Comparison of Myosteatosis, Myopenia, Must Tool and Subcutaneous Adipose Tissue as Risk Factors for Anastomotic Leak in Patients with Colorectal Cancer

Comparison of Myosteatosis, Myopenia, Must Tool and Subcutaneous Adipose Tissue as Risk Factors for Anastomotic Leak in Patients with Colorectal Cancer | 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 Comparison of Myosteatosis, Myopenia, Must Tool and Subcutaneous Adipose Tissue as Risk Factors for Anastomotic Leak in Patients with Colorectal Cancer Andrea Chirivella Chirivella Fernández, Ester Ramirez Caballero, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8118549/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract INTRODUCTION Myosteatosis, myopenia, the Malnutrition Universal Screening Tool (MUST), and the amount of subcutaneous adipose tissue have been identified as significant risk factors for postoperative complications in patients with colorectal cancer. However, cut-off points to predict anastomotic dehiscence and severe complications have not been established. METHODS A prospective study was carried out in patients undergoing resection of colorectal tumors with anastomosis between June 2022 and November 2024. The MUST score, average psoas density, muscle mass, and amount of subcutaneous tissue at the L3 level on computed tomography (CT) were documented. Anastomotic dehiscence and severe postoperative complications according to the Clavien-Dindo (CD) classification were recorded. RESULTS A total of 250 patients were included. Only myosteatosis showed a statistically significant association with the occurrence of severe complications (AUC: 0.788; p < 0.001) and anastomotic dehiscence (AUC: 0.881; p < 0.001) on ROC curves. Additionally, myosteatosis was significantly associated with postoperative complications (RR: 3.448, 95% CI: 2.695–4.347, p < 0.01) and severe complications (RR: 7.88, 95% CI: 4.27–14.59, p < 0.01) before hospital discharge. CONCLUSIONS Myosteatosis, assessed through radiologic density on preoperative CT imaging, is a significant predictor of severe postoperative complications (CD ≥ III) in colorectal cancer patients, as well as anastomotic dehiscence. Identifying myosteatosis may help clinicians recognize high perioperative risk patients early and improve preoperative planning. Myosteatosis Myopenia MUST Subcutaneous adipose tissue Anastomotic dehiscence Radiological sarcopenia Colorectal cancer Postoperative complications Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Myosteatosis, myopenia, the MUST score and the amount of subcutaneous adipose tissue have been identified as significant risk factors for mortality in patients with colorectal cancer (1–5). Myosteatosis refers to fat infiltration in skeletal muscle and is evaluated by measuring the radiation attenuation of skeletal muscle in Hounsfield Units (HU) (2) in the computed tomography (CT), while myopenia is defined as a decrease in muscle mass and is assessed using the Skeletal Muscle Mass Index (SMI)(5). Radiological sarcopenia is defined as the loss of muscle mass (myopenia) and/or quality (myosteatosis), both of them assessed through axial CT slices at the level of the third lumbar vertebra (L3). Despite increasing evidence linking sarcopenia with postoperative complications, most studies assess mortality to establish cut-off points for radiological sarcopenia. However, no accepted cut-off value currently exists to diagnose radiological sarcopenia for the purpose of reducing the risk of serious postoperative complications and anastomotic dehiscence (2–6). The MUST scale is a widely used tool to assess risk of malnutrition in oncologic patients and has shown a significant association with increased hospital stay and mortality in patients with colorectal cancer (1). However, its ability to predict specific complications such as anastomotic dehiscence has not been established. Furthermore, the growing prevalence of obesity in the current population, along with chronic inflammation in oncologic patients which may contribute to weight gain, as well as altering metabolism and body composition (7), may complicate the accurate assessment of malnutrition risk using this scale, as it is based on parameters such as weight loss, Body Mass Index (BMI), and the patient's intake capability (1). Regarding the amount of subcutaneous adipose tissue (SAT), which is measured on the same axial CT slice, it refers to the fat area located just beneath the skin and above the muscles. It has been less studied in relation to postoperative complications, but its assessment may provide additional information about nutritional status and surgical risk (4–5)(8). Currently, efforts are being made to implement imaging techniques that better assess the nutritional risk of oncologic patients in order to select the patients in need for optimization of their preoperative status. Identifying radiological sarcopenia in these patients is crucial for implementing prehabilitation strategies that include nutritional optimization and exercise, with the goal of improving surgical outcomes. Appropriate preoperative supplementation can help patients reach surgery in the best possible conditions, thereby reducing the risk of complications and anastomotic dehiscence (2–4). To effectively manage the perioperative care of patients with colorectal cancer and improve postoperative outcomes, it is essential to establish an appropriate cut-off point for MUST, SAT and radiological sarcopenia according to myosteatosis or myopenia, that enables the identification of patients at higher risk of dehiscence and severe postoperative complications in order to optimize their preoperative management (9). Therefore, the objective of this study is to independently evaluate these parameters and establish cut-off points using ROC curve analysis to best predict anastomotic dehiscence and severe complications in colorectal cancer patients. Identifying these cut-off points may improve preoperative risk stratification and guide targeted interventions to reduce postoperative complications. METHODS A prospective cohort study was conducted in patients diagnosed with colorectal cancer who underwent surgical resection with curative intent, performed by colorectal surgeons between June 2023 and November 2024. Patients over 18 years of age were included. Those who underwent transanal minimally invasive surgery (TAMIS), abdominoperineal amputation or colostomy creation, as well as those who underwent emergency surgery, were excluded. Outcomes Primary Objective: To evaluate and compare the predictive ability of myosteatosis, myopenia, the MUST score, and SAT to identify the risk of anastomotic leakage in patients with colorectal cancer undergoing surgery with anastomosis. Secondary Objectives: As secondary objectives, we aimed to determine the ability of these parameters (myosteatosis, myopenia, MUST, and SAT) to predict the occurrence of severe postoperative complications (CD ≥ III), as well as to establish optimal cut-off values based on muscle density in HU, subcutaneous adipose tissue area and IMME. We also sought to analyze the relationship between myosteatosis and various epidemiological variables, including age, sex, ASA classification, neoadjuvant treatment, and tumor location. Finally, we evaluated the impact of myosteatosis on specific postoperative events as Surgical Side Infection (SSI), reintervention, readmission, and mortality. Data Collection The variables collected in the study included age, sex, and the patient’s preoperative physical status according to the American Society of Anesthesiologists (ASA), the need for neoadjuvant treatment, and tumor location—right/transverse colon, left colon, or rectum. All patients' staging CT scans were analyzed using Centricity image visualization software at the axial cut level of L3. At this level, the density of both psoas muscles was measured (10), and the NIH ImageJ software version 2.0 (from the National Institutes of Health) was used to assess both muscle mass and subcutaneous adipose tissue (11) (Image I). Image I: CT scan in axial section at the L3 level from ImageJ software (Version 2.0). Area used for SMI calculation: 1a: right paravertebral muscles (iliocostalis, longissimus, and spinalis); 1b: left paravertebral muscles; 2a: right psoas muscle; 2b: left psoas muscle; 3: abdominal wall muscles (transversus abdominis, internal oblique, external oblique, and rectus abdominis). 4: SAT: subcutaneous adipose tissue. Patients were followed-up until hospital discharge, and early postoperative complications (< 30 days) were recorded: clinically or radiologically confirmed anastomotic dehiscence, reoperation, mortality, readmission, and surgical site infection. Complications were classified according to the Clavien-Dindo (CD) classification (12) and categorized as binary outcomes: major complications (CD ≥ 3) and minor complications (CD < 3). Informed consent was given to all participants prior to the inclusion in the study. This study was reviewed and approved by our hospital's Ethics Committee. The approval code was CHUC_23_203. Statistical Analysis Statistical tests were conducted using SPSS 26.0. The correlation between risk factors (myosteatosis, myopenia, MUST score, and subcutaneous adipose tissue) and outcomes (anastomotic dehiscence and major complications) was evaluated using ROC curve analysis. Statistical significance was defined as a p-value < 0.05. The software used was SPSS 26.0. Subsequently, ROC curve analysis was applied to examine the accuracy for each parameter in predicting the occurrence of anastomotic dehiscence and major complications in the postoperative period. This analysis allowed us to determine the area under the curve (AUC) for each predictor and identify the optimal cut-off points offering the best balance between sensitivity and specificity. Thereafter, descriptive analysis of the epidemiological variables was performed. RESULTS Initially, 329 patients who underwent surgery during the study period were included. After applying the exclusion criteria, a final sample of 250 patients remained. ROC Curve Analysis In the analysis of the correlation of potential risk factors, myosteatosis showed a statistically significant association with the occurrence of anastomotic leakage (AUC = 0.881; p < 0.001) and severe complications (AUC = 0.788; p < 0.001) following colorectal cancer surgery (Figures I–II). Regarding severe complications, the ROC curve for myosteatosis was able to correctly identify a considerable proportion of patients who later developed serious complications. Additionally, a threshold of ≤ 39.5 HU was identified as a predictive cut-off for severe complications, with a sensitivity of 69.57% (95% CI: 47.1–86.8) and a specificity of 81.86% (95% CI: 76.2–86.7). Concerning anastomotic leakage, results indicated that myosteatosis was a significant predictor. The cut-off point of radiological density ≤ 44 HU was established as a predictor of anastomotic leakage. This threshold showed a sensitivity of 94.12% (95% CI: 71.3–99.9) and a specificity of 72.53% (95% CI: 66.3–78.2). The MUST scale with a score above 2, indicating severe malnutrition, myopenia based on the IMME, and subcutaneous adipose tissue area on CT did not show significant predictive capacity for these adverse events in our ROC analysis. Figure I: ROC curve for risk assessment of severe complications (CD ≥ 3). UH corresponds to the mean Hounsfield unit on computed tomography (CT); MUST, the Malnutrition Universal Screening Tool score; TAS, the subcutaneous adipose tissue area; and IMME, the skeletal muscle mass index on CT. Figure II. ROC curves for the prediction of anastomotic leakage using different preoperative risk assessment tools. UH corresponds to the mean Hounsfield unit on computed tomography (CT); MUST, the Malnutrition Universal Screening Tool score; TAS, the subcutaneous adipose tissue area; and IMME, the skeletal muscle mass index on CT. Epidemiological Characteristics: The epidemiological variables analyzed comparatively according to the cut-off point established in the previous ROC curve are shown in Table I. Statistically significant differences were found regarding patient sex, with myosteatosis being more frequent in men, with a relative risk (RR) of 2.001 (95% CI: 1.279–3.131; p = 0.009). Mioesteatosis n = 80 No mioesteatosis n = 170 p value Age (years) Mean (SD) 72,48 (10,61) 69,42 (10,60) 0,096 Sex (Male) -n (%) 61 (76,3%) 93 (54,7%) 0,009 ASA -n (%) I-II 50 (62,5%) 114 (67,1%) 0,479 III-IV 30 (37,5%) 56 (32,9%) Location Right hemicolectomy (including right hemicolectomy, extended right hemicolectomy, transverse) 35 (43,8%) 65 (38,2%) 0,378 Descending (including left hemicolectomy, sigmoidectomy, Splenic Angle) 19 (23,8%) 55 (32,4%) Anterior resection of the rectum (including Ultralow anterior resection of the rectum, Low anterior resection of the rectum) 26 (32,5%) 50 (29,4%) Neoadjuvant theraphy 19 (23,8%) 30 (17,6%) 1,286 (p = 0,257) Table I. Epidemiological variables. SD: Standard Deviation; Neoadjuvant therapy includes chemotherapy, immunotherapy, and radiotherapy. Postoperative Outcomes According to the cut-off points established in the previous section, 32% (n = 80) of the patients were diagnosed with myosteatosis based on CT (Table II). These patients were associated with a higher frequency of severe complications or CD ≥ 3 (40.0% vs 3.8%) with a RR of 7.880 (95% CI: 4.27–14.59; p < 0.001). Anastomotic leakage was also significantly more frequent in patients with myosteatosis (20.0% vs 0.6%), with a RR of 3.448 (95% CI: 2.695–4.347; p < 0.001). Specific complications were evaluated by subgroups using the ≤ 39.5 HU cut-off point. The rate of surgical site infection (SSI) was higher in patients with myosteatosis (31.3% vs 3.5%) with a RR of 3.869 (95% CI: 1.878–7.970; p < 0.001). Similarly, hospital readmission rate was more common in patients with myosteatosis (10.0% vs 1.8%) with a RR of 6.185 (95% CI: 1.595–6.749; p = 0.003). Likewise, the reoperation rate was higher in the myosteatosis group (17.5% vs 2.0%) with a RR of 8.803 (95% CI: 2.795–12.724; p < 0.001). Finally, the difference in mortality rate also reached statistical significance (p = 0.048) and a higher mortality was observed in the myosteatosis group (3.8% vs 1.8%), with a RR of 1.584 (95% CI: 1.073–3.597). Variable Mioesteatosis (n = 80) (%) No Mioesteatosis (n = 170) (%) χ 2 (p) RR (IC) Complication CD ≥ 3 -n (%) 32 (40,0%) 7 (3,8%) 50,726 (p < 0,001) 7,88 (4,27–14,59) Reintervention -n (%) 14 (17,5%) 4 (2,0%) 18,680 (p < 0,001) 8,803 (2,795–12,724) Radmission -n (%) 8 (10,0%) 3 (1,8%) 8,771 (p = 0,003) 6,185 (1,595–6,749) SSI -n (%) 25 (31,3%) 6 (3,5%) 38,484 (p < 0,001) 3,869 (1,878–7,970) Mortality -n (%) 3 (3,8%) 3 (1,8%) 1,254 (p = 0,048) 1,584 (1,073–3,597) Leakage -n (%) 16 (20,0%) 1 (0,6%) 32,345 (p < 0,001) 3,448 (2,695–4,347) Table II : CD: Clavien-Dindo Classification; SSI: Surgical Site Infection DISCUSSION Radiological sarcopenia defined as myosteatosis or myopenia, along with a high-risk MUST score and subcutaneous adipose tissue (SAT), have been associated in previous studies with anastomotic leakage and severe complications. However, to date, no specific cut-off points have been established that reliably predict critical clinical events such as anastomotic leakage or severe complications, as prior studies have generally used thresholds based solely on mortality (1–6). To determine which of these factors holds the greatest clinical potential as a prognostic marker for anastomotic leakage and severe complications, ROC curve analyses were performed. No significant association was found between the MUST scale (using a threshold indicating high malnutrition risk) and neither severe complications or anastomotic leakage. Preoperative nutritional assessment is important, and when evaluated through myosteatosis, reflecting the intrinsic quality of muscle tissue, it provides a more accurate assessment of specific postoperative risk in this population. On the contrary, the lack of predictive power of myopenia suggests that muscle quality is more relevant than muscle mass quantity in this context. Moreover, subcutaneous adipose tissue, at least by this measuring technique, did not prove to be a reliable predictor of the adverse outcomes studied. Thus, the best predictor of postoperative complications and anastomotic leakage is radiological sarcopenia, diagnosed as myosteatosis. For predicting severe complications, a radiological density cut-off of ≤ 39.5 HU was identified, with a sensitivity of 69.57% and specificity of 81.86%. In contrast, the reference threshold for predicting anastomotic leakage was ≤ 44 HU, with a sensitivity of 94.12% and specificity of 72.53%. Previous studies have analyzed radiological sarcopenia as a risk factor for leakage using lower cut-off points (3). The risk of CT-detected myosteatosis is twice as high in males (RR: 2.001 [95% CI: 1.279–3.131]), making it a risk factor for developing serious postoperative complications and anastomotic leakage (13). Therefore, future studies should consider establishing cut-off points according to sex. However, no differences were found according to age, high ASA classification (III–IV), tumor location, or prior neoadjuvant therapy (1–4)(12). Patients with myosteatosis had an almost eightfold increased risk of developing severe postoperative complications (RR: 7.88 [95% CI: 4.27–14.59]) and nearly a fourfold increased risk of anastomotic leakage (RR: 3.448 [95% CI: 2.695–4.347]). These findings support radiological density as a key predictor of surgical outcomes across different populations (1–3). Furthermore, an increased risk of reoperation was observed (RR: 8.803 [95% CI: 2.795–12.724]), suggesting that fat infiltration of muscle may interfere with tissue recovery mechanisms or promote complications such as bleeding, leakage, or infections requiring additional surgery. Similarly, the risk of hospital readmission in these patients was six times higher compared to patients without radiological sarcopenia (RR: 6.185 [95% CI: 1.595–6.749]), highlighting a clinical, economic, and logistical impact on healthcare systems. Surgical site infection (SSI) rates were also higher in patients with radiological sarcopenia based on myosteatosis (RR: 3.869 [95% CI: 1.878–7.970]). This finding is consistent with previous studies associating intramuscular fat infiltration with reduced tissue perfusion, local immune dysfunction, and an impaired inflammatory response (14)(15). Additionally, radiological sarcopenia established by myosteatosis has been associated in prior studies with chronic pro-inflammatory states and anabolic resistance, factors that compromise the body's ability to tolerate surgical stress and may help explain the increased rate of adverse events after colorectal cancer surgery (16). While the findings are clinically relevant, certain limitations should be noted. The study was conducted at a single center, which may affect the generalizability of the results to the general population. In addition, the cohort included a higher proportion of male patients, which may introduce a degree of sex-based bias. Future research should consider sex-stratified analyses or studies specifically designed to explore sex-related differences in outcomes. CONCLUSION Among the risk factors analyzed, myosteatosis is the most significant predictor of anastomotic leakage and severe complications in patients undergoing colorectal cancer surgery. Preoperative identification of myosteatosis as part of the nutritional assessment of surgical patients may facilitate to establish the clinically relevant diagnosis of radiological sarcopenia, offering a more practical, fast, simple, and reproducible evaluation of specific postoperative risk in this population. With high sensitivity—especially in predicting anastomotic leakage using the ≤ 44 HU threshold—it can serve as a valuable preoperative marker, potentially more effective than the MUST scale in guiding perioperative patient management. Declarations ETHICS DECLARATIONS Conflict of interest The authors did not receive support from any organisation for the submitted work. The authors declare they have no financial interests. The authors have no relevant financial or non-financial interests to disclose. Funding No funding was obtained for this study. Ethical approval Approval was obtained from the ethics committee of our hospital. The procedures used in this study adhere to the tenets of the Declaration of Helsinki. The Approval No. was CHUC_23_203. 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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-8118549","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":557202730,"identity":"77585690-1f02-45cc-a833-167e7ebb24f8","order_by":0,"name":"Andrea Chirivella Chirivella 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16:33:54","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":30166,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8118549/v1/1a503a94ea42c418e3e60462.png"},{"id":97992317,"identity":"ccbfa8f0-696f-42bf-8c33-217abbcd9809","added_by":"auto","created_at":"2025-12-11 14:42:20","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47205,"visible":true,"origin":"","legend":"","description":"","filename":"e6ae60c7c7c945e2a9bf4bf4e543b4351structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8118549/v1/c41cfb14d1a2d259c3d89e67.xml"},{"id":98425707,"identity":"abba3335-9903-4abf-b461-a0e8e62bbc55","added_by":"auto","created_at":"2025-12-17 16:35:07","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":58229,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8118549/v1/2173520a11e3c8a5d833661d.html"},{"id":98424252,"identity":"fdcd0174-3fad-420c-8b59-46270b9876f1","added_by":"auto","created_at":"2025-12-17 16:33:06","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":171802,"visible":true,"origin":"","legend":"\u003cp\u003eImage I: CT scan in axial section at the L3 level from ImageJ software (Version 2.0). Area used for SMI calculation: 1a: right paravertebral muscles (iliocostalis, longissimus, and spinalis); 1b: left paravertebral muscles; 2a: right psoas muscle; 2b: left psoas muscle; 3: abdominal wall muscles (transversus abdominis, internal oblique, external oblique, and rectus abdominis). 