Latent class analysis of symptom clusters in preventive enterostomy with colorectal cancer patients based on nutritional status

Latent class analysis of symptom clusters in preventive enterostomy with colorectal cancer patients based on nutritional status | 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 Latent class analysis of symptom clusters in preventive enterostomy with colorectal cancer patients based on nutritional status Rujia Lin, Lan Li, Xinlei Wu, Ting Zhang, Weina Wang, Jiayi Lin, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6188108/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background There is a close relationship between nutritional status and symptom clusters. However, research on the characteristics of symptom clusters in different nutritional statuses is still limited. The purpose of this study was to explore the heterogeneity of symptom clusters in different patient categories by using latent class analysis and to provide direction and key guidance for clinical symptom cluster management in different patient populations. Methods This cross-sectional study used convenience sampling to recruit colorectal cancer patients with preventive enterostomy from three tertiary hospitals in Fujian Province. Data were collected using the following instruments: a general information questionnaire, the Chinese version of the Adult Pain Behavior Scale (APBS), the Hamilton Anxiety Scale (HAMA), the Hamilton Depression Scale (HAMD), the Athens Insomnia Scale (AIS), and the Cancer Appetite and Symptom Questionnaire (CASQ). After data collection, latent class analysis (LCA) was applied to explore heterogeneous subgroups of nutritional status-symptom clusters. Univariate and multivariate analyses were conducted to identify factors influencing subgroup classification. Results A total of 350 questionnaires were collected, which revealed four latent categories: the malnourished-high symptom cluster group, the suboptimal nutrition-higher symptom cluster group, the moderate nutrition-moderate symptom cluster group, and the well-nourished-low symptom cluster group. Multivariate logistic regression analysis showed that chronic diseases and tumor location were significant factors influencing the latent categories ( P < 0.05). Conclusion The findings of this study indicated that the subgroups of disease symptoms under different nutritional statuses exhibited distinct characteristics. By identifying the subgroups of symptoms, it is helpful to provide reference and guidance for formulating more effective and accurate intervention and management strategies for patients with preventive enterostomy. Preventive enterostomy Symptom clusters Nutritional status Latent class analysis Colorectal cancer Figures Figure 1 Introduction Preventive enterostomy, also known as a protective or diversion stoma, involves the surgical fixation of the intestine to the abdominal wall to create a temporary end ileostomy or transverse colostomy, which diverts feces to reduce the incidence of postoperative anastomotic leakage and the risk of abdominal and pelvic infections and abscesses [1]. It is widely used in sphincter-preserving surgery for low rectal cancer and acute obstructive colorectal cancer surgery. The clinical utilization rate of preventive enterostomy in China ascended from 49.6% in 2019 to 62.8% in 2021 [2], and in some countries, it even reached 88%-100% [3]. However, owing to partial intestinal resection and changes in intestinal structure, enterostomy may cause intestinal dysfunction, nutrient loss, malabsorption, and dietary restrictions, which lead to malnutrition [4]. The incidence of malnutrition in stoma patients is higher than that in general colorectal cancer surgery patients, ranging from 61.4–90.91% [5–7]. Additionally, cancer patients often experience a series of physical and psychological disorders during treatment, such as anxiety, depression, aches, sleep disturbances, and loss of appetite. These symptoms occur concurrently and are interrelated, forming different symptom cluster synergistic effects, collectively referred to as "symptom clusters". The phenomenon of symptom clusters is also prevalent in enterostomy patients [8]. Consequently, managing symptom clusters in preventive enterostomy patients has always been a hot topic in clinical research. Currently, the association between the nutritional status of cancer patients and disease symptoms has been widely concerned. A large-scale survey on the nutritional status of patients with common malignant tumors in China indicated that symptom clusters (such as appetite loss and nausea) would directly affect nutritional intake, while deterioration of nutritional status would aggravate symptoms through immunosuppression, metabolic disorder, and other channels [9]. In addition, several studies [10–12] demonstrated that there is a positive correlation between weight loss, weight loss rate, or other nutrition-related indicators with the severity of symptom clusters, and with appropriate nutritional support, symptom clusters can also be notably ameliorated [13]. Nutritional status is the outcome of the result of multi-factor comprehensive influence [14]. Although it has also been pointed out in the literature that the severity of symptom groups can predict the change in the nutritional status of patients [15], the heterogeneity of disease symptom groups among individuals under nutritional status has not been taken into account yet. In fact, even under the same nutritional status assessment, the characteristics of symptom clusters may differ owing to patients' sociodemographic factors, disease conditions, and treatment modalities [16]. Identifying the differences in symptom cluster characteristics in different nutritional statuses is of great significance for selecting targeted interventions in clinical practice. Thus, it is necessary to explore the differences in symptom clusters. Latent class analysis (LCA) is a statistical method employed to discover the latent structure of data, concentrating on classifying and identifying unobserved latent categories or subgroups in the data. This method elucidates the relationships between observed categorical variables by estimating the probability of each individual belonging to each latent category, thereby revealing hidden structures in the data [17]. Latent class analysis offers a new perspective for research on nutrition and symptom clusters in preventive enterostomy patients. This study aims to utilize latent class analysis to explore the "pain-anxiety-depression-sleep disturbance-loss of appetite" symptom cluster based on nutritional status classification, and to clarify the relationship between influencing factors and latent categories of symptom clusters, thereby providing theoretical support for personalized nutrition and symptom management in these patients. Methods Study Subjects and Sample Size Calculation This cross-sectional study adopted convenience sampling to recruit colorectal cancer patients with preventive enterostomy from the gastrointestinal surgery departments of Zhongshan Hospital Affiliated to Xiamen University, Fujian Cancer Hospital, and the 909th Hospital of the Joint Logistics Support Force of the People's Liberation Army in Fujian Province from March 2022 to August 2023. Inclusion criteria: ① Patients must meet the diagnostic criteria for primary colorectal cancer and with preventive enterostomy during tumor resection; ② Patients should be at least 18 years old; ③ Patients are conscious and capable of completing the study; ④ Patients and their families are informed and agree to participate in the study. Exclusion criteria: ① Combined with or previously diagnosed with primary malignant tumors in other locations; ② Combined with hyperthyroidism, tuberculosis, and other consumptive diseases; ③ Complicated with other severe acute diseases and other chronic diseases without treatment. Nutritional status assessment criteria: Nutritional risk was screened using NRS2002(Nutritional Risk Screening 2002). A score of less than 3 points indicated no or potential malnutrition risk. Conversely, a score of 3 points or more indicated that the nutritional assessment should be conducted using the PG-SGA ༈Patient-Generated Subjective Global Assessment༉scale [18]. This study has been approved by the Ethics Committee of Zhongshan Hospital Affiliated to Xiamen University (Ethics Approval No.: XZSYY 2022 − 140). According to the sample size calculation formula for measurement data n = Z 2 α/2 p (1 - p) / δ 2 [19], where α = 0.05 and Z α/2 = 1.96; based on previous research results, the average incidence of malnutrition in preventive enterostomy patients with colorectal cancer is 76%, with a permissible error δ of 0.06, considering a 15% attrition rate, the final calculated sample size is at least 276 cases. Research Tools General Information Questionnaire Designed through a comprehensive literature review and consultation with clinical nursing experts, including demographic and disease-related information. Demographic information includes age, gender, education level, marital status, monthly income, chronic diseases, and disease-related information, including tumor location, tumor stage, stoma site, chemotherapy or not, radiotherapy or not. Chinese Version of the Adult Pain Behavior Scale (APBS) The APBS was developed by a group of Chinese experts based on literature review and existing objective pain assessment tools, taking into account China's national conditions. It includes five items: facial expression, rest state, muscle tension, soothing effect, and vocalization., each scored 0–2, with a total score of 0–10. Higher scores indicate more severe pain [20]. The Cronbach's α of this scale was 0.733. Hamilton Anxiety Scale (HAMA) The HAMA, developed by Hamilton, assesses anxiety levels in both psychological and somatic dimensions, each dimension contains seven items. Each item is scored 0–4, with a total score of 56. A score of less than 7 indicates no anxiety, 7–14 indicates possible anxiety, 15–21 indicates anxiety, 22–28 indicates significant anxiety, and a score greater than 28 indicates severe anxiety [21]. The Cronbach's α of this scale was 0.856. Hamilton Depression Scale (HAMD) The HAMD comprises seven dimensions: physical condition, cognitive status, recent weight changes, diurnal variation, psychomotor retardation, sleep condition, and hopelessness, with 24 items. Fourteen items are scored 0–4, and ten items are scored 0–2, with a total score of 0–76. A score of 7 or less indicates no depression, 8–20 indicates possible depression, 21–35 indicates depression, and a score greater than 35 indicates severe depression [22]. The Cronbach's α of this scale was 0.870. Athens Insomnia Scale (AIS) Designed by Soldatos et al [23], the AIS is utilized for self-assessment of sleep disorders, including eight items: sleep induction, nocturnal awakening, early morning awakening, sleep satisfaction, sleep quality impact, daytime sleepiness, etc. Each item is scored 0–3, with a total score of 0–24. A score of 3 or less indicates no sleep disorder, 4–6 indicates suspected insomnia, and a score of 7 or more indicates insomnia. The Cronbach's α of this scale was 0.875. Cancer Appetite and Symptom Questionnaire (CASQ) The CASQ was developed by Professor V. Halliday from the Department of Nutrition at the University of Nottingham, based on the Common Nutritional Appetite Questionnaire (CNAQ) [24]. The questionnaire is composed of 12 items, each scored 0–4, with a total score of 0–48. Lower scores indicate worse appetite, with a score of 30 or less indicating loss of appetite and a score greater than 30 indicating normal appetite. The Cronbach's α of this scale