Body composition analysis using CT at three aspects of the lumbar third vertebra and its impact on the diagnosis of sarcopenia

Body composition analysis using CT at three aspects of the lumbar third vertebra and its impact on the diagnosis of sarcopenia | 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 Body composition analysis using CT at three aspects of the lumbar third vertebra and its impact on the diagnosis of sarcopenia Hui Yang, Huaiqing Zhi, Qingzheng Shen, Zekan Gao, Wentao Cai, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4045367/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Feb, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted 10 You are reading this latest preprint version Abstract Purpose The European Working Group on Sarcopenia in Older People (EWGSOP) revised the consensus in 2018, including that using computed tomography (CT) imaging of the lumbar third vertebra (L3) for the evaluation of muscle mass. However, there is currently discrepancy and confusion in the application of specific cross-sectional and cutoff values for L3. This study aimed to standardize the diagnosis of low muscle mass using L3-CT. Materials and Methods This study included patients who underwent radical gastrectomy for gastric cancer between July 2014 and February 2019. Sarcopenia factors were measured preoperatively. Patients were followed up to obtain actual clinical outcomes. We used the cutoff values obtained based on the inferior aspect of L3-CT images to diagnose sarcopenia in three aspects, respectively. Univariate and multivariate analyses were used to compare long-term and short-term postoperative prognostic differences. Results Sarcopenia was found to be an independent risk factor for postoperative complications and overall survival in patients with all three diagnoses of sarcopenia. According to the multivariate model for predicting postoperative complications, patients with inferior-L3 sarcopenia had a greater odds ratio (OR) than patients with superior-L3 sarcopenia or transverse-L3 sarcopenia did (OR, inferior sarcopenia vs. superior sarcopenia, transverse sarcopenia, 2.030 vs. 1.608, 1.679). Furthermore, patients with inferior-L3 sarcopenia had the highest hazard ratio (HR) (HR, inferior sarcopenia vs. superior sarcopenia, transverse sarcopenia, 1.491 vs. 1.408, 1.376) in the multivariate model for predicting overall survival. Conclusion We recommend that when diagnosing low muscle mass using L3-CT, the intercepted cross section should be uniform and consistent with the aspect on which the cutoff value is based. Sarcopenia Gastric cancer Muscle quantity Lumbar third vertebra Computed tomography Figures Figure 1 Figure 2 Figure 3 Introduction Sarcopenia is a syndrome characterized by a progressive decrease in skeletal muscle mass, strength, and physical performance with aging.[ 1 ] Both the European Working Group on Sarcopenia in Older People (EWGSOP) and the Asian Working Group for Sarcopenia (AWGS) have clarified the diagnosis of skeletal muscle strength, including convenient measurement methods and corresponding cutoff values.[ 2 , 3 ] However, the diagnostic method for skeletal muscle mass has certain limitations, as its measurement methods, such as dual-energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA), are not easily available in clinical practice. Additionally, the accuracy of DXA and BIA measurements depends largely on the accuracy of the equipment equations and evaluation conditions, such as temperature, humidity, and skin conditions. Therefore, there is a need for more convenient, accessible, and accurate methods for diagnosing muscle mass. Since the gold standard for skeletal muscle mass is derived from whole-body computed tomography (CT)[ 4 ], in clinical practice, the whole body of a patient is rarely scanned. Thus, we generally adopt the aspect of muscle area on CT to reflect whole-body muscle mass.[ 5 , 6 ] The skeletal muscle area (SMA) of the thoracic 12th vertebra CT imaging and lumbar 3rd vertebra (L3) CT imaging have been widely applied to evaluate muscle mass in sarcopenia patients, and their correlation with whole-body muscle mass has been confirmed by several studies.[ 7 – 11 ] Gastric cancer is the fifth most common malignancy and the fourth leading cause of cancer-related death worldwide and is mainly treated by curative gastrectomy.[ 12 ] Several studies have found that sarcopenia is an independent risk factor for postoperative complications and overall survival in patients with gastric cancer.[ 13 – 17 ] Patients with gastric cancer routinely undergo preoperative CT of the abdomen to assess gastric cancer staging. Thus, the SMA can be measured via L3-CT imaging without additional examinations to facilitate the clinical assessment of sarcopenia. Several research teams have used different L3-CT imaging cross-sections to diagnose skeletal muscle mass. Carey et al. used the superior aspect[ 18 ], Martin et al. intercepted the transverse aspect[ 19 ], and Zhuang et al. used the inferior aspect as the foundation for their diagnoses[ 14 ]. Moreover, certain teams lack precise representations of the chosen cross-sections,[ 20 ] while others have intercepted aspects that utilize the cutoffs of other teams that are inconsistent with the aspect from which the cutoff originates.[ 15 , 21 , 22 ] This study compared data, including muscle area, on three aspects of L3-CT imaging and compared prognostic differences in the diagnosis of sarcopenia for the first time using different L3-CT imaging aspects. Materials and Methods Patients This study was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University. All patients who underwent radical gastrectomy for gastric cancer in the Department of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, between July 2014 and February 2019 were included in this study. The inclusion criteria were as follows: (1) planned to undergo gastrectomy with curative intent for gastric cancer; (2) had preoperative abdominal CT available for review (no more than 1 month prior to surgery); and (3) agreed to participate in this study and signed an informed consent form. The exclusion criteria included (1) having physical deformities that prevented them from performing muscle strength or physical fitness tests and (2) those who underwent palliative surgery. All patients were routinely managed according to the 2010 Japanese Gastric Cancer Treatment Guidelines (ver. 3)[ 23 ]. All procedures were performed by experienced surgeons who independently performed > 200 standard gastric cancer surgeries. Follow-up All patients were followed up within 1 month of surgery. Thereafter, patients were followed-up every 3 months for 2 years, every 6 months thereafter for up to 5 years, and every 1 year thereafter. Patients were contacted by telephone and scheduled to return to the hospital at the aforementioned time points to complete the follow-up program. The follow-up schedule included laboratory tests, ultrasound, computed tomography (CT), or endoscopy. The final follow-up date was November 2021. Assessment of the skeletal muscle index All patients underwent routine preoperative abdominal computed tomography. As shown in Fig. 1 , L3-CT images of the superior, transverse, and inferior aspects was intercepted from the Picture Archiving and Communication System. According to the EWGSOP, we used skeletal muscle area to represent skeletal muscle mass.[ 2 ] ImageJ (National Institutes of Health, Bethesda, MD, USA, 1.52v) was used to assess the skeletal muscle area using particular Hounsfield Unit (HU) criteria of -29 to 150. As needed, tissue boundaries were manually drawn for each of the three aspects. Muscle area was normalized by height squared and reported as the skeletal muscle index (SMI, cm 2 /m 2 ). Muscle strength and physical performance Preoperative grip strength and a usual gait speed of 6 m were measured according to the EWGSOP and AWGS definitions of sarcopenia to separately determine the muscle strength and physical performance of each patient. Patients were tested for preoperative grip strength using an electronic hand dynamometer (EH101; Camry Electronics Co., Ltd., Zhongshan, Guangdong, China) with a dominant hand squeeze. The time between the first and last steps over 6 m was used to measure the usual gait speed. Both parameters were measured within 7 days preoperatively, and the maximum value of three repeated tests was recorded. The diagnosis of sarcopenia Patients with low skeletal muscle mass, low muscle strength, and/or low physical performance were considered to have sarcopenia, as defined by the EWGSOP and the AWGS. In this study, sarcopenia was diagnosed as follows: (1) low muscle mass (L3 skeletal muscle index (SMI) ≤ 40.8 cm 2 /m 2 in males and ≤ 34.9 cm 2 /m 2 in females)[ 2 , 14 ]; (2) low muscle strength (grip strength < 28 kg in males and < 18 kg in females)[ 3 ]; and (3) low muscle performance (6 m usual gait speed < 1 m/s)[ 3 ]. The cutoff value was based on the inferior aspect of the L3-CT image. Sarcopenia diagnosed in the muscle area from the superior aspect of L3-CT images was referred to as superior sarcopenia, the transverse aspect of L3-CT imaging as transverse sarcopenia, and the inferior aspect of L3-CT images was considered inferior sarcopenia. Data collection For each patient enrolled in this study, the following data were prospectively collected: (1) preoperative patient characteristics, including age, sex, body mass index (BMI), and Charlson comorbidity index; (2) surgical details, including laparoscopic-assisted surgery, combined organ resection, type of resection, and operative time; and (3) postoperative outcomes, including tumor pathological features and postoperative complications (within 30 days postsurgery). Analysis The agreement of SMA and SMI among the three aspects of L3-CT was calculated using the Wilcoxon rank sum test, and the agreement among the three diagnoses of sarcopenia was analyzed using kappa tests. Student’s t test was used to compare continuous normally distributed data, and the Mann‒Whitney U test was applied to continuous nonnormally distributed data. Categorical data were compared using the chi-square test or Fisher's exact test. Univariate analysis was used to assess the relationships between categorical variables. Univariate Cox proportional hazards models with all potential baseline predictors were constructed to calculate risk ratios (HR) and 95% CI. Variables with a trend (P < 0.05) in the univariate analysis were selected, and multivariate logistic regression or Cox proportional risk models were constructed using forward stepwise variable selection. The Kaplan‒Meier method was used to estimate survival curves, and the log-rank test was used to compare the data. The data analysis was performed using the statistical package IBM SPSS Statistics software (SPSS) version 25.0. Results Comparison of body composition data at three L3 aspects We divided all patients into two groups according to sex, and the SMA and SMI of males and females according to the three aspects are summarized in Table 1. As shown, there were significant differences in the SMA and SMI between these three dimensions for both men and women, all with increases from top to