4: SAT: subcutaneous adipose tissue.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8118549/v1/cf2421416b5a43a586ebc7c9.jpeg"},{"id":97992314,"identity":"23dfd726-4ef1-4899-a8f7-537c4662f824","added_by":"auto","created_at":"2025-12-11 14:42:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":91484,"visible":true,"origin":"","legend":"\u003cp\u003eFigure I: ROC curve for risk assessment of severe complications (CD ≥3). UH corresponds to the mean Hounsfield unit on computed tomography (CT); MUST, the Malnutrition Universal Screening Tool score; TAS, the subcutaneous adipose tissue area; and IMME, the skeletal muscle mass index on CT.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8118549/v1/723580f5979fb2f8707d5fe7.png"},{"id":97992320,"identity":"eb876759-a778-455a-aa1d-784abe9e2954","added_by":"auto","created_at":"2025-12-11 14:42:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":91299,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure II. \u003c/strong\u003eROC curves for the prediction of anastomotic leakage using different preoperative risk assessment tools. UH corresponds to the mean Hounsfield unit on computed tomography (CT); MUST, the Malnutrition Universal Screening Tool score; TAS, the subcutaneous adipose tissue area; and IMME, the skeletal muscle mass index on CT.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8118549/v1/bd7fe9694826f3db11a15f14.png"},{"id":98444067,"identity":"0c1c4a13-e77d-406f-a58f-8159b90fa3ac","added_by":"auto","created_at":"2025-12-17 17:15:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1089369,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8118549/v1/3c652d0a-37b3-4fc7-a3e2-ca815caf60a6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eComparison of Myosteatosis, Myopenia, Must Tool and Subcutaneous Adipose Tissue as Risk Factors for Anastomotic Leak in Patients with Colorectal Cancer\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMyosteatosis, myopenia, the MUST score and the amount of subcutaneous adipose tissue have been identified as significant risk factors for mortality in patients with colorectal cancer (1\u0026ndash;5).\u003c/p\u003e\u003cp\u003eMyosteatosis refers to fat infiltration in skeletal muscle and is evaluated by measuring the radiation attenuation of skeletal muscle in Hounsfield Units (HU) (2) in the computed tomography (CT), while myopenia is defined as a decrease in muscle mass and is assessed using the Skeletal Muscle Mass Index (SMI)(5). Radiological sarcopenia is defined as the loss of muscle mass (myopenia) and/or quality (myosteatosis), both of them assessed through axial CT slices at the level of the third lumbar vertebra (L3). Despite increasing evidence linking sarcopenia with postoperative complications, most studies assess mortality to establish cut-off points for radiological sarcopenia. However, no accepted cut-off value currently exists to diagnose radiological sarcopenia for the purpose of reducing the risk of serious postoperative complications and anastomotic dehiscence (2\u0026ndash;6).\u003c/p\u003e\u003cp\u003eThe MUST scale is a widely used tool to assess risk of malnutrition in oncologic patients and has shown a significant association with increased hospital stay and mortality in patients with colorectal cancer (1). However, its ability to predict specific complications such as anastomotic dehiscence has not been established. Furthermore, the growing prevalence of obesity in the current population, along with chronic inflammation in oncologic patients which may contribute to weight gain, as well as altering metabolism and body composition (7), may complicate the accurate assessment of malnutrition risk using this scale, as it is based on parameters such as weight loss, Body Mass Index (BMI), and the patient's intake capability (1).\u003c/p\u003e\u003cp\u003eRegarding the amount of subcutaneous adipose tissue (SAT), which is measured on the same axial CT slice, it refers to the fat area located just beneath the skin and above the muscles. It has been less studied in relation to postoperative complications, but its assessment may provide additional information about nutritional status and surgical risk (4\u0026ndash;5)(8).\u003c/p\u003e\u003cp\u003eCurrently, efforts are being made to implement imaging techniques that better assess the nutritional risk of oncologic patients in order to select the patients in need for optimization of their preoperative status. Identifying radiological sarcopenia in these patients is crucial for implementing prehabilitation strategies that include nutritional optimization and exercise, with the goal of improving surgical outcomes. Appropriate preoperative supplementation can help patients reach surgery in the best possible conditions, thereby reducing the risk of complications and anastomotic dehiscence (2\u0026ndash;4).\u003c/p\u003e\u003cp\u003eTo effectively manage the perioperative care of patients with colorectal cancer and improve postoperative outcomes, it is essential to establish an appropriate cut-off point for MUST, SAT and radiological sarcopenia according to myosteatosis or myopenia, that enables the identification of patients at higher risk of dehiscence and severe postoperative complications in order to optimize their preoperative management (9). Therefore, the objective of this study is to independently evaluate these parameters and establish cut-off points using ROC curve analysis to best predict anastomotic dehiscence and severe complications in colorectal cancer patients. Identifying these cut-off points may improve preoperative risk stratification and guide targeted interventions to reduce postoperative complications.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eA prospective cohort study was conducted in patients diagnosed with colorectal cancer who underwent surgical resection with curative intent, performed by colorectal surgeons between June 2023 and November 2024.\u003c/p\u003e\u003cp\u003ePatients over 18 years of age were included. Those who underwent transanal minimally invasive surgery (TAMIS), abdominoperineal amputation or colostomy creation, as well as those who underwent emergency surgery, were excluded.\u003c/p\u003e\u003cp\u003eOutcomes\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePrimary Objective:\u003c/h2\u003e\u003cp\u003eTo evaluate and compare the predictive ability of myosteatosis, myopenia, the MUST score, and SAT to identify the risk of anastomotic leakage in patients with colorectal cancer undergoing surgery with anastomosis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSecondary Objectives:\u003c/h3\u003e\n\u003cp\u003eAs secondary objectives, we aimed to determine the ability of these parameters (myosteatosis, myopenia, MUST, and SAT) to predict the occurrence of severe postoperative complications (CD\u0026thinsp;\u0026ge;\u0026thinsp;III), as well as to establish optimal cut-off values based on muscle density in HU, subcutaneous adipose tissue area and IMME.