ObjectiveTo compare the properties of hernia repair mesh of different materials used in clinical practice, so as to provide reference for clinical selection of numerous meshes at present. MethodThe literatures of different materials of hernia mesh in the treatment of abdominal hernia and inguinal hernia at home and abroad were reviewed.ResultsThe synthetic mesh, especially the polypropylene mesh with wide-pore mesh in the midweight mesh, might be the most ideal synthetic mesh. The new coating material improved the defect of polypropylene material to a great extent. The status of biological mesh in complex hernia repair had been waxed, and it had a tendency to be replaced by absorbable synthetic mesh.ConclusionsCurrently, there is no single mesh suitable for all types of hernia repair. Polypropylene mesh is still an effective and low cost mesh material, and there may be more room for the development of absorbable synthetic materials and antimicrobial coatings.
ObjectiveTo summarize the research status of risk factors of chronic postoperative inguinal pain (CPIP).MethodWe searched and summarized the domestic and foreign literatures about the risk factors of CPIP in recent years.ResultsThere was no doubt that the risk factors of CPIP included preoperative pain, acute pain at postoperative, recurrent inguinal hernia, smaller hernia sac, higher body mass index (BMI), and surgical methods. These effects were controversial such as age, gender, and the mesh. In recent years, hypertension and a past history of chronic pain may also be risk factors for the development of CPIP.ConclusionsThe risk factors of CPIP still need the further study.
目的 探讨胃大部切除术后吻合口溃疡的诊治方法。方法 1985年3月至2008年6月期间兰州大学第一医院收治的胃大部切除术后吻合口溃疡患者29例，均经胃镜证实，其中男16例，女13例； 年龄30～51（40±3.0）岁； 19例为十二指肠球部溃疡术后，10例为胃溃疡术后。初次手术到溃疡再发症状的时间，最短1例为1个月，其余28例为3～4年。2例吻合口溃疡穿孔及4例吻合口溃疡出血者行包括吻合口在内的残胃部分切除、胃空肠Roux-Y吻合术； 其余均给予非手术治疗。结果 行再手术治疗者术后发生切口感染1例，行保守治疗； 所有患者均治愈，随访1～5年，未出现溃疡复发。结论 吻合口溃疡首选保守治疗，多数可治愈。再次手术方式可采用残胃部分切除加胃空肠Roux-Y吻合术。
ObjectiveTo summarise the influencing factors of gut microbiota in the perioperative period and its regulatory mechanism in postoperative pain, with the aim of providing clinical reference for postoperative pain management. MethodRelevant literatures on gut microbiota and postoperative pain in recent years were systematically reviewed and synthesised. ResultsAnaesthesia, preoperative mechanical bowel preparation, surgical stress, etc. could cause gut microbiota dysbiosis. Gut microbiota directly or indirectly modulated the excitability of primary sensory neurons through their derived metabolites and pathogen-associated molecular patterns and influenced the pain signalling process by activating immune cells to release cytokines. ConclusionsGut microbiota play an important role in the development and progression of postoperative pain. Future studies should further clarify its role in different types of postoperative pain and develop innovative therapeutic strategies based on the regulation of gut microbiota to improve the management of postoperative pain.
ObjectiveTo investigate the risk factors and establish the predictive pattern of the metachronous liver metastasis after curative surgery for patientswith gastric cancer. MethodsThe clinicopathologic data of patients who underwent radical gastric cancer surgery and met the inclusion and exclusion criteria from January 1, 2015 and January 1, 2018 in the First Hospital of Lanzhou University were retrospectively analyzed. The risk factors affecting metachronous liver metastasis of gastric cancer were screened out by univariate and multivariate logistic regression analysis. And a nomogram prediction model based on the risk factors screened out was established and its predictive efficiency was evaluated. ResultsA total of 203 patients were collected in this study, of whom 41 (20.4%) developed metachronous liver metastasis of gastric cancer. The results of multivariate logistic regression analysis showed that the tumor diameter ≥5 cm, increasing intraoperative bleeding, carcinoembryonic antigen (CEA) ≥5 μg/L, and lymphovascular invasion increased the risks of metachronous liver metastasis of gastric cancer (all P<0.05). The area under the receiver operating characteristic curve and its 95% confidence interval (95%CI) of the nomogram based on these risk factors in predicting metachronous liver metastasis of gastric cancer was 0.850 (0.793, 0.908), and the consistency index (95%CI) was 0.812 (0.763, 0.859). The calibration curve for predicting the risk of metachronous liver metastasis in gastric cancer by the nomogram was close to the 45° ideal curve and had a stronger calibration (Hosmer Limeshow goodness-of-fit test, χ2=2.116, P=0.347). ConclusionsThe results of this study conclude metachronous liver metastasis of gastric cancer is not low, and the patient with lymphovascular invasion, higher level of CEA (≥5 μg/L), more intraoperative bleeding, and larger tumor diameter (≥5 cm) has a higher risk of metachronous liver metastasis of gastric cancer. The nomogram prediction model established based on these risk factors has a good predictive efficiency and can provide reference for clinicians to identify high-risk patient and take early interventions.
