ObejectiveTo summarize the research progress of risk factors contributing to postoperative pulmonary infection in gastric cancer, so as to provide reference for medical decision-makers and clinical practitioners to effectively control the incidence of postoperative pulmonary infection in gastric cancer, ensure medical safety and improve the quality of life of patients. MethodThe researches at home and abroad on the factors contributing to pulmonary infection after gastric cancer surgery in recent years were reviewed and analyzed. ResultsThere was currently no uniform diagnostic standard for pulmonary infection. The incidence of postoperative pulmonary infection for gastric cancer varied in the different countries and regions. The pathogenic bacteria that caused postoperative pulmonary infection of gastric cancer was mainly gram-negative bacteria, especially Pseudomonas aeruginosa, Escherichia coli, Acinetobacter boulardii, and Klebsiella pneumoniae. The patient’s age, history of smoking, preoperative pulmonary function, preoperative laboratory indicators, preoperative comorbidities, preoperative nutritional status, preoperative weakness, anesthesia, tumor location, surgical modality, duration of surgery, blood transfusion, indwelling gastrointestinal decompression tube, wound pain, and so on were possible factors associated with postoperative pulmonary infection of gastric cancer. ConclusionsThe incidence of postoperative pulmonary infection for gastric cancer is not promising. Based on the recognition of related factors, it is proposed that it is necessary to develop a risk prediction model for postoperative pulmonary infection of gastric cancer to identify high-risk patients. In addition to the conventional intervention strategy, taking the pathogenesis as the breakthrough, finding the key factors that lead to the occurrence of postoperative pulmonary infection of gastric cancer is the fundamental way to reduce its occurrence.
ObjectiveTo explore the relation between preoperative serum gamma-glutamyl transpeptidase to platelet ratio (GPR) and overall survival (OS) of patients with hepatitis B virus-associated hepatocellular carcinoma (Abbreviated as “patients with HCC”), and to establish a nomogram for predicting OS. MethodsAccording to the inclusion and exclusion criteria, the clinicopathologic data of patients with HCC who underwent radical resection in the Department of Hepatobiliary Surgery of Xianyang Central Hospital, from January 15, 2012 to December 15, 2018, were retrospectively analyzed. The optimal critical value of GPR was determined by receiver operating characteristic curve, then the patients were divided into a low GPR group (GPR was optimal critical value or less ) and high GPR group (GPR was more optimal critical value). The Kaplan-Meier method was used to draw the survival curve and analyze the OS of patients. The univariate and multivariate Cox proportional hazards regression model were used to analyze the factors influencing prognosis in the patients with HCC. According to the risk factors of OS for patients with HCC, a nomogram was established. The consistency index and calibration curve in predicting the 3-year and 5-year accumulative OS rates of patients with HCC were evaluated. ResultsA total of 213 patients were gathered. The optimal critical value of GPR was 0.906. There were 114 patients in the low GPR group and 99 patients in the high GPR group. The Kaplan-Meier survival curve analysis showed that the 1-, 3- and 5-year accumulative OS rates were 99.1%, 81.8%, 60.6% in the low GPR group, respectively, which were 74.2%, 49.1%, 35.7% in the low GPR group, respectively. The OS curve of the low GPR group was better than that of the high GPR group (χ2=25.893, P<0.001). The multivariate analysis results showed that the microvascular invasion, incomplete capsule, intraoperative bleeding ＞1 000 mL, postoperative complications, GPR >0.906, low tumor differentiation, and late TNM stage did not contribute to accumulative OS in the patients with HCC (P<0.05). The consistency index (95%CI) of the nomogram in predicting accumulative OS rates at 3- and 5-year for patients with HCC were 0.761 (0.739, 0.783) and 0.735 (0.702, 0.838), respectively. The calibration curves of 3- and 5-year accumulative OS rates of the nomogram were in good agreement with the actual results. ConclusionsPreoperative GPR is associated with OS, and patients with higher GPR have worse prognosis. The nomogram based on GPR has a good accuracy and differentiation.
ObjectiveTo explore the association between wearing dentures and the risk of head and neck cancer using meta-analysis. MethodsPubMed, EMbase, CNKI, and WanFang Data were searched up to April 30th, 2014, for cohort studies and case-control studies about the association between wearing dentures and the risk of head and neck cancer. Literature screening according to the inclusion and exclusion criteria, data extraction and methodological quality assessment of included studies were completed by two reviewers independently. Then meta-analysis was conducted using Comprehensive Meta-Analysis v 2.2 software. ResultsEight case-control studies in 7 reports were finally included. The results of meta-analysis revealed that, low-degree association existed between wearing dentures and the risk of head and neck cancer (OR=1.08, 95%CI 1.00 to 1.16); and the results of further subgroup analysis (according to gender, cancer lesions, confounders adjustment, and publication years) also showed no significant difference. ConclusionWearing dentures is not significantly associated with the risk of head and neck cancer (no difference regarding gender or cancer lesions). Due to limitations of this meta-analysis, high-quality studies with large sample size are needed to further verify the above conclusion.
