Development of a Nomogram for Predicting Surgical Conversion After Failure of Intestinal Obstruction Catheter Treatment in Adhesive Small Bowel Obstruction: A Single-Center Retrospective Study

Development of a Nomogram for Predicting Surgical Conversion After Failure of Intestinal Obstruction Catheter Treatment in Adhesive Small Bowel Obstruction: A Single-Center Retrospective Study | 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 Development of a Nomogram for Predicting Surgical Conversion After Failure of Intestinal Obstruction Catheter Treatment in Adhesive Small Bowel Obstruction: A Single-Center Retrospective Study Kai Deng, Yi-ran Li, Teng-long Guo, Jun-zhe Dou, Yu-liang Cui, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6445977/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: Nonoperative management (NOM) with nasoenteric decompression tubes is a preferred strategy for adhesive small bowel obstruction (ASBO), yet treatment failure may lead to delayed surgery and increased mortality. Current predictive tools lack integration of clinical, laboratory, and imaging indicators. Objective: To develop and validate a nomogram for predicting the risk of NOM failure requiring surgical conversion in ASBO patients. Methods: This retrospective study included 61 ASBO patients treated with nasoenteric decompression at Qilu Hospital of Shandong University Dezhou Hospital (January 2022–January 2025). Independent predictors were identified via univariate and multivariate logistic regression. A nomogram was constructed and internally validated using 1000 bootstrap resamples. Model performance was assessed using ROC curves, calibration curves, and decision curve analysis (DCA). Results: Multivariate analysis identified three independent predictors: History of previous adhesive small bowel obstruction (OR=6.661, 95% CI: 1.210–36.680), low hemoglobin (OR=0.951, 95% CI: 0.906–0.998), and Small bowel feces sign (OR=0.11, 95% CI: 0.022–0.542). The nomogram demonstrated excellent discrimination (AUC=0.864, 95% CI: 0.753–0.946), calibration (Brier score=0.039), and clinical net benefit (0.361 within a threshold probability of 15%–65%). Conclusion: This nomogram, integrating clinical, laboratory, and imaging data, provides a practical tool for early identification of high-risk ASBO patients. Adhesive Small Bowel Obstruction Nomogram Surgical Conversion Nonoperative Management Predictive Model Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Adhesive small bowel obstruction (ASBO) is a common postoperative complication, occurring in 5–30% of patients after abdominal surgery, with approximately 15% requiring reoperation[1, 2]. Current guidelines from the Eastern Association for the Surgery of Trauma (EAST)[3] the World Society of Emergency Surgery (WSES) [4], and the Chinese Medical Association [5] recommend NOM as the first-line approach for ASBO without signs of peritonitis or ischemia. Nasoenteric decompression tubes are widely used, achieving success rates of 70–90% [6–8]. However, delayed surgical intervention due to failed NOM may increase the risk of bowel resection and mortality [5, 9]. Despite its clinical significance, evidence on the optimal timing for surgical conversion remains limited [10, 11]. Existing studies lack comprehensive tools integrating clinical, laboratory, and radiological predictors. This study aimed to develop a nomogram model to quantify the risk of NOM failure, facilitating timely surgical decision-making. 2. Materials and Methods 2.1. Study Population Clinical data of 61 ASBO patients treated with nasoenteric decompression between January 2022 and January 2025 were retrospectively analyzed. Ethical approval was obtained from the Ethics Committee of Qilu Hospital of Shandong University Dezhou Hospital (Approval No. 202504021740000530408). Informed consent was waived due to the anonymized nature of the data. 2.2. Inclusion and Exclusion Criteria Inclusion criteria: (1) Age > 18 years; (2) Confirmed diagnosis of ASBO; (3) Nasoenteric decompression tube placement; (4) Prior laparotomy history. Exclusion criteria: (1) Strangulation, peritonitis, or active infection; (2) Recent abdominal surgery (< 4 weeks); (3) Inflammatory bowel disease or mesenteric vascular disease; (4) Other causes of obstruction (Paralytic ileus, fecal impaction, peritoneal carcinomatosis, incarcerated hernia, etc.). The decision to proceed with surgical intervention was made by the attending physician based on clinical symptoms (e.g., persistent abdominal pain, vomiting), physical examination findings (e.g., rebound tenderness, rigidity), and auxiliary diagnostic tests (e.g., CT evidence of bowel ischemia, worsening laboratory markers). 2.3. Variables Data included: 1. Demographics and clinical features : Age, sex, BMI, comorbidities (hypertension, Cardiovascular disease ,diabetes,Cerebrovascular disease), Previous abdominal surgical site, abdominal pain duration, and catheterization time. 2. Laboratory tests : White blood cell count, Neutrophil count, Lymphocyte count, hemoglobin, platelets, albumin. 3. Imaging findings : Ascites sign, small bowel dilatation (diameter ≥ 40 mm), The thickness of the small intestine wall, and Small bowel feces sign (Fig. 1). 2.4. Statistical Analysis Statistical analyses were performed using SPSS 27.0 and R 4.4.2. Categorical variables were compared using chi-square or Fisher’s exact tests; continuous variables were analyzed via t-tests or Mann-Whitney U tests. Multivariate logistic regression identified independent predictors. A nomogram was constructed using the "rms" package. Model performance was evaluated using ROC curves (AUC), calibration curves (Brier score), and DCA. Internal validation was performed via 1000 bootstrap resamples. 3. Results 3.1. Baseline Characteristics A total of 61 patients with adhesive small bowel obstruction (ASBO) treated with nasojejunal obstruction nonoperative management (NOM) were included in this study. The mean age of the patients was 59.05 ± 18.11 years, with 34 (55.7%) male patients and 27 (44.3%) female patients. Treatment failure occurred in 22 (36.1%) patients, necessitating surgical intervention, while the remaining 39 (63.9%) patients had their obstruction successfully resolved with nonoperative management (NOM). 3.2. Univariate Analysis In the univariate analysis, no significant differences were found between the two groups in terms of gender, age, hypertension, coronary heart disease, diabetes, cerebrovascular disease, previous number of abdominal surgeries, previous surgical site, temperature > 38.5°C, duration of abdominal pain, presence of ascites, small bowel wall thickness, white blood cell count, neutrophil count, lymphocyte count, platelet count, or albumin level (all p > 0.05). However, significant differences were observed in BMI, history of previous adhesive small bowel obstruction, hemoglobin level, small bowel dilatation diameter, and small bowel feces sign (p < 0.05), indicating that these factors are key determinants of the failure of catheter treatment for ASBO (Table 1 ). Table 1 Single factor analysis of the Clinical Data Between Two Groups Items Non-surgical intervention Surgical intervention χ2/t p Gender woman 16(41.03) 11(50.00) 0.459 0.498 man 23(58.97) 11(50.00) Age (years) <60 19(48.72) 9(40.91) 0.345 0.557 ≥ 60 20(51.28) 13(59.09) BMI (kg/㎡) <23.9 23(58.97) 19(86.36) 4.92 0.027 ≥ 23.9 16(41.03) 3(13.64) Hypertension NO 26(66.67) 17(77.27) 0.761 0.383 YES 13(33.33) 5(22.73) Cardiovascular disease NO 34(87.18) 20(90.91) 0.193 0.661 YES 5(12.82) 2(9.09) Diabetes NO 32(82.05) 20(90.91) 0.877 0.349 YES 7(17.95) 2(9.09) Cerebrovascular disease NO 34(87.18) 20(90.91) 0.193 0.661 YES 5(12.82) 2(9.09) Temperature (°C) 5 4(10.26) 6(27.27) Ascites sign NO 34(87.18) 16(72.73) 1.988 0.159 YES 5(12.82) 6(27.27) Small bowel dilatation(mm) <40 21(53.85) 5(22.73) 