With the development and improved availability of low-dose computed tomography (LDCT), an increasing number of patients are clinically diagnosed with lung cancer manifesting as ground-glass nodules. Although radical surgery is currently the mainstay of treatment for patients with early-stage lung cancer, traditional anatomic lobectomy and mediastinal lymph node dissection (MLND) are not ideal for every patient. Clinically, it is critical to adopt an appropriate approach to pulmonary lobectomy, determine whether it is necessary to perform MLND, establish standard criteria to define the scope of lymph node dissection, and optimize the decision-making process. Thereby avoiding over- and under-treatment of lung cancer with surgical intervention and achieving optimal results from clinical diagnosis and treatment are important issues before us.
ObjectiveProlonged mechanical ventilation (PMV) is a prognostic marker for short-term adverse outcomes in patients after lung transplantation.The risk of prolonged mechanical ventilation after lung transplantation is still not clear. The study to identify the risk factors of prolonged mechanical ventilation (PMV) after lung transplantation.Methods This retrospective observational study recruited patients who underwent lung transplantation in Wuxi People’s Hospital from January 2020 to December 2022. Relevant information was collected from patients and donors, including recipient data (gender, age, BMI, blood type, comorbidities), donor data (age, BMI, time of endotracheal intubation, oxygenation index, history of smoking, and any comorbidity with multidrug-resistant bacterial infections), and surgical data (surgical mode, incision type, operation time, cold ischemia time of the donor lung, intraoperative bleeding, and ECMO support), and postoperative data (multi-resistant bacterial lung infection, multi-resistant bacterial bloodstream infection, and mean arterial pressure on postoperative admission to the monitoring unit). Patients with a duration of mechanical ventilation ≤72 hours were allocated to the non-prolonged mechanical ventilation group, and patients with a duration of mechanical ventilation>72 hours were allocated to the prolonged mechanical ventilation group. LASSO regression analysis was applied to screen risk factors., and a clinical prediction model for the risk of prolonged mechanical ventilation after lung.ResultsPatients who met the inclusion criteria were divided into the training set and the validation set. There were 307 cases in the training set group and 138 cases in the validation set group. The basic characteristics of the training set and the validation set were compared. There were statistically significant differences in the recipient’s BMI, donor’s gender, CRKP of the donor lung swab, whether the recipient had pulmonary infection before the operation, the type of transplantation, the cold ischemia time of the donor lung, whether ECMO was used during the operation, the duration of ECMO assistance, CRKP of sputum, and the CRE index of the recipient's anal test (P<0.05). 2. The results of the multivariate logistic regression model showed that female recipients, preoperative mechanical ventilation in recipients, preoperative pulmonary infection in recipients, intraoperative application of ECMO, and the detection of multi-drug resistant Acinetobacter baumannii, multi-drug resistant Klebsiella pneumoniae and maltoclomonas aeruginosa in postoperative sputum were independent risk factors for prolonged mechanical ventilation after lung transplantation. The AUC of the clinical prediction model in the training set and the validation set was 0.838 and 0.828 respectively, suggesting that the prediction model has good discrimination. In the decision curves of the training set and the validation set, the threshold probabilities of the curves in the range of 0.05-0.98 and 0.02-0.85 were higher than the two extreme lines, indicating that the model has certain clinical validity.ConclusionsFemale patