ObjectiveTo analyze the risk factors relevant retrograde type A aortic dissection (RTAD) after thoracic endovascular aortic repair (TEVAR) for Stanford type B aortic dissection and provide a reference for its prevention and management. MethodsA retrospective analysis was conducted on patients with Stanford type B aortic dissection who underwent TEVAR at the First Affiliated Hospital of Chongqing Medical University from January 2017 to June 2023. The patients met the inclusion and exclusion criteria were included in the study. The multivariate logistic regression was used to analyze the risk factors for RTAD, with a test level of α=0.05. ResultsA total of 176 patients were included, among whom 7 developed RTAD, with an occurrence rate of 3.98%. The multivariate logistic regression analysis revealed that the larger τ angle between the centerline of the aorta [OR (95%CI)=1.195 (1.032, 1.384)] and the degree of curvature of the aortic arch (the curve distance from the proximal brachiocephalic trunk to the distal left subclavian artery) [OR (95%CI)=0.756 (0.572, 0.999)], the higher probability of RTAD after TEVAR (P＜0.05). ConclusionsFrom the results of this study, it can be seen that for patients with Stanford B-type aortic dissection underwent TEVAR treatment, careful preoperative evaluation of morphological characteristics of the aortic arch (particularly the τ angle of the aorta centerline and the degree of curvature of the aortic arch (the curve distance from the proximal brachiocephalic trunk to the distal left subclavian artery) is crucial for reducing the occurrence of RTAD after TEVAR in patients with Stanford type B aortic dissection.
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 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.
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.
Objective To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) undergoing total knee arthroplasty (TKA). Methods A retrospective cohort study was conducted including RA patients who underwent unilateral TKA between January 2019 and December 2024. Inpatient and 30-day postoperative outpatient follow-up data were collected. Six machine learning algorithms, including decision tree (DT), random forest (RF), logistic regression (LR), support vector machine (SVM), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), were used to construct predictive models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall. SHAP values were employed to interpret and rank the importance of individual variables. Results According to the inclusion criteria, a total of 1 548 patients were enrolled. Ultimately, 18 preoperative indicators were identified as effective predictive features, and 8 postoperative complications were defined as prediction labels for inclusion in the study. Within 30 days after surgery, 453 patients (29.2%) developed one or more complications. Considering overall accuracy, precision, recall, and F1-score, the random forest model [AUC=0.930, 95%CI(0.910, 0.950)] and the extreme gradient boosting model [AUC=0.909, 95%CI(0.880, 0.938)] demonstrated the best predictive performance. SHAP analysis revealed that anti-cyclic citrullinated peptide antibody, C-reactive protein, rheumatoid factor, interleukin-6, body mass index, age, and smoking status made significant contributions to the overall prediction of postoperative complications. Conclusion Machine learning-based models enable accurate prediction of postoperative complication risks among RA patients undergoing TKA. Inflammatory and immune-related blood biomarkers, such as anti- cyclic citrullinated peptide antibody, C-reactive protein, and rheumatoid factor, interleukin-6, play key predictive roles, highlighting their potential value in perioperative risk stratification and individualized management.
Objective A comparative study of in-hospital mortality and risk factors of ventilator-associated pneumonia (VAP) caused by carbapenem-resistant gram-negative bacteria (CRGNB) and non-carbapenem-resistant gram-negative bacteria (nCRGNB) in China was conducted to investigate whether there is a higher in-hospital mortality of VAP caused by CRGNB and its unique associated risk factors. Methods Relevant literatures published at home and abroad in PubMed, EMBASE, Cochrane library, Web of Science, CNKI and Wanfang databases were retrieved from the date of establishment to June 1, 2021, and the quality of the included literatures was evaluated using Newcastle-Ottawa scale. Meta-analysis of literatures meeting the criteria was performed using RevMan 5.3 software. Results A total of 5 literatures were included, all of which were case-control studies with a total of 574 cases, including 302 cases in the CRGNB group and 272 cases in the nCRGNB group. The results showed that the in-patient mortality of VAP caused by CRGNB infection was significantly increased compared with that of VAP caused by nCRGNB infection (OR=2.51, 95%CI 1.71 - 3.67, P<0.00001). Risk factor analysis of CRGNB infection showed that statistically significant risk factors included mechanical ventilation duration ≥7 days (OR=2.66, 95%CI 1.23 - 5.75, P=0.01), secondary intubation (OR=4.48, 95%CI 2.61 - 7.69], P<0.00001), combined with antibiotics (OR=2.83, 95%CI 1.76 - 4.54, P<0.0001), using carbapenem antibiotics (OR=2.78, 95%CI 1.76 - 4.40, P<0.0001). In addition, two studies showed that tigecycline was sensitive to CRGNB in vitro. Conclusions Compared with nCRGNB-induced VAP, CRGNB infection significantly increases the in-hospital mortality of VAP patients in China, indicating that the in-hospital mortality of CRGNB infection is related to drug resistance, and had little relationship with region and drug resistance mechanism. Among them, mechanical ventilation duration ≥7 days, secondary intubation, combined use of antibiotics and carbapenem antibiotics are risk factors for CRGNB infection in VAP patients. Tigecycline is sensitive to most CRGNB strains in China and is an important choice for the treatment of CRGNB in China.
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.
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 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.
Percutaneous renal puncture biopsy is an invasive procedure, and there are still some risks in its application. Bleeding after puncture is a major risk of percutaneous renal biopsy. In order to improve the safety of percutaneous renal puncture biopsy, clinical researchers have been exploring and studying the possible etiology, risk factors and prevention measures of postoperative bleeding in recent years. It is of great significance to clarify the risk factors of bleeding after percutaneous renal puncture biopsy and take timely targeted measures to reduce the risk to the maximum extent for improving the control effect of postoperative bleeding and other complications. This article intends to analyze and summarize the clinical research progress on the occurrence and risk factors of bleeding after percutaneous renal biopsy, in order to provide reference for the prevention and treatment of bleeding after percutaneous renal puncture biopsy.