5.57 0.018 ≥ 40 18(46.15) 17(77.27) Small bowel feces sign NO 12(30.77) 18(81.82) 14.666 5 20(51.28) 12(54.55) Previous Abdominal Surgeries (Times) ≤ 1 27(69.23) 19(86.36) 2.227 0.136 >1 12(30.77) 3(13.64) Previous abdominal surgical site lower 21(53.85) 15(68.18) 1.195 0.274 upper 18(46.15) 7(31.82) History of previous adhesive small bowel obstruction NO 35(89.74) 11(50.00) 11.981 0.001 YES 4(10.26) 11(50.00) White blood cell count(10⁹/L) 8.47 ± 3.00 9.54 ± 4.90 -0.927 0.361 Neutrophil count(10⁹/L) 6.63 ± 2.82 7.89 ± 5.12 -1.063 0.297 Lymphocyte count(10⁹/L) 1.23 ± 0.72 1.04 ± 0.57 1.1 0.276 Hemoglobin (g/L) 138.74 ± 17.55 121.32 ± 18.19 3.676 0.001 Platelets (10⁹/L) 233.97 ± 88.96 265.55 ± 110.04 -1.221 0.227 Albumin (g/L) 39.58 ± 4.27 37.87 ± 5.50 1.347 0.183 The thickness of the small intestine wall(mm) 4.69 ± 1.61 5.09 ± 1.51 -0.95 0.346 3.3. Multivariate Analysis Multivariate logistic regression analysis was performed with the failure of catheter treatment and surgical conversion as the dependent variable, and the variables with statistical significance in Table 1 as the independent variables. The results revealed that history of previous adhesive small bowel obstruction (OR = 6.661, 95% CI: 1.210–36.680), hemoglobin level (OR = 0.951 per 1 g/L increase, 95% CI: 0.906–0.998), and small bowel feces sign (OR = 0.11, 95% CI: 0.022–0.542) were independent risk factors for the failure of catheter treatment and surgical conversion in ASBO (Table 2 ). Table 2 Multivariate analysis of the Failure of Catheter Treatment and surgical conversion in Adhesive Small Bowel Obstruction Items B SE z-value Wald χ2 P OR 95% CI BMI(kg/㎡) -1.481 1.01 -1.467 2.152 0.142 0.227 0.031 ~ 1.645 History of previous adhesive small bowel obstruction 1.896 0.87 2.179 4.746 0.029 6.661 1.210 ~ 36.680 Hemoglobin(g/L) -0.05 0.025 -2.029 4.117 0.042 0.951 0.906 ~ 0.998 Small bowel dilatation(mm) 1.23 0.818 1.505 2.264 0.132 3.421 0.689 ~ 16.987 Small bowel feces sign -2.204 0.812 -2.714 7.366 0.007 0.11 0.022 ~ 0.542 3.4. Nomogram Construction Based on the three independent risk factors identified by multivariate logistic regression analysis—history of previous adhesive small bowel obstruction, hemoglobin level, and small bowel feces sign—a nomogram prediction model was constructed to predict the risk of failure of catheter treatment and surgical conversion in ASBO (Fig. 2 ). 3.5. Validation of the Nomogram Prediction Model Internal validation using the Bootstrap method demonstrated that the predicted curve had a high degree of fit with the standard model curve, with a mean absolute error of 0.039 (Fig. 3 ). The ROC curve analysis showed an AUC of 0.864 (95% CI: 0.753–0.946), with an optimal threshold of 0.334, sensitivity of 0.818, and specificity of 0.769, indicating strong predictive capability of the nomogram model (Fig. 4 ). 3.6. Clinical Effectiveness Evaluation of the Nomogram Model Decision curve analysis (DCA) was used to assess the clinical utility of the nomogram prediction model. The results showed that the model had a maximum net benefit value of 0.361, indicating high clinical applicability and the potential to provide clinical net benefit (Fig. 5 ). 4. Discussion This study retrospectively analyzed 61 patients with adhesive small bowel obstruction (ASBO) treated with nasojejunal obstruction nonoperative management (NOM) and constructed a nomogram prediction model based on multivariate Logistic regression to quantitatively assess the risk of failure of nonoperative management (NOM) and the need for conversion to surgery. The model included three independent risk factors: history of previous adhesive small bowel obstruction, hemoglobin level, and small bowel feces sign, and demonstrated good predictive performance (AUC = 0.864) and clinical utility (DCA net benefit value 0.361). The following discussion will focus on the significance of the study, the value of the model, and its limitations. 4.1. Key Findings and Clinical Implications Our study confirmed that history of previous adhesive small bowel obstruction (OR = 6.661) is the strongest predictor of treatment failure. This finding aligns with previous research indicating that recurrent obstruction is more likely to require surgical intervention due to more severe adhesions[12]. Each new episode of ASBO increases the risk of recurrence, with shorter intervals between episodes, leading to a higher likelihood of surgical intervention[13]. Epidemiological data show that the more episodes of ASBO a patient has, the higher the risk of recurrence and the shorter the interval between episodes. Therefore, in patients with frequent recurrences, new episodes may be more difficult to prevent[14–16]. We believe that patients with recurrent ASBO typically have more severe intra-abdominal adhesions, which reduce intestinal mobility and limit the effectiveness of decompression. Additionally, the chronic inflammatory microenvironment may accelerate fibrosis, further increasing the risk of mechanical obstruction. The finding that hemoglobin level is a predictor (OR = 0.951) highlights its dual significance: (1) as a marker of chronic anemia due to malnutrition or occult blood loss, and (2) as an indicator of tissue hypoxia exacerbating intestinal ischemia. As a carrier of oxygen, decreased hemoglobin levels may indicate intestinal ischemia and insufficient oxygen supply. Therefore, correcting anemia during nasojejunal obstruction nonoperative management (NOM) may help reduce the risk of intestinal ischemia[17, 18]. Moreover, the absence of the small bowel feces sign (OR = 0.11) was significantly associated with treatment failure. Imaging studies have shown that the small bowel feces sign occurs in 61.9% of cases with membranous adhesions and in 28.3% of cases with band-like adhesions, with a statistically significant difference between the two[19]. Experts have suggested that after intestinal obstruction occurs[20], the pressure in the intestinal lumen increases. In the early stages of obstruction, the absorption function of the intestinal wall is greater than its secretory function, which helps to reduce the pressure in the intestinal lumen. The absorption function of the intestinal wall is carried out by mucosal cells consuming ATP through membrane transport. When ATP is depleted, the intestinal wall temporarily loses its absorption function. If the obstruction is not relieved at this time, the pressure in the intestinal lumen continues to rise. Once the intestinal wall mucosal cells replenish ATP, they will repeat the process of absorption and secretion. After several cycles, the liquid contents in the intestinal lumen turn into a mixture of fine particles and small gas bubbles, which appears as the small bowel feces sign on CT. However, in cases of acute severe obstruction, the pressure in the intestinal lumen rises too quickly for the intestinal wall to complete absorption in a short time, leading to a continued increase in pressure. Once the pressure exceeds a certain level, the intestinal wall also loses its absorption function, and the intestinal lumen does not form fecal-like material. Therefore, the presence of the small bowel feces sign often indicates that the obstruction is slow and mild, and most cases can be relieved by conservative treatment. This finding further confirms the value of imaging biomarkers in the prognostic assessment of ASBO[21, 22]. 