was 0.820. Data Collection and Quality Control Prior to filling out the questionnaire, trained research team members employed uniform instructions to elucidate the purpose and significance of the survey to the subjects. The questionnaires were distributed by research team members and completed independently by the patients. The questionnaires were collected on the spot, and any missing items were checked and supplemented by the subjects. A total of 360 questionnaires were distributed, and 350 valid questionnaires were collected, with a valid questionnaire recovery rate of 97.22%. Data Analyses The collected data were double-entered into the database and verified to ensure accuracy. Normally distributed measurement data were described using mean ± standard deviation; count data or grade data were presented as frequency and percentage. We utilized Mplus 8.3 software for exploratory latent profile analysis to classify the symptom clusters of preventive enterostomy patients. Model fit evaluation indicators included: ① Akaike Information Criterion (AIC), with smaller values indicating better fit; ② Bayesian Information Criterion (BIC), with smaller values denoted better fit, generally choosing the model with the smallest BIC as the optimal model; ③ Entropy index, the most sensitive indicator for judging model classification error rate, ranging from 0 to 1, with values closer to 1 indicating more accurate model classification. If the entropy value was greater than 0.7, the model classification accuracy is good; ④ Bootstrapped Likelihood Ratio Test (BLRT) and Lo-Mendell-Rubin (LMR) likelihood ratio tests were used for model comparison, with P < 0.05 indicating rejection of the k-1 category model and support for the k category model. Finally, based on the latent class analysis results, we determined the optimal classification model of nutritional status-symptom clusters in preventive enterostomy patients with colorectal cancer, and then used SPSS 26.0 software for multivariate logistic regression analysis to explore the influencing factors of latent categories in preventive enterostomy patients with colorectal cancer. Results Latent Class Analysis of Nutritional Status-Related Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer Based on the principles of lower AIC, BIC, and aBIC values, higher entropy (≥ 0.7), and statistically significant BLRT and LMR, this study explored four latent category models. Commencing with a single category, the number of categories was incrementally increased sequentially.. As the number of categories increased, the AIC, BIC, and aBIC values gradually decreased, and the entropy value also showed an upward trend. Nevertheless, given that the P values of the BLRT for the three-category and five-category models were greater than 0.05, the model fit was not suitable (Table 1 ). After a comprehensive comparison, the final fitting model was determined to have four categories (Fig. 1 ). After determining the final fitting model with four categories, the belonging probabilities of the four latent categories were 0.736–0.939, all greater than 70%, indicating reliable model classification (Table 2 ). Table 1 Latent Class Fit Results of Nutritional Status in Preventive Enterostomy Patients (n = 350) Number Of Categories AIC BIC aBIC Entropy BLRT( P ) LMR( P ) class probability 1 2681.905 2705.052 2686.018 1 2 2493.311 2543.465 2502.224 0.726 <0.01 <0.01 0.394/0.605 3 2476.645 2553.803 2490.356 0.695 0.2286 <0.01 0.382/0.131/0.487 4 2463.534 2567.698 2482.045 0.724 0.0484 <0.01 0.286/0.129/0.42/0.166 5 2460.274 2591.444 2483.584 0.858 0.1583 <0.05 0.186/0.09/0.409/0.14/0.174 Table 2 Average Belonging Probability Matrix of Each Latent Category Category Category 1 Category 2 Category 3 Category 4 Category 1 0.736 0.036 0.191 0.037 Category 2 0.000 0.939 0.000 0.061 Category 3 0.056 0.004 0.939 0.000 Category 4 0.156 0.059 0.000 0.784 Analysis of Latent Category Characteristics of Nutritional Status-Related Symptom Clusters in Preventive Enterostomy Patients The latent category characteristics of nutritional status in patients are shown in Fig. 1 . Based on their characteristics, they were named as follows: Category 1 (C1, orange line) had a 100% probability of malnutrition or malnutrition risk, and the scores for "depression" and "sleep disturbance" were significantly higher than those of other groups. Thus, it was named the "malnourished-high symptom cluster response group"; Category 2 (C2, green line) had a 94.9% probability of malnutrition or malnutrition risk, and the scores for each symptom cluster were relatively high, so it was named the "suboptimal nutrition-higher symptom cluster response group"; Category 3 (C3, blue line) had a 35.6% probability of malnutrition or malnutrition risk, and the scores for each symptom cluster were moderate, so it was named the "moderate nutrition-moderate symptom cluster response group"; Category 4 (C4, yellow line) had a 1.6% probability of malnutrition or malnutrition risk, and the scores for each symptom cluster were low, so it was named the "well-nourished-low symptom cluster response group." Univariate Analysis of Latent Categories in Preventive Enterostomy Patients with Colorectal Cancer Univariate analysis of variance showed that the distributions of gender, presence of chronic diseases, tumor location, and tumor stage among different latent category groups were statistically significant ( P < 0.05), as shown in Table 3 . Multivariate Analysis of Influencing Factors of Latent Categories of Nutritional Status-Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer Each latent category was employed as the dependent variable (with the malnourished-high symptom cluster response group serving as the reference category). Factors that demonstrated statistical significance in the univariate analysis of variance were utilized as independent variables to construct an unordered multi-class logistic regression model for the purpose of multivariate analysis. The variable assignments were as follows: ① Gender: female was assigned a value of 0, and male was assigned a value of 1; ② Presence of chronic diseases: no = 0, yes = 1; ③ Tumor location: rectum = 0, colon = 1; ④ Tumor stage: stage II and below = 0, stage III and above = 1. The multivariate analysis revealed that the "presence of chronic diseases" and "tumor location" were significant factors influencing latent class categorization. Compared to the "malnourished-high symptom cluster response group (C1)", patients without chronic diseases had a higher likelihood of belonging to the "moderate nutrition-moderate symptom cluster response group (C3)" (OR = 2.001, P < 0.017). Meanwhile, patients with rectal tumors showed greater probabilities of being classified into the "suboptimal nutrition-higher symptom cluster response group (C2)" and "moderate nutrition-moderate symptom cluster response group (C3)" (OR = 7.952, P = 0.008; OR = 2.261, P = 0.026). These findings indicated that the absence of chronic diseases and rectal tumor location served as protective factors against malnutrition and severe symptom clusters in colorectal cancer patients with preventive enterostomy.. Details are shown in Table 4 . Table 3 Univariate Analysis of Latent Categories in Preventive Enterostomy Patients with Colorectal Cancer Feature C1 (n = 100) C2 (n = 45) C3 (n = 147) C4 (n = 58) F P Gender 2.710 <0.05 Female 25 6 48 12 Male 75 39 99 46 Age 1.610 0.187 <39 1 1 5 0 40–59 36 17 61 19 ≥ 60 63 27 81 39 Education Level 0.653 0.582 Junior High School And Below 53 27 74 34 High School And Above 47 18 73 24 Marital Status 0.592 0.621 Married 87 41 134 50 Unmarried Other 13 4 13 8 Residence Status 0.245 0.865 Living With Others 92 40 136 54 Live Alone 8 5 11 4 Monthly Income 0.587 0.624 <5000 89 41 128 54 ≥ 5000 11 4 19 4 Chronic Diseases 19.762 <0.05 None 62 13 113 20 Have 38 32 34 38 Tumor Site 4.192 <0.05 Rectum 77 43 131 46 Colon 23 2 16 12 Tumor Stage 5.409 <0.05 Stage Ⅱ And Below 10 1 31 4 Stage Ⅲ And Above 90 44 116 54 Stoma Site 1.123 0.340 Colon 16 10 17 8 Ileum 84 35 130 50 Chemotherapy Or Not? − - No 0 0 0 0 Yes 100 45 147 58 Radiotherapy Or Not? 1.464 0.224 No 73 35 123 44 Yes 27 10 24 14 Table 4. Multivariate analysis of potential categories of colorectal cancer patients with prevent colostomy Project C2 C3 C4 OR 95% Cl P OR 95% Cl P OR 95% Cl P Floor Upper Limit Floor Upper Limit Floor Upper Limit Gender 0.377 0.138 1.029 0.057 1.379 0.768 2.477 0.282 0.740 0.332 1.652 0.463 Chronic Diseases 0.241 0.110 0.526 P ＜0.01 2.001 1.133 3.535 0.017 0.322 0.164 0.635 0.001 Tumor Site 7.952 1.739 36.536 0.008 2.261 1.105 4.625 0.026 1.240 0.546 2.817 0.607 Tumor Stage 0.196 0.024 1.627 0.131 2.141 0.985 4.651 0.055 0.729 0.212 2.503 0.616 Note: Gender is compared with "female"; presence of chronic diseases is compared with "yes"; tumor location is compared with "rectum"; tumor stage is compared with "stage III and above." Discussion Differences in Nutritional Status-Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer This study found that patients with preventive enterostomy for colorectal cancer exhibited diverse types of symptom clusters, which are in accordance with Mello's research [25]. Based on nutritional status, symptom clusters can be divided into four categories: the malnourished-high symptom cluster response group, the suboptimal nutrition-higher symptom cluster response group, the moderate nutrition-moderate symptom cluster response group, and the well-nourished-low symptom cluster response group, indicated heterogeneity among symptom cluster categories. In the "malnourished-high symptom cluster response group (C1)", patients' depression and sleep disturbance scores were significantly higher than those of other groups, this finding highlights a robust association between malnutrition and depression and sleep disturbance, as also reported in Hwang's research [26]. On the one hand, malnutrition may lead to brain dysfunction, including neurotransmitter imbalance, cognitive decline, and emotional regulation disorders, which increase the risk of depression. There exists a bidirectional relationship between depression, and sleep disturbance. Depressive symptoms can lead to a deterioration in sleep quality, and sleep disturbance can exacerbate depressive symptoms; on the other hand, depression and sleep disturbance share the multiple risk factors, such as social isolation, life stress, and disease burden, which may simultaneously affect individuals' nutritional status, mental health, and sleep quality. This implied that during the daily treatment and care of malnourished stoma patients, attention should devoted not only to nutritional status but also to their psychological status and sleep condition. Future research should consider implementing interventions from psychological and sleep perspectives to improve patients' nutritional status. The pain symptoms in this group were at an extremely low level, potentially due to two reasons: ① malnutrition leads to reduced physical condition and cognitive function, thereby reducing patients' sensitivity and perception of pain; ②negative emotions, psychological stress, and sleep disturbance may cause patients to overinterpret pain or exhibit fear-related avoidance behaviors, thus consequently leading them to deliberately refrain from reporting high pain scores [27]. Therefore, in clinical practice, effective pain assessment and management should be implemented for such patients, and pain education should be emphasized. In the "suboptimal nutrition-higher symptom cluster response group (C2)", patients' symptoms were at a relatively elevated level, and the loss of appetite was significantly higher compared to that of other groups. This