International journal of surgery最新文献

{"title":"A commentary on \"Prognostic value of iron-metabolism biomarkers in critically ill patients with atrial fibrillation: a machine learning-based retrospective cohort study\".","authors":"Xuesi Chen, Xiaoya Mao, Minmin Cai","doi":"10.1097/JS9.0000000000002978","DOIUrl":"https://doi.org/10.1097/JS9.0000000000002978","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Commentary on \"Usefulness of fluorescence imaging with indocyanine green for evaluation of bowel perfusion in the urgency setting: a systematic review and meta-analysis\".","authors":"Xinchao Yang, Liang Chen, Xionghui He","doi":"10.1097/JS9.0000000000002970","DOIUrl":"https://doi.org/10.1097/JS9.0000000000002970","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global Disparities in Healthcare Resources and Cancer Burden: A Population-based Systematic Analysis of 171 Countries in 2022.","authors":"Qian Zhu, Kexin Sun, Yifei Yao, Xiang Li, Min Dai, Wenqiang Wei, Freddie Bray, Rongshou Zheng","doi":"10.1097/JS9.0000000000002960","DOIUrl":"https://doi.org/10.1097/JS9.0000000000002960","url":null,"abstract":"<p><strong>Background: </strong>Global disparities in healthcare resources impact diagnosis, treatment, and ongoing supportive care for cancer. As these resource levels can be considered modifiable factors of health inequality on a global scale, we aimed to explore their association with the global cancer burden and quantify the extent of these inequalities.</p><p><strong>Methods: </strong>Healthcare resource capacity was measured using the universal health coverage (UHC) index and current health expenditure as a percentage of gross domestic product (CHE/GDP (%)). Cancer data were sourced from the GLOBOCAN database. Variables such as age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and a proxy of 5-year survival [1- mortality to incidence ratio (1-M/I)] were calculated. Absolute and relative inequalities in cancer burden were assessed using the slope index of inequality (SII) and concentration index (CCI). The association between healthcare resources and cancer burden was further explored by negative binomial regression. Counterfactual simulations quantify inequalities based on healthcare resource levels.</p><p><strong>Results: </strong>Marked absolute and relative inequalities were found in the burden of most cancer types related to the UHC index and the CHE/GDP (%) gradient. Both the absolute and relative burdens of cancer were concentrated in areas with high UHC index and CHE/GDP (%) levels. A significant positive association was found between the ASIR (IRR: 1.77, 95%CI: 1.57 to 2.00) and survival (IRR: 1.60, 95%CI: 1.48 to 1.73) with the UHC index. A weaker positive association was found for CHE/GDP (%) with ASIR (IRR: 1.37, 95%CI: 1.20 to 1.56) and survival (IRR: 1.23, 95%CI: 1.13 to 1.35). No significant association was found between ASMR and either the UHC index or CHE/GDP (%). An estimated 21% of cancer deaths were associated with the potential to be prevented with survival rates matching the most advanced nations in each region, and over 31% of cancer deaths were associated with the potential to be prevented with survival rates matching the most advanced nations worldwide.</p><p><strong>Conclusions: </strong>Substantial inequalities in the cancer burden related to healthcare resources are apparent worldwide. Allocating healthcare resources at optimal levels can improve survival and reduce cancer-related deaths. These findings emphasize the need for targeted interventions and policies to address inequalities in healthcare resource allocation and ensure equitable access to cancer treatment.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective multicenter validation of a machine learning model for predicting anastomotic leakage in patients with gastric adenocarcinoma undergoing total or proximal gastrectomy.","authors":"Shengli Shao, Yanqi Li, Huangrong Cheng, Chao Chen, Ying Zeng, Wenjun Huang, Haiping Luo, Xiaoming Yu, Xiaoping Yin, Xinmeng Sun, Jichao Qin","doi":"10.1097/JS9.0000000000003025","DOIUrl":"https://doi.org/10.1097/JS9.0000000000003025","url":null,"abstract":"<p><strong>Objective: </strong>Predicting esophago-gastric and esophagojejunal anastomotic leakage (AL) is inherently challenging. The aim of the present study was to investigate the clinical utility of a real-time machine learning model for predicting AL.</p><p><strong>Background: </strong>AL is one of the most serious postoperative complications following esophagogastric and esophagojejunal anastomoses. Traditional risk stratification methods have often struggled to accurately predict which patients are most at risk, owing to the multifactorial nature of AL and the variability in patient and operative factors.</p><p><strong>Methods: </strong>In this prospective study, gastric adenocarcinoma patients who were scheduled for total or proximal gastrectomy from four medical centers were enrolled between January 2022 and January 2024. During operations, a developed machine learning model was used to assess the risk of AL. The primary outcome is the occurrence of AL.</p><p><strong>Results: </strong>A total of 512 patients were included. AL was observed in 13 patients (2.54%). The model yielded an area under the operating characteristic curve of 0.780, a sensitivity of 0.769, a specificity of 0.577 and a negative predictive value of 0.990. Of the 512 patients, 221 were identified as high-risk and 291 as low-risk. Compared with the low-risk group, the AL rate was significantly higher in the high-risk group (10/221 vs. 3/291; P = 0.027). Post hoc analysis revealed ~ 35% (risk score<0.45)patients can safely avoid intensive monitoring.