4.2. Comparison with Existing Literature Some scholars have established a nomogram model based on the platelet-to-lymphocyte ratio (PLR) to predict the failure of nonoperative management (NOM) of small bowel obstruction with obstruction nonoperative management (NOM)[23]. We also analyzed the PLR in our study data. After univariate and multivariate analyses, PLR was found to be an independent risk factor for failure of nonoperative management (NOM) and conversion to surgery. However, the prediction accuracy of the nomogram based on PLR was not as good as that based on hemoglobin, so it was not adopted. This discrepancy may be related to the limited sample size (n = 61) in our study or the heterogeneity of the population baseline characteristics (such as the proportion of comorbidities). To further verify the clinical value of PLR, we plan to expand the sample size (target n ≥ 300) through a multicenter prospective cohort study and stratify the analysis of PLR's predictive stability in different subgroups (such as age, underlying diseases). It is worth noting that small bowel dilatation diameter (≥ 40 mm) and BMI (≥ 23.9 kg/m²) showed statistical significance in univariate analysis but were not selected in multivariate regression. This result is inconsistent with some studies. For example, Matsuda et al. emphasized that the diameter of small bowel dilatation is linearly related to the risk of intestinal ischemia[10]. In contrast, obese patients, due to the upregulation of anti-inflammatory cytokines (such as IL-10) and antimicrobial peptides (such as defensins), may have a protective effect against intestinal ischemia[24]. We did not observe a similar association in our study, and we speculate that the reasons may include: (1) the small sample size leading to insufficient statistical power; (2) the bias in the population BMI distribution (only 15% of patients in our study were obese). Future studies will include a more diverse population (with a proportion of BMI ≥ 30 of at least 25%) and combine radiomics to quantify the morphological characteristics of small bowel dilatation, thereby improving the objectivity of variable measurement. 4.3. Limitations and Future Directions The nomogram model integrates clinical, laboratory, and imaging indicators to provide a visual tool for individualized risk assessment. For example, for patients with hemoglobin levels below 120 g/L and no small bowel feces sign, the model can quickly identify their high-risk status and assist clinicians in making earlier decisions within the window of nonoperative management (NOM) to avoid complications such as intestinal necrosis or increased mortality due to delayed surgery. The DCA curve further shows that within the threshold probability range of 15–65%, the application of this model can significantly improve clinical net benefit, outperforming the strategies of "full intervention" or "no intervention." The model is based on multidimensional data, covering easily accessible clinical indicators, and is suitable for institutions with limited resources. The internal validation through the Bootstrap method (Brier score = 0.039) shows that the predicted probability is highly consistent with the actual risk. However, the study has the following limitations: (1) the single-center retrospective design may lead to selection bias, and the small sample size (n = 61) affects statistical power; (2) the lack of biomarkers (such as lactate, inflammatory factors) or dynamic monitoring data (such as catheter drainage volume) may miss potential predictive variables; (3) the absence of external validation means that the generalizability of the model needs further verification. Our future research will be deepened in three aspects: (1) conducting multicenter prospective cohort studies to expand the sample size and include a more diverse population (such as patients with chronic diseases); (2) combining machine learning algorithms (such as random forests or neural networks) to explore non-linear relationships in high-dimensional data and improve model accuracy; (3) exploring the integration of the model with clinical pathways, for example, by developing mobile risk assessment tools to enable real-time dynamic prediction. Additionally, future research could further elucidate the specific mechanisms by which hemoglobin levels are associated with intestinal ischemia, providing a theoretical basis for intervention targets. 5. Conclusion The nomogram model constructed in this study can effectively predict the risk of failure of nonoperative management (NOM) in patients with ASBO and provides a quantitative tool for clinical decision-making. Although further validation and optimization are needed, its simplicity, practicality, and high discriminative ability make it a potentially important auxiliary means for improving the prognosis of patients with ASBO. Declarations Funding This work was supported by the Natural Science Foundation of Shandong Province (Grant No. ZR2021QH181) for author Yu-liang Cui. No other funding was received for this study. References Xie, Y., Zheng, C., Tan, X., Li, Z., Zhang, Y., & Liu, Y. (2022). Clinical efficacy of acupuncture in patients with adhesive intestinal obstruction: A meta-analysis. Medicine (Baltimore), 101(40), e30257. https://doi.org/10.1097/md.0000000000030257 Medvecz, A. J., Dennis, B. M., Wang, L., Lindsell, C. J., & Guillamondegui, O. D. (2020). Impact of Operative Management on Recurrence of Adhesive Small Bowel Obstruction: A Longitudinal Analysis of a Statewide Database. J Am Coll Surg, 230(4), 544-551.e541. https://doi.org/10.1016/j.jamcollsurg.2019.12.006 Maung, A. 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Asian J Surg, 44(1), 292-297. https://doi.org/10.1016/j.asjsur.2020.07.012 Hou ZB, He Y, Zhao H, et al. Study on the Prediction of Non-surgical Treatment Failure in Patients with Small Bowel Obstruction by Platelet/Lymphocyte Ratio. Parenteral & Enteral Nutrition 2024;31(4):233-238. (In Chi). DOI: 10.16151/j.1007-810x.2024.04.005. Cho, Y. J., Park, I. S., Kim, J., Cho, H. J., Gwak, G. H., Yang, K. H., Bae, B. N., & Kim, K. H. (2020). Factors Predicting the Need for Early Surgical Intervention for Small Bowel Obstruction. Ann Coloproctol, 36(4), 223-228. https://doi.org/10.3393/ac.2019.09.30 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6445977","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":474761392,"identity":"1814cbaa-df28-427d-8978-ae147ca5ee90","order_by":0,"name":"Kai Deng","email":"","orcid":"","institution":"Qilu Hospital Of Shandong University Dezhou Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Deng","suffix":""},{"id":474761393,"identity":"29cf6924-bb2d-4097-ac85-5e932457068a","order_by":1,"name":"Yi-ran Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACPmYGhgNAup6fv/nAgQ8VRGhhg2pJkJxxLPHgjDPEaIHSCQYHcowP87YQo4Wdx/BwRc2dPIYDZz4c4G1gkOcXO0DIYTwGB88ce1bM2Ny74YDkDgbDmbMTiNDSwHaYsZnh7IYDhmeALrxNlJZ/hxnbGHIeHEhsI1ZLY9vhxB6GHIYDB4nTwlZwsLHvsLGExDGgdWckCPuFn//w5o8N3w7L2Z9vfvz5T4WNPL80AS0MDBwGyDwJQspBgP0BMapGwSgYBaNgJAMAXYJK8NvMTPMAAAAASUVORK5CYII=","orcid":"","institution":"Qilu Hospital Of Shandong University Dezhou Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yi-ran","middleName":"","lastName":"Li","suffix":""},{"id":474761394,"identity":"7944d4fe-2f3b-4063-97a7-10ac1b892aa8","order_by":2,"name":"Teng-long Guo","email":"","orcid":"","institution":"Qilu Hospital Of Shandong University Dezhou Hospital","correspondingAuthor":false,"prefix":"","firstName":"Teng-long","middleName":"","lastName":"Guo","suffix":""},{"id":474761395,"identity":"dac3e92d-73d3-4c83-8a1a-472fab1699ec","order_by":3,"name":"Jun-zhe Dou","email":"","orcid":"","institution":"Qilu Hospital Of Shandong University Dezhou Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jun-zhe","middleName":"","lastName":"Dou","suffix":""},{"id":474761396,"identity":"a3b30198-10ac-45ed-8449-57a3ce87794e","order_by":4,"name":"Yu-liang Cui","email":"","orcid":"","institution":"Qilu Hospital Of Shandong University Dezhou Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yu-liang","middleName":"","lastName":"Cui","suffix":""},{"id":474761397,"identity":"afc9b017-0285-43b1-b981-22e5364a324c","order_by":5,"name":"Jie Zhang","email":"","orcid":"","institution":"Qilu Hospital Of Shandong University