ObjectiveTo analyze the risk factors affecting delayed gastric emptying (DGE) after laparoscopic distal gastrectomy for gastric cancer. MethodsThe gastric cancer patients who underwent laparoscopic distal gastrectomy in the Jiaozuo People’s Hospital from January 1, 2013 to December 31, 2022 were retrospectively collected. The occurrence of DGE was recorded. Meanwhile, the multivariate binary logistic regression analysis was performed to screen the risk factors affecting the DGE. ResultsA total of 350 gastric cancer patients underwent laparoscopic distal gastrectomy and met the inclusion and exclusion criteria of this study were included, 17 (4.9%) of whom developed DGE. The multivariate binary logistic regression analysis results showed that the preoperative gastric outflow tract obstruction (OR=8.582, P=0.009), intraoperative jejunal nutrition tube indwelling (OR=14.317, P=0.010), more peritoneal drainage tube placement (OR=5.455, P=0.006), and intraoperative blood loss ≥140 mL (OR=4.912, P=0.018) increased the risk of DGE. ConclusionAccording to the results of this study, when patients undergoing laparoscopic distal radical gastrectomy for gastric cancer accompanied by preoperative gastric outflow tract obstruction, intraoperative jejunal nutrition tube indwelling, more peritoneal drainage tube placement, and more intraoperative blood loss, it should be paid more attention to prevention DGE, and early detection and treatment, so as to improve the prognosis of patients.
Objective To assess the risk factors associated with postoperative infection after elective abdominal operation for elderly in department of general surgery. Methods One hundred and fifty-nine consecutive elderly patients admitted to the department of general surgery in our hospital for elective abdominal operation between May 2010 and February 2012 were considered for inclusion and retrospectively analyzed. Thirty-eight patients （23.90%）with postoperative infection were taken as the infection group and 121 patients without postoperative infection as noninfection group. The differences in the objective physiological indicators， subjective health status indicators， operation status， the incidence of postoperative infective complications， and mortality were compared between the two groups. Results Of enrolled 159 patients in this study， the incidence of postoperative infective complications was 23.90% （38/159）； 2 patients died， and the postoperative mortality rate was 1.26%. Single factor and multivariate logistic regression analysis showed that preoperative malnutrition risk， history of diabetes， and chronic respiratory system disease were the independent risk factors of postoperative infection complications in elective abdominal surgery for elderly patients. Conclusion Improving preoperative respiratory function， diabetes mellitus， and nutritional status would help to reduce incidence of postoperative infection for elderly patients with elective abdominal operation.
The high incidence and mortality of acute kidney injury (AKI) have brought great challenges to global health. In recent years, China has made some achievements in the epidemiology, risk factors and treatment of AKI. However, further prevention and treatment are still facing difficulties. Based on current new ideas and research progress, this paper summarized and analyzed the management throughout the whole course of AKI, including AKI risk assessment, early prevention, early identification, treatment and follow-up. The aim is to make Chinese nephrologists realize the focus of AKI prevention and treatment, standardize the management of AKI, and explore the prevention and treatment strategy suitable for AKI in China.
ObjectiveTo identify the risk factors of bone metastasis in breast cancer and construct a predictive model. MethodsThe data of breast cancer patients met inclusion and exclusion criteria from 2010 to 2015 were obtained from the SEER*Stat database. Additionally, the data of breast cancer patients diagnosed with distant metastasis in the Affiliated Hospital of Southwest Medical University from 2021 to 2023 were collected. The patients from the SEER database were randomly divided into training (70%) and validation (30%) sets using R software, and the breast cancer patients from the Affiliated Hospital of Southwest Medical University were included in the validation set. The univariate and multivariate logistic regressions were used to identify risk factors of breast cancer bone metastasis. A nomogram predictive model was then constructed based on these factors. The predictive effect of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis. ResultsThe study included 8 637 breast cancer patients, with 5 998 in the training set and 2 639 (including 68 patients in the Affiliated Hospital of Southwest Medical University) in the validation set. The statistical differences in the race and N stage were observed between the training and validation sets (P<0.05). The multivariate logistic regression analysis revealed that being of white race, having a low histological grade (Ⅰ–Ⅱ), positive estrogen and progesterone receptors status, negative human epidermal growth factor receptor 2 status, and non-undergoing surgery for the primary breast cancer site increased the risk of breast cancer bone metastasis (P<0.05). The nomogram based on these risk factors showed that the AUC (95% CI) of the training and validation sets was 0.676 (0.533, 0.744) and 0.690 (0.549, 0.739), respectively. The internal calibration using 1 000 Bootstrap samples demonstrated that the calibration curves for both sets closely approximated the ideal 45-degree reference line. The decision curve analysis indicated a stronger clinical utility within a certain probability threshold range. ConclusionsThis study constructs a nomogram predictive model based on factors related to the risk of breast cancer bone metastasis, which demonstrates a good consistency between actual and predicted outcomes in both training and validation sets. The nomogram shows a stronger clinical utility, but further analysis is needed to understand the reasons of the lower differentiation of nomogram in both sets.