suggests that in the daily treatment and care of such patients, attention should be paid to psychological care and pain management, and various strategies, such as increasing the variety of the diet, using seasonings appropriately, and having small and frequent meals, should be adopted to encourage patients to eat so as to prevent the deterioration of their nutritional status. If the loss of appetite, nausea, and vomiting are induced by chemotherapy and other treatments, appetite stimulants and antiemetics can be administered as prescribed to promote patients' food intake [28]. For the "moderate nutrition-moderate symptom cluster response group (C3)", it is evident that some patients, despite not being malnourished, may have a higher level of anxiety. This can be attributed to factors such as a limited understanding of the disease, prognosis, and treatment, fear of recurrence and death, the economic and physical burden of the disease, pain, and lack of social support [29]. This indicated that when dealing with these patients, the causes of anxiety should be understood, and formulate corresponding strategies for psychological counseling. Patient education and social support should also be emphasized. Regarding the "well-nourished-low symptom cluster response group (C4)", although patients' other symptoms were at a low level, anxiety, depression, and sleep disturbance still posed certain challenges. This indicated that even when patients have a good nutritional status, their psychological state and sleep condition should not be ignored. Clinically, nurses should be encouraged to communicate with patients appropriately during the care process to understand their immediate and potential needs [30]. Influencing Factors of Latent Categories of Nutritional Status-Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer The multivariate analysis conducted in this study demonstrated that the presence of chronic diseases and tumor location were significant factors influencing the latent categories of nutritional status-symptom clusters in preventive enterostomy patients with colorectal cancer. The absence of other chronic diseases serves as a protective factor for the well-nourished-low symptom cluster response. Cancer itself is a chronic consumptive disease, and other chronic diseases, such as diabetes and chronic kidney disease, can further deteriorate patients' nutritional status and impose more stringent dietary restrictions[31], This, in turn, increases the risk of malnutrition and contributes to the development of adverse psychological and deteriorate states. Colon cancer patients are more susceptible to malnutrition and symptom clusters compared to rectal cancer patients, which is consistent with previous consensus [32]. On one hand, colon cancer typically occurs in the right colon, whereas rectal cancer is located in the left colon. Since the right colon is mainly responsible for water absorption and fecal concentration, its lesions often lead to more severe diarrhea and ascites, which increases the risk of malabsorption. On the other hand, lesions in the right colon may also cause more obvious symptoms such as loss of appetite, nausea, vomiting, and negative emotions, as well as intestinal dysfunction and symptom clusters, which directly affect patients' dietary intake and nutritional status, either directly or indirectly contributing to the emergence and progression of symptom clusters. Furthermore, during data analysis, it was noted that "gender" and "tumor stage" showed statistical significance in univariate analysis but not in multivariate analysis, this phenomenon can also observed in Pan's study [33]. This discrepancy may stem from the fact that univariate analysis examines the relationship between the individual variables and outcomes in isolation, without accounting for variable interactions or confounding effects [34]. In this study, "gender" and "tumor stage" might have exhibited collinearity or interaction with other variables (e.g., chronic diseases, tumor location) during the univariate phase, leading to their significance being overshadowed or diluted by these covariates. In multivariate analysis, the independent effect of "gender" and "tumor stage" could be weakened due to synergistic interactions with the "presence of chronic diseases" or "tumor location"(for example, advanced-stage patients are more prone to comorbidities), thereby rendering them statistically nonsignificant. These findings suggested that the retained variables in multivariate analysis—"presence of chronic diseases" and "tumor location"—hold greater clinical value and should be prioritized in clinical interventions and nursing care. Meanwhile, the roles of "gender" and "tumor stage" required cautious interpretation, and future studies could employ subgroup analyses or larger sample sizes to elucidate their potential effects. Limitations This study has several limitations. Firstly, it was confined to surveying preventive enterostomy patients with colorectal cancer in three tertiary hospitals in Fujian Province. This limitation may introduce a certain degree of selection bias, and the generalization of the research findings requires further verification. Secondly, as a cross-sectional survey, this study is unable to establish a causal relationship between variables or observe the temporal changes in symptom clusters. Implications for clinical practice and future research Despite the limitations of the study's conclusions, they may still offer some valuable insights. In clinical practice, when managing the nutritional status of colorectal cancer patients with preventive enterostomy, different priorities should be set to avoid adverse events according to the different characteristics of the nutritional status and symptoms of colorectal cancer patients with preventive enterostomy. For patients with good nutritional status, healthcare professionals should focus not only on disease education but also on addressing sleep-related issues. For those with moderate or poor nutritional status, their psychological well-being should be closely monitored. In the case of malnourished patients, healthcare professionals should enhance both physical and psychological care and provide appropriate pain education. This study provides valuable insights for future research, which is essential to advance our understanding of the complex relationship between nutrition and symptomatology in colorectal cancer patients with preventive enterostomy. For instance, qualitative approaches should be incorporated to investigate patients' subjective experiences of symptom clusters in various nutritional states. Machine learning-based methods could also be utilized to identify early biomarkers of these clusters, aiding in the prediction of nutritional risks. Furthermore, longitudinal studies are recommended to track the dynamic trajectories of symptom clusters alongside nutritional changes over time, thereby facilitating timely clinical interventions. These methodological approaches will collectively enhance our ability to predict and manage nutritional risks in colorectal cancer patients, ultimately improving their clinical outcomes. Conclusion This study revealed that, irrespective of their nutritional status, patients with preventive enterostomy exhibited diverse physiological-psychological symptoms. Moreover, the presence of chronic diseases and tumor location were significant factors influence their classification. This finding implies that medical staff should not only assess patients' nutritional status in clinical care but also pay close attention to the manifestation of their symptom clusters and take appropriate measures to alleviate them. Declarations Funding This research was supported by Innovative Training Project for College Students in Fujian Province in 2024, with the grant number [S202410393027] and Nursing Research Project of Zhongshan Hospital Affiliated to Xiamen University, with the grant number [2023zsyyhlky-013]. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted Ethics Committee of Zhongshan Hospital Affiliated to Xiamen University, Fujian Province (Approval No.: Xiamen Zhongshan Medical University 2022-140). Consent to participate Informed consent was obtained from all individual participants involved in the study Consent for publication Participants signed informed consent form regarding publishing their data Conflict of interest The authors declare that there are no competing interests. Author Contribution All authors contributed to this study. Study concept and material preparation were performed by L Y and RJ L. Patient recruitment and data collection were performed by L L and T Z. Data analysis were performed by RJ L, Xl W, Yp Y. The first draft of the manuscript was written by RJ L, Xl W, Jy L and Wn Wang. L Y, Gz W and Yh X reviewed and critically revised the important knowledge contents of the manuscript, and all authors read and approved the final manuscript. In addition, L L and Rj L made the same contribution to this manuscript, so they are tied as the first author. Data Availability Data is provided within the manuscript or supplementary information files References Chinese Medical Association Colorectal Cancer Branch Stoma Professional Committee, Chinese Medical Association Colorectal Cancer Branch, Chinese Medical Association Surgery Branch Colorectal Surgery Group, et al. Chinese Expert Consensus on Preventive Enterostomy for Middle and Low Rectal Cancer Surgery (2022 Edition) [J]. Chinese Journal of Gastrointestinal Surgery, 2022, 25(6): 471-478. doi:10.3760/cma.j.cn441530-20220421-00169. Gu Lei, An Yongbo, Ren Mingyang, et al. Incidence and Risk Factors of Anastomotic Leakage After Transanal Total Mesorectal Excision in China: A Retrospective Analysis Based on the National Collaborative Research Database [J]. Chinese Journal of Gastrointestinal Surgery, 2021, 24(6): 505-512. doi:10.3760/cma.j.cn.441530-20210226-00084. Penna M, Hompes R, Arnold S, et al. Incidence and Risk Factors for Anastomotic Failure in 1594 Patients Treated by Transanal Total Mesorectal Excision: Results From the International TaTME Registry. Ann Surg. 2019;269(4):700-711. doi:10.1097/SLA.0000000000002653 Selimoglu MA, Kansu A, Aydogdu S, et al. Nutritional Support in Malnourished Children With Compromised Gastrointestinal Function: Utility of Peptide-Based Enteral Therapy. Front Pediatr. 2021;9:610275. Published 2021 Jun 7. doi:10.3389/fped.2021.610275 Qi Yang, Wang Xuan, Liu Feng, et al. Analysis of the Correlation Between Peristomal Skin Condition and Nutrition in Colorectal Cancer Stoma Patients [J]. Integrated Traditional Chinese and Western Medicine Nursing (Chinese and English), 2020, 6(5): 1-5. doi:10.11997/nitcwm.202005001. Hubert M, Gabriel D, El Khouda S, et al. Energy and Protein Intake After Return Home in Colorectal Surgery Patients With an Enhanced Recovery Program: A Prospective Observational Study. Nutr Clin Pract. 2021;36(3):639-647. doi:10.1002/ncp.10617 Choudhary M, Kaur H. Experiences of Living with Intestinal Ostomy: A Qualitative Meta-Synthesis. Indian J Palliat Care. 2020;26(4):421-427. doi:10.4103/IJPC.IJPC_21_20 Li Wei, Zhang Wenbin, Li Wei, et al. Analysis of Postoperative Anxiety and Depression Status and Influencing Factors in Preventive Enterostomy Patients [J]. International Journal of Psychiatry, 2024, 51(02): 606-609. doi:10.13479/j.cnki.jip.2024.02.077. Song Chunhua, Wang Kunhua, Guo Zengqing, et al. Nutritional status of common malignant tumor patients in China [J]. China Science (Life Sciences), 2020, 50 (12):1437-1452. doi:10.1360/SSV-2020-0297. Cintoni M, Palombaro M, Raoul P, Chiloiro G, Romano A, Meldolesi E, De Giacomo F, Leonardi E, Egidi G, Grassi F, Pulcini G, Rinninella E, Capristo E, Gasbarrini A, Gambacorta MA, Mele MC. Assessing Quality of Life with the Novel QLQ-CAX24 Questionnaire and Body Composition Parameters in Rectal Cancer Patients: A Single-Center Prospective Study. Nutrients. 