Dezhou Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-04-14 12:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6445977/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6445977/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85367265,"identity":"087e8c51-f01f-44f6-bce9-05ea7cdd36f1","added_by":"auto","created_at":"2025-06-25 06:58:19","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63685,"visible":true,"origin":"","legend":"\u003cp\u003e→Small bowel feces sign\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6445977/v1/8c7fe51dadc98f5afd582cfd.jpg"},{"id":85367266,"identity":"62607528-1703-4684-9eba-802d8591ce83","added_by":"auto","created_at":"2025-06-25 06:58:19","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":133728,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram for Predicting Failure of Catheter Treatment and Conversion to Surgery in Adhesive Small Bowel Obstruction\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6445977/v1/a6a181f795ed1d4553401cac.jpg"},{"id":85367899,"identity":"b632fa23-fe72-4465-b61a-58e58c7eb8b7","added_by":"auto","created_at":"2025-06-25 07:06:19","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":419941,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration curve of the nomogram prediction model.\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6445977/v1/1e199bb52fde0b3840de8192.jpg"},{"id":85367268,"identity":"18905679-bb41-4af9-86c1-9a141b0baf33","added_by":"auto","created_at":"2025-06-25 06:58:19","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":59244,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve evaluation of the nomogram prediction model.\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6445977/v1/6fe23bf1accf99b5eff914a5.jpg"},{"id":85367274,"identity":"979807d9-8a95-49bb-9a4b-2c29b8661ddf","added_by":"auto","created_at":"2025-06-25 06:58:19","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":78951,"visible":true,"origin":"","legend":"\u003cp\u003eDCA curves used to evaluate the clinical effectiveness of the prediction\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6445977/v1/c239b44ee5cf234c25c45816.jpg"},{"id":85370892,"identity":"11b7cb85-2568-4e15-97aa-c73bb0404cf2","added_by":"auto","created_at":"2025-06-25 07:30:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1548673,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6445977/v1/c7b75579-c6a7-411d-bda8-ce692fdd84a2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of a Nomogram for Predicting Surgical Conversion After Failure of Intestinal Obstruction Catheter Treatment in Adhesive Small Bowel Obstruction: A Single-Center Retrospective Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAdhesive small bowel obstruction (ASBO) is a common postoperative complication, occurring in 5\u0026ndash;30% of patients after abdominal surgery, with approximately 15% requiring reoperation[1, 2]. Current guidelines from the Eastern Association for the Surgery of Trauma (EAST)[3] the World Society of Emergency Surgery (WSES) [4], and the Chinese Medical Association [5] recommend NOM as the first-line approach for ASBO without signs of peritonitis or ischemia. Nasoenteric decompression tubes are widely used, achieving success rates of 70\u0026ndash;90% [6\u0026ndash;8]. However, delayed surgical intervention due to failed NOM may increase the risk of bowel resection and mortality [5, 9]. Despite its clinical significance, evidence on the optimal timing for surgical conversion remains limited [10, 11].\u003c/p\u003e\n\u003cp\u003eExisting studies lack comprehensive tools integrating clinical, laboratory, and radiological predictors. This study aimed to develop a nomogram model to quantify the risk of NOM failure, facilitating timely surgical decision-making.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv\u003e\n\u003ch2\u003e2.1. Study Population\u003c/h2\u003e\nClinical data of 61 ASBO patients treated with nasoenteric decompression between January 2022 and January 2025 were retrospectively analyzed. Ethical approval was obtained from the Ethics Committee of Qilu Hospital of Shandong University Dezhou Hospital (Approval No. 202504021740000530408). Informed consent was waived due to the anonymized nature of the data.\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e2.2. Inclusion and Exclusion Criteria\u003c/h2\u003e\nInclusion criteria: (1) Age\u0026thinsp;\u0026gt;\u0026thinsp;18 years; (2) Confirmed diagnosis of ASBO; (3) Nasoenteric decompression tube placement; (4) Prior laparotomy history.\u003cbr /\u003e\n\u003cp\u003eExclusion criteria: (1) Strangulation, peritonitis, or active infection; (2) Recent abdominal surgery (\u0026lt;\u0026thinsp;4 weeks); (3) Inflammatory bowel disease or mesenteric vascular disease; (4) Other causes of obstruction (Paralytic ileus, fecal impaction, peritoneal carcinomatosis, incarcerated hernia, etc.).\u003c/p\u003e\n\u003cp\u003eThe decision to proceed with surgical intervention was made by the attending physician based on clinical symptoms (e.g., persistent abdominal pain, vomiting), physical examination findings (e.g., rebound tenderness, rigidity), and auxiliary diagnostic tests (e.g., CT evidence of bowel ischemia, worsening laboratory markers).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e2.3. Variables\u003c/h2\u003e\n\u003cp\u003eData included:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1. Demographics and clinical features\u003c/strong\u003e: Age, sex, BMI, comorbidities (hypertension, Cardiovascular disease ,diabetes,Cerebrovascular disease), Previous abdominal surgical site, abdominal pain duration, and catheterization time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Laboratory tests\u003c/strong\u003e: White blood cell count, Neutrophil count, Lymphocyte count, hemoglobin, platelets, albumin.\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3. Imaging findings\u003c/strong\u003e: Ascites sign, small bowel dilatation (diameter\u0026thinsp;\u0026ge;\u0026thinsp;40 mm), The thickness of the small intestine wall, and Small bowel feces sign (Fig.\u0026nbsp;1).\u0026nbsp;\u003c/p\u003e\n\u003cdiv\u003e\n\u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e\n\u003cp\u003eStatistical analyses were performed using SPSS 27.0 and R 4.4.2. Categorical variables were compared using chi-square or Fisher\u0026rsquo;s exact tests; continuous variables were analyzed via t-tests or Mann-Whitney U tests. Multivariate logistic regression identified independent predictors. A nomogram was constructed using the \"rms\" package. Model performance was evaluated using ROC curves (AUC), calibration curves (Brier score), and DCA. Internal validation was performed via 1000 bootstrap resamples.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1. Baseline Characteristics\u003c/h2\u003e\n\u003cp\u003eA total of 61 patients with adhesive small bowel obstruction (ASBO) treated with nasojejunal obstruction nonoperative management (NOM) were included in this study. The mean age of the patients was 59.05\u0026thinsp;\u0026plusmn;\u0026thinsp;18.11 years, with 34 (55.7%) male patients and 27 (44.3%) female patients. Treatment failure occurred in 22 (36.1%) patients, necessitating surgical intervention, while the remaining 39 (63.9%) patients had their obstruction successfully resolved with nonoperative management (NOM).