ObjectiveTo explore the risk factors affecting sentinel lymph node (SLN) metastasis in patients with early-stage (N0) breast cancer and establish a predictive model for SLN metastasis, so as to assist in decision-making of axillary surgery in clinical practice. MethodsThe unilateral early-stage breast cancer patients who underwent surgical treatment and SLN biopsy at the Affiliated Hospital of Southwest Medical University from September 2020 to December 2023 were selected as the study subjects. The univariate and multivariable logistic regression analyses were adopted to analyze the relevant risk factors of SLN metastasis, then a predictive model evaluating the risk of SLN metastasis was constructed. The area under receiver operating characteristic curve (AUC) was used to assess the distinguishing ability of risk factors for SLN metastasis. ResultsA total of 351 patients with early-stage breast cancer patients who met the inclusion criteria were enrolled, 136 of whom with SLN metastasis, the SLN metastasis rate was 38.7%. The results of the multivariate logistic regression analysis showed that the maximum tumor diameter >2.5 cm, estrogen receptor (ER) positive, Ki-67 >20%, and vascular invasion were the risk factors affecting SLN metastasis [maximum tumor diameter: OR(95%CI)=1.897(1.186, 3.034), P=0.008; ER positive: OR(95%CI)=2.721(1.491, 4.967), P=0.001; Ki-67 >20%: OR(95%CI)=1.825(1.125, 2.960), P=0.015; vascular invasion: OR(95%CI)=2.858(1.641, 4.976), P<0.001]. The AUC for the SLN metastasis by these four factors was 0.693(0.637, 0.749), with a sensitivity and specificity of 70.59% and 57.21%, respectively. ConclusionsThe results from this study suggest that SLN biopsy is recommended to guide postoperative adjuvant treatment strategies for cN0 early-stage breast cancer patients with a maximum tumor diameter >2.5 cm, ER positivity, Ki-67>20%, and vascular invasion. However, the predictive model constructed based on these four factors in this study has a general ability to distinguish the occurrence of SLN metastasis, then the reasons can be further analyzed in the future.
ObjectiveTo explore the risk factors affecting catheter obstruction during hyperthermic intraperitoneal chemotherapy (HIPEC). MethodsBased on the inclusion and exclusion criteria, the patients who underwent HIPEC at the First Affiliated Hospital of Xi’an Jiaotong University from February 2023 to December 2023 were retrospectively collected. The data were analyzed using univariate analysis and machine learning. The statistical significance was defined as α=0.05. ResultsA total of 210 patients underwent HIPEC and met the inclusion criteria were included, 51 (24.3%) experienced catheter obstruction. The univariate analysis revealed that the inflow-outflow temperature gradient of the perfusate (ΔT of the perfusate), flow velocity of perfusate, neoadjuvant chemotherapy exposure, hypertension status, surgical approach, and HIPEC catheter length were associated with catheter obstruction (P<0.05). Subsequently, combining the results of the univariate analysis with feature values screened by machine learning, the following factors were selected, including HIPEC catheter length, ΔT of the perfusate, flow velocity of perfusate, age, gender, neoadjuvant chemotherapy exposure, fibrinogen level, hypertension status, surgical approach, and blood transfusion. A predictive model for HIPEC catheter obstruction based on these features was established, achieving an area under the receiver operating characteristic curve (95%CI) of 0.825 (0.757, 0.893). ConclusionThis study preliminarily identifies key factors influencing the incidence of catheter obstruction during HIPEC treatment, such as ΔT of the perfusate, flow velocity of perfusate, neoadjuvant chemotherapy exposure, surgical approach, HIPEC catheter length, and hypertension, continuously monitoring these factors, thereby reducing the risk of catheter obstruction.
ObjectiveTo use machine learning technology to predict the recurrence of atrial fibrillation (AF) after radiofrequency ablation, and try to find the risk factors affecting postoperative recurrence. MethodsA total of 300 patients with valvular AF who underwent radiofrequency ablation in West China Hospital and its branch (Shangjin Hospital) from January 2017 to January 2021 were enrolled, including 129 males and 171 females with a mean age of 52.56 years. We built 5 machine learning models to predict AF recurrence, combined the 3 best performing models into a voting classifier, and made prediction again. Finally, risk factor analysis was performed using the SHApley Additive exPlanations method. ResultsThe voting classifier yielded a prediction accuracy rate of 75.0%, a recall rate of 61.0%, and an area under the receiver operating characteristic curve of 0.79. In addition, factors such as left atrial diameter, ejection fraction, and right atrial diameter were found to have an influence on postoperative recurrence. ConclusionMachine learning-based prediction of recurrence of valvular AF after radiofrequency ablation can provide a certain reference for the clinical diagnosis of AF, and reduce the risk to patients due to ineffective ablation. According to the risk factors found in the study, it can provide patients with more personalized treatment.