bottom. All three aspects remained highly correlated between the two aspects for both sexes (superior aspect vs. transverse aspect: SMA-R 2 =0.956; SMI-R 2 =0.935; transverse aspect vs. inferior aspect: SMA-R 2 =0.952; SMI-R 2 =0.930; inferior aspect vs. superior aspect: SMA-R 2 =0.924; and SMI-R 2 =0.887). Overall male female Median (range) R 2 Median (range) R 2 Median (range) R 2 Superior aspect 114.5 (60.9-189.7) 0.956 b 122.6 (76.4-189.7) a,b 0.924 b 89.0 (60.9-142.6) a,b 0.909 b SMA Transverse aspect 117.2 (59.7-199.4) 0.952 c 126.5 (78.9-199.4) a,c 0.914 c 91.8 (59.7-142.4) a,c 0.917 c Inferior aspect 120.1 (64.0-197.3) 0.924 d 129.7 (78.2-197.3) a,d 0.869 d 92.8 (64.0-153.5) a,d 0.840 d Superior aspect 42.7 (24.7-66.7) 0.935 b 44.3 (26.9-66.7) a,b 0.915 b 36.1 (24.7-53.0) a,b 0.895 b SMI Transverse aspect 43.7 (24.3-70.6) 0.930 c 45.8 (27.5-70.6) a,c 0.903 c 37.0 (24.3-52.9) a,c 0.902 c Inferior aspect 44.8 (25.0-70.1) 0.887 d 46.6 (27.5-70.1) a,d 0.854 d 38.4 (25.0-57.0) a,d 0.813 d Table 1. SMA (cm 2 ) and SMI (cm 2 /m 2 ) measurements of three aspects of L3-CT and the coefficient of determination between adjacent aspects. SMA, skeletal muscle area; SMI, skeletal muscle index a Statistically significant. b Comparison between superior aspect and transverse aspect c Comparison between the transverse aspect and the inferior aspect d Comparison between superior aspect and inferior aspect Diagnostic consistency of three aspects of L3 We considered inferior sarcopenia the gold standard. As shown in Table 2 and Figure 2, the sensitivity of the superior aspect was 0.955, the specificity was 0.924, and the AUC value was 0.939. The sensitivity of the transverse aspect was 0.941, the specificity was 0.949, and the AUC value was 0.945, which suggests that the diagnosis of the transverse aspect and the superior aspect had a high degree of agreement with that of the inferior aspect. The kappa value for the transverse aspect was 0.803, and the kappa value for the superior aspect was 0.745; both of these factors also showed a high degree of consistency compared to that of the inferior aspect. Inferior aspect Transverse aspect superior aspect Normal sarcopenia Normal sarcopenia Normal 913 49 899 73 sarcopenia 9 145 7 147 Table 2. The concordance and discrepancy of diagnosis of the three aspects. The data are expressed as the number of patients. Sensitivity at the transverse aspect = 0.941; specificity = 0.949 The sensitivity at the superior aspect = 0.955, specificity = 0.924 Population heterogeneity in three types of sarcopenia As shown in Table 3, the prevalence of superior sarcopenia, transverse sarcopenia, and inferior sarcopenia were 19.7%, 17.4%, and 13.8%, respectively, which revealed that the superior and transverse aspects were used to screen more patients with sarcopenia than was the inferior aspect. However, there were no significant differences in hospitalization costs (superior sarcopenia vs. inferior sarcopenia, p=0.622; transverse sarcopenia vs. inferior sarcopenia, p=0.511), postoperative hospitalization time (superior sarcopenia vs. inferior sarcopenia, p=0.335; transverse sarcopenia vs. inferior sarcopenia, p=0.255), or other indicators between superior sarcopenia and transverse sarcopenia with inferior sarcopenia. Thus, we divided the patients into superior sarcopenia and transverse sarcopenia groups and found that patients with superior sarcopenia and without inferior sarcopenia, both men and women, had slightly higher SMI compared with those with inferior sarcopenia; moreover, their hospitalization cost was reduced by approximately 10%, and their overall hospitalization time was shortened by one day. Furthermore, patients with transverse sarcopenia without inferior sarcopenia had a slightly greater SMI in both men and women, compared with those with inferior sarcopenia, and while women with transverse sarcopenia without inferior sarcopenia had a slightly greater BMI than did those with inferior sarcopenia. Factors superior aspect Transverse aspect Inferior aspect Superior Sarcopenia b Superior sarcopenia alone b Transverse Sarcopenia b Transverse sarcopenia alone b Inferior sarcopenia c Normal b number 220 a 73 194 a,b 49 154 962 Age, mean (SD), (years) 71(11) 70(12) 72(11) 72(11) 72(12) 64(14) gender(males) 142(64.5%) 51(69.9%) 123(63.4%) 33(67.3%) 95(61.7%) 722(75.1%) BMI, mean (SD), (kg/m 2 ) Total 20.7(2.4) 21.1(2.4) a 20.7(2.4) 21.3(2.3) a 20.5(5.8) 22.9(3.0) male 20.7(2.3) 20.9(1.9) 20.5(2.4) 22.1(2.7) 20.4(2.5) 22.9(2.9) female 20.8(2.5) 21.5(3.3) 21.0(2.2) 21.0(2.1) a 20.6(2.2) 23.2(3.2) SMI, median (IQR), (cm 2 /m 2 ) total 34.8(6.2) 38.3(5.5) a 34.8(5.6) 38.6(6.0) a 34.9(6.1) 45.9(8.3) male 37.7(4.5) 39.7(2.1) a 37.6(4.4) 39.8(1.9) a 38.2(3.7) 48.0(7.5) female 31.4(4.1) 33.8(1.7) a 32.2(3.3) 34.2(1.2) a 32.5(3.0) 39.7(5.7) Tumor size, median (IQR), (cm) 4(3.5) 4(3.5) 4(3.3) 3.5(3.6) 4(3.5) 3(3) TNM stage I 66 25 57 17 45 360 II 52 11 47 6 42 194 III 102 37 90 26 67 408 hospitalization time, median (IQR), (days) 14(9) 13(6) a 14(10) 13(7) 14(10) 13(6) Hospitalization expenses, median (IQR), (¥) 63835 (25752) 59275 (21122) a 64333 (25198) 60158 (16415) a 65869 (30724) 57928 (21176) Table 3. Comparisons among patients with superior sarcopenia, transverse sarcopenia and inferior sarcopenia. The data are expressed as the number of patients unless indicated otherwise. BMI, body mass index; SMI, skeletal muscle index; SD, standard deviation; IQR, interquartile range; Superior sarcopenia alone, exclusion of patients with inferior sarcopenia from those with superior sarcopenia; Transverse sarcopenia alone, exclusion of patients with inferior sarcopenia from those with transverse sarcopenia a Statistically significant, P <0.05 b Compared with inferior sarcopenia patients. c Compared with normal. Short-term postoperative complications We evaluated postoperative complications that occurred within 30 days after gastrectomy and graded the complications according to the Clavien system[24], including those of Grade II or higher. The results of the univariate and multivariate analyses of the predictors of postoperative complications are presented in Table 4. The univariate analysis showed that advanced age, superior sarcopenia, transverse sarcopenia, inferior sarcopenia, Charlson Comorbidity Index, TNM staging, combined organ removal, and open surgery were risk factors for postoperative complications. The multivariate analysis showed a higher dominance ratio for inferior sarcopenia (OR=2.030, p<0.001) than for superior sarcopenia (OR= 1.608, p=0.005) and transverse sarcopenia (OR=1.679, p=0.004). Factors Univariate analysis Multivariate analysis Superior sarcopenia Transverse sarcopenia Inferior sarcopenia OR (95%CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P Age <0.001 a 0.011 a 0.014 a 0.019 a ≥75/25/<25 0.999(0.711-1.405) Superior sarcopenia <0.001 a 0.006 a Yes/No 1.852(1.348-2.543) 1.608(1.145-2.257) Transverse sarcopenia <0.001 a 0.004 a Yes/No 1.989(1.431-2.764) 1.679(1.180-2.389) Inferior sarcopenia <0.001 a <0.001 a Yes/No 2.335(1.638-3.329) 2.030(1.389-2.968) Charlson Comorbidity Index 1/0 1.521(1.104-2.097) 0.010 a 1.439(1.033-2.004) 0.031 a 1.424(1.023-1.984) 0.036 a 1.446(1.037-2.017) 0.030 a ≥2/0 2.587(1.810-3.696) <0.001 a 2.410(1.664-3.491) <0.001 a 2.407(1.662-3.488) <0.001 a 2.446(1.687-3.547) <0.001 a Histologic type 0.339 Undifferentiated/differentiated 0.875(0.667-1.150) TNM stage II/I 1.878(1.296-2.719) 0.001 a III/I 1.613(1.174-2.218) 0.003 a Type of resection 0.021 a Total/Subtotal 1.380(1.049-1.816) Combined resection 0.002 a 0.032 a 0.030 a 0.036 a Yes/No 2.067(1.302-3.281) 1.702(1.045-2.770) 1.718(1.055-2.798) 1.691(1.035-2.761) Laparoscopic surgery <0.001 a <0.001 a <0.001 a 4 hours 0.528 Yes/No 0.908(0.671-1.227) Table 4. Univariate and multivariate logistic regression analyses for postoperative complications a Statistically significant. Long-term postoperative survival outcome The median postoperative follow-up period was 59 months. The 5-year survival rates were 66.2%, 65.9%, and 65.5% for patients with superior, transverse, and inferior sarcopenia, respectively. As shown in Figure 3, Kaplan‒Meier analysis revealed that overall survival (OS) (log-rank, superior sarcopenia, p=0.0015; transverse sarcopenia, p=0.0024; inferior sarcopenia, p=0.003) was significantly shorter in patients with sarcopenia than in those without sarcopenia, regardless of the aspect-based diagnosis of sarcopenia. As shown in Table 5, multivariate Cox models showed that inferior sarcopenia (HR=1.491, p=0.004), histologic type, TNM staging, and resection type were independently associated with poorer overall survival. When using superior sarcopenia (HR=1.408, p=0.005) or transverse sarcopenia (HR=1.376, p=0.012) instead of inferior sarcopenia, the inclusion of sarcopenia remained in the multifactorial model. Compared to those of inferior sarcopenia, the risks of superior sarcopenia and transverse sarcopenia appeared to be lower. Factors Univariate analysis Multivariate analysis Superior sarcopenia Transverse sarcopenia Inferior sarcopenia HR (95% CI) P HR (95% CI) P HR (95% CI) P HR (95% CI) P Age <0.001 a ≥75/25/<25 0.854(0.654-1.114) Superior sarcopenia 0.002 a 0.005 a Yes/No 1.463(1.153-1.857) 1.408(1.109-1.788) Transverse sarcopenia 0.003 a 0.012 a Yes/No 1.460(1.139-1.872) 1.376(1.073-1.766) Inferior sarcopenia 0.004 a 0.004 a Yes/No 1.494(1.139-1.959) 1.491(1.135-1.959) Charlson Comorbidity Index 1/0 1.236(0.977-1.562) 0.077 ≥2/0 1.211(0.911-1.619) 0.187 Histologic type <0.001 a 0.002 a 0.002 a 0.003 a Undifferentiated/differentiated 1.824(1.477-2.251) 1.396(1.127-1.729) 1.395(1.126-1.728) 1.387(1.119-1.718) TNM stage II/I 2.517(1.712-3.700) <0.001 a 2.172(1.471-3.206) <0.001 a 2.169(1.469-3.203) <0.001 a 2.139(1.448-3.161) <0.001 a III/I 7.071(5.152-9.705) <0.001 a 5.623(4.052-7.804) <0.001 a 5.640(4.064-7.926) <0.001 a 5.657(4.078-7.848) <0.001 a Type of resection <0.001 a <0.001 a <0.001 a <0.001 a Total/Subtotal 2.088(1.703-2.560) Combined resection 0.001 a Yes/No 1.732(1.243-2.414) Laparoscopic surgery 4 hour 0.327 Yes/No 1.118(0.895-1.396) Table 5. Univariate and multivariate analyses for predictors of overall survival a Statistically significant. Discussion This study compared skeletal muscle area among three aspects of L3-CT imaging and investigated, for the first time, the differences in predicting patient prognosis caused by the diagnosis of sarcopenia using muscle data obtained from different aspects of L3-CT imaging. This study showed that the SMA and the SMI increased sequentially from the top to the bottom of the L3-CT image. However, there was a high correlation among these three aspects, and the results were consistent with those of previous studies.