ObjectiveTo explore the CT imaging features and independent risk factors for cystic pulmonary nodules and establish a malignant probability prediction model. Methods The patients with cystic pulmonary nodules admitted to the Department of Thoracic Surgery of the First People's Hospital of Neijiang from January 2017 to February 2022 were retrospectively enrolled. They were divided into a malignant group and a benign group according to the pathological results. The clinical data and preoperative chest CT imaging features of the two groups were collected, and the independent risk factors for malignant cystic pulmonary nodules were screened out by logistic regression analysis, so as to establish a prediction model for benign and malignant cystic pulmonary nodules. ResultsA total of 107 patients were enrolled. There were 76 patients in the malignant group, including 36 males and 40 females, with an average age of 59.65±11.74 years. There were 31 patients in the benign group, including 16 males and 15 females, with an average age of 58.96±13.91 years. Multivariate logistic analysis showed that the special CT imaging features such as cystic wall nodules [OR=3.538, 95%CI (1.231, 10.164), P=0.019], short burrs [OR=4.106, 95%CI (1.454, 11.598), P=0.008], cystic wall morphology [OR=6.978, 95%CI (2.374, 20.505), P<0.001], and the number of cysts [OR=4.179, 95%CI (1.438, 12.146), P=0.009] were independent risk factors for cystic lung cancer. A prediction model was established: P=ex/(1+ex), X=–2.453+1.264×cystic wall nodules+1.412×short burrs+1.943×cystic wall morphology+1.430×the number of cysts. The area under the receiver operating charateristic curve was 0.830, the sensitivity was 82.9%, and the specificity was 74.2%. ConclusionCystic wall nodules, short burrs, cystic wall morphology, and the number of cysts are the independent risk factors for cystic lung cancer, and the established prediction model can be used as a screening method for cystic pulmonary nodules.
ObjectiveTo construct a prediction model for the postoperative recurrence risk of granulomatous lobular mastitis (GM) based on multiple systemic inflammatory indicators and clinicopathologic characteristics, with the aim of guiding clinical treatment. MethodsThe GM patients who underwent lesion resection at Sichuan Provincial Hospital for Women and Children from January 2017 to March 2024 were retrospectively collected. The univariate and multivariate logistic regression analyses were used to screen the risk factors for recurrence after GM lesion resection, and a nomogram prediction model was constructed based on the risk factors. The test level was set at α=0.05. ResultsA total of 533 patients with GM were included in this study, of whom 118 cases (22.1%) developed postoperative recurrence. The results of multivariate analysis showed that the not taking oral bromocriptine, having microabscess formation in postoperative pathological examination, systemic immune inflammation index (SII) >789.0×109/L, and immunoglobulin E (IgE) >64.4 U/mL were the independent risk factors for recurrence after GM lesion resection. Based on the risk factors, the nomogram predicting recurrence risk was constructed. The area under the receiver operating characteristic curve (95%CI) was 0.913 (0.895, 0.932), and its sensitivity and specificity were 90.5% and 88.9%, respectively. The calibration curve showed that the probability of recurrence after GM lesion resection predicted by using the nomogram was highly consistent with the actual recurrence probability. The decision curve analysis showed that the nomogram had a good clinical net benefit. ConclusionsThe findings of this study suggest that close postoperative monitoring for recurrence is warranted in patients who did not receive oral bromocriptine treatment, presented with microabscess formation on pathological examination, and exhibited elevated SII and IgE level. The postoperative GM recurrence prediction nomogram model constructed based on risk factors demonstrates a good predictive performance, providing a valuable reference for early treatment and management strategies of GM.
Objective To review the application and research progress of artificial intelligence (AI) technology in trauma treatment. MethodsThe recent research literature on the application of AI and related technologies in trauma treatment was reviewed and summarized in terms of prehospital assistance, in-hospital emergency care, and post-traumatic stress disorder risk regression prediction, meanwhile, the development trend of AI technology in trauma treatment were outlooked. Results The AI technology can rapidly analyze and manage large amount of clinical data to help doctors identify patients’ situation of trauma and predict the risk of possible complications more accurately. The application of AI technology in surgical assistance and robotic operations can achieve precise surgical plan and treatment, reduce surgical risks, and shorten the operation time, so as to improve the efficiency and long-term effectiveness of the trauma treatment. ConclusionThere is a promising future for the application of AI technology in the trauma treatment. However, it is still in the stage of exploration and development, and there are many difficulties of historical data bias, application condition limitations, as well as ethical and moral issues need to be solved.