2024 Dec 11;16(24):4277. doi: 10.3390/nu16244277. PMID: 39770899; PMCID: PMC11678168. Xiao W, Chan CWH, Fan Y, et al. Symptom Clusters in Patients with Nasopharyngeal Carcinoma During Radiotherapy. Eur J Oncol Nurs. 2017;28:7-13. doi:10.1016/j.ejon.2017.02.004 Wang Y, Lu Q, Zhang L, et al. Nutrition Impact Symptom Clusters in Patients With Head and Neck Cancer Receiving Concurrent Chemoradiotherapy. J Pain Symptom Manage. 2021;62(2):277-285. doi:10.1016/j.jpainsymman.2020.12.013 Løhre ET, Solheim TS, Jakobsen G, Vagnildhaug OM, Schmidberger Karlsen TL, Habberstad RH, Balstad TR, Thronæs M. Parenteral Nutrition in Palliative Cancer Care: Detrimental, Futile, or Beneficial? Curr Oncol. 2024 May 11;31(5):2748-2757. doi: 10.3390/curroncol31050208. PMID: 38785489; PMCID: PMC11120543. Sheas MN, Ali SR, Safdar W, et al. Nutritional Assessment in Cancer Patients. Cancer Treat Res. 2023;185:285-310. doi:10.1007/978-3-031-27156-4_14 Molassiotis A, Farrell C, Bourne K, Brearley SG, Pilling M. An Exploratory Study to Clarify the Cluster of Symptoms Predictive of Chemotherapy-Related Nausea Using Random Forest Modeling. J Pain Symptom Manage. 2012 Nov;44(5):692-703. doi: 10.1016/j.jpainsymman.2011.11.003. Epub 2012 Jun 5. PMID: 22672920. Bergsneider BH, Armstrong TS, Conley YP, Cooper B, Hammer M, Levine JD, Paul S, Miaskowski C, Celiku O. Symptom Network Analysis and Unsupervised Clustering of Oncology Patients Identifies Drivers of Symptom Burden and Patient Subgroups With Distinct Symptom Patterns. Cancer Med. 2024 Oct;13(19):e70278. doi: 10.1002/cam4.70278. PMID: 39377555; PMCID: PMC11460217. Kamata A, Kara Y, Patarapichayatham C, Lan P. Evaluation of Analysis Approaches for Latent Class Analysis with Auxiliary Linear Growth Model. Front Psychol. 2018;9:130. Published 2018 Feb 22. doi:10.3389/fpsyg.2018.00130 Chinese Medical Association Radiation Oncology Branch. Expert Consensus on Standardized Management of Radiotherapy Nutrition [J]. Chinese Journal of Radiation Oncology, 2020, 29(5): 324-331. doi:10.3760/cma.j.cn113030-20191212-00002. Xiao Shunzhen. Nursing Research [M]. Version 3. People's Health Publishing House, 2006:54. Chen Jie, Wu Xiaoying, Zhan Ying, et al. Development and Reliability and Validity Test of the Chinese Version of the Adult Pain Behavior Scale [J]. Chinese Journal of Pain Medicine, 2016, 22(1): 28-33. doi:10.3969/j.issn.1006-9852.2016.01.007. HAMILTON M. The assessment of anxiety states by rating. Br J Med Psychol. 1959;32(1):50-5. doi: 10.1111/j.2044-8341.1959.tb00467.x. PMID: 13638508. HAMILTON M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960 Feb;23(1):56-62. doi: 10.1136/jnnp.23.1.56. PMID: 14399272; PMCID: PMC495331. Soldatos CR, Dikeos DG, Paparrigopoulos TJ. Athens Insomnia Scale: Validation of an Instrument Based on ICD-10 Criteria. J Psychosom Res. 2000;48(6):555-560. doi:10.1016/s0022-3999(00)00095-7 Halliday V, Porock D, Arthur A, Manderson C, Wilcock A. Development and Testing of a Cancer Appetite and Symptom Questionnaire. J Hum Nutr Diet. 2012;25(3):217-224. doi:10.1111/j.1365-277X.2012.01233.x Mello MRSP, Moura SF, Muzi CD, GuimarÃes RM. CLINICAL EVALUATION AND PATTERN OF SYMPTOMS IN COLORECTAL CANCER PATIENTS. Arq Gastroenterol. 2020 Apr-Jun;57(2):131-136. doi: 10.1590/s0004-2803.202000000-24. PMID: 32401950. Hwang G, Cho YH, Kim EJ, et al. Differential Effects of Sleep Disturbance and Malnutrition on Late-Life Depression Among Community-Dwelling Older Adults. Front Psychiatry. 2022;13:820427. Published 2022 May 6. doi:10.3389/fpsyt.2022.820427 Yuan Y, Schreiber K, Flowers KM, et al. The Relationship Between Emotion Regulation and Pain Catastrophizing in Patients with Chronic Pain. Pain Med. 2024;25(7):468-477. doi:10.1093/pm/pnae009 Herrstedt J, Clark-Snow R, Ruhlmann CH, Molassiotis A, Olver I, Rapoport BL, Aapro M, Dennis K, Hesketh PJ, Navari RM, Schwartzberg L, Affronti ML, Garcia-Del-Barrio MA, Chan A, Celio L, Chow R, Fleury M, Gralla RJ, Giusti R, Jahn F, Iihara H, Maranzano E, Radhakrishnan V, Saito M, Sayegh P, Bosnjak S, Zhang L, Lee J, Ostwal V, Smit T, Zilic A, Jordan K, Scotté F; participants of the MASCC/ESMO Consensus Conference 2022. Electronic address: [email protected] . 2023 MASCC and ESMO guideline update for the prevention of chemotherapy- and radiotherapy-induced nausea and vomiting. ESMO Open. 2024 Feb;9(2):102195. doi: 10.1016/j.esmoop.2023.102195IF: 7.1 Q1 . Epub 2024 Jan 11. PMID: 38458657; PMCID: PMC10937211. Yuan P, Wang D, Xie D. Anxiety and Depression After Colorectal Cancer Surgery: A Systematic Review and Meta-Analysis of Short- and Long-Term Outcomes. Alpha Psychiatry. 2024;25(4):429-439. Published 2024 Aug 1. doi:10.5152/alphapsychiatry.2024.231359 Liu Dandan. The Impact of Nursing Intervention Guided by Maslow's Hierarchy of Needs Theory on Self-Care Ability and Complications in Patients After Enterostomy [J]. Diabetes World, 2023(1): 249-250. doi:10.3969/j.issn.1672-7851.2023.01.125. McGovern J, Dolan RD, Skipworth RJ, Laird BJ, McMillan DC. Cancer cachexia: a nutritional or a systemic inflammatory syndrome? Br J Cancer. 2022 Aug;127(3):379-382. doi: 10.1038/s41416-022-01826-2. Epub 2022 May 6. PMID: 35523879; PMCID: PMC9073809. Cancer Nutrition Committee of China Anti-Cancer Association, Parenteral and Enteral Nutrition Society of Chinese Medical Association. Expert consensus on nutritional therapy for colorectal cancer patients [J]. Electronic Journal of Oncology Metabolism and Nutrition, 2022, 9 (6):735-740. doi:10.16689/j.cnki.cn11-9349/r.2022.06.009. Pan XT, Lu Y, Cheng X, et al. Investigation and analysis of hemoglobin changes and anemia in cancer patients before and after treatment [J]. Chinese Journal of Cancer Prevention and Treatment, 2008, 15 (20):1540- 1543. doi:10.16073/j.cnki.cjcpt.2008.20.006. Dai Jinhui, Yuan Jing. Comparison of one-way ANOVA and multiple linear regression test methods [J]. Statistics and Decision Making, 2016,(09):23-26. doi:10.13546/j.cnki.tjyjc.2016.09.005. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6188108","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":427749594,"identity":"08b6ab5e-c9ae-4349-88eb-73f605df552e","order_by":0,"name":"Rujia Lin","email":"","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Rujia","middleName":"","lastName":"Lin","suffix":""},{"id":427749595,"identity":"7c5d01c2-e2de-4f3b-9129-85ed8b0f80bb","order_by":1,"name":"Lan Li","email":"","orcid":"","institution":"Zhongshan Hospital Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Lan","middleName":"","lastName":"Li","suffix":""},{"id":427749596,"identity":"43feb337-362b-429f-9cbe-64ed44aae40f","order_by":2,"name":"Xinlei Wu","email":"","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xinlei","middleName":"","lastName":"Wu","suffix":""},{"id":427749597,"identity":"95e7639a-d927-4e57-b17f-70aec106fd05","order_by":3,"name":"Ting Zhang","email":"","orcid":"","institution":"Zhangzhou Health Vocational College","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Zhang","suffix":""},{"id":427749598,"identity":"f410ee50-46ba-42c7-b25d-ea1616105ce3","order_by":4,"name":"Weina Wang","email":"","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Weina","middleName":"","lastName":"Wang","suffix":""},{"id":427749599,"identity":"a861ce05-5262-4c5c-8d10-3a121004fdcc","order_by":5,"name":"Jiayi Lin","email":"","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiayi","middleName":"","lastName":"Lin","suffix":""},{"id":427749600,"identity":"df62bc48-7688-4e3c-83d7-26be209ecba9","order_by":6,"name":"Guizhen Wen","email":"","orcid":"","institution":"Fujian Medical University Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Guizhen","middleName":"","lastName":"Wen","suffix":""},{"id":427749601,"identity":"4cf3c14a-1eea-4968-b162-8c4305230303","order_by":7,"name":"Yuhong Xie","email":"","orcid":"","institution":"Fujian Medical University Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuhong","middleName":"","lastName":"Xie","suffix":""},{"id":427749603,"identity":"2cae33fa-51c8-444a-bd85-3fb81e3951be","order_by":8,"name":"Yiping Yang","email":"","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yiping","middleName":"","lastName":"Yang","suffix":""},{"id":427749604,"identity":"2e65b12f-9eb2-4bd2-8288-84bb1bd6a384","order_by":9,"name":"Yang Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3QvQrCMBDA8SuBuhRdK8WPR4gEqqD4LBXBLlEcHQuuxd236Bt4ksFF6dqxLuLgUHQVNFbntG6C+UMgw/3gEgCd7ldLKTQrAeZ3IyhFPArMQvEVARiFSEoSujuIszcXfmjE22sCg0aE5JQqyX426XlUTEMQxOEwYRGaXaokyF36IhsQJuEgRhFapq0k8SUnvvUmjxIk4SyVxPsQLCb15OLKT/Y78i3M4XTM1sJ0laQac5Zl937LsrfHG18MG6vd8qQkbYTPGja+9pSHqOZlrQBIlt9qQcGoTqfT/W1PWGNNcbaAQ4cAAAAASUVORK5CYII=","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Yang","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-03-09 10:23:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6188108/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6188108/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78690851,"identity":"d0ceaeff-d93e-494e-8c56-307c70d9a36a","added_by":"auto","created_at":"2025-03-17 16:15:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37154,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLatent Category Diagram of Nutritional Status-Related Symptom Clusters in Preventive Enterostomy Patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6188108/v1/30734472f1ba60a96715438a.png"},{"id":83718181,"identity":"26ebae7a-f6f6-4967-a099-7f7c3cbf6b47","added_by":"auto","created_at":"2025-06-01 01:16:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1399134,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6188108/v1/d6ff0d69-b7e0-4f82-9441-5c9a8de680cb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Latent class analysis of symptom clusters in preventive enterostomy with colorectal cancer patients based on nutritional status","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePreventive enterostomy, also known as a protective or diversion stoma, involves the surgical fixation of the intestine to the abdominal wall to create a temporary end ileostomy or transverse colostomy, which diverts feces to reduce the incidence of postoperative anastomotic leakage and the risk of abdominal and pelvic infections and abscesses [1]. It is widely used in sphincter-preserving surgery for low rectal cancer and acute obstructive colorectal cancer surgery. The clinical utilization rate of preventive enterostomy in China ascended from 49.6% in 2019 to 62.8% in 2021 [2], and in some countries, it even reached 88%-100% [3]. However, owing to partial intestinal resection and changes in intestinal structure, enterostomy may cause intestinal dysfunction, nutrient loss, malabsorption, and dietary restrictions, which lead to malnutrition [4]. The incidence of malnutrition in stoma patients is higher than that in general colorectal cancer surgery patients, ranging from 61.4\u0026ndash;90.91% [5\u0026ndash;7]. Additionally, cancer patients often experience a series of physical and psychological disorders during treatment, such as anxiety, depression, aches, sleep disturbances, and loss of appetite. These symptoms occur concurrently and are interrelated, forming different symptom cluster synergistic effects, collectively referred to as \"symptom clusters\". The phenomenon of symptom clusters is also prevalent in enterostomy patients [8]. Consequently, managing symptom clusters in preventive enterostomy patients has always been a hot topic in clinical research.