[ 25 ] For this reason, more patients were diagnosed with sarcopenia in a descending sequence, from top to bottom, with more patients diagnosed with sarcopenia in the superior and transverse aspects than in the inferior aspect. Overall, there was high agreement in the diagnosis of the three aspects (superior sarcopenia vs. inferior sarcopenia, kappa value = 0.745, p < 0.001; transverse sarcopenia vs. inferior sarcopenia, kappa value = 0.803, p < 0.001). There were also significant differences in the SMA and SMI among the three aspects, with a certain consistency in diagnosis. Therefore, further analysis is needed to clarify whether this difference impacts the prediction of clinical outcomes. Several studies have shown that patients with sarcopenia have higher hospitalization costs[ 26 ], longer hospital stays[ 26 ], and shorter postoperative survival[ 14 ] than patients without sarcopenia, in agreement with the findings of our study. We found no significant differences in postoperative length of stay and hospitalization costs among the three sarcopenia populations. After further splitting the patients into superior sarcopenia and transverse sarcopenia cohorts, patients with superior sarcopenia alone (negative for inferior sarcopenia) had a greater SMI in both sexes than did those with inferior sarcopenia. Patients in these groups also spent less on hospitalization than patients with inferior sarcopenia and had a slightly shorter length of postoperative hospitalization, while patients with transverse sarcopenia alone (negative for inferior sarcopenia) had the same SMI and postoperative hospitalization cost as patients with superior sarcopenia alone. Previous studies have revealed that a low SMI can be used as an independent risk factor for predicting postoperative length of stay[ 27 ], cost[ 28 ], complications[ 29 ] and long-term prognosis[ 30 ], whereas patients with a high SMI have been found to have a better postoperative prognosis. This may partially explain the relatively better length of stay and cost performance of patients with superior sarcopenia and transverse sarcopenia. Further analysis of postoperative complications revealed that inferior sarcopenia had the best predictive ability (superior sarcopenia, OR = 1.608; transverse sarcopenia, OR = 1.769; inferior sarcopenia, OR = 2.030). According to our analysis of long-term survival, inferior sarcopenia appeared to retain high predictive power for survival (superior sarcopenia, HR = 1.408; transverse sarcopenia, HR = 1.376; inferior sarcopenia, HR = 1.491). Taken together, these findings showed that patients with superior and transverse sarcopenia had relatively high SMI, as described previously. This was perhaps because the superior and transverse sarcopenia cohort included more patients with suspected sarcopenia, for whom the short- and long-term prognostic performance was slightly better than that of patients with inferior sarcopenia. This has led to superior and transverse sarcopenia to present a relatively low risk predictive ability in prognostic predictions. At the root of this, despite the high correlation of SMA between the three aspects, differences remain in SMA values. We uniformly used a cutoff that was obtained according to the L3 inferior aspect as the basis for the diagnosis of low SMI in this study, and applying this cutoff to the superior aspect and transverse aspect may be the underlying cause of this difference. In this study, we explored in detail the diagnosis of low muscle mass in patients with sarcopenia and found that when using a uniform cutoff at the inferior aspect, it may be possible that a lower SMI at the superior and transverse aspects, compared to the inferior aspect screened out more critical patients with suspected sarcopenia, which is clearly detrimental to the predictive power of the model. We recommend that when diagnosing low SMI, the aspect of interception should be uniform and consistent with the aspect of the truncation values. Since it has the potential to be incorporated into risk-scoring systems for postoperative prognosis and to improve clinical decision-making in patients, this study of patients with gastric cancer emphasizes the need for a standardized assessment of sarcopenia. This study has several limitations. First, this was a single-center study, and a larger multicenter study is needed to validate our findings. In addition, although we clarified that the cutoff value should be consistent with the intercept, whether a specific aspect of L3 selection would yield a better prognostic value remains unclear. Declarations Ethics approval and consent to participate The studies involving human participants were reviewed and approved by the Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding authors on reasonable request. Competing interests The authors declare that they have no competing interests Funding No funds were involved in this study. Authors' contributions W.Z, X.C and X.S. made substantial contributions to the conception and design of the study. H.Y., H.Q., Q.S. and Z.G. were involved in the collection and analysis of the data, H.Y. wrote the manuscript, and W.C. and X.W. provided final approval and revised the manuscript. All the authors read and approved the final manuscript. 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Sarcopenia is an Independent Predictor of Severe Postoperative Complications and Long-Term Survival After Radical Gastrectomy for Gastric Cancer: Analysis from a Large-Scale Cohort. Med (Baltim). 2016;95(13):e3164. Tegels JJW, van Vugt JLA, Reisinger KW, Hulsewé KWE, Hoofwijk AGM, Derikx JPM, et al. Sarcopenia is highly prevalent in patients undergoing surgery for gastric cancer but not associated with worse outcomes. J Surg Oncol. 2015;112(4):403–7. Fukuda Y, Yamamoto K, Hirao M, Nishikawa K, Nagatsuma Y, Nakayama T, et al. Sarcopenia is associated with severe postoperative complications in elderly gastric cancer patients undergoing gastrectomy. Gastric Cancer. 2016;19(3):986–93. Huang D-D, Zhou C-J, Wang S-L, Mao S-T, Zhou X-Y, Lou N, et al. Impact of different sarcopenia stages on the postoperative outcomes after radical gastrectomy for gastric cancer. Surgery. 2017;161(3):680–93. Carey EJ, Lai JC, Wang CW, Dasarathy S, Lobach I, Montano-Loza AJ, et al. A multicenter study to define sarcopenia in patients with end-stage liver disease. Liver Transpl. 2017;23(5):625–33. Martin L, Birdsell L, Macdonald N, Reiman T, Clandinin MT, McCargar LJ, et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol. 2013;31(12):1539–47. Takagi K, Yagi T, Yoshida R, Shinoura S, Umeda Y, Nobuoka D, et al. Sarcopenia and American Society of Anesthesiologists Physical Status in the Assessment of Outcomes of Hepatocellular Carcinoma Patients Undergoing Hepatectomy. Acta Med Okayama. 2016;70(5):363–70. Ebadi M, Wang CW, Lai JC, Dasarathy S, Kappus MR, Dunn MA, et al. Poor performance of psoas muscle index for identification of patients with higher waitlist mortality risk in cirrhosis. J Cachexia Sarcopenia Muscle. 2018;9(6):1053–62. Bhanji RA, Narayanan P, Moynagh MR, Takahashi N, Angirekula M, Kennedy CC, et al. Differing Impact of Sarcopenia and Frailty in Nonalcoholic Steatohepatitis and Alcoholic Liver Disease. Liver Transpl. 2019;25(1):14–24. Japanese gastric cancer treatment. guidelines 2010 (ver. 3). Gastric Cancer. 2011;14(2):113–23. Dindo D, Demartines N, Clavien P-A. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205–13. Schweitzer L, Geisler C, Pourhassan M, Braun W, Glüer C-C, Bosy-Westphal A, et al. What is the best reference site for a single MRI slice to assess whole-body skeletal muscle and adipose tissue volumes in healthy adults? Am J Clin Nutr. 2015;102(1):58–65. Lo Y-TC, Wahlqvist ML, Huang Y-C, Chuang S-Y, Wang C-F, Lee M-S. Medical costs of a low skeletal muscle mass are modulated by dietary diversity and physical activity in community-dwelling older Taiwanese: a longitudinal study. Int J Behav Nutr Phys Act. 2017;14(1):31. Giani M, Rezoagli E, Grassi A, Porta M, Riva L, Famularo S, et al. Low skeletal muscle index and myosteatosis as predictors of mortality in critically ill surgical patients. Nutrition. 2022;101:111687. Koter S, Cohnert TU, Hindermayr KB, Lindenmann J, Brückner M, Oswald WK, et al. Increased hospital costs are associated with low skeletal muscle mass in patients undergoing elective open aortic surgery. J Vasc Surg. 2019;69(4):1227–32. Ansari E, Chargi N, van Gemert JTM, van Es RJJ, Dieleman FJ, Rosenberg AJWP, et al. Low skeletal muscle mass is a strong predictive factor for surgical complications and a prognostic factor in oral cancer patients undergoing mandibular reconstruction with a free fibula flap. Oral Oncol. 2020;101:104530. Zheng Z-F, Lu J, Xie J-W, Wang J-B, Lin J-X, Chen Q-Y, et al. Preoperative skeletal muscle index vs the controlling nutritional status score: Which is a better objective predictor of long-term survival for gastric cancer patients after radical gastrectomy? Cancer Med. 2018;7(8):3537–47. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Feb, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted Editorial decision: Revision requested 07 May, 2024 Reviews received at journal 28 Apr, 2024 Reviews received at journal 22 Apr, 2024 Reviewers agreed at journal 14 Apr, 2024 Reviewers agreed at journal 13 Apr, 2024 Reviewers agreed at journal 27 Mar, 2024 Reviewers invited by journal 25 Mar, 2024 Editor assigned by journal 23 Mar, 2024 Submission checks completed at journal 13 Mar, 2024 First submitted to journal 08 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4045367","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278984764,"identity":"ab58c86c-cfb1-491d-bc94-96947dc7cd4d","order_by":0,"name":"Hui Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Yang","suffix":""},{"id":278984765,"identity":"34625ba4-784f-4add-abfb-420a4fc342f3","order_by":1,"name":"Huaiqing Zhi","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huaiqing","middleName":"","lastName":"Zhi","suffix":""},{"id":278984766,"identity":"744e639a-dfde-4810-99d1-96ca10eb5395","order_by":2,"name":"Qingzheng Shen","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qingzheng","middleName":"","lastName":"Shen","suffix":""},{"id":278984767,"identity":"4f939385-0e47-4533-9a83-dc043ef53b1e","order_by":3,"name":"Zekan Gao","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zekan","middleName":"","lastName":"Gao","suffix":""},{"id":278984768,"identity":"7e4e8104-076c-4dbc-8b1c-a438a6e3db9d","order_by":4,"name":"Wentao Cai","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wentao","middleName":"","lastName":"Cai","suffix":""},{"id":278984769,"identity":"57fd84e3-beeb-4926-a84e-f6e494bdb4ea","order_by":5,"name":"Xiang Wang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Wang","suffix":""},{"id":278984770,"identity":"44d08e7d-3bd8-4859-a315-938a85e4d9a9","order_by":6,"name":"Xiaodong Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaodong","middleName":"","lastName":"Chen","suffix":""},{"id":278984771,"identity":"ba097b11-ade0-46ac-897f-c6b8ef1948b7","order_by":7,"name":"Xian Shen","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xian","middleName":"","lastName":"Shen","suffix":""},{"id":278984772,"identity":"44e312cc-14a5-4818-8025-fec33c583ddd","order_by":8,"name":"Weiteng Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBACxgYQ8Yetnp+Z+eAD4rUcbOBLkGxnSzYg3qqDDXIJBud5zASIUs08I/2Z9McdZnnGhxnMGBhqbKIJO2xGQprEwTNpxWaHGdIeMBxLy20gQsuxGwfYjjFuO8xw3ICx4TAxWhLbgFr+M25uZmyTIFJLMtuNg21siRuYmdmI1NLzjP3HmTNsxhKH2ZgNEojxi2F7+mODigo2Of7+8x8ffKixIULLhAQkXgIOVShAnv8AMcpGwSgYBaNgRAMAGAlDxYbg+VIAAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Weiteng","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-03-08 14:17:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4045367/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4045367/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12957-024-03634-9","type":"published","date":"2025-02-26T15:58:16+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52787038,"identity":"73d128d9-10e2-4f35-be6e-bc6df3859160","added_by":"auto","created_at":"2024-03-15 18:55:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":293513,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram of CT image intercept levels of the superior(A), transverse(B) and inferior(C) aspects of L3.