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2. Univariate Analysis\u003c/h2\u003e\n\u003cp\u003eIn the univariate analysis, no significant differences were found between the two groups in terms of gender, age, hypertension, coronary heart disease, diabetes, cerebrovascular disease, previous number of abdominal surgeries, previous surgical site, temperature\u0026thinsp;\u0026gt;\u0026thinsp;38.5\u0026deg;C, duration of abdominal pain, presence of ascites, small bowel wall thickness, white blood cell count, neutrophil count, lymphocyte count, platelet count, or albumin level (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, significant differences were observed in BMI, history of previous adhesive small bowel obstruction, hemoglobin level, small bowel dilatation diameter, and small bowel feces sign (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that these factors are key determinants of the failure of catheter treatment for ASBO (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSingle factor analysis of the Clinical Data Between Two Groups\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eItems\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNon-surgical intervention\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSurgical intervention\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026chi;2/t\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ewoman\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(41.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.459\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.498\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eman\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23(58.97)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003cp\u003e(years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19(48.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(40.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.345\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.557\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20(51.28)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13(59.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003cp\u003e(kg/㎡)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;23.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23(58.97)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19(86.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.027\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;23.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(41.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3(13.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26(66.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17(77.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.761\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.383\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13(33.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(22.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCardiovascular\u003c/p\u003e\n\u003cp\u003edisease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e34(87.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20(90.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.193\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.661\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(12.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(9.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDiabetes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32(82.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20(90.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.877\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.349\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7(17.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(9.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCerebrovascular disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e34(87.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20(90.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.193\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.661\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(12.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(9.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eTemperature\u003c/p\u003e\n\u003cp\u003e(\u0026deg;C)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;38.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35(89.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19(86.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.158\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.691\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;38.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4(10.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3(13.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAbdominal pain duration (day)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35(89.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(72.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.972\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.085\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026gt;5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4(10.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6(27.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAscites sign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e34(87.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(72.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.988\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.159\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(12.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6(27.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSmall bowel dilatation(mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21(53.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(22.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18(46.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17(77.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSmall bowel feces sign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12(30.77)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18(81.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.666\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27(69.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4(18.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCatheterization Time(day)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19(48.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10(45.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.806\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026gt;5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20(51.28)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12(54.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ePrevious Abdominal Surgeries (Times)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27(69.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19(86.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.227\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.136\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026gt;1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12(30.77)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3(13.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ePrevious abdominal surgical site\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003elower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21(53.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15(68.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.195\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.274\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eupper\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18(46.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7(31.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eHistory of previous adhesive small bowel obstruction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35(89.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.981\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4(10.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWhite blood cell count(10⁹/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.54\u0026thinsp;\u0026plusmn;\u0026thinsp;4.