\u003c/p\u003e\u003cp\u003eWe also sought to analyze the relationship between myosteatosis and various epidemiological variables, including age, sex, ASA classification, neoadjuvant treatment, and tumor location. Finally, we evaluated the impact of myosteatosis on specific postoperative events as Surgical Side Infection (SSI), reintervention, readmission, and mortality.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eThe variables collected in the study included age, sex, and the patient\u0026rsquo;s preoperative physical status according to the American Society of Anesthesiologists (ASA), the need for neoadjuvant treatment, and tumor location\u0026mdash;right/transverse colon, left colon, or rectum.\u003c/p\u003e\u003cp\u003eAll patients' staging CT scans were analyzed using Centricity image visualization software at the axial cut level of L3. At this level, the density of both psoas muscles was measured (10), and the NIH ImageJ software version 2.0 (from the National Institutes of Health) was used to assess both muscle mass and subcutaneous adipose tissue (11) (Image I).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eImage I: CT scan in axial section at the L3 level from ImageJ software (Version 2.0). Area used for SMI calculation: 1a: right paravertebral muscles (iliocostalis, longissimus, and spinalis); 1b: left paravertebral muscles; 2a: right psoas muscle; 2b: left psoas muscle; 3: abdominal wall muscles (transversus abdominis, internal oblique, external oblique, and rectus abdominis). 4: SAT: subcutaneous adipose tissue.\u003c/p\u003e\u003cp\u003ePatients were followed-up until hospital discharge, and early postoperative complications (\u0026lt;\u0026thinsp;30 days) were recorded: clinically or radiologically confirmed anastomotic dehiscence, reoperation, mortality, readmission, and surgical site infection. Complications were classified according to the Clavien-Dindo (CD) classification (12) and categorized as binary outcomes: major complications (CD\u0026thinsp;\u0026ge;\u0026thinsp;3) and minor complications (CD\u0026thinsp;\u0026lt;\u0026thinsp;3).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003cp\u003ewas given to all participants prior to the inclusion in the study. This study was reviewed and approved by our hospital's Ethics Committee. The approval code was CHUC_23_203.\u003c/p\u003e\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical tests were conducted using SPSS 26.0. The correlation between risk factors (myosteatosis, myopenia, MUST score, and subcutaneous adipose tissue) and outcomes (anastomotic dehiscence and major complications) was evaluated using ROC curve analysis. Statistical significance was defined as a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The software used was SPSS 26.0.\u003c/p\u003e\u003cp\u003eSubsequently, ROC curve analysis was applied to examine the accuracy for each parameter in predicting the occurrence of anastomotic dehiscence and major complications in the postoperative period. This analysis allowed us to determine the area under the curve (AUC) for each predictor and identify the optimal cut-off points offering the best balance between sensitivity and specificity. Thereafter, descriptive analysis of the epidemiological variables was performed.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eInitially, 329 patients who underwent surgery during the study period were included. After applying the exclusion criteria, a final sample of 250 patients remained.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eROC Curve Analysis\u003c/h2\u003e\u003cp\u003eIn the analysis of the correlation of potential risk factors, myosteatosis showed a statistically significant association with the occurrence of anastomotic leakage (AUC\u0026thinsp;=\u0026thinsp;0.881; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and severe complications (AUC\u0026thinsp;=\u0026thinsp;0.788; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) following colorectal cancer surgery (Figures I\u0026ndash;II).\u003c/p\u003e\u003cp\u003eRegarding severe complications, the ROC curve for myosteatosis was able to correctly identify a considerable proportion of patients who later developed serious complications. Additionally, a threshold of \u0026le;\u0026thinsp;39.5 HU was identified as a predictive cut-off for severe complications, with a sensitivity of 69.57% (95% CI: 47.1\u0026ndash;86.8) and a specificity of 81.86% (95% CI: 76.2\u0026ndash;86.7).\u003c/p\u003e\u003cp\u003eConcerning anastomotic leakage, results indicated that myosteatosis was a significant predictor. The cut-off point of radiological density\u0026thinsp;\u0026le;\u0026thinsp;44 HU was established as a predictor of anastomotic leakage. This threshold showed a sensitivity of 94.12% (95% CI: 71.3\u0026ndash;99.9) and a specificity of 72.53% (95% CI: 66.3\u0026ndash;78.2).\u003c/p\u003e\u003cp\u003eThe MUST scale with a score above 2, indicating severe malnutrition, myopenia based on the IMME, and subcutaneous adipose tissue area on CT did not show significant predictive capacity for these adverse events in our ROC analysis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure I: ROC curve for risk assessment of severe complications (CD\u0026thinsp;\u0026ge;\u0026thinsp;3). UH corresponds to the mean Hounsfield unit on computed tomography (CT); MUST, the Malnutrition Universal Screening Tool score; TAS, the subcutaneous adipose tissue area; and IMME, the skeletal muscle mass index on CT.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure II.\u003c/b\u003e ROC curves for the prediction of anastomotic leakage using different preoperative risk assessment tools. UH corresponds to the mean Hounsfield unit on computed tomography (CT); MUST, the Malnutrition Universal Screening Tool score; TAS, the subcutaneous adipose tissue area; and IMME, the skeletal muscle mass index on CT.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEpidemiological Characteristics:\u003c/h3\u003e\n\u003cp\u003eThe epidemiological variables analyzed comparatively according to the cut-off point established in the previous ROC curve are shown in Table I. Statistically significant differences were found regarding patient sex, with myosteatosis being more frequent in men, with a relative risk (RR) of 2.001 (95% CI: 1.279\u0026ndash;3.131; p\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMioesteatosis\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;80\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo mioesteatosis\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;170\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72,48 (10,61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69,42 (10,60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,096\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex (Male) -n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61 (76,3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93 (54,7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eASA -n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eI-II\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50 (62,5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e114 (67,1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0,479\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eIII-IV\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (37,5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (32,9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eRight hemicolectomy (including right hemicolectomy, extended right