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4045367/v1/1d34eb70f3e5d62368c04d65.png"},{"id":52787001,"identity":"02352538-53f8-4e4c-beb5-6428dc65bb82","added_by":"auto","created_at":"2024-03-15 18:55:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":30234,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC curve of superior sarcopenia and transverse sarcopenia. (superior sarcopenia, AUC=0.939; transverse sarcopenia, AUC=0.945)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4045367/v1/771ccfd54f07b6f2af832a64.png"},{"id":52787032,"identity":"cc373934-b232-4b76-9452-c525ed9ee3ac","added_by":"auto","created_at":"2024-03-15 18:55:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":229173,"visible":true,"origin":"","legend":"\u003cp\u003eKaplaneMeier curves for overall survival in patients with and in those without sarcopenia (A, superior sarcopenia; B, transverse sarcopenia; C, Inferior sarcopenia). A, P = 0.0015; B, P = 0.0024; C, P=0.003(log rank test).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4045367/v1/89771a72e949628dd12bb360.png"},{"id":77622601,"identity":"e63b5c69-8d6d-4340-9251-454d504f1dc8","added_by":"auto","created_at":"2025-03-03 16:08:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2079332,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4045367/v1/7e73d4c5-42e0-44f6-8039-cd38f4584125.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Body composition analysis using CT at three aspects of the lumbar third vertebra and its impact on the diagnosis of sarcopenia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSarcopenia is a syndrome characterized by a progressive decrease in skeletal muscle mass, strength, and physical performance with aging.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Both the European Working Group on Sarcopenia in Older People (EWGSOP) and the Asian Working Group for Sarcopenia (AWGS) have clarified the diagnosis of skeletal muscle strength, including convenient measurement methods and corresponding cutoff values.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] However, the diagnostic method for skeletal muscle mass has certain limitations, as its measurement methods, such as dual-energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA), are not easily available in clinical practice. Additionally, the accuracy of DXA and BIA measurements depends largely on the accuracy of the equipment equations and evaluation conditions, such as temperature, humidity, and skin conditions. Therefore, there is a need for more convenient, accessible, and accurate methods for diagnosing muscle mass. Since the gold standard for skeletal muscle mass is derived from whole-body computed tomography (CT)[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], in clinical practice, the whole body of a patient is rarely scanned. Thus, we generally adopt the aspect of muscle area on CT to reflect whole-body muscle mass.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] The skeletal muscle area (SMA) of the thoracic 12th vertebra CT imaging and lumbar 3rd vertebra (L3) CT imaging have been widely applied to evaluate muscle mass in sarcopenia patients, and their correlation with whole-body muscle mass has been confirmed by several studies.[\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eGastric cancer is the fifth most common malignancy and the fourth leading cause of cancer-related death worldwide and is mainly treated by curative gastrectomy.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Several studies have found that sarcopenia is an independent risk factor for postoperative complications and overall survival in patients with gastric cancer.[\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Patients with gastric cancer routinely undergo preoperative CT of the abdomen to assess gastric cancer staging. Thus, the SMA can be measured via L3-CT imaging without additional examinations to facilitate the clinical assessment of sarcopenia.\u003c/p\u003e \u003cp\u003eSeveral research teams have used different L3-CT imaging cross-sections to diagnose skeletal muscle mass. Carey et al. used the superior aspect[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Martin et al. intercepted the transverse aspect[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and Zhuang et al. used the inferior aspect as the foundation for their diagnoses[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, certain teams lack precise representations of the chosen cross-sections,[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] while others have intercepted aspects that utilize the cutoffs of other teams that are inconsistent with the aspect from which the cutoff originates.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] This study compared data, including muscle area, on three aspects of L3-CT imaging and compared prognostic differences in the diagnosis of sarcopenia for the first time using different L3-CT imaging aspects.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003ePatients\u003c/p\u003e \u003cp\u003e This study was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University. All patients who underwent radical gastrectomy for gastric cancer in the Department of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, between July 2014 and February 2019 were included in this study. The inclusion criteria were as follows: (1) planned to undergo gastrectomy with curative intent for gastric cancer; (2) had preoperative abdominal CT available for review (no more than 1 month prior to surgery); and (3) agreed to participate in this study and signed an informed consent form. The exclusion criteria included (1) having physical deformities that prevented them from performing muscle strength or physical fitness tests and (2) those who underwent palliative surgery. All patients were routinely managed according to the 2010 Japanese Gastric Cancer Treatment Guidelines (ver. 3)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. All procedures were performed by experienced surgeons who independently performed\u0026thinsp;\u0026gt;\u0026thinsp;200 standard gastric cancer surgeries.\u003c/p\u003e \u003cp\u003eFollow-up\u003c/p\u003e \u003cp\u003eAll patients were followed up within 1 month of surgery. Thereafter, patients were followed-up every 3 months for 2 years, every 6 months thereafter for up to 5 years, and every 1 year thereafter. Patients were contacted by telephone and scheduled to return to the hospital at the aforementioned time points to complete the follow-up program. The follow-up schedule included laboratory tests, ultrasound, computed tomography (CT), or endoscopy. The final follow-up date was November 2021.\u003c/p\u003e \u003cp\u003eAssessment of the skeletal muscle index\u003c/p\u003e \u003cp\u003eAll patients underwent routine preoperative abdominal computed tomography. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, L3-CT images of the superior, transverse, and inferior aspects was intercepted from the Picture Archiving and Communication System. According to the EWGSOP, we used skeletal muscle area to represent skeletal muscle mass.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] ImageJ (National Institutes of Health, Bethesda, MD, USA, 1.52v) was used to assess the skeletal muscle area using particular Hounsfield Unit (HU) criteria of -29 to 150. As needed, tissue boundaries were manually drawn for each of the three aspects. Muscle area was normalized by height squared and reported as the skeletal muscle index (SMI, cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMuscle strength and physical performance\u003c/p\u003e \u003cp\u003ePreoperative grip strength and a usual gait speed of 6 m were measured according to the EWGSOP and AWGS definitions of sarcopenia to separately determine the muscle strength and physical performance of each patient. Patients were tested for preoperative grip strength using an electronic hand dynamometer (EH101; Camry Electronics Co., Ltd., Zhongshan, Guangdong, China) with a dominant hand squeeze. The time between the first and last steps over 6 m was used to measure the usual gait speed. Both parameters were measured within 7 days preoperatively, and the maximum value of three repeated tests was recorded.\u003c/p\u003e \u003cp\u003eThe diagnosis of sarcopenia\u003c/p\u003e \u003cp\u003ePatients with low skeletal muscle mass, low muscle strength, and/or low physical performance were considered to have sarcopenia, as defined by the EWGSOP and the AWGS. In this study, sarcopenia was diagnosed as follows: (1) low muscle mass (L3 skeletal muscle index (SMI)\u0026thinsp;\u0026le;\u0026thinsp;40.8 cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e in males and \u0026le;\u0026thinsp;34.9 cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e in females)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]; (2) low muscle strength (grip strength\u0026thinsp;\u0026lt;\u0026thinsp;28 kg in males and \u0026lt;\u0026thinsp;18 kg in females)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]; and (3) low muscle performance (6 m usual gait speed\u0026thinsp;\u0026lt;\u0026thinsp;1 m/s)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The cutoff value was based on the inferior aspect of the L3-CT image. Sarcopenia diagnosed in the muscle area from the superior aspect of L3-CT images was referred to as superior sarcopenia, the transverse aspect of L3-CT imaging as transverse sarcopenia, and the inferior aspect of L3-CT images was considered inferior sarcopenia.\u003c/p\u003e \u003cp\u003eData collection\u003c/p\u003e \u003cp\u003eFor each patient enrolled in this study, the following data were prospectively collected: (1) preoperative patient characteristics, including age, sex, body mass index (BMI), and Charlson comorbidity index; (2) surgical details, including laparoscopic-assisted surgery, combined organ resection, type of resection, and operative time; and (3) postoperative outcomes, including tumor pathological features and postoperative complications (within 30 days postsurgery).