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.927\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.361\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutrophil count(10⁹/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.89\u0026thinsp;\u0026plusmn;\u0026thinsp;5.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-1.063\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.297\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLymphocyte count(10⁹/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.276\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHemoglobin\u003c/p\u003e\n\u003cp\u003e(g/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e138.74\u0026thinsp;\u0026plusmn;\u0026thinsp;17.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e121.32\u0026thinsp;\u0026plusmn;\u0026thinsp;18.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.676\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePlatelets\u003c/p\u003e\n\u003cp\u003e(10⁹/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e233.97\u0026thinsp;\u0026plusmn;\u0026thinsp;88.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e265.55\u0026thinsp;\u0026plusmn;\u0026thinsp;110.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-1.221\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.227\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlbumin\u003c/p\u003e\n\u003cp\u003e(g/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39.58\u0026thinsp;\u0026plusmn;\u0026thinsp;4.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e37.87\u0026thinsp;\u0026plusmn;\u0026thinsp;5.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.347\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.183\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe thickness of the small intestine wall(mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.346\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3. Multivariate Analysis\u003c/h2\u003e\nMultivariate logistic regression analysis was performed with the failure of catheter treatment and surgical conversion as the dependent variable, and the variables with statistical significance in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e as the independent variables. The results revealed that history of previous adhesive small bowel obstruction (OR\u0026thinsp;=\u0026thinsp;6.661, 95% CI: 1.210\u0026ndash;36.680), hemoglobin level (OR\u0026thinsp;=\u0026thinsp;0.951 per 1 g/L increase, 95% CI: 0.906\u0026ndash;0.998), and small bowel feces sign (OR\u0026thinsp;=\u0026thinsp;0.11, 95% CI: 0.022\u0026ndash;0.542) were independent risk factors for the failure of catheter treatment and surgical conversion in ASBO (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003cbr /\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eMultivariate analysis of the Failure of Catheter Treatment and surgical conversion in Adhesive Small Bowel Obstruction\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eItems\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eB\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSE\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ez-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eWald \u0026chi;2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95% CI\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI(kg/㎡)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-1.481\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-1.467\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.152\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.142\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.227\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.031\u0026thinsp;~\u0026thinsp;1.645\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHistory of previous adhesive small bowel obstruction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.896\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.746\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.029\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.661\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.210\u0026thinsp;~\u0026thinsp;36.680\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHemoglobin(g/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.025\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-2.029\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.117\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.951\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.906\u0026thinsp;~\u0026thinsp;0.998\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmall bowel dilatation(mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.818\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.505\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.264\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.132\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.421\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.689\u0026thinsp;~\u0026thinsp;16.987\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmall bowel feces sign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-2.204\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.812\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-2.714\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.366\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.022\u0026thinsp;~\u0026thinsp;0.542\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4. Nomogram Construction\u003c/h2\u003e\nBased on the three independent risk factors identified by multivariate logistic regression analysis\u0026mdash;history of previous adhesive small bowel obstruction, hemoglobin level, and small bowel feces sign\u0026mdash;a nomogram prediction model was constructed to predict the risk of failure of catheter treatment and surgical conversion in ASBO (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003e3.5. Validation of the Nomogram Prediction Model\u003c/h2\u003e\nInternal validation using the Bootstrap method demonstrated that the predicted curve had a high degree of fit with the standard model curve, with a mean absolute error of 0.039 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The ROC curve analysis showed an AUC of 0.864 (95% CI: 0.753\u0026ndash;0.946), with an optimal threshold of 0.334, sensitivity of 0.818, and specificity of 0.769, indicating strong predictive capability of the nomogram model (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003e3.6. Clinical Effectiveness Evaluation of the Nomogram Model\u003c/h2\u003e\nDecision curve analysis (DCA) was used to assess the clinical utility of the nomogram prediction model. The results showed that the model had a maximum net benefit value of 0.361, indicating high clinical applicability and the potential to provide clinical net benefit (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study retrospectively analyzed 61 patients with adhesive small bowel obstruction (ASBO) treated with nasojejunal obstruction nonoperative management (NOM) and constructed a nomogram prediction model based on multivariate Logistic regression to quantitatively assess the risk of failure of nonoperative management (NOM) and the need for conversion to surgery. The model included three independent risk factors: history of previous adhesive small bowel obstruction, hemoglobin level, and small bowel feces sign, and demonstrated good predictive performance (AUC\u0026thinsp;=\u0026thinsp;0.864) and clinical utility (DCA net benefit value 0.361). The following discussion will focus on the significance of the study, the value of the model, and its limitations.