hemicolectomy, transverse)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (43,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65 (38,2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0,378\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDescending (including\u0026nbsp;left hemicolectomy,\u0026nbsp;sigmoidectomy, Splenic Angle)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (23,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55 (32,4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eAnterior resection of the rectum (including\u0026nbsp;Ultralow anterior resection of the rectum, Low anterior resection of the rectum)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (32,5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50 (29,4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNeoadjuvant theraphy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (23,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (17,6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1,286\u003c/p\u003e\u003cp\u003e(p\u0026thinsp;=\u0026thinsp;0,257)\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\u003cb\u003eTable I. Epidemiological variables.\u003c/b\u003e SD: Standard Deviation; Neoadjuvant therapy includes chemotherapy, immunotherapy, and radiotherapy.\u003c/p\u003e\n\u003ch3\u003ePostoperative Outcomes\u003c/h3\u003e\n\u003cp\u003eAccording to the cut-off points established in the previous section, 32% (n\u0026thinsp;=\u0026thinsp;80) of the patients were diagnosed with myosteatosis based on CT (Table II). These patients were associated with a higher frequency of severe complications or CD\u0026thinsp;\u0026ge;\u0026thinsp;3 (40.0% vs 3.8%) with a RR of 7.880 (95% CI: 4.27\u0026ndash;14.59; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eAnastomotic leakage was also significantly more frequent in patients with myosteatosis (20.0% vs 0.6%), with a RR of 3.448 (95% CI: 2.695\u0026ndash;4.347; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eSpecific complications were evaluated by subgroups using the \u0026le;\u0026thinsp;39.5 HU cut-off point. The rate of surgical site infection (SSI) was higher in patients with myosteatosis (31.3% vs 3.5%) with a RR of 3.869 (95% CI: 1.878\u0026ndash;7.970; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, hospital readmission rate was more common in patients with myosteatosis (10.0% vs 1.8%) with a RR of 6.185 (95% CI: 1.595\u0026ndash;6.749; p\u0026thinsp;=\u0026thinsp;0.003). Likewise, the reoperation rate was higher in the myosteatosis group (17.5% vs 2.0%) with a RR of 8.803 (95% CI: 2.795\u0026ndash;12.724; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eFinally, the difference in mortality rate also reached statistical significance (p\u0026thinsp;=\u0026thinsp;0.048) and a higher mortality was observed in the myosteatosis group (3.8% vs 1.8%), with a RR of 1.584 (95% CI: 1.073\u0026ndash;3.597).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\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\u003cem\u003eVariable\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eMioesteatosis (n\u0026thinsp;=\u0026thinsp;80) (%)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eNo Mioesteatosis (n\u0026thinsp;=\u0026thinsp;170) (%)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e (p)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRR (IC)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComplication\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCD\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/b\u003e \u003cem\u003e-n (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (40,0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (3,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50,726\u003c/p\u003e\u003cp\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0,001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7,88\u003c/p\u003e\u003cp\u003e(4,27\u0026ndash;14,59)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReintervention\u003c/b\u003e \u003cem\u003e-n (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (17,5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (2,0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18,680\u003c/p\u003e\u003cp\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0,001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8,803\u003c/p\u003e\u003cp\u003e(2,795\u0026ndash;12,724)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRadmission\u003c/b\u003e \u003cem\u003e-n (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (10,0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (1,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8,771\u003c/p\u003e\u003cp\u003e(p\u0026thinsp;=\u0026thinsp;0,003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6,185\u003c/p\u003e\u003cp\u003e(1,595\u0026ndash;6,749)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSSI\u003c/b\u003e \u003cem\u003e-n (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (31,3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (3,5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38,484\u003c/p\u003e\u003cp\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0,001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3,869\u003c/p\u003e\u003cp\u003e(1,878\u0026ndash;7,970)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e \u003cem\u003e-n (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (3,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (1,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,254\u003c/p\u003e\u003cp\u003e(p\u0026thinsp;=\u0026thinsp;0,048)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1,584\u003c/p\u003e\u003cp\u003e(1,073\u0026ndash;3,597)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLeakage\u003c/b\u003e \u003cem\u003e-n (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (20,0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0,6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32,345\u003c/p\u003e\u003cp\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0,001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3,448\u003c/p\u003e\u003cp\u003e(2,695\u0026ndash;4,347)\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\u003cb\u003eTable II\u003c/b\u003e: CD: Clavien-Dindo Classification; SSI: Surgical Site Infection\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eRadiological sarcopenia defined as myosteatosis or myopenia, along with a high-risk MUST score and subcutaneous adipose tissue (SAT), have been associated in previous studies with anastomotic leakage and severe complications. However, to date, no specific cut-off points have been established that reliably predict critical clinical events such as anastomotic leakage or severe complications, as prior studies have generally used thresholds based solely on mortality (1\u0026ndash;6).\u003c/p\u003e\u003cp\u003eTo determine which of these factors holds the greatest clinical potential as a prognostic marker for anastomotic leakage and severe complications, ROC curve analyses were performed. No significant association was found between the MUST scale (using a threshold indicating high malnutrition risk) and neither severe complications or anastomotic leakage. Preoperative nutritional assessment is important, and when evaluated through myosteatosis, reflecting the intrinsic quality of muscle tissue, it provides a more accurate assessment of specific postoperative risk in this population. On the contrary, the lack of predictive power of myopenia suggests that muscle quality is more relevant than muscle mass quantity in this context. Moreover, subcutaneous adipose tissue, at least by this measuring technique, did not prove to be a reliable predictor of the adverse outcomes studied.