\u003c/p\u003e \u003cp\u003eAnalysis\u003c/p\u003e \u003cp\u003eThe agreement of SMA and SMI among the three aspects of L3-CT was calculated using the Wilcoxon rank sum test, and the agreement among the three diagnoses of sarcopenia was analyzed using kappa tests. Student\u0026rsquo;s t test was used to compare continuous normally distributed data, and the Mann‒Whitney U test was applied to continuous nonnormally distributed data. Categorical data were compared using the chi-square test or Fisher's exact test. Univariate analysis was used to assess the relationships between categorical variables. Univariate Cox proportional hazards models with all potential baseline predictors were constructed to calculate risk ratios (HR) and 95% CI. Variables with a trend (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the univariate analysis were selected, and multivariate logistic regression or Cox proportional risk models were constructed using forward stepwise variable selection. The Kaplan‒Meier method was used to estimate survival curves, and the log-rank test was used to compare the data. The data analysis was performed using the statistical package IBM SPSS Statistics software (SPSS) version 25.0.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eComparison of body composition data at three L3 aspects\u003c/p\u003e\n\u003cp\u003eWe divided all patients into two groups according to sex, and the SMA and SMI of males and females according to the three aspects are summarized in Table 1. As shown, there were significant differences in the SMA and SMI between these three dimensions for both men and women, all with increases from top to bottom. All three aspects remained highly correlated between the two aspects for both sexes (superior aspect vs. transverse aspect: SMA-R\u003csup\u003e2\u003c/sup\u003e=0.956; SMI-R\u003csup\u003e2\u003c/sup\u003e=0.935; transverse aspect vs. inferior aspect: SMA-R\u003csup\u003e2\u003c/sup\u003e=0.952; SMI-R\u003csup\u003e2\u003c/sup\u003e=0.930; inferior aspect vs. superior aspect: SMA-R\u003csup\u003e2\u003c/sup\u003e=0.924; and SMI-R\u003csup\u003e2\u003c/sup\u003e=0.887).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.358752166377815%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.518197573656845%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.61005199306759%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.464471403812826%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.878682842287695%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.16984402079723%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003efemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.342560553633218%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.494809688581315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.705882352941176%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.342560553633218%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.494809688581315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuperior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.705882352941176%\" valign=\"top\"\u003e\n \u003cp\u003e114.5\u003c/p\u003e\n \u003cp\u003e(60.9-189.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.956\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e122.6\u003c/p\u003e\n \u003cp\u003e(76.4-189.7)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.924\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e89.0\u003c/p\u003e\n \u003cp\u003e(60.9-142.6)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.909\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.342560553633218%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.494809688581315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransverse aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.705882352941176%\" valign=\"top\"\u003e\n \u003cp\u003e117.2\u003c/p\u003e\n \u003cp\u003e(59.7-199.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.952\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e126.5\u003c/p\u003e\n \u003cp\u003e(78.9-199.4)\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.914\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e91.8\u003c/p\u003e\n \u003cp\u003e(59.7-142.4)\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.917\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.342560553633218%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.494809688581315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInferior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.705882352941176%\" valign=\"top\"\u003e\n \u003cp\u003e120.1\u003c/p\u003e\n \u003cp\u003e(64.0-197.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.924\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e129.7\u003c/p\u003e\n \u003cp\u003e(78.2-197.3)\u003csup\u003ea,d\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.869\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e92.8\u003c/p\u003e\n \u003cp\u003e(64.0-153.5)\u003csup\u003ea,d\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.840\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.342560553633218%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.494809688581315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuperior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.705882352941176%\" valign=\"top\"\u003e\n \u003cp\u003e42.7\u003c/p\u003e\n \u003cp\u003e(24.7-66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.935\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e44.3\u003c/p\u003e\n \u003cp\u003e(26.9-66.7)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.915\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003cp\u003e(24.7-53.0)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.895\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.342560553633218%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.494809688581315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransverse aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.705882352941176%\" valign=\"top\"\u003e\n \u003cp\u003e43.7\u003c/p\u003e\n \u003cp\u003e(24.3-70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.930\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e45.8\u003c/p\u003e\n \u003cp\u003e(27.5-70.6)\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.903\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e37.0\u003c/p\u003e\n \u003cp\u003e(24.3-52.9)\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.902\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.342560553633218%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.494809688581315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInferior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.705882352941176%\" valign=\"top\"\u003e\n \u003cp\u003e44.8\u003c/p\u003e\n \u003cp\u003e(25.0-70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.887\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e46.6\u003c/p\u003e\n \u003cp\u003e(27.5-70.1)\u003csup\u003ea,d\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.854\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.43598615916955%\" valign=\"top\"\u003e\n \u003cp\u003e38.4\u003c/p\u003e\n \u003cp\u003e(25.0-57.0)\u003csup\u003ea,d\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.86159169550173%\" valign=\"top\"\u003e\n \u003cp\u003e0.813\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 1. SMA (cm\u003csup\u003e2\u003c/sup\u003e) and SMI (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e) measurements of three aspects of L3-CT and the coefficient of determination between adjacent aspects.\u003c/p\u003e\n\u003cp\u003eSMA, skeletal muscle area; SMI, skeletal muscle index\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Comparison between superior aspect and transverse aspect\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Comparison between the transverse aspect and the inferior aspect\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ed\u003c/sup\u003e Comparison between superior aspect and inferior aspect\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDiagnostic consistency of three aspects of L3\u003c/p\u003e\n\u003cp\u003eWe considered inferior sarcopenia the gold standard. As shown in Table 2 and Figure 2, the sensitivity of the superior aspect was 0.955, the specificity was 0.924, and the AUC\u0026nbsp;value was 0.939. The sensitivity of the transverse aspect was 0.941, the specificity was 0.949, and the AUC value was 0.945, which suggests that the diagnosis of the transverse aspect and the superior aspect had a high degree of agreement with that of the inferior aspect. The kappa value for the transverse aspect was 0.803, and the kappa value for the superior aspect was 0.745; both of these factors also showed a high degree of consistency compared to that of the inferior aspect.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInferior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.18518518518518%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransverse aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.51851851851852%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003esuperior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003esarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003esarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003esarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.296296296296298%\" valign=\"top\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. The concordance and discrepancy of diagnosis of the three aspects.\u003c/p\u003e\n\u003cp\u003eThe data are expressed as the number of patients.\u003c/p\u003e\n\u003cp\u003eSensitivity at the transverse aspect = 0.941; specificity = 0.949\u003c/p\u003e\n\u003cp\u003eThe sensitivity at the superior aspect = 0.955, specificity = 0.924\u003c/p\u003e\n\u003cp\u003ePopulation heterogeneity in three types of sarcopenia\u003c/p\u003e\n\u003cp\u003eAs shown in Table 3, the prevalence of superior sarcopenia, transverse sarcopenia, and inferior sarcopenia were 19.7%, 17.4%, and 13.8%, respectively, which revealed that the superior and transverse aspects were used to screen more patients with sarcopenia than was the inferior aspect. However, there were no significant differences in hospitalization costs (superior sarcopenia vs. inferior sarcopenia, p=0.622; transverse sarcopenia vs. inferior sarcopenia, p=0.511), postoperative hospitalization time (superior sarcopenia vs. inferior sarcopenia, p=0.335; transverse sarcopenia vs. inferior sarcopenia, p=0.255), or other indicators between superior sarcopenia and transverse sarcopenia with inferior sarcopenia. Thus, we divided the patients into superior sarcopenia and transverse sarcopenia groups and found that patients with superior sarcopenia and without inferior sarcopenia, both men and women, had slightly higher SMI compared with those with inferior sarcopenia; moreover, their hospitalization cost was reduced by approximately 10%, and their overall hospitalization time was shortened by one day. Furthermore, patients with transverse sarcopenia without inferior sarcopenia had a slightly greater SMI in both men and women, compared with those with inferior sarcopenia, and while women with transverse sarcopenia without inferior sarcopenia had a slightly greater BMI than did those with inferior sarcopenia.