\u003c/p\u003e\n\u003cdiv\u003e\n\u003ch2\u003e4.1. Key Findings and Clinical Implications\u003c/h2\u003e\n\u003cp\u003eOur study confirmed that history of previous adhesive small bowel obstruction (OR\u0026thinsp;=\u0026thinsp;6.661) is the strongest predictor of treatment failure. This finding aligns with previous research indicating that recurrent obstruction is more likely to require surgical intervention due to more severe adhesions[12]. Each new episode of ASBO increases the risk of recurrence, with shorter intervals between episodes, leading to a higher likelihood of surgical intervention[13]. Epidemiological data show that the more episodes of ASBO a patient has, the higher the risk of recurrence and the shorter the interval between episodes. Therefore, in patients with frequent recurrences, new episodes may be more difficult to prevent[14\u0026ndash;16]. We believe that patients with recurrent ASBO typically have more severe intra-abdominal adhesions, which reduce intestinal mobility and limit the effectiveness of decompression. Additionally, the chronic inflammatory microenvironment may accelerate fibrosis, further increasing the risk of mechanical obstruction.\u003c/p\u003e\n\u003cp\u003eThe finding that hemoglobin level is a predictor (OR\u0026thinsp;=\u0026thinsp;0.951) highlights its dual significance: (1) as a marker of chronic anemia due to malnutrition or occult blood loss, and (2) as an indicator of tissue hypoxia exacerbating intestinal ischemia. As a carrier of oxygen, decreased hemoglobin levels may indicate intestinal ischemia and insufficient oxygen supply. Therefore, correcting anemia during nasojejunal obstruction nonoperative management (NOM) may help reduce the risk of intestinal ischemia[17, 18].\u003c/p\u003e\n\u003cp\u003eMoreover, the absence of the small bowel feces sign (OR\u0026thinsp;=\u0026thinsp;0.11) was significantly associated with treatment failure. Imaging studies have shown that the small bowel feces sign occurs in 61.9% of cases with membranous adhesions and in 28.3% of cases with band-like adhesions, with a statistically significant difference between the two[19]. Experts have suggested that after intestinal obstruction occurs[20], the pressure in the intestinal lumen increases. In the early stages of obstruction, the absorption function of the intestinal wall is greater than its secretory function, which helps to reduce the pressure in the intestinal lumen. The absorption function of the intestinal wall is carried out by mucosal cells consuming ATP through membrane transport. When ATP is depleted, the intestinal wall temporarily loses its absorption function. If the obstruction is not relieved at this time, the pressure in the intestinal lumen continues to rise. Once the intestinal wall mucosal cells replenish ATP, they will repeat the process of absorption and secretion. After several cycles, the liquid contents in the intestinal lumen turn into a mixture of fine particles and small gas bubbles, which appears as the small bowel feces sign on CT. However, in cases of acute severe obstruction, the pressure in the intestinal lumen rises too quickly for the intestinal wall to complete absorption in a short time, leading to a continued increase in pressure. Once the pressure exceeds a certain level, the intestinal wall also loses its absorption function, and the intestinal lumen does not form fecal-like material. Therefore, the presence of the small bowel feces sign often indicates that the obstruction is slow and mild, and most cases can be relieved by conservative treatment. This finding further confirms the value of imaging biomarkers in the prognostic assessment of ASBO[21, 22].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e4.2. Comparison with Existing Literature\u003c/h2\u003e\n\u003cp\u003eSome scholars have established a nomogram model based on the platelet-to-lymphocyte ratio (PLR) to predict the failure of nonoperative management (NOM) of small bowel obstruction with obstruction nonoperative management (NOM)[23]. We also analyzed the PLR in our study data. After univariate and multivariate analyses, PLR was found to be an independent risk factor for failure of nonoperative management (NOM) and conversion to surgery. However, the prediction accuracy of the nomogram based on PLR was not as good as that based on hemoglobin, so it was not adopted. This discrepancy may be related to the limited sample size (n\u0026thinsp;=\u0026thinsp;61) in our study or the heterogeneity of the population baseline characteristics (such as the proportion of comorbidities). To further verify the clinical value of PLR, we plan to expand the sample size (target n\u0026thinsp;\u0026ge;\u0026thinsp;300) through a multicenter prospective cohort study and stratify the analysis of PLR's predictive stability in different subgroups (such as age, underlying diseases).\u003c/p\u003e\n\u003cp\u003eIt is worth noting that small bowel dilatation diameter (\u0026ge;\u0026thinsp;40 mm) and BMI (\u0026ge;\u0026thinsp;23.9 kg/m\u0026sup2;) showed statistical significance in univariate analysis but were not selected in multivariate regression. This result is inconsistent with some studies. For example, Matsuda et al. emphasized that the diameter of small bowel dilatation is linearly related to the risk of intestinal ischemia[10]. In contrast, obese patients, due to the upregulation of anti-inflammatory cytokines (such as IL-10) and antimicrobial peptides (such as defensins), may have a protective effect against intestinal ischemia[24]. We did not observe a similar association in our study, and we speculate that the reasons may include: (1) the small sample size leading to insufficient statistical power; (2) the bias in the population BMI distribution (only 15% of patients in our study were obese). Future studies will include a more diverse population (with a proportion of BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 of at least 25%) and combine radiomics to quantify the morphological characteristics of small bowel dilatation, thereby improving the objectivity of variable measurement.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e4.3. Limitations and Future Directions\u003c/h2\u003e\n\u003cp\u003eThe nomogram model integrates clinical, laboratory, and imaging indicators to provide a visual tool for individualized risk assessment. For example, for patients with hemoglobin levels below 120 g/L and no small bowel feces sign, the model can quickly identify their high-risk status and assist clinicians in making earlier decisions within the window of nonoperative management (NOM) to avoid complications such as intestinal necrosis or increased mortality due to delayed surgery. The DCA curve further shows that within the threshold probability range of 15\u0026ndash;65%, the application of this model can significantly improve clinical net benefit, outperforming the strategies of \"full intervention\" or \"no intervention.\"\u003c/p\u003e\n\u003cp\u003eThe model is based on multidimensional data, covering easily accessible clinical indicators, and is suitable for institutions with limited resources. The internal validation through the Bootstrap method (Brier score\u0026thinsp;=\u0026thinsp;0.039) shows that the predicted probability is highly consistent with the actual risk. However, the study has the following limitations: (1) the single-center retrospective design may lead to selection bias, and the small sample size (n\u0026thinsp;=\u0026thinsp;61) affects statistical power; (2) the lack of biomarkers (such as lactate, inflammatory factors) or dynamic monitoring data (such as catheter drainage volume) may miss potential predictive variables; (3) the absence of external validation means that the generalizability of the model needs further verification.