\u003c/p\u003e \u003cp\u003eCurrently, the association between the nutritional status of cancer patients and disease symptoms has been widely concerned. A large-scale survey on the nutritional status of patients with common malignant tumors in China indicated that symptom clusters (such as appetite loss and nausea) would directly affect nutritional intake, while deterioration of nutritional status would aggravate symptoms through immunosuppression, metabolic disorder, and other channels [9]. In addition, several studies [10\u0026ndash;12] demonstrated that there is a positive correlation between weight loss, weight loss rate, or other nutrition-related indicators with the severity of symptom clusters, and with appropriate nutritional support, symptom clusters can also be notably ameliorated [13].\u003c/p\u003e \u003cp\u003eNutritional status is the outcome of the result of multi-factor comprehensive influence [14]. Although it has also been pointed out in the literature that the severity of symptom groups can predict the change in the nutritional status of patients [15], the heterogeneity of disease symptom groups among individuals under nutritional status has not been taken into account yet. In fact, even under the same nutritional status assessment, the characteristics of symptom clusters may differ owing to patients' sociodemographic factors, disease conditions, and treatment modalities [16]. Identifying the differences in symptom cluster characteristics in different nutritional statuses is of great significance for selecting targeted interventions in clinical practice. Thus, it is necessary to explore the differences in symptom clusters.\u003c/p\u003e \u003cp\u003eLatent class analysis (LCA) is a statistical method employed to discover the latent structure of data, concentrating on classifying and identifying unobserved latent categories or subgroups in the data. This method elucidates the relationships between observed categorical variables by estimating the probability of each individual belonging to each latent category, thereby revealing hidden structures in the data [17]. Latent class analysis offers a new perspective for research on nutrition and symptom clusters in preventive enterostomy patients. This study aims to utilize latent class analysis to explore the \"pain-anxiety-depression-sleep disturbance-loss of appetite\" symptom cluster based on nutritional status classification, and to clarify the relationship between influencing factors and latent categories of symptom clusters, thereby providing theoretical support for personalized nutrition and symptom management in these patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Subjects and Sample Size Calculation\u003c/h2\u003e \u003cp\u003eThis cross-sectional study adopted convenience sampling to recruit colorectal cancer patients with preventive enterostomy from the gastrointestinal surgery departments of Zhongshan Hospital Affiliated to Xiamen University, Fujian Cancer Hospital, and the 909th Hospital of the Joint Logistics Support Force of the People's Liberation Army in Fujian Province from March 2022 to August 2023. Inclusion criteria: ① Patients must meet the diagnostic criteria for primary colorectal cancer and with preventive enterostomy during tumor resection; ② Patients should be at least 18 years old; ③ Patients are conscious and capable of completing the study; ④ Patients and their families are informed and agree to participate in the study. Exclusion criteria: ① Combined with or previously diagnosed with primary malignant tumors in other locations; ② Combined with hyperthyroidism, tuberculosis, and other consumptive diseases; ③ Complicated with other severe acute diseases and other chronic diseases without treatment. Nutritional status assessment criteria: Nutritional risk was screened using NRS2002(Nutritional Risk Screening 2002). A score of less than 3 points indicated no or potential malnutrition risk. Conversely, a score of 3 points or more indicated that the nutritional assessment should be conducted using the PG-SGA ༈Patient-Generated Subjective Global Assessment༉scale [18]. This study has been approved by the Ethics Committee of Zhongshan Hospital Affiliated to Xiamen University (Ethics Approval No.: XZSYY 2022\u0026thinsp;\u0026minus;\u0026thinsp;140).\u003c/p\u003e \u003cp\u003eAccording to the sample size calculation formula for measurement data n\u0026thinsp;=\u0026thinsp;Z\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eα/2\u003c/sub\u003e p (1 - p) / δ\u003csup\u003e2\u003c/sup\u003e [19], where α\u0026thinsp;=\u0026thinsp;0.05 and Z\u003csub\u003eα/2\u003c/sub\u003e = 1.96; based on previous research results, the average incidence of malnutrition in preventive enterostomy patients with colorectal cancer is 76%, with a permissible error δ of 0.06, considering a 15% attrition rate, the final calculated sample size is at least 276 cases.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResearch Tools\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGeneral Information Questionnaire\u003c/h2\u003e \u003cp\u003eDesigned through a comprehensive literature review and consultation with clinical nursing experts, including demographic and disease-related information. Demographic information includes age, gender, education level, marital status, monthly income, chronic diseases, and disease-related information, including tumor location, tumor stage, stoma site, chemotherapy or not, radiotherapy or not.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChinese Version of the Adult Pain Behavior Scale (APBS)\u003c/h3\u003e\n\u003cp\u003e The APBS was developed by a group of Chinese experts based on literature review and existing objective pain assessment tools, taking into account China's national conditions. It includes five items: facial expression, rest state, muscle tension, soothing effect, and vocalization., each scored 0\u0026ndash;2, with a total score of 0\u0026ndash;10. Higher scores indicate more severe pain [20]. The Cronbach's α of this scale was 0.733.\u003c/p\u003e\n\u003ch3\u003eHamilton Anxiety Scale (HAMA)\u003c/h3\u003e\n\u003cp\u003eThe HAMA, developed by Hamilton, assesses anxiety levels in both psychological and somatic dimensions, each dimension contains seven items. Each item is scored 0\u0026ndash;4, with a total score of 56. A score of less than 7 indicates no anxiety, 7\u0026ndash;14 indicates possible anxiety, 15\u0026ndash;21 indicates anxiety, 22\u0026ndash;28 indicates significant anxiety, and a score greater than 28 indicates severe anxiety [21]. The Cronbach's α of this scale was 0.856.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHamilton Depression Scale (HAMD)\u003c/h2\u003e \u003cp\u003eThe HAMD comprises seven dimensions: physical condition, cognitive status, recent weight changes, diurnal variation, psychomotor retardation, sleep condition, and hopelessness, with 24 items. Fourteen items are scored 0\u0026ndash;4, and ten items are scored 0\u0026ndash;2, with a total score of 0\u0026ndash;76. A score of 7 or less indicates no depression, 8\u0026ndash;20 indicates possible depression, 21\u0026ndash;35 indicates depression, and a score greater than 35 indicates severe depression [22]. The Cronbach's α of this scale was 0.870.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAthens Insomnia Scale (AIS)\u003c/h3\u003e\n\u003cp\u003eDesigned by Soldatos et al [23], the AIS is utilized for self-assessment of sleep disorders, including eight items: sleep induction, nocturnal awakening, early morning awakening, sleep satisfaction, sleep quality impact, daytime sleepiness, etc. Each item is scored 0\u0026ndash;3, with a total score of 0\u0026ndash;24. A score of 3 or less indicates no sleep disorder, 4\u0026ndash;6 indicates suspected insomnia, and a score of 7 or more indicates insomnia. The Cronbach's α of this scale was 0.875.\u003c/p\u003e\n\u003ch3\u003eCancer Appetite and Symptom Questionnaire (CASQ)\u003c/h3\u003e\n\u003cp\u003eThe CASQ was developed by Professor V. Halliday from the Department of Nutrition at the University of Nottingham, based on the Common Nutritional Appetite Questionnaire (CNAQ) [24]. The questionnaire is composed of 12 items, each scored 0\u0026ndash;4, with a total score of 0\u0026ndash;48. Lower scores indicate worse appetite, with a score of 30 or less indicating loss of appetite and a score greater than 30 indicating normal appetite. The Cronbach's α of this scale was 0.820.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Collection and Quality Control\u003c/h2\u003e \u003cp\u003ePrior to filling out the questionnaire, trained research team members employed uniform instructions to elucidate the purpose and significance of the survey to the subjects. The questionnaires were distributed by research team members and completed independently by the patients. The questionnaires were collected on the spot, and any missing items were checked and supplemented by the subjects. A total of 360 questionnaires were distributed, and 350 valid questionnaires were collected, with a valid questionnaire recovery rate of 97.22%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData Analyses\u003c/h2\u003e \u003cp\u003eThe collected data were double-entered into the database and verified to ensure accuracy. Normally distributed measurement data were described using mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation; count data or grade data were presented as frequency and percentage. We utilized Mplus 8.3 software for exploratory latent profile analysis to classify the symptom clusters of preventive enterostomy patients. Model fit evaluation indicators included: ① Akaike Information Criterion (AIC), with smaller values indicating better fit; ② Bayesian Information Criterion (BIC), with smaller values denoted better fit, generally choosing the model with the smallest BIC as the optimal model; ③ Entropy index, the most sensitive indicator for judging model classification error rate, ranging from 0 to 1, with values closer to 1 indicating more accurate model classification. If the entropy value was greater than 0.7, the model classification accuracy is good; ④ Bootstrapped Likelihood Ratio Test (BLRT) and Lo-Mendell-Rubin (LMR) likelihood ratio tests were used for model comparison, with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating rejection of the k-1 category model and support for the k category model.\u003c/p\u003e \u003cp\u003eFinally, based on the latent class analysis results, we determined the optimal classification model of nutritional status-symptom clusters in preventive enterostomy patients with colorectal cancer, and then used SPSS 26.0 software for multivariate logistic regression analysis to explore the influencing factors of latent categories in preventive enterostomy patients with colorectal cancer.