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"682\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.43906020558003%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.076358296622614%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.494860499265787%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003esuperior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.788546255506606%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransverse aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.201174743024964%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eInferior aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003eSuperior\u003c/p\u003e\n \u003cp\u003eSarcopenia\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003eSuperior\u003c/p\u003e\n \u003cp\u003esarcopenia alone\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003eTransverse\u003c/p\u003e\n \u003cp\u003eSarcopenia\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003eTransverse sarcopenia alone\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003eInferior sarcopenia\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003eNormal\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003enumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e220\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e194\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e962\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, mean (SD), (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e71(11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e70(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e72(11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e72(11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e72(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e64(14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003egender(males)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e142(64.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e51(69.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e123(63.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e33(67.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e95(61.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e722(75.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI, mean (SD),\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e20.7(2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e21.1(2.4)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e20.7(2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e21.3(2.3)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e20.5(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e22.9(3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.261194029850746%\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.111940298507463%\"\u003e\n \u003cp\u003e20.7(2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.738805970149254%\"\u003e\n \u003cp\u003e20.9(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.044776119402986%\"\u003e\n \u003cp\u003e20.5(2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e22.1(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e20.4(2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.485074626865671%\"\u003e\n \u003cp\u003e22.9(2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.261194029850746%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.111940298507463%\"\u003e\n \u003cp\u003e20.8(2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.738805970149254%\"\u003e\n \u003cp\u003e21.5(3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.044776119402986%\"\u003e\n \u003cp\u003e21.0(2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e21.0(2.1)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e20.6(2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.485074626865671%\"\u003e\n \u003cp\u003e23.2(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMI, median (IQR),\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e34.8(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e38.3(5.5)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e34.8(5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e38.6(6.0)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e34.9(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e45.9(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.261194029850746%\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.111940298507463%\"\u003e\n \u003cp\u003e37.7(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.738805970149254%\"\u003e\n \u003cp\u003e39.7(2.1)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.044776119402986%\"\u003e\n \u003cp\u003e37.6(4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e39.8(1.9)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e38.2(3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.485074626865671%\"\u003e\n \u003cp\u003e48.0(7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.261194029850746%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.111940298507463%\"\u003e\n \u003cp\u003e31.4(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.738805970149254%\"\u003e\n \u003cp\u003e33.8(1.7)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.044776119402986%\"\u003e\n \u003cp\u003e32.2(3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e34.2(1.2)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\"\u003e\n \u003cp\u003e32.5(3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.485074626865671%\"\u003e\n \u003cp\u003e39.7(5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor size,\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003emedian (IQR), (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e4(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e4(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e4(3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e3.5(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e4(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e3(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNM stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003eII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003ehospitalization time,\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003emedian (IQR), (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e14(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e13(6)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e14(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e13(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e14(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e13(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.407624633431084%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospitalization expenses,\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003emedian (IQR), (\u0026yen;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.064516129032258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.87683284457478%\"\u003e\n \u003cp\u003e63835\u003c/p\u003e\n \u003cp\u003e(25752)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.583577712609971%\"\u003e\n \u003cp\u003e59275\u003c/p\u003e\n \u003cp\u003e(21122)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.609970674486803%\"\u003e\n \u003cp\u003e64333\u003c/p\u003e\n \u003cp\u003e(25198)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e60158\u003c/p\u003e\n \u003cp\u003e(16415)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143695014662757%\"\u003e\n \u003cp\u003e65869\u003c/p\u003e\n \u003cp\u003e(30724)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.17008797653959%\"\u003e\n \u003cp\u003e57928\u003c/p\u003e\n \u003cp\u003e(21176)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3. Comparisons among patients with superior sarcopenia, transverse sarcopenia and inferior sarcopenia.\u003c/p\u003e\n\u003cp\u003eThe data are expressed as the number of patients unless indicated otherwise.\u003c/p\u003e\n\u003cp\u003eBMI, body mass index; SMI, skeletal muscle index; SD, standard deviation; IQR, interquartile range; Superior sarcopenia alone, exclusion of patients with inferior sarcopenia from those with superior sarcopenia; Transverse sarcopenia alone, exclusion of patients with inferior sarcopenia from those with transverse sarcopenia\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Statistically significant, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Compared with inferior sarcopenia patients.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Compared with normal.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eShort-term postoperative complications\u003c/p\u003e\n\u003cp\u003eWe evaluated postoperative complications that occurred within 30 days after gastrectomy and graded the complications according to the Clavien system[24], including those of Grade II or higher. The results of the univariate and multivariate analyses of the predictors of postoperative complications are presented in Table 4. The univariate analysis showed that advanced age, superior sarcopenia, transverse sarcopenia, inferior sarcopenia, Charlson Comorbidity Index, TNM staging, combined organ removal, and open surgery were risk factors for postoperative complications. The multivariate analysis showed a higher dominance ratio for inferior sarcopenia (OR=2.030, p\u0026lt;0.001) than for superior sarcopenia (OR= 1.608, p=0.005) and transverse sarcopenia (OR=1.679, p=0.004).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"665\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.639097744360901%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.804511278195488%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"62.556390977443606%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.639097744360901%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.804511278195488%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.75187969924812%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSuperior sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.353383458646615%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTransverse sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.451127819548873%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInferior sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003e(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.011\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.014\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.019\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;75/\u0026lt;75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e2.040(1.478-2.815)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e1.561(1.107-2.201)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.543(1.093-2.179)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e1.514(1.072-2.138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale/female\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.045(0.770-1.419)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;25/\u0026lt;25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e0.999(0.711-1.405)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuperior sarcopenia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.852(1.348-2.543)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e1.608(1.145-2.257)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransverse sarcopenia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.989(1.431-2.764)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.679(1.180-2.389)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInferior sarcopenia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e2.335(1.638-3.329)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e2.030(1.389-2.968)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson Comorbidity Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1/0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.521(1.104-2.097)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.010\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e1.439(1.033-2.