\u003c/p\u003e\u003cp\u003eThus, the best predictor of postoperative complications and anastomotic leakage is radiological sarcopenia, diagnosed as myosteatosis. For predicting severe complications, a radiological density cut-off of \u0026le;\u0026thinsp;39.5 HU was identified, with a sensitivity of 69.57% and specificity of 81.86%. In contrast, the reference threshold for predicting anastomotic leakage was \u0026le;\u0026thinsp;44 HU, with a sensitivity of 94.12% and specificity of 72.53%. Previous studies have analyzed radiological sarcopenia as a risk factor for leakage using lower cut-off points (3).\u003c/p\u003e\u003cp\u003eThe risk of CT-detected myosteatosis is twice as high in males (RR: 2.001 [95% CI: 1.279\u0026ndash;3.131]), making it a risk factor for developing serious postoperative complications and anastomotic leakage (13). \u003cb\u003eTherefore, future studies should consider establishing cut-off points according to sex.\u003c/b\u003e However, no differences were found according to age, high ASA classification (III\u0026ndash;IV), tumor location, or prior neoadjuvant therapy (1\u0026ndash;4)(12).\u003c/p\u003e\u003cp\u003ePatients with myosteatosis had an almost eightfold increased risk of developing severe postoperative complications (RR: 7.88 [95% CI: 4.27\u0026ndash;14.59]) and nearly a fourfold increased risk of anastomotic leakage (RR: 3.448 [95% CI: 2.695\u0026ndash;4.347]). These findings support radiological density as a key predictor of surgical outcomes across different populations (1\u0026ndash;3).\u003c/p\u003e\u003cp\u003eFurthermore, an increased risk of reoperation was observed (RR: 8.803 [95% CI: 2.795\u0026ndash;12.724]), suggesting that fat infiltration of muscle may interfere with tissue recovery mechanisms or promote complications such as bleeding, leakage, or infections requiring additional surgery. Similarly, the risk of hospital readmission in these patients was six times higher compared to patients without radiological sarcopenia (RR: 6.185 [95% CI: 1.595\u0026ndash;6.749]), highlighting a clinical, economic, and logistical impact on healthcare systems.\u003c/p\u003e\u003cp\u003eSurgical site infection (SSI) rates were also higher in patients with radiological sarcopenia based on myosteatosis (RR: 3.869 [95% CI: 1.878\u0026ndash;7.970]). This finding is consistent with previous studies associating intramuscular fat infiltration with reduced tissue perfusion, local immune dysfunction, and an impaired inflammatory response (14)(15). Additionally, radiological sarcopenia established by myosteatosis has been associated in prior studies with chronic pro-inflammatory states and anabolic resistance, factors that compromise the body's ability to tolerate surgical stress and may help explain the increased rate of adverse events after colorectal cancer surgery (16).\u003c/p\u003e\u003cp\u003eWhile the findings are clinically relevant, certain limitations should be noted. The study was conducted at a single center, which may affect the generalizability of the results to the general population. In addition, the cohort included a higher proportion of male patients, which may introduce a degree of sex-based bias. Future research should consider sex-stratified analyses or studies specifically designed to explore sex-related differences in outcomes.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eAmong the risk factors analyzed, myosteatosis is the most significant predictor of anastomotic leakage and severe complications in patients undergoing colorectal cancer surgery. Preoperative identification of myosteatosis as part of the nutritional assessment of surgical patients may facilitate to establish the clinically relevant diagnosis of radiological sarcopenia, offering a more practical, fast, simple, and reproducible evaluation of specific postoperative risk in this population. With high sensitivity\u0026mdash;especially in predicting anastomotic leakage using the \u0026le;\u0026thinsp;44 HU threshold\u0026mdash;it can serve as a valuable preoperative marker, potentially more effective than the MUST scale in guiding perioperative patient management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eETHICS DECLARATIONS\u003c/p\u003e\n\u003cp\u003eConflict of interest\u003c/p\u003e\n\u003cp\u003eThe authors did not receive support from any organisation for the submitted work. The authors declare they have no financial interests. The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for this study.\u003c/p\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eApproval was obtained from the ethics committee of our hospital. The procedures used in this study adhere to the tenets of the Declaration of Helsinki. The Approval No. was CHUC_23_203.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eDatasets is presented in the main manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThe Relation Between Malnutrition Universal Screening Tool (MUST), Computed Tomography-Derived Body Composition, Systemic Inflammation, and Clinical Outcomes in Patients Undergoing Surgery for Colorectal Cancer. Almasaudi AS, McSorley ST, Dolan RD, Edwards CA, McMillan DC.The American Journal of Clinical Nutrition. 2019;110(6):1327-1334. doi:10.1093/ajcn/nqz230.\u003c/li\u003e\n\u003cli\u003eRadiologic Myosteatosis Predicts Major Complication Risk Following Esophagectomy for Cancer: A Multicenter Experience. Park JS, Colby M, Spencer J, et al.Journal of Gastrointestinal Surgery : Official Journal of the Society for Surgery of the Alimentary Tract. 2024;28(11):1861-1869. doi:10.1016/j.gassur.2024.09.002.\u003c/li\u003e\n\u003cli\u003eDolan RD, Almasaudi AS, Dieu LB, Horgan PG, McSorley ST, McMillan DC. The relationship between computed tomography-derived body composition, systemic inflammatory response, and survival in patients undergoing surgery for colorectal cancer. J Cachexia Sarcopenia Muscle. 2019 Feb;10(1):111-122. doi: 10.1002/jcsm.12357. Epub 2018 Nov 20. PMID: 30460764; PMCID: PMC6438413.\u003c/li\u003e\n\u003cli\u003eAssessment of Computed Tomography (CT)-Defined Muscle and Adipose Tissue Features in Relation to Short-Term Outcomes After Elective Surgery for Colorectal Cancer: A Multicenter Approach. Martin L, Hopkins J, Malietzis G, et al.Annals of Surgical Oncology. 2018;25(9):2669-2680. doi:10.1245/s10434-018-6652-x.\u003c/li\u003e\n\u003cli\u003eSarcopenia Determined by Skeletal Muscle Index Predicts Overall Survival, Disease-Free Survival, and Postoperative Complications in Resectable Esophageal Cancer: A Systematic Review and Meta-Analysis.\u003c/li\u003e\n\u003cli\u003eAssociation Between Two Muscle-Related Parameters and Postoperative Complications in Patients Undergoing Colorectal Tumor Resection Surgery. Gao D, Miao H, Sheng W, et al.Anesthesia and Analgesia. 2024;:00000539-990000000-01028. doi:10.1213/ANE.0000000000007301.\u003c/li\u003e\n\u003cli\u003eObesity, Inflammation, and Cancer. Deng T, Lyon CJ, Bergin S, Caligiuri MA, Hsueh WA. Annual Review of Pathology. 