ObjectiveTo evaluate existing predictive models for surgical site infection (SSI) following colorectal cancer (CRC) surgery, aiming to provide a scientific basis for refining risk prediction models and developing clinically practical and widely applicable screening tools. MethodA comprehensive review of existing literature on predictive models for SSI following CRC surgery, both domestically and internationally, were conducted. ResultsThe determination of SSI following CRC surgery primarily relied on the Centers for Disease Control and Prevention standard of USA, which presented issues of consistency and accuracy. Various predictive models had been developed, including traditional statistical models and machine learning models, with 0.991 of an area under the operating characteristic curve of predictive model. However, most studies were based on retrospective and single-center data, which limited their applicability and accuracy. ConclusionsAlthough existing models provide strong support for predicting SSI following CRC surgery, there is a need for multi-center, prospective studies to enhance the generalizability and accuracy of these models. Additionally, future research should focus on improving model interpretability to better apply them in clinical practice, providing personalized risk assessments and intervention strategies for patients.
Objective To understand the changes of intestinal flora during perioperative period of colorectal cancer and the mechanism affecting the occurrence of postoperative anastomotic leakage, so as to improve perioperative management of patients and find possible measures to decrease the incidence rate of anastomotic leakage. Method The literature related to perioperative intestinal flora assessment, anastomotic healing, and anastomotic leakage of colorectal cancer in recent years was comprehensively searched in the CNKI, PubMed, and Embase databases and made an review. ResultsDue to the various perioperative interventions, the diversity and abundance of intestinal flora had changed after colorectal cancer surgery, and some conditional pathogenic bacteria such as Enterococcus faecalis, Pseudomonas aeruginosa, etc. increased obviously, which led to collagen degradation through the expression of bacterial collagenase or the excessive activation of matrix metalloproteinases in the host intestine, then might lead to the poor anastomotic healing and even the anastomotic leakage. ConclusionAlthough the evidence of effect of intestinal flora on anastomotic leakage mainly comes from animal experiments, it still shows the potential role of intestinal flora in the occurrence of anastomotic leakage after colorectal cancer surgery, and can be regulated by perioperative intervention, which suggests that it may provide a new strategy for prevention of anastomotic leakage.
ObjectiveTo systematically summarize the research progress in risk prediction models for postoperative anastomotic leakage in gastric cancer, and to explore the advantages and limitations of models constructed using traditional statistical methods and machine learning, thereby providing a theoretical basis for clinical precision prediction and early intervention. MethodBy analyzing domestic and international literature, the construction strategies of logistic regression, least absolute shrinkage and selection operator (LASSO) regression, and machine learning models (support vector machine, random forest, deep learning) were systematically reviewed, and their predictive performance and clinical applicability were compared. ResultsThe traditional logistic regression and LASSO regression models performed excellently in terms of interpretability and in small-sample scenarios but were limited by linear assumptions. The machine learning models significantly enhanced predictive capabilities for complex data through non-linear modeling and automatic feature extraction, but required larger data scales and had higher demands for interpretability. ConclusionsDifferent prediction models have their own advantages and limitations; in practical clinical applications, they should be flexibly selected or complementarily applied based on specific scenarios. Current anastomotic leakage prediction models are evolving from single factor analysis to multi-modal dynamic integration. Future efforts should combine artificial intelligence and multi-center prospective clinical studies to validate, so advancing the development of precise and individualized anastomotic leakage predictive tools for patients after gastric cancer resection.