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.031\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.424(1.023-1.984)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.036\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e1.446(1.037-2.017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.030\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;2/0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e2.587(1.810-3.696)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e2.410(1.664-3.491)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e2.407(1.662-3.488)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e2.446(1.687-3.547)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistologic type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUndifferentiated/differentiated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e0.875(0.667-1.150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNM stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eII/I\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.878(1.296-2.719)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIII/I\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.613(1.174-2.218)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of resection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.021\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal/Subtotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.380(1.049-1.816)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCombined resection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.032\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.030\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e0.036\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e2.067(1.302-3.281)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e1.702(1.045-2.770)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e1.718(1.055-2.798)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e1.691(1.035-2.761)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaparoscopic surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e0.441(0.323-0.602)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e0.487(0.351-0.676)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e0.49(0.353-0.681)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e0.488(0.351-0.678)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOperative durations\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;4 hours\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.615615615615615%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e0.908(0.671-1.227)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.00900900900901%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312312312312311%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.762762762762764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.861861861861861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4. Univariate and multivariate logistic regression analyses for postoperative complications\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Statistically significant.\u003c/p\u003e\n\u003cp\u003eLong-term postoperative survival outcome\u003c/p\u003e\n\u003cp\u003eThe median postoperative follow-up period was 59 months. The 5-year survival rates were 66.2%, 65.9%, and 65.5% for patients with superior, transverse, and inferior sarcopenia, respectively. As shown in Figure 3, Kaplan‒Meier analysis revealed that overall survival (OS) (log-rank, superior sarcopenia, p=0.0015; transverse sarcopenia, p=0.0024; inferior sarcopenia, p=0.003) was significantly shorter in patients with sarcopenia than in those without sarcopenia, regardless of the aspect-based diagnosis of sarcopenia. As shown in Table 5, multivariate Cox models showed that inferior sarcopenia (HR=1.491, p=0.004), histologic type, TNM staging, and resection type were independently associated with poorer overall survival. When using superior sarcopenia (HR=1.408, p=0.005) or transverse sarcopenia (HR=1.376, p=0.012) instead of inferior sarcopenia, the inclusion of sarcopenia remained in the multifactorial model. Compared to those of inferior sarcopenia, the risks of superior sarcopenia and transverse sarcopenia appeared to be lower.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"119%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.28571428571429%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSuperior sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTransverse sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInferior sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;75/\u0026lt;75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.910(1.520-2.401)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale/female\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.322(1.035-1.688)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;25/\u0026lt;25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e0.854(0.654-1.114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eSuperior sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.463(1.153-1.857)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e1.408(1.109-1.788)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eTransverse sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.012\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.460(1.139-1.872)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e1.376(1.073-1.766)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eInferior sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.494(1.139-1.959)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e1.491(1.135-1.959)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1/0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.236(0.977-1.562)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;2/0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.211(0.911-1.619)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eHistologic type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUndifferentiated/differentiated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.824(1.477-2.251)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e1.396(1.127-1.729)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e1.395(1.126-1.728)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e1.387(1.119-1.718)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eII/I\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e2.517(1.712-3.700)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e2.172(1.471-3.206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e2.169(1.469-3.203)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e2.139(1.448-3.161)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIII/I\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e7.071(5.152-9.705)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e5.623(4.052-7.804)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e5.640(4.064-7.926)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e5.657(4.078-7.848)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eType of resection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal/Subtotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e2.088(1.703-2.560)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eCombined resection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.732(1.243-2.414)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eLaparoscopic surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e0.582(0.461-0.737)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003eOperative durations\u0026gt;4 hour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes/No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1.118(0.895-1.396)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 5. Univariate and multivariate analyses for predictors of overall survival\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Statistically significant.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study compared skeletal muscle area among three aspects of L3-CT imaging and investigated, for the first time, the differences in predicting patient prognosis caused by the diagnosis of sarcopenia using muscle data obtained from different aspects of L3-CT imaging. This study showed that the SMA and the SMI increased sequentially from the top to the bottom of the L3-CT image. However, there was a high correlation among these three aspects, and the results were consistent with those of previous studies.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] For this reason, more patients were diagnosed with sarcopenia in a descending sequence, from top to bottom, with more patients diagnosed with sarcopenia in the superior and transverse aspects than in the inferior aspect. Overall, there was high agreement in the diagnosis of the three aspects (superior sarcopenia vs. inferior sarcopenia, kappa value\u0026thinsp;=\u0026thinsp;0.745, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; transverse sarcopenia vs. inferior sarcopenia, kappa value\u0026thinsp;=\u0026thinsp;0.803, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There were also significant differences in the SMA and SMI among the three aspects, with a certain consistency in diagnosis. Therefore, further analysis is needed to clarify whether this difference impacts the prediction of clinical outcomes.\u003c/p\u003e \u003cp\u003eSeveral studies have shown that patients with sarcopenia have higher hospitalization costs[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], longer hospital stays[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], and shorter postoperative survival[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] than patients without sarcopenia, in agreement with the findings of our study. We found no significant differences in postoperative length of stay and hospitalization costs among the three sarcopenia populations. After further splitting the patients into superior sarcopenia and transverse sarcopenia cohorts, patients with superior sarcopenia alone (negative for inferior sarcopenia) had a greater SMI in both sexes than did those with inferior sarcopenia. Patients in these groups also spent less on hospitalization than patients with inferior sarcopenia and had a slightly shorter length of postoperative hospitalization, while patients with transverse sarcopenia alone (negative for inferior sarcopenia) had the same SMI and postoperative hospitalization cost as patients with superior sarcopenia alone. Previous studies have revealed that a low SMI can be used as an independent risk factor for predicting postoperative length of stay[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], cost[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], complications[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and long-term prognosis[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], whereas patients with a high SMI have been found to have a better postoperative prognosis. This may partially explain the relatively better length of stay and cost performance of patients with superior sarcopenia and transverse sarcopenia.