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLatent Class Analysis of Nutritional Status-Related Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer\u003c/h2\u003e \u003cp\u003eBased on the principles of lower AIC, BIC, and aBIC values, higher entropy (\u0026ge;\u0026thinsp;0.7), and statistically significant BLRT and LMR, this study explored four latent category models. Commencing with a single category, the number of categories was incrementally increased sequentially.. As the number of categories increased, the AIC, BIC, and aBIC values gradually decreased, and the entropy value also showed an upward trend. Nevertheless, given that the \u003cem\u003eP\u003c/em\u003e values of the BLRT for the three-category and five-category models were greater than 0.05, the model fit was not suitable (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After a comprehensive comparison, the final fitting model was determined to have four categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After determining the final fitting model with four categories, the belonging probabilities of the four latent categories were 0.736\u0026ndash;0.939, all greater than 70%, indicating reliable model classification (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLatent Class Fit Results of Nutritional Status in Preventive Enterostomy Patients (n\u0026thinsp;=\u0026thinsp;350)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber Of Categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eaBIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEntropy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBLRT(\u003cem\u003eP\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLMR(\u003cem\u003eP\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eclass probability\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2681.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2705.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2686.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2493.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2543.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2502.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.394/0.605\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2476.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2553.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2490.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.2286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.382/0.131/0.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2463.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2567.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2482.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.286/0.129/0.42/0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2460.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2591.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2483.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.186/0.09/0.409/0.14/0.174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAverage Belonging Probability Matrix of Each Latent Category\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCategory 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCategory 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of Latent Category Characteristics of Nutritional Status-Related Symptom Clusters in Preventive Enterostomy Patients\u003c/h2\u003e \u003cp\u003eThe latent category characteristics of nutritional status in patients are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Based on their characteristics, they were named as follows: Category 1 (C1, orange line) had a 100% probability of malnutrition or malnutrition risk, and the scores for \"depression\" and \"sleep disturbance\" were significantly higher than those of other groups. Thus, it was named the \"malnourished-high symptom cluster response group\"; Category 2 (C2, green line) had a 94.9% probability of malnutrition or malnutrition risk, and the scores for each symptom cluster were relatively high, so it was named the \"suboptimal nutrition-higher symptom cluster response group\"; Category 3 (C3, blue line) had a 35.6% probability of malnutrition or malnutrition risk, and the scores for each symptom cluster were moderate, so it was named the \"moderate nutrition-moderate symptom cluster response group\"; Category 4 (C4, yellow line) had a 1.6% probability of malnutrition or malnutrition risk, and the scores for each symptom cluster were low, so it was named the \"well-nourished-low symptom cluster response group.\"\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate Analysis of Latent Categories in Preventive Enterostomy Patients with Colorectal Cancer\u003c/h2\u003e \u003cp\u003eUnivariate analysis of variance showed that the distributions of gender, presence of chronic diseases, tumor location, and tumor stage among different latent category groups were statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMultivariate Analysis of Influencing Factors of Latent Categories of Nutritional Status-Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEach latent category was employed as the dependent variable (with the malnourished-high symptom cluster response group serving as the reference category). Factors that demonstrated statistical significance in the univariate analysis of variance were utilized as independent variables to construct an unordered multi-class logistic regression model for the purpose of multivariate analysis. The variable assignments were as follows: ① Gender: female was assigned a value of 0, and male was assigned a value of 1; ② Presence of chronic diseases: no\u0026thinsp;=\u0026thinsp;0, yes\u0026thinsp;=\u0026thinsp;1; ③ Tumor location: rectum\u0026thinsp;=\u0026thinsp;0, colon\u0026thinsp;=\u0026thinsp;1; ④ Tumor stage: stage II and below =\u0026thinsp;0, stage III and above =\u0026thinsp;1.\u003c/p\u003e \u003cp\u003eThe multivariate analysis revealed that the \"presence of chronic diseases\" and \"tumor location\" were significant factors influencing latent class categorization. Compared to the \"malnourished-high symptom cluster response group (C1)\", patients without chronic diseases had a higher likelihood of belonging to the \"moderate nutrition-moderate symptom cluster response group (C3)\" (OR\u0026thinsp;=\u0026thinsp;2.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.017). Meanwhile, patients with rectal tumors showed greater probabilities of being classified into the \"suboptimal nutrition-higher symptom cluster response group (C2)\" and \"moderate nutrition-moderate symptom cluster response group (C3)\" (OR\u0026thinsp;=\u0026thinsp;7.952, P\u0026thinsp;=\u0026thinsp;0.008; OR\u0026thinsp;=\u0026thinsp;2.261, P\u0026thinsp;=\u0026thinsp;0.026). These findings indicated that the absence of chronic diseases and rectal tumor location served as protective factors against malnutrition and severe symptom clusters in colorectal cancer patients with preventive enterostomy.. Details are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate Analysis of Latent Categories in Preventive Enterostomy Patients with Colorectal Cancer\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC2\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC3\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;147)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC4\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.582\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior High School And Below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School And Above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried Other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving With Others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLive Alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly Income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic Diseases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor Site\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRectum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor Stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage Ⅱ And Below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage Ⅲ And Above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStoma Site\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIleum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy Or Not?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003csub\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiotherapy Or Not?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/br\u003e\u003cp\u003e\u003cstrong\u003eTable 4. Multivariate analysis of potential categories of colorectal cancer patients with prevent colostomy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"753\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;Project\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 225px;\"\u003e\n \u003cp\u003eC4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 117px;\"\u003e\n \u003cp\u003e95%\u003cem\u003eCl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 114px;\"\u003e\n \u003cp\u003e95%\u003cem\u003eCl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 114px;\"\u003e\n \u003cp\u003e95%\u003cem\u003eCl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 57px;\"\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 style=\"width: 54px;\"\u003e\n \u003cp\u003eFloor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eUpper Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eFloor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eUpper Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eFloor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eUpper Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e1.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic Diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e＜0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e2.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor Site\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e7.952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e36.536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e2.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e4.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2.817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor Stage\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e2.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e4.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Gender is compared with \u0026quot;female\u0026quot;; presence of chronic diseases is compared with \u0026quot;yes\u0026quot;; tumor location is compared with \u0026quot;rectum\u0026quot;; tumor stage is compared with \u0026quot;stage III and above.\u0026quot;\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eDifferences in Nutritional Status-Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer\u003c/h2\u003e \u003cp\u003eThis study found that patients with preventive enterostomy for colorectal cancer exhibited diverse types of symptom clusters, which are in accordance with Mello's research [25]. Based on nutritional status, symptom clusters can be divided into four categories: the malnourished-high symptom cluster response group, the suboptimal nutrition-higher symptom cluster response group, the moderate nutrition-moderate symptom cluster response group, and the well-nourished-low symptom cluster response group, indicated heterogeneity among symptom cluster categories.\u003c/p\u003e \u003cp\u003eIn the \"malnourished-high symptom cluster response group (C1)\", patients' depression and sleep disturbance scores were significantly higher than those of other groups, this finding highlights a robust association between malnutrition and depression and sleep disturbance, as also reported in Hwang's research [26]. On the one hand, malnutrition may lead to brain dysfunction, including neurotransmitter imbalance, cognitive decline, and emotional regulation disorders, which increase the risk of depression. There exists a bidirectional relationship between depression, and sleep disturbance. Depressive symptoms can lead to a deterioration in sleep quality, and sleep disturbance can exacerbate depressive symptoms; on the other hand, depression and sleep disturbance share the multiple risk factors, such as social isolation, life stress, and disease burden, which may simultaneously affect individuals' nutritional status, mental health, and sleep quality. This implied that during the daily treatment and care of malnourished stoma patients, attention should devoted not only to nutritional status but also to their psychological status and sleep condition. Future research should consider implementing interventions from psychological and sleep perspectives to improve patients' nutritional status. The pain symptoms in this group were at an extremely low level, potentially due to two reasons: ① malnutrition leads to reduced physical condition and cognitive function, thereby reducing patients' sensitivity and perception of pain; ②negative emotions, psychological stress, and sleep disturbance may cause patients to overinterpret pain or exhibit fear-related avoidance behaviors, thus consequently leading them to deliberately refrain from reporting high pain scores [27]. Therefore, in clinical practice, effective pain assessment and management should be implemented for such patients, and pain education should be emphasized.