basis for optimizing ERAS protocols within the LESS domain. Currently, SEM has become a mainstream tool in gynecological oncology for analyzing multidimensional clinical factor associations, with its advantages in handling latent variables and revealing causal pathways widely recognized [29]. This study pioneers its application to gynecological single-port laparoscopy, not only expanding SEM’s utility in minimally invasive surgery but also clarifying TLOS influencing mechanisms. This provides an analytical framework for similar research, highlighting SEM’s irreplaceable value in integrating clinical data and guiding precision medicine. Although this study lacks a control group, it is the first to systematically dissect multidimensional pathways influencing TLOS in single-port laparoscopy using SEM, identifying intraoperative efficiency (e.g., operative time, fluid volume) as the core modifiable factor. This discovery generates a key hypothesis—that optimizing intraoperative protocols may shorten TLOS more effectively in single-port surgery than in other approaches—laying the groundwork for future comparative studies of single-port, multiport laparoscopic, and open surgeries. As exploratory research, its primary contribution lies in providing a novel analytical framework and testable hypotheses for mechanistic studies of hospitalization duration in gynecological minimally invasive surgery, rather than establishing universally applicable conclusions across surgical approaches. Limitations This study has several limitations. As a single-center, retrospective, single-arm investigation, the findings may be influenced by institution-specific practices, surgeon preferences, patient demographics, flexible discharge criteria implementation, and regional healthcare policies, thereby limiting generalizability. The absence of multiport laparoscopy or open surgery control groups precludes comparisons of TLOS determinants across surgical approaches and obscures whether identified key factors (e.g., intraoperative efficiency) are unique to single-port surgery, necessitating further research. Additionally, the study did not incorporate psychosocial variables (e.g., patient psychological status, social support) or clinical nuances (e.g., surgeon experience, minor intraoperative complications), potentially underestimating their impact on TLOS. Furthermore, retrospective design and methodological constraints of structural equation modeling (SEM) can only reveal association strengths and pathways—not establish definitive causality—due to residual confounding. These issues warrant validation through multicenter prospective controlled and interventional studies. Conclusion This study systematically analyzed factors influencing the total length of stay (TLOS) following gynecological laparoendoscopic single-site surgery (LESS) using structural equation modeling (SEM). Results demonstrate that: Preoperative factors (Patient Characteristics) and Intraoperative Factors exert direct effects on TLOS, with the latter demonstrating a marginally stronger influence; Postoperative Factors impact TLOS indirectly through their associations with preoperative and intraoperative factors.These interconnected elements collectively constitute the core mechanism governing TLOS. Our findings provide critical insights for optimizing LESS clinical workflows:Precision patient selection (e.g., considering age, obstetric history) and enhanced intraoperative standardization (e.g., reducing operative time, optimizing fluid management) can directly reduce TLOS;Strengthened postoperative recovery protocols (e.g., promoting early oral intake and ambulation) indirectly synergize to shorten hospitalization by accelerating functional recovery. SEM offers unique advantages in deciphering complex mechanisms influencing postoperative hospitalization, providing quantitative foundations for refining clinical pathways in LESS and other minimally invasive surgeries. Future multicenter prospective studies should validate this model and incorporate additional latent variables to enhance explanatory power, ultimately enabling more precise strategies to reduce TLOS and improve healthcare resource utilization efficiency. Declarations 1. Author Contributions All authors have made substantial contributions to this study, with specific responsibilities as follows: Li Li, Chenxi Zhao, Yukun Lang, Xiaojing Zhou, Penghuan Jia, and Xiangcui Guo were responsible for study design, data collection and collation, statistical analysis, and drafting of the initial manuscript; Xiaoming Guan provided academic guidance on the study protocol and interpretation of data; Qianqing Wang, as the corresponding author, oversaw the entire research process, including responsibility for study design, quality control, manuscript revision, and finalization of the manuscript. All authors have read and approved the final version of the manuscript, and guarantee the authenticity and integrity of the data. 2. Funding Statement This study did not receive any specific funding from public, commercial, or non-profit organizations. The research funds were borne by the institutions where the researchers are affiliated, and there are no interest associations related to funding. 3. Conflicts of Interest All authors declare that there are no conflicts of interest, such as financial interests, personal relationships, or professional competition, that could affect the objectivity of the study during the process of study design, implementation, data analysis, and manuscript writing. The research results are not interfered with by any external factors. 4. Acknowledgments We would like to thank the Electronic Medical Record (EMR) management team of Xinxiang Central Hospital for providing support in data extraction for this study, all patients and clinical medical staff who participated in this study for their cooperation, and the research team of the Fourth Clinical College of Henan Medical University for their assistance in consulting on statistical methods. 5. Ethical Statement This study is a retrospective cohort study, and all procedures were conducted in accordance with the Declaration of Helsinki and relevant medical ethical standards. The study protocol was approved by the Ethics Review Committee of Xinxiang Central Hospital, with an approval date of April 30, 2025, and a project number of 2025-154-01 (K). During the study, strict de-identification processing was performed on the electronic medical record data of all patients to protect patient privacy and ensure that data use complies with the requirements of medical information security management. Reference 1. Schmitt, A., et al., The Effects of a Laparoscopy by Single-Port Endoscopic Access in Benign Adnexal Surgery: A Randomized Controlled Trial. J Minim Invasive Gynecol, 2024. 31 (5): p. 397-405.2. Lequertier, V., et al., Hospital Length of Stay Prediction Methods: A Systematic Review. Med Care, 2021. 59 (10): p. 929-938.3. 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Keywords gynaecological surgery gynaecological surgery: laparoscopy Authors Affiliations Li Li Xinxiang Medical University View all articles by this author Chenxi Zhao 0009-0004-1168-6519 Xinxiang Medical University View all articles by this author Yukun Lang Xinxiang Medical University View all articles by this author Xiaojing Zhou Xinxiang Medical University View all articles by this author Penghuan Jia Xinxiang Medical University View all articles by this author Xiangcui Guo Xinxiang Medical University View all articles by this author Xiaoming Guan Baylor College of Medicine Department of Obstetrics and Gynecology View all articles by this author Qianqing Wang [email protected] Xinxiang Medical University View all articles by this author Metrics & Citations Metrics Article Usage 148 views 108 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Li Li, Chenxi Zhao, Yukun Lang, et al. 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