ObjectiveTo investigate the effect of CYP2C9 and APOE on the dose of stable warfarin and model prediction in Hainan population.MethodsFrom August 2016 to July 2018, 368 patients who required heart valve replacement and agreed to take warfarin anticoagulation at the second department of cardiothoracic surgery in our hospital were enrolled, including 152 males aged 48.5–70.5 (60.03±10.18) years and 216 females aged 43.5–65.6 (54.24±11.35) years. CYP2C9 and APOE were amplified by polymerase chain reaction. The gene fragment was sequenced by the Single Nucleotide Polymorphisms (SNP) site. The patients' age, sex, weight, history of smoking and drinking, and the dose of stable warfarin were recorded. Regression analysis of these clinical data was made to construct a dose prediction model.ResultsAmong 368 patients, CYP2C9 genotype test results showed 301 patients (81.8%) with *1*1 genotype, and 67 patients (18.2%) with *1*3 type. For different CYP2C9 genotype patients, the difference was statistically significant in the dose of stable warfarin (P<0.05). The results of APOE genotype showed 93 patients (25.3%) with E2 genotype, 221 patients (60.1%) with E3 genotype, and 54 patients (14.7%) with E4 genotype; the dose of stable warfarin in patients with different APOE genotypes was statistically significant (P<0.05). Multiple regression analysis showed that patients' age, body weight, and CYP2C9 and APOE genotypes were correlated with the dose of stable warfarin. The correlation coefficient R2 was 0.572, and the prediction model was statistically significant (P<0.05).ConclusionCYP2C9 and APOE gene polymorphisms exist in Hainan population. There is significant difference in the dose of stable warfarin among different genotypes of patients. The model to predict stable warfarin can partly explain the difference of warfarin among different patients.
Objective To explore the risk factors of chronic postoperative inguinal pain (CPIP) after transabdominal preperitoneal hernia repair (TAPP), establish and verify the risk prediction model, and then evaluate the prediction effectiveness of the model. Methods The clinical data of 362 patients who received TAPP surgery was retrospectively analyzed and divided into model group (n=300) and validation group (n=62). The risk factors of CPIP in the model group were screened by univariate analysis and multivariate logistic regression analysis, and the risk prediction model was established and tested. Results The incidence of CPIP at 6 months after operation was 27.9% (101/362). Univariate analysis showed that gender (χ2= 12.055, P=0.001), age (t=–4.566, P<0.01), preoperative pain (χ2=44.686, P<0.01) and early pain at 1 week after operation (χ2=150.795, P<0.01) were related to CPIP. Multivariate logistic regression analysis showed that gender, age, preoperative pain, early pain at 1 week after operation, and history of lower abdominal surgery were independent risk predictors of CPIP. The area under curve (AUC) of the receiver operating characteristic (ROC) of the risk prediction model was calculated to be 0.933 [95%CI (0.898, 0.967)], and the optimal cut-off value was 0.129, while corresponding specificity and sensitivity were 87.6% and 91.5% respectively. The prediction accuracy, specificity and sensitivity of the model were 91.9% (57/62), 90.7% and 94.7%, respectively when the validation group data were substituted into the prediction model. Conclusion Female, age≤64 years old, preoperative pain, early pain at 1 week after operation and without history of lower abdominal surgery are independent risk factors for the incidence of CPIP after TAPP, and the risk prediction model established on this basis has good predictive efficacy, which can further guide the clinical practice.
Red blood cells are destroyed when the shear stress in the blood pump exceeds a threshold, which in turn triggers hemolysis in the patient. The impeller design of centrifugal blood pumps significantly influences the hydraulic characteristics and hemolytic properties of these devices. Based on this premise, the present study employs a multiphase flow approach to numerically simulate centrifugal blood pumps, investigating the performance of pumps with varying numbers of blades and blade deflection angles. This analysis encompassed the examination of flow field characteristics, hydraulic performance, and hemolytic potential. Numerical results indicated that the concentration of red blood cells and elevated shear stresses primarily occurred at the impeller and volute tongue, which drastically increased the risk of hemolysis in these areas. It was found that increasing the number of blades within a certain range enhanced the hydraulic performance of the pump but also raised the potential for hemolysis. Moreover, augmenting the blade deflection angle could improve the hemolytic performance, particularly in pumps with a higher number of blades. The findings from this study can provide valuable insights for the structural improvement and performance enhancement of centrifugal blood pumps.