\u003c/p\u003e \u003cp\u003eIn the \"suboptimal nutrition-higher symptom cluster response group (C2)\", patients' symptoms were at a relatively elevated level, and the loss of appetite was significantly higher compared to that of other groups. This suggests that in the daily treatment and care of such patients, attention should be paid to psychological care and pain management, and various strategies, such as increasing the variety of the diet, using seasonings appropriately, and having small and frequent meals, should be adopted to encourage patients to eat so as to prevent the deterioration of their nutritional status. If the loss of appetite, nausea, and vomiting are induced by chemotherapy and other treatments, appetite stimulants and antiemetics can be administered as prescribed to promote patients' food intake [28].\u003c/p\u003e \u003cp\u003eFor the \"moderate nutrition-moderate symptom cluster response group (C3)\", it is evident that some patients, despite not being malnourished, may have a higher level of anxiety. This can be attributed to factors such as a limited understanding of the disease, prognosis, and treatment, fear of recurrence and death, the economic and physical burden of the disease, pain, and lack of social support [29]. This indicated that when dealing with these patients, the causes of anxiety should be understood, and formulate corresponding strategies for psychological counseling. Patient education and social support should also be emphasized.\u003c/p\u003e \u003cp\u003eRegarding the \"well-nourished-low symptom cluster response group (C4)\", although patients' other symptoms were at a low level, anxiety, depression, and sleep disturbance still posed certain challenges. This indicated that even when patients have a good nutritional status, their psychological state and sleep condition should not be ignored. Clinically, nurses should be encouraged to communicate with patients appropriately during the care process to understand their immediate and potential needs [30].\u003c/p\u003e \u003cp\u003e \u003cb\u003eInfluencing Factors of Latent Categories of Nutritional Status-Symptom Clusters in Preventive Enterostomy Patients with Colorectal Cancer\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe multivariate analysis conducted in this study demonstrated that the presence of chronic diseases and tumor location were significant factors influencing the latent categories of nutritional status-symptom clusters in preventive enterostomy patients with colorectal cancer.\u003c/p\u003e \u003cp\u003eThe absence of other chronic diseases serves as a protective factor for the well-nourished-low symptom cluster response. Cancer itself is a chronic consumptive disease, and other chronic diseases, such as diabetes and chronic kidney disease, can further deteriorate patients' nutritional status and impose more stringent dietary restrictions[31], This, in turn, increases the risk of malnutrition and contributes to the development of adverse psychological and deteriorate states.\u003c/p\u003e \u003cp\u003eColon cancer patients are more susceptible to malnutrition and symptom clusters compared to rectal cancer patients, which is consistent with previous consensus [32]. On one hand, colon cancer typically occurs in the right colon, whereas rectal cancer is located in the left colon. Since the right colon is mainly responsible for water absorption and fecal concentration, its lesions often lead to more severe diarrhea and ascites, which increases the risk of malabsorption. On the other hand, lesions in the right colon may also cause more obvious symptoms such as loss of appetite, nausea, vomiting, and negative emotions, as well as intestinal dysfunction and symptom clusters, which directly affect patients' dietary intake and nutritional status, either directly or indirectly contributing to the emergence and progression of symptom clusters.\u003c/p\u003e \u003cp\u003eFurthermore, during data analysis, it was noted that \"gender\" and \"tumor stage\" showed statistical significance in univariate analysis but not in multivariate analysis, this phenomenon can also observed in Pan's study [33]. This discrepancy may stem from the fact that univariate analysis examines the relationship between the individual variables and outcomes in isolation, without accounting for variable interactions or confounding effects [34]. In this study, \"gender\" and \"tumor stage\" might have exhibited collinearity or interaction with other variables (e.g., chronic diseases, tumor location) during the univariate phase, leading to their significance being overshadowed or diluted by these covariates. In multivariate analysis, the independent effect of \"gender\" and \"tumor stage\" could be weakened due to synergistic interactions with the \"presence of chronic diseases\" or \"tumor location\"(for example, advanced-stage patients are more prone to comorbidities), thereby rendering them statistically nonsignificant. These findings suggested that the retained variables in multivariate analysis\u0026mdash;\"presence of chronic diseases\" and \"tumor location\"\u0026mdash;hold greater clinical value and should be prioritized in clinical interventions and nursing care. Meanwhile, the roles of \"gender\" and \"tumor stage\" required cautious interpretation, and future studies could employ subgroup analyses or larger sample sizes to elucidate their potential effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. Firstly, it was confined to surveying preventive enterostomy patients with colorectal cancer in three tertiary hospitals in Fujian Province. This limitation may introduce a certain degree of selection bias, and the generalization of the research findings requires further verification. Secondly, as a cross-sectional survey, this study is unable to establish a causal relationship between variables or observe the temporal changes in symptom clusters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eImplications for clinical practice and future research\u003c/h2\u003e \u003cp\u003eDespite the limitations of the study's conclusions, they may still offer some valuable insights. In clinical practice, when managing the nutritional status of colorectal cancer patients with preventive enterostomy, different priorities should be set to avoid adverse events according to the different characteristics of the nutritional status and symptoms of colorectal cancer patients with preventive enterostomy. For patients with good nutritional status, healthcare professionals should focus not only on disease education but also on addressing sleep-related issues. For those with moderate or poor nutritional status, their psychological well-being should be closely monitored. In the case of malnourished patients, healthcare professionals should enhance both physical and psychological care and provide appropriate pain education.\u003c/p\u003e \u003cp\u003eThis study provides valuable insights for future research, which is essential to advance our understanding of the complex relationship between nutrition and symptomatology in colorectal cancer patients with preventive enterostomy. For instance, qualitative approaches should be incorporated to investigate patients' subjective experiences of symptom clusters in various nutritional states. Machine learning-based methods could also be utilized to identify early biomarkers of these clusters, aiding in the prediction of nutritional risks. Furthermore, longitudinal studies are recommended to track the dynamic trajectories of symptom clusters alongside nutritional changes over time, thereby facilitating timely clinical interventions. These methodological approaches will collectively enhance our ability to predict and manage nutritional risks in colorectal cancer patients, ultimately improving their clinical outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that, irrespective of their nutritional status, patients with preventive enterostomy exhibited diverse physiological-psychological symptoms. Moreover, the presence of chronic diseases and tumor location were significant factors influence their classification. This finding implies that medical staff should not only assess patients' nutritional status in clinical care but also pay close attention to the manifestation of their symptom clusters and take appropriate measures to alleviate them.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was supported by Innovative Training Project for College Students in Fujian Province in 2024, with the grant number [S202410393027] and \u0026nbsp;Nursing Research Project of Zhongshan Hospital Affiliated to Xiamen University, with the grant number [2023zsyyhlky-013].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted Ethics Committee of Zhongshan Hospital Affiliated to Xiamen University, Fujian Province (Approval No.: Xiamen Zhongshan Medical University 2022-140).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants involved in the study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParticipants signed informed consent form regarding publishing their data\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to this study. Study concept and material preparation were performed by L Y and RJ L. Patient recruitment and data collection were performed by L L and T Z. Data analysis were performed by RJ L, Xl W, Yp Y. The first draft of the manuscript was written by RJ L, Xl W, Jy L and Wn Wang. L Y, Gz W and Yh X reviewed and critically revised the important knowledge contents of the manuscript, and all authors read and approved the final manuscript. In addition, L L and Rj L made the same contribution to this manuscript, so they are tied as the first author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChinese Medical Association Colorectal Cancer Branch Stoma Professional Committee, Chinese Medical Association Colorectal Cancer Branch, Chinese Medical Association Surgery Branch Colorectal Surgery Group, et al. Chinese Expert Consensus on Preventive Enterostomy for Middle and Low Rectal Cancer Surgery (2022 Edition) [J]. Chinese Journal of Gastrointestinal Surgery, 2022, 25(6): 471-478. doi:10.3760/cma.j.cn441530-20220421-00169.\u003c/li\u003e\n\u003cli\u003eGu Lei, An Yongbo, Ren Mingyang, et al. Incidence and Risk Factors of Anastomotic Leakage After Transanal Total Mesorectal Excision in China: A Retrospective Analysis Based on the National Collaborative Research Database [J]. Chinese Journal of Gastrointestinal Surgery, 2021, 24(6): 505-512. doi:10.3760/cma.j.cn.441530-20210226-00084.\u003c/li\u003e\n\u003cli\u003ePenna M, Hompes R, Arnold S, et al. Incidence and Risk Factors for Anastomotic Failure in 1594 Patients Treated by Transanal Total Mesorectal Excision: Results From the International TaTME Registry. Ann Surg. 2019;269(4):700-711. doi:10.1097/SLA.0000000000002653\u003c/li\u003e\n\u003cli\u003eSelimoglu MA, Kansu A, Aydogdu S, et al. Nutritional Support in Malnourished Children With Compromised Gastrointestinal Function: Utility of Peptide-Based Enteral Therapy. Front Pediatr. 