2016;11:421-49. doi:10.1146/annurev-pathol-012615-044359.\u003c/li\u003e\n\u003cli\u003eCornier MA, Despr\u0026eacute;s JP, Davis N, et al. Assessing Adiposity: A Scientific Statement From the American Heart Association. Circulation. 2011;124(18):1996-2019. doi:10.1161/CIR.0b013e318233bc6a.\u003c/li\u003e\n\u003cli\u003eBozzetti F. Evolving Concepts on Perioperative Nutrition of Sarcopenic Cancer Patients. European Journal of Surgical Oncology : The Journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology. 2024;50(5):106748. doi:10.1016/j.ejso.2022.10.008.\u003c/li\u003e\n\u003cli\u003eHerrod PJJ, Boyd-Carson H, Doleman B, Trotter J, Schlichtemeier S, Sathanapally G, Somerville J, Williams JP, Lund JN. Quick and simple; psoas density measurement is an independent predictor of anastomotic leak and other complications after colorectal resection. Tech Coloproctol. 2019 Feb;23(2):129-134. doi: 10.1007/s10151-019-1928-0. Epub 2019 Feb 21. PMID: 30790102; PMCID: PMC6441102.\u003c/li\u003e\n\u003cli\u003eNIH ImageJ. (2025). Tutorial: A step-by-step guide (version 2.0) for measuring abdominal circumference and skeletal muscle from a single cross-sectional computed-tomography image using the National Institutes of Health ImageJ. National Institutes of Health. Recuperado de https://imagej.nih.gov/ij\u003c/li\u003e\n\u003cli\u003eClavien, P.A., et al. \u0026quot;A classification of surgical complications. Surgical complications.\u0026quot; Annals of Surgery, 2004; 240(2): 205-213.\u003c/li\u003e\n\u003cli\u003eYang J, Guo G, Yang F, et al. A Sex-Oriented Analysis Concerning Skeletal Muscle Quantity and Quality and Associations to Quality of Life in Hospitalized Patients With Cirrhosis. Health and Quality of Life Outcomes. 2024;22(1):78. doi:10.1186/s12955-024-02295-2.\u003c/li\u003e\n\u003cli\u003eMontano-Loza AJ, Angulo P, Meza-Junco J, Prado CM, Sawyer MB, Beaumont C, et al. Sarcopenic obesity and myosteatosis are associated with higher mortality in patients with cirrhosis. J Cachexia Sarcopenia Muscle. 2016;7(2):126\u0026ndash;135. doi:10.1002/jcsm.12039\u003c/li\u003e\n\u003cli\u003eLooijaard WGPM, Mullie L, Van Vught LA, Molinger J, Bosmans J, Peelen LM, et al. Low muscle quality is associated with increased hospital length of stay in critically ill patients. Crit Care. 2018;22(1):342. doi:10.1186/s13054-018-2297-4.\u003c/li\u003e\n\u003cli\u003eReisinger KW, van Vugt JLA, Tegels JJW, Snijders C, Hulsew\u0026eacute; KWE, Hoofwijk AGM, et al. Functional compromise reflected by sarcopenia, frailty, and nutritional depletion predicts adverse postoperative outcome after colorectal cancer surgery. \u003cem\u003eAnn Surg\u003c/em\u003e. 2015;261(2):345\u0026ndash;352. doi:10.1097/SLA.0000000000000628.\u003c/li\u003e\n\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":"international-journal-of-colorectal-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijcd","sideBox":"Learn more about [International Journal of Colorectal Disease](http://link.springer.com/journal/384)","snPcode":"384","submissionUrl":"https://submission.nature.com/new-submission/384/3","title":"International Journal of Colorectal Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Myosteatosis, Myopenia, MUST, Subcutaneous adipose tissue, Anastomotic dehiscence, Radiological sarcopenia, Colorectal cancer, Postoperative complications","lastPublishedDoi":"10.21203/rs.3.rs-8118549/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8118549/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eINTRODUCTION\u003c/h2\u003e\u003cp\u003eMyosteatosis, myopenia, the Malnutrition Universal Screening Tool (MUST), and the amount of subcutaneous adipose tissue have been identified as significant risk factors for postoperative complications in patients with colorectal cancer. However, cut-off points to predict anastomotic dehiscence and severe complications have not been established.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e\u003cp\u003eA prospective study was carried out in patients undergoing resection of colorectal tumors with anastomosis between June 2022 and November 2024. The MUST score, average psoas density, muscle mass, and amount of subcutaneous tissue at the L3 level on computed tomography (CT) were documented. Anastomotic dehiscence and severe postoperative complications according to the Clavien-Dindo (CD) classification were recorded.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e\u003cp\u003eA total of 250 patients were included. Only myosteatosis showed a statistically significant association with the occurrence of severe complications (AUC: 0.788; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and anastomotic dehiscence (AUC: 0.881; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) on ROC curves. Additionally, myosteatosis was significantly associated with postoperative complications (RR: 3.448, 95% CI: 2.695\u0026ndash;4.347, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and severe complications (RR: 7.88, 95% CI: 4.27\u0026ndash;14.59, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) before hospital discharge.\u003c/p\u003e\u003ch2\u003eCONCLUSIONS\u003c/h2\u003e\u003cp\u003eMyosteatosis, assessed through radiologic density on preoperative CT imaging, is a significant predictor of severe postoperative complications (CD\u0026thinsp;\u0026ge;\u0026thinsp;III) in colorectal cancer patients, as well as anastomotic dehiscence. Identifying myosteatosis may help clinicians recognize high perioperative risk patients early and improve preoperative planning.\u003c/p\u003e","manuscriptTitle":"Comparison of Myosteatosis, Myopenia, Must Tool and Subcutaneous Adipose Tissue as Risk Factors for Anastomotic Leak in Patients with Colorectal Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-11 14:42:14","doi":"10.21203/rs.3.rs-8118549/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-21T07:11:41+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"113613325346981392275244463551005125236","date":"2025-12-17T03:44:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-14T14:48:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216095845744200761747028229171251131159","date":"2025-12-13T04:24:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11560978678706502762399653663826765236","date":"2025-12-08T19:50:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-08T19:35:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-18T08:38:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-18T03:32:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Colorectal Disease","date":"2025-11-14T23:56:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-colorectal-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijcd","sideBox":"Learn more about [International Journal of Colorectal Disease](http://link.springer.com/journal/384)","snPcode":"384","submissionUrl":"https://submission.nature.com/new-submission/384/3","title":"International Journal of Colorectal Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e5415a34-69e2-4606-b348-740f08fe95b8","owner":[],"postedDate":"December 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T06:39:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-11 14:42:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8118549","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8118549","identity":"rs-8118549","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}