\u003c/p\u003e \u003cp\u003eFurther analysis of postoperative complications revealed that inferior sarcopenia had the best predictive ability (superior sarcopenia, OR\u0026thinsp;=\u0026thinsp;1.608; transverse sarcopenia, OR\u0026thinsp;=\u0026thinsp;1.769; inferior sarcopenia, OR\u0026thinsp;=\u0026thinsp;2.030). According to our analysis of long-term survival, inferior sarcopenia appeared to retain high predictive power for survival (superior sarcopenia, HR\u0026thinsp;=\u0026thinsp;1.408; transverse sarcopenia, HR\u0026thinsp;=\u0026thinsp;1.376; inferior sarcopenia, HR\u0026thinsp;=\u0026thinsp;1.491). Taken together, these findings showed that patients with superior and transverse sarcopenia had relatively high SMI, as described previously. This was perhaps because the superior and transverse sarcopenia cohort included more patients with suspected sarcopenia, for whom the short- and long-term prognostic performance was slightly better than that of patients with inferior sarcopenia. This has led to superior and transverse sarcopenia to present a relatively low risk predictive ability in prognostic predictions. At the root of this, despite the high correlation of SMA between the three aspects, differences remain in SMA values. We uniformly used a cutoff that was obtained according to the L3 inferior aspect as the basis for the diagnosis of low SMI in this study, and applying this cutoff to the superior aspect and transverse aspect may be the underlying cause of this difference.\u003c/p\u003e \u003cp\u003eIn this study, we explored in detail the diagnosis of low muscle mass in patients with sarcopenia and found that when using a uniform cutoff at the inferior aspect, it may be possible that a lower SMI at the superior and transverse aspects, compared to the inferior aspect screened out more critical patients with suspected sarcopenia, which is clearly detrimental to the predictive power of the model. We recommend that when diagnosing low SMI, the aspect of interception should be uniform and consistent with the aspect of the truncation values. Since it has the potential to be incorporated into risk-scoring systems for postoperative prognosis and to improve clinical decision-making in patients, this study of patients with gastric cancer emphasizes the need for a standardized assessment of sarcopenia.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, this was a single-center study, and a larger multicenter study is needed to validate our findings. In addition, although we clarified that the cutoff value should be consistent with the intercept, whether a specific aspect of L3 selection would yield a better prognostic value remains unclear.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved by the Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding authors on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funds were involved in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eW.Z, X.C and X.S. made substantial contributions to the conception and design of the study. H.Y., H.Q., Q.S. and Z.G. were involved in the collection and analysis of the data, H.Y. wrote the manuscript, and W.C. and X.W. provided final approval and revised the manuscript. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank our patients, without whom this study would not be possible.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCruz-Jentoft A, Sayer A, Sarcopenia. Lancet (London England). 2019;393(10191):2636\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCruz-Jentoft A, Bahat G, Bauer J, Boirie Y, Bruy\u0026egrave;re O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. 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Liver Transpl. 2017;23(5):625\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartin L, Birdsell L, Macdonald N, Reiman T, Clandinin MT, McCargar LJ, et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol. 2013;31(12):1539\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakagi K, Yagi T, Yoshida R, Shinoura S, Umeda Y, Nobuoka D, et al. Sarcopenia and American Society of Anesthesiologists Physical Status in the Assessment of Outcomes of Hepatocellular Carcinoma Patients Undergoing Hepatectomy. Acta Med Okayama. 2016;70(5):363\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEbadi M, Wang CW, Lai JC, Dasarathy S, Kappus MR, Dunn MA, et al. Poor performance of psoas muscle index for identification of patients with higher waitlist mortality risk in cirrhosis. J Cachexia Sarcopenia Muscle. 2018;9(6):1053\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhanji RA, Narayanan P, Moynagh MR, Takahashi N, Angirekula M, Kennedy CC, et al. Differing Impact of Sarcopenia and Frailty in Nonalcoholic Steatohepatitis and Alcoholic Liver Disease. Liver Transpl. 2019;25(1):14\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJapanese gastric cancer treatment. guidelines 2010 (ver. 3). Gastric Cancer. 2011;14(2):113\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDindo D, Demartines N, Clavien P-A. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchweitzer L, Geisler C, Pourhassan M, Braun W, Gl\u0026uuml;er C-C, Bosy-Westphal A, et al. What is the best reference site for a single MRI slice to assess whole-body skeletal muscle and adipose tissue volumes in healthy adults? Am J Clin Nutr. 2015;102(1):58\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLo Y-TC, Wahlqvist ML, Huang Y-C, Chuang S-Y, Wang C-F, Lee M-S. Medical costs of a low skeletal muscle mass are modulated by dietary diversity and physical activity in community-dwelling older Taiwanese: a longitudinal study. Int J Behav Nutr Phys Act. 2017;14(1):31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiani M, Rezoagli E, Grassi A, Porta M, Riva L, Famularo S, et al. Low skeletal muscle index and myosteatosis as predictors of mortality in critically ill surgical patients. Nutrition. 2022;101:111687.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoter S, Cohnert TU, Hindermayr KB, Lindenmann J, Br\u0026uuml;ckner M, Oswald WK, et al. Increased hospital costs are associated with low skeletal muscle mass in patients undergoing elective open aortic surgery. J Vasc Surg. 2019;69(4):1227\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnsari E, Chargi N, van Gemert JTM, van Es RJJ, Dieleman FJ, Rosenberg AJWP, et al. Low skeletal muscle mass is a strong predictive factor for surgical complications and a prognostic factor in oral cancer patients undergoing mandibular reconstruction with a free fibula flap. Oral Oncol. 2020;101:104530.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng Z-F, Lu J, Xie J-W, Wang J-B, Lin J-X, Chen Q-Y, et al. Preoperative skeletal muscle index vs the controlling nutritional status score: Which is a better objective predictor of long-term survival for gastric cancer patients after radical gastrectomy? Cancer Med. 2018;7(8):3537\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sarcopenia, Gastric cancer, Muscle quantity, Lumbar third vertebra, Computed tomography","lastPublishedDoi":"10.21203/rs.3.rs-4045367/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4045367/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThe European Working Group on Sarcopenia in Older People (EWGSOP) revised the consensus in 2018, including that using computed tomography (CT) imaging of the lumbar third vertebra (L3) for the evaluation of muscle mass. However, there is currently discrepancy and confusion in the application of specific cross-sectional and cutoff values for L3. This study aimed to standardize the diagnosis of low muscle mass using L3-CT.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eThis study included patients who underwent radical gastrectomy for gastric cancer between July 2014 and February 2019. Sarcopenia factors were measured preoperatively. Patients were followed up to obtain actual clinical outcomes. We used the cutoff values obtained based on the inferior aspect of L3-CT images to diagnose sarcopenia in three aspects, respectively. Univariate and multivariate analyses were used to compare long-term and short-term postoperative prognostic differences.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSarcopenia was found to be an independent risk factor for postoperative complications and overall survival in patients with all three diagnoses of sarcopenia. According to the multivariate model for predicting postoperative complications, patients with inferior-L3 sarcopenia had a greater odds ratio (OR) than patients with superior-L3 sarcopenia or transverse-L3 sarcopenia did (OR, inferior sarcopenia vs. superior sarcopenia, transverse sarcopenia, 2.030 vs. 1.608, 1.679). Furthermore, patients with inferior-L3 sarcopenia had the highest hazard ratio (HR) (HR, inferior sarcopenia vs. superior sarcopenia, transverse sarcopenia, 1.491 vs. 1.408, 1.376) in the multivariate model for predicting overall survival.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eWe recommend that when diagnosing low muscle mass using L3-CT, the intercepted cross section should be uniform and consistent with the aspect on which the cutoff value is based.\u003c/p\u003e","manuscriptTitle":"Body composition analysis using CT at three aspects of the lumbar third vertebra and its impact on the diagnosis of sarcopenia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-15 18:50:21","doi":"10.21203/rs.3.rs-4045367/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-07T13:34:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-28T15:13:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-22T22:50:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1ade4271-cf6c-439e-890c-74d8e9885afd","date":"2024-04-15T00:36:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18e4d8cb-5cbd-428b-9316-86b246ef7904","date":"2024-04-13T05:10:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"207bb685-4701-42c8-b6b3-2f63cdfb9ef0","date":"2024-03-27T10:57:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-25T09:55:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-24T01:38:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-13T04:01:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"World Journal of Surgical Oncology","date":"2024-03-08T14:14:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"123ad3e4-4505-4f43-9b57-4e28ba7bc94a","owner":[],"postedDate":"March 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-03T16:03:31+00:00","versionOfRecord":{"articleIdentity":"rs-4045367","link":"https://doi.org/10.1186/s12957-024-03634-9","journal":{"identity":"world-journal-of-surgical-oncology","isVorOnly":false,"title":"World Journal of Surgical Oncology"},"publishedOn":"2025-02-26 15:58:16","publishedOnDateReadable":"February 26th, 2025"},"versionCreatedAt":"2024-03-15 18:50:21","video":"","vorDoi":"10.1186/s12957-024-03634-9","vorDoiUrl":"https://doi.org/10.1186/s12957-024-03634-9","workflowStages":[]},"version":"v1","identity":"rs-4045367","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4045367","identity":"rs-4045367","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}