2021;9:610275. Published 2021 Jun 7. doi:10.3389/fped.2021.610275\u003c/li\u003e\n\u003cli\u003eQi Yang, Wang Xuan, Liu Feng, et al. Analysis of the Correlation Between Peristomal Skin Condition and Nutrition in Colorectal Cancer Stoma Patients [J]. Integrated Traditional Chinese and Western Medicine Nursing (Chinese and English), 2020, 6(5): 1-5. doi:10.11997/nitcwm.202005001.\u003c/li\u003e\n\u003cli\u003eHubert M, Gabriel D, El Khouda S, et al. Energy and Protein Intake After Return Home in Colorectal Surgery Patients With an Enhanced Recovery Program: A Prospective Observational Study. Nutr Clin Pract. 2021;36(3):639-647. doi:10.1002/ncp.10617\u003c/li\u003e\n\u003cli\u003eChoudhary M, Kaur H. Experiences of Living with Intestinal Ostomy: A Qualitative Meta-Synthesis. Indian J Palliat Care. 2020;26(4):421-427. doi:10.4103/IJPC.IJPC_21_20\u003c/li\u003e\n\u003cli\u003eLi Wei, Zhang Wenbin, Li Wei, et al. Analysis of Postoperative Anxiety and Depression Status and Influencing Factors in Preventive Enterostomy Patients [J]. International Journal of Psychiatry, 2024, 51(02): 606-609. doi:10.13479/j.cnki.jip.2024.02.077.\u003c/li\u003e\n\u003cli\u003eSong Chunhua, Wang Kunhua, Guo Zengqing, et al. Nutritional status of common malignant tumor patients in China [J]. China Science (Life Sciences), 2020, 50 (12):1437-1452. doi:10.1360/SSV-2020-0297.\u003c/li\u003e\n\u003cli\u003eCintoni M, Palombaro M, Raoul P, Chiloiro G, Romano A, Meldolesi E, De Giacomo F, Leonardi E, Egidi G, Grassi F, Pulcini G, Rinninella E, Capristo E, Gasbarrini A, Gambacorta MA, Mele MC. Assessing Quality of Life with the Novel QLQ-CAX24 Questionnaire and Body Composition Parameters in Rectal Cancer Patients: A Single-Center Prospective Study. Nutrients. 2024 Dec 11;16(24):4277. doi: 10.3390/nu16244277. PMID: 39770899; PMCID: PMC11678168.\u003c/li\u003e\n\u003cli\u003eXiao W, Chan CWH, Fan Y, et al. Symptom Clusters in Patients with Nasopharyngeal Carcinoma During Radiotherapy. Eur J Oncol Nurs. 2017;28:7-13. doi:10.1016/j.ejon.2017.02.004\u003c/li\u003e\n\u003cli\u003eWang Y, Lu Q, Zhang L, et al. Nutrition Impact Symptom Clusters in Patients With Head and Neck Cancer Receiving Concurrent Chemoradiotherapy. J Pain Symptom Manage. 2021;62(2):277-285. doi:10.1016/j.jpainsymman.2020.12.013\u003c/li\u003e\n\u003cli\u003eL\u0026oslash;hre ET, Solheim TS, Jakobsen G, Vagnildhaug OM, Schmidberger Karlsen TL, Habberstad RH, Balstad TR, Thron\u0026aelig;s M. Parenteral Nutrition in Palliative Cancer Care: Detrimental, Futile, or Beneficial? Curr Oncol. 2024 May 11;31(5):2748-2757. doi: 10.3390/curroncol31050208. PMID: 38785489; PMCID: PMC11120543.\u003c/li\u003e\n\u003cli\u003eSheas MN, Ali SR, Safdar W, et al. Nutritional Assessment in Cancer Patients. Cancer Treat Res. 2023;185:285-310. doi:10.1007/978-3-031-27156-4_14\u003c/li\u003e\n\u003cli\u003eMolassiotis A, Farrell C, Bourne K, Brearley SG, Pilling M. An Exploratory Study to Clarify the Cluster of Symptoms Predictive of Chemotherapy-Related Nausea Using Random Forest Modeling. J Pain Symptom Manage. 2012 Nov;44(5):692-703. doi: 10.1016/j.jpainsymman.2011.11.003. Epub 2012 Jun 5. PMID: 22672920.\u003c/li\u003e\n\u003cli\u003eBergsneider BH, Armstrong TS, Conley YP, Cooper B, Hammer M, Levine JD, Paul S, Miaskowski C, Celiku O. Symptom Network Analysis and Unsupervised Clustering of Oncology Patients Identifies Drivers of Symptom Burden and Patient Subgroups With Distinct Symptom Patterns. Cancer Med. 2024 Oct;13(19):e70278. doi: 10.1002/cam4.70278. PMID: 39377555; PMCID: PMC11460217.\u003c/li\u003e\n\u003cli\u003eKamata A, Kara Y, Patarapichayatham C, Lan P. Evaluation of Analysis Approaches for Latent Class Analysis with Auxiliary Linear Growth Model. Front Psychol. 2018;9:130. Published 2018 Feb 22. doi:10.3389/fpsyg.2018.00130\u003c/li\u003e\n\u003cli\u003eChinese Medical Association Radiation Oncology Branch. Expert Consensus on Standardized Management of Radiotherapy Nutrition [J]. Chinese Journal of Radiation Oncology, 2020, 29(5): 324-331. doi:10.3760/cma.j.cn113030-20191212-00002.\u003c/li\u003e\n\u003cli\u003eXiao Shunzhen. Nursing Research [M]. Version 3. People\u0026apos;s Health Publishing House, 2006:54. \u003c/li\u003e\n\u003cli\u003eChen Jie, Wu Xiaoying, Zhan Ying, et al. Development and Reliability and Validity Test of the Chinese Version of the Adult Pain Behavior Scale [J]. Chinese Journal of Pain Medicine, 2016, 22(1): 28-33. doi:10.3969/j.issn.1006-9852.2016.01.007.\u003c/li\u003e\n\u003cli\u003eHAMILTON M. The assessment of anxiety states by rating. Br J Med Psychol. 1959;32(1):50-5. doi: 10.1111/j.2044-8341.1959.tb00467.x. PMID: 13638508.\u003c/li\u003e\n\u003cli\u003eHAMILTON M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960 Feb;23(1):56-62. doi: 10.1136/jnnp.23.1.56. PMID: 14399272; PMCID: PMC495331.\u003c/li\u003e\n\u003cli\u003eSoldatos CR, Dikeos DG, Paparrigopoulos TJ. Athens Insomnia Scale: Validation of an Instrument Based on ICD-10 Criteria. J Psychosom Res. 2000;48(6):555-560. doi:10.1016/s0022-3999(00)00095-7\u003c/li\u003e\n\u003cli\u003eHalliday V, Porock D, Arthur A, Manderson C, Wilcock A. Development and Testing of a Cancer Appetite and Symptom Questionnaire. J Hum Nutr Diet. 2012;25(3):217-224. doi:10.1111/j.1365-277X.2012.01233.x\u003c/li\u003e\n\u003cli\u003eMello MRSP, Moura SF, Muzi CD, Guimar\u0026Atilde;es RM. CLINICAL EVALUATION AND PATTERN OF SYMPTOMS IN COLORECTAL CANCER PATIENTS. Arq Gastroenterol. 2020 Apr-Jun;57(2):131-136. doi: 10.1590/s0004-2803.202000000-24. PMID: 32401950.\u003c/li\u003e\n\u003cli\u003eHwang G, Cho YH, Kim EJ, et al. Differential Effects of Sleep Disturbance and Malnutrition on Late-Life Depression Among Community-Dwelling Older Adults. Front Psychiatry. 2022;13:820427. Published 2022 May 6. doi:10.3389/fpsyt.2022.820427\u003c/li\u003e\n\u003cli\u003eYuan Y, Schreiber K, Flowers KM, et al. The Relationship Between Emotion Regulation and Pain Catastrophizing in Patients with Chronic Pain. Pain Med. 2024;25(7):468-477. doi:10.1093/pm/pnae009\u003c/li\u003e\n\u003cli\u003eHerrstedt J, Clark-Snow R, Ruhlmann CH, Molassiotis A, Olver I, Rapoport BL, Aapro M, Dennis K, Hesketh PJ, Navari RM, Schwartzberg L, Affronti ML, Garcia-Del-Barrio MA, Chan A, Celio L, Chow R, Fleury M, Gralla RJ, Giusti R, Jahn F, Iihara H, Maranzano E, Radhakrishnan V, Saito M, Sayegh P, Bosnjak S, Zhang L, Lee J, Ostwal V, Smit T, Zilic A, Jordan K, Scott\u0026eacute; F; participants of the MASCC/ESMO Consensus Conference 2022. Electronic address: [email protected]. 2023 MASCC and ESMO guideline update for the prevention of chemotherapy- and radiotherapy-induced nausea and vomiting. ESMO Open. 2024 Feb;9(2):102195. doi: 10.1016/j.esmoop.2023.102195IF: 7.1 Q1 . Epub 2024 Jan 11. PMID: 38458657; PMCID: PMC10937211.\u003c/li\u003e\n\u003cli\u003eYuan P, Wang D, Xie D. Anxiety and Depression After Colorectal Cancer Surgery: A Systematic Review and Meta-Analysis of Short- and Long-Term Outcomes. Alpha Psychiatry. 2024;25(4):429-439. Published 2024 Aug 1. doi:10.5152/alphapsychiatry.2024.231359\u003c/li\u003e\n\u003cli\u003eLiu Dandan. The Impact of Nursing Intervention Guided by Maslow\u0026apos;s Hierarchy of Needs Theory on Self-Care Ability and Complications in Patients After Enterostomy [J]. Diabetes World, 2023(1): 249-250. doi:10.3969/j.issn.1672-7851.2023.01.125.\u003c/li\u003e\n\u003cli\u003eMcGovern J, Dolan RD, Skipworth RJ, Laird BJ, McMillan DC. Cancer cachexia: a nutritional or a systemic inflammatory syndrome? Br J Cancer. 2022 Aug;127(3):379-382. doi: 10.1038/s41416-022-01826-2. Epub 2022 May 6. PMID: 35523879; PMCID: PMC9073809.\u003c/li\u003e\n\u003cli\u003eCancer Nutrition Committee of China Anti-Cancer Association, Parenteral and Enteral Nutrition Society of Chinese Medical Association. Expert consensus on nutritional therapy for colorectal cancer patients [J]. Electronic Journal of Oncology Metabolism and Nutrition, 2022, 9 (6):735-740. doi:10.16689/j.cnki.cn11-9349/r.2022.06.009. \u003c/li\u003e\n\u003cli\u003ePan XT, Lu Y, Cheng X, et al. Investigation and analysis of hemoglobin changes and anemia in cancer patients before and after treatment [J]. Chinese Journal of Cancer Prevention and Treatment, 2008, 15 (20):1540- 1543. doi:10.16073/j.cnki.cjcpt.2008.20.006. \u003c/li\u003e\n\u003cli\u003eDai Jinhui, Yuan Jing. Comparison of one-way ANOVA and multiple linear regression test methods [J]. Statistics and Decision Making, 2016,(09):23-26. doi:10.13546/j.cnki.tjyjc.2016.09.005. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Preventive enterostomy, Symptom clusters, Nutritional status, Latent class analysis, Colorectal cancer","lastPublishedDoi":"10.21203/rs.3.rs-6188108/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6188108/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is a close relationship between nutritional status and symptom clusters. However, research on the characteristics of symptom clusters in different nutritional statuses is still limited. The purpose of this study was to explore the heterogeneity of symptom clusters in different patient categories by using latent class analysis and to provide direction and key guidance for clinical symptom cluster management in different patient populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study used convenience sampling to recruit colorectal cancer patients with preventive enterostomy from three tertiary hospitals in Fujian Province. Data were collected using the following instruments: a general information questionnaire, the Chinese version of the Adult Pain Behavior Scale (APBS), the Hamilton Anxiety Scale (HAMA), the Hamilton Depression Scale (HAMD), the Athens Insomnia Scale (AIS), and the Cancer Appetite and Symptom Questionnaire (CASQ). After data collection, latent class analysis (LCA) was applied to explore heterogeneous subgroups of nutritional status-symptom clusters. Univariate and multivariate analyses were conducted to identify factors influencing subgroup classification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 350 questionnaires were collected, which revealed four latent categories: the malnourished-high symptom cluster group, the suboptimal nutrition-higher symptom cluster group, the moderate nutrition-moderate symptom cluster group, and the well-nourished-low symptom cluster group. Multivariate logistic regression analysis showed that chronic diseases and tumor location were significant factors influencing the latent categories (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings of this study indicated that the subgroups of disease symptoms under different nutritional statuses exhibited distinct characteristics. By identifying the subgroups of symptoms, it is helpful to provide reference and guidance for formulating more effective and accurate intervention and management strategies for patients with preventive enterostomy.\u003c/p\u003e","manuscriptTitle":"Latent class analysis of symptom clusters in preventive enterostomy with colorectal cancer patients based on nutritional status","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-17 16:15:07","doi":"10.21203/rs.3.rs-6188108/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4df581bf-db22-40d6-a964-e816fb323b64","owner":[],"postedDate":"March 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-01T01:08:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-17 16:15:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6188108","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6188108","identity":"rs-6188108","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}