</p><p><strong>Conclusions: </strong>By achieving high sensitivity while excluding nearly half of the non-AL subgroups, the model (https://gasal.21cloudbox.com/) provides effective risk stratification of AL in patients with gastric adenocarcinoma undergoing esophagogastrostomy or esophagojejunostomy.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk factors for acute kidney injury following radical cystectomy: a systematic review and meta-analysis.","authors":"Liang Liu, Jing-Po Li, Li-Xia Gao, Lin An, Dong Wei, Qiang Wang, Ji Zheng","doi":"10.1097/JS9.0000000000002537","DOIUrl":"https://doi.org/10.1097/JS9.0000000000002537","url":null,"abstract":"<p><strong>Background: </strong>The factors contributing to acute kidney injury (AKI) after radical cystectomy (RC) remain uncertain. This study aimed to determine the risk factors for AKI following RC and guide clinicians in implementing effective interventions for high-risk groups.</p><p><strong>Methods: </strong>Three English databases were searched for relevant articles published until November 2024. The odds ratio (OR), 95% confidence interval (CI), and P value were determined for each study using univariate or multivariate analysis. Random effects models were applied for high heterogeneity (I2 ≥ 50% or P < 0.05) instead of fixed effects models. Moreover, descriptive analysis was performed when meta-analysis was unfeasible. We investigated heterogeneity by performing subgroup and sensitivity analyses. A funnel plot was used to test for publication bias when the number of included studies was > 10.</p><p><strong>Results: </strong>Nine studies were included in the meta-analysis. The meta-analysis revealed that older age (OR = 1.02, 95% CI = [1.00, 1.03], P = 0.008), operative route (robot versus open, OR = 2.41, 95% CI = [1.35, 4.31], P = 0.003), and non-steroidal anti-inflammatory drug use (OR = 1.50, 95% CI = [1.01, 2.23], P = 0.05) were risk factors for postoperative AKI. Female gender (OR = 0.55, 95% CI = [0.35, 0.88], P = 0.01) was identified as a protective factor against postoperative AKI. Body mass index (OR = 1.02, 95% CI = [1.00, 1.04], P = 0.06), diabetes (OR = 1.00, 95% CI = [0.65, 1.53], P = 0.98), hypertension (OR = 1.76, 95% CI = [0.79, 3.93], P = 0.17), smoking (OR = 1.01, 95% CI = [0.74, 1.39], P = 0.94), cardiovascular disease (OR = 1.37, 95% CI = [0.70, 2.68], P = 0.35), estimated glomerular filtration rate (OR = 1.00, 95% CI = [0.98, 1.02], P = 0.89), neoadjuvant chemotherapy (OR = 1.23, 95% CI = [0.69, 2.20], P = 0.49), operation time (OR = 1.00, 95% CI = [0.99, 1.01], P = 0.87), intraoperative bleeding volume (OR = 1.00, 95% CI = [1.00, 1.00], P = 0.73), blood transfusion (OR = 1.46, 95% CI = [0.79, 2.72], P = 0.23), enhanced recovery after surgery program (OR = 1.35, 95% CI = [0.65, 2.78], P = 0.42), and urinary diversion (OR = 1.03, 95% CI = [0.45, 2.39], P = 0.94) were not associated with increased risk of AKI after RC.</p><p><strong>Conclusion: </strong>Obvious risk factors for AKI include one patient-related risk factor, such as older age, and two therapy-related risk factors, such as robot surgery and the use of non-steroidal anti-inflammatory drugs. Moreover, obvious protective factors for AKI include one patient-related factor, such as the female gender. However, these findings should be approached carefully, as most of these risk factors exhibited minimal effect sizes. Nonetheless, they could aid clinicians in identifying high-risk patients for better prognosis.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging regenerative medicine with digital intelligence: enhancing stem cell therapy for female infertility through AI and digital health.","authors":"Jingxuan Peng, Sha Li, Zhengyan Tang","doi":"10.1097/JS9.0000000000003086","DOIUrl":"https://doi.org/10.1097/JS9.0000000000003086","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence in digital pathology of breast cancer, new era of practice?","authors":"Wenjing Li, Sijing Ye, Zimeng Jin, Lin Chen, Yuqing Chao, Guikang Wei, Qinyi Huang, Huakang Tu, Qinchuan Wang","doi":"10.1097/JS9.0000000000002953","DOIUrl":"https://doi.org/10.1097/JS9.0000000000002953","url":null,"abstract":"<p><p>Breast cancer is the most common cancers among women worldwide. Early diagnosis and personalized medicine are crucial for the treatment of breast cancer. With the development of computer science and the emergence of whole slide imaging technology (WSIs), artificial intelligence(AI) is having a surprisingly positive impact on the field of pathology, including breast pathology. The deployment of AI provides powerful tools for research in digital pathology and provides potential solutions in precision medicine in breast cancer. In this review, we systematically reviewed the applications of AI in digital pathology of breast cancer, including the identification of histological features, such as tumor-infiltrating lymphocytes (TILs), and the evaluation of classical biomarkers, such as human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), progesterone receptor (PR). We also introduce the combined use of AI with multi-omics data in outcome prediction and treatment in breast cancer, and outline the evolution of AI methods applied in digital pathology. Collectively, the robustly evolving AI technologies would profoundly impact the precision pathology and medicine in breast cancer.