ObjectiveTo analyze the relationship between preoperative pulmonary function indexes and postoperative pneumonia (POP) in patients undergoing upper gastrointestinal surgery.MethodsThe clinical data of 303 patients who underwent lung function examination and upper gastrointestinal surgery in West China Hospital, Sichuan University from September 2020 to January 2021 were prospectively collected and analyzed. There were 217 males and 86 females, with an average age of 61.61±10.42 years. Pulmonary function was evaluated from four aspects including ventilatory function, pulmonary volume, diffusion function and airway resistance. Relevant pulmonary function indicators were displayed as the percentage of actual measured value to predicted value (%pred). The outcome index was pneumonia within 30 days after the surgery. Logistic regression was used to analyze the relationship between preoperative pulmonary function indicators and POP.ResultsA total of 196 patients with gastric cancer and 107 patients with esophageal cancer were included, and the incidence of POP in patients undergoing upper gastrointestinal surgery was 26.7% (81/303). Patients with preoperative low peak expiratory flow (PEF%pred) had a 3.094 times higher risk of developing POP than those with normal PEF%pred [OR=3.094, 95%CI (1.362, 7.032), P=0.007]. The incidence of POP had no correlation with the other preoperative indicators.ConclusionPreoperative PEF%pred may be an important indicator for predicting the occurrence of POP in patients undergoing upper gastrointestinal surgery.
In intensive care units (ICU), the occurrence of acute hypotensive episodes (AHE) is the key problem for the clinical research and it is meaningful for clinical care if we can use appropriate computational technologies to predict the AHE. In this study, based on the records of patients in ICU from the MIMICⅡclinical data, the chaos signal analysis method was applied to the time series of mean artery pressure, and then the patient's Lyapunov exponent curve was drawn ultimately. The research showed that a curve mutation appeared before AHE symptoms took place. This is powerful and clear basis for AHE determination. It is also expected that this study may offer a reference to research of AHE theory and clinical application.
ObjectiveTo explore the risk factors of lymph node metastasis (LNM) in patients with early gastric cancer (EGC), and try to establish a risk prediction model for LNM of EGC.MethodsThe clinicopathologic data of EGC patients who underwent radical gastrectomy and lymph node dissection from January 1, 2015 to December 31, 2019 in this hospital were retrospectively analyzed. Univariate analysis and logistic regression analysis were used to determine the risk factors for LNM of EGC, and the risk prediction model for LNM of EGC was established based on the multivariate results.ResultsA total of 311 cases of EGC were included in this study, and 60 (19.3%) cases had LNM. Univariate and multivariate analysis showed that age (younger), depth of tumor invasion (submucosa), vascular invasion, and undifferentiated carcinoma were the risk factors for LNM of EGC (P<0.05). The optimal threshold for predicting LNM of EGC was 0.158 (area under the receiver operating characteristic curve was 0.864), the sensitivity was 80.0%, and the specificity was 79.3%.ConclusionsFrom results of this study, risk factors for LNM of EGC have age, depth of invasion, vascular invasion, and differentiation degree. Risk prediction model for LNM of EGC established on this results has high sensitivity and specificity, which could provide some references for treatment strategy of EGC.
ObjectiveTo summarize the current status and update of the use of medical imaging in risk prediction of pancreatic fistula following pancreaticoduodenectomy (PD).MethodA systematic review was performed based on recent literatures regarding the radiological risk factors and risk prediction of pancreatic fistula following PD.ResultsThe risk prediction of pancreatic fistula following PD included preoperative, intraoperative, and postoperative aspects. Visceral obesity was the independent risk factor for clinically relevant postoperative pancreatic fistula (CR-POPF). Radiographically determined sarcopenia had no significant predictive value on CR-POPF. Smaller pancreatic duct diameter and softer pancreatic texture were associated with higher incidence of pancreatic fistula. Besides the surgeons’ subjective intraoperative perception, quantitative assessment of the pancreatic texture based on medical imaging had been reported as well. In addition, the postoperative laboratory results such as drain amylase and serum lipase level on postoperative day 1 could also be used for the evaluation of the risk of pancreatic fistula.ConclusionsRisk prediction of pancreatic fistula following PD has considerable clinical significance, it leads to early identification and early intervention of the risk factors for pancreatic fistula. Medical imaging plays an important role in this field. Results from relevant studies could be used to optimize individualized perioperative management of patients undergoing PD.