\u003c/p\u003e\n\u003cp\u003eOur future research will be deepened in three aspects: (1) conducting multicenter prospective cohort studies to expand the sample size and include a more diverse population (such as patients with chronic diseases); (2) combining machine learning algorithms (such as random forests or neural networks) to explore non-linear relationships in high-dimensional data and improve model accuracy; (3) exploring the integration of the model with clinical pathways, for example, by developing mobile risk assessment tools to enable real-time dynamic prediction. Additionally, future research could further elucidate the specific mechanisms by which hemoglobin levels are associated with intestinal ischemia, providing a theoretical basis for intervention targets.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe nomogram model constructed in this study can effectively predict the risk of failure of nonoperative management (NOM) in patients with ASBO and provides a quantitative tool for clinical decision-making. Although further validation and optimization are needed, its simplicity, practicality, and high discriminative ability make it a potentially important auxiliary means for improving the prognosis of patients with ASBO.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Natural Science Foundation of Shandong Province (Grant No. ZR2021QH181) for author Yu-liang Cui. No other funding was received for this study.\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eXie, Y., Zheng, C., Tan, X., Li, Z., Zhang, Y., \u0026amp; Liu, Y. (2022). Clinical efficacy of acupuncture in patients with adhesive intestinal obstruction: A meta-analysis. Medicine (Baltimore), 101(40), e30257. https://doi.org/10.1097/md.0000000000030257\u003c/li\u003e\n\u003cli\u003eMedvecz, A. J., Dennis, B. M., Wang, L., Lindsell, C. J., \u0026amp; Guillamondegui, O. D. (2020). Impact of Operative Management on Recurrence of Adhesive Small Bowel Obstruction: A Longitudinal Analysis of a\u0026nbsp;Statewide\u0026nbsp;Database. J Am Coll Surg, 230(4), 544-551.e541. https://doi.org/10.1016/j.jamcollsurg.2019.12.006\u003c/li\u003e\n\u003cli\u003eMaung, A. A., Johnson, D. C., Piper, G. L., Barbosa, R. R., \u0026amp; Trauma, E. A. S. (2012). 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Development and external validation of prediction risk scores (STRISK and NOFA) to predict immediate surgical need in adhesive small bowel obstruction: an observational prospective multicentre study. Br J Surg, 112(3). https://doi.org/10.1093/bjs/znaf025\u003c/li\u003e\n\u003cli\u003eFu, W. J., Xiao, X., Gao, Y. H., Hu, S., \u0026amp; Yang, Q. (2023). Analysis of risk factors for recurrence and prognosis of adhesive small bowel obstruction. Asian J Surg, 46(9), 3491-3495. https://doi.org/10.1016/j.asjsur.2022.09.133\u003c/li\u003e\n\u003cli\u003eBehman, R., Nathens, A. B., Mason, S., Byrne, J. P., Hong, N. L., Pechlivanoglou, P., \u0026amp; Karanicolas, P. (2019). Association of Surgical Intervention for Adhesive Small-Bowel Obstruction With the Risk of Recurrence. JAMA Surg, 154(5), 413-420. https://doi.org/10.1001/jamasurg.2018.5248\u003c/li\u003e\n\u003cli\u003eYang, K. M., Yu, C. S., Lee, J. L., Kim, C. W., Yoon, Y. S., Park, I. J., Lim, S. B., \u0026amp; Kim, J. C. (2017). 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R., Tu, P. S., Chen, W. X., Chen, S., Chen, Q. F., Weng, Z. Q., Shang-Guan, X. C., Lin, B. Q., \u0026amp; Chen, X. Q. (2024). Comparison of the effect between traditional conservation and nasointestinal tube placement in adhesive small bowel obstruction: A matched case-control study. Asian J Surg, 47(5), 2168-2177. https://doi.org/10.1016/j.asjsur.2024.02.042\u003c/li\u003e\n\u003cli\u003eSun FT, Zhang HN, Yu Lu, et al. Value of Multilayer Spiral CT in Differential Diagnosis of Membranous and Band-like Adhesions Causing Small Bowel Obstruction. Journal of Practical Radiology 2020;36(9):1422-1425,1465. (In Chi). DOI: 10.3969/j.issn.1002-1671.2020.09.017.\u003c/li\u003e\n\u003cli\u003eZhou CJ, Huang WJ, Chen JL, et al. CT Feature Classification of Adhesive Small Bowel Obstruction and Its Clinical Significance. Modern Medical Imaging 2021;30(5):793-800.\u003c/li\u003e\n\u003cli\u003evan Veen, T., Ramanathan, P., Ramsey, L., Dort, J., \u0026amp; Tabello, D. (2023). Predictive factors for operative intervention and ideal length of non-operative trial in adhesive small bowel obstruction. Surg Endosc, 37(11), 8628-8635. https://doi.org/10.1007/s00464-023-10282-9\u003c/li\u003e\n\u003cli\u003eYamamoto, Y., Miyagawa, Y., Kitazawa, M., Tanaka, H., Kuroiwa, M., Hondo, N., Koyama, M., Nakamura, S., Tokumaru, S., Muranaka, F., \u0026amp; Soejima, Y. (2021). Association of feces sign with prognosis of non-emergency adhesive small bowel obstruction. Asian J Surg, 44(1), 292-297. https://doi.org/10.1016/j.asjsur.2020.07.012\u003c/li\u003e\n\u003cli\u003eHou ZB, He Y, Zhao H, et al. Study on the Prediction of Non-surgical Treatment Failure in Patients with Small Bowel Obstruction by Platelet/Lymphocyte Ratio. Parenteral \u0026amp; Enteral Nutrition 2024;31(4):233-238. (In Chi). DOI: 10.16151/j.1007-810x.2024.04.005.\u003c/li\u003e\n\u003cli\u003eCho, Y. J., Park, I. S., Kim, J., Cho, H. J., Gwak, G. H., Yang, K. H., Bae, B. N., \u0026amp; Kim, K. H. (2020). Factors Predicting the Need for Early Surgical Intervention for Small Bowel Obstruction. Ann Coloproctol, 36(4), 223-228. https://doi.org/10.3393/ac.2019.09.30\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Adhesive Small Bowel Obstruction, Nomogram, Surgical Conversion, Nonoperative Management, Predictive Model","lastPublishedDoi":"10.21203/rs.3.rs-6445977/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6445977/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eNonoperative management (NOM) with nasoenteric decompression tubes is a preferred strategy for adhesive small bowel obstruction (ASBO), yet treatment failure may lead to delayed surgery and increased mortality. Current predictive tools lack integration of clinical, laboratory, and imaging indicators.\u003cbr\u003e\n\u003cstrong\u003eObjective: \u003c/strong\u003eTo develop and validate a nomogram for predicting the risk of NOM failure requiring surgical conversion in ASBO patients.\u003cbr\u003e\n\u003cstrong\u003eMethods: \u003c/strong\u003eThis retrospective study included 61 ASBO patients treated with nasoenteric decompression at Qilu Hospital of Shandong University Dezhou Hospital (January 2022–January 2025). Independent predictors were identified via univariate and multivariate logistic regression. A nomogram was constructed and internally validated using 1000 bootstrap resamples. Model performance was assessed using ROC curves, calibration curves, and decision curve analysis (DCA).\u003cbr\u003e\n\u003cstrong\u003eResults: \u003c/strong\u003eMultivariate analysis identified three independent predictors: History of previous adhesive small bowel obstruction (OR=6.661, 95% CI: 1.210–36.680), low hemoglobin (OR=0.951, 95% CI: 0.906–0.998), and Small bowel feces sign (OR=0.11, 95% CI: 0.022–0.542). The nomogram demonstrated excellent discrimination (AUC=0.864, 95% CI: 0.753–0.946), calibration (Brier score=0.039), and clinical net benefit (0.361 within a threshold probability of 15%–65%).\u003cbr\u003e\n\u003cstrong\u003eConclusion: \u003c/strong\u003eThis nomogram, integrating clinical, laboratory, and imaging data, provides a practical tool for early identification of high-risk ASBO patients.\u003c/p\u003e","manuscriptTitle":"Development of a Nomogram for Predicting Surgical Conversion After Failure of Intestinal Obstruction Catheter Treatment in Adhesive Small Bowel Obstruction: A Single-Center Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 06:58:14","doi":"10.21203/rs.3.rs-6445977/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":"603887f7-aadd-4b8a-bb0d-d3d31fa8a004","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-25T06:58:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-25 06:58:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6445977","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6445977","identity":"rs-6445977","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}