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stemness-associated WNT3A and EDN3 as key regulators of tumor progression and immunotherapy efficacy in LUAD.","authors":"Yuan Yuan, Xiaoliang Jin, Ma Long, Qingchao Sun, Liwei Zhang","doi":"10.1097/JS9.0000000000003029","DOIUrl":"https://doi.org/10.1097/JS9.0000000000003029","url":null,"abstract":"<p><strong>Abstract: </strong>Lung adenocarcinoma (LUAD) is a common and aggressive cancer. Stemness-related genes may play key roles in tumor progression and immune response, but their specific contributions in LUAD remain unclear.</p><p><strong>Methods: </strong>Differential expression analysis, WGCNA, and survival analysis were used to study WNT3A and EDN3 in LUAD. GSEA was performed to explore biological pathways associated with WNT3A. Immune infiltration analysis evaluated the tumor microenvironment, and immunotherapy response was assessed. Experimental validation was conducted using qPCR and Western Blot on lung cancer cell lines.</p><p><strong>Results: </strong>WNT3A and EDN3 expression were significantly correlated with LUAD patient survival and showed high diagnostic value. GSEA revealed that high WNT3A expression activated pathways involved in tumor proliferation, metabolism, and immune escape. Patients with high WNT3A expression had lower macrophage infiltration and higher immune scores. Immunotherapy analysis showed better response rates in patients with high WNT3A expression, while EDN3 had no significant association. qPCR and Western Blot confirmed low WNT3A and EDN3 expression in lung cancer cells.</p><p><strong>Conclusions: </strong>WNT3A and EDN3 are potential prognostic biomarkers for LUAD. WNT3A, in particular, is associated with enhanced immunotherapy response, making it a promising target for future clinical applications.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating clinical-pathological-MRI features to construct a prediction model for pathological complete remission of axillary lymph nodes after neoadjuvant therapy: a retrospective study.","authors":"Jiabei Shang, Jianzhe Chen, Xudong Gao, Zhipeng Wan, Ruirong Yang, Zhenli Lei, Siqi Chen, Meining Chen, Yi Quan, Jiao Bai","doi":"10.1097/JS9.0000000000003070","DOIUrl":"10.1097/JS9.0000000000003070","url":null,"abstract":"<p><strong>Background: </strong>Accurate assessment of axillary lymph node (ALN) metastasis is essential for developing an effective treatment strategy for breast cancer (BC). Despite advancements in imaging and surgical techniques, a critical need remains for reliable, non-invasive methods to predict axillary response to neoadjuvant therapy (NAT). This study aimed to identify key factors influencing axillary lymph node pathological complete response (pCR) following NAT and to develop a predictive model for axillary pCR (apCR) to support clinical decision-making regarding the necessity of axillary lymph node dissection (ALND).</p><p><strong>Materials and methods: </strong>Clinical data from female patients diagnosed with breast cancer (BC) between January 2019 and December 2024 were retrospectively collected. All patients had biopsy-confirmed metastasis to ipsilateral axillary lymph nodes at initial presentation, received standardized neoadjuvant therapy (NAT), and subsequently underwent ALND. Patients were randomly divided into a training set (n = 354) and a test set (n = 151) in a 7:3 ratio. Based on ALND results, patients were classified into the apCR (axillary pathological complete response) and non-apCR groups, and their clinicopathological and magnetic resonance imaging (MRI) features were compared. Independent predictors of apCR were identified using multivariate logistic regression analysis, and feature selection was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) method. Two predictive models were developed, a Clinical-Pathological-MRI model and a Clinical-Pathological-Delta-MRI model. The predictive performance of both models was evaluated and compared.</p><p><strong>Results: </strong>A total of 505 patients were enrolled, including 237 patients in the apCR group and 268 in the non-apCR group. The AUC values for the Clinical-Pathological-MRI model were 0.817 in the training set and 0.680 in the test set. For the Clinical-Pathological-Delta-MRI model, the AUC values were 0.844 in the training set and 0.793 in the test set, indicating superior predictive performance. Decision curve analysis (DCA) further demonstrated that the Clinical-Pathological-Delta-MRI model provided greater net clinical benefit compared to the Clinical-Pathological-MRI model in both the training and test sets.</p><p><strong>Conclusion: </strong>This model may provide valuable support for individualized surgical decision-making and help guide the selective omission of axillary lymph node dissection in appropriate candidates.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A commentary on \"A novel approach to cancer rehabilitation: assessing the influence of exercise intervention on postoperative recovery and survival rates\".","authors":"Xing-Chen Zhou, Da-Ming Wang, Zuo-Bing Chen","doi":"10.1097/JS9.0000000000002873","DOIUrl":"https://doi.org/10.1097/JS9.0000000000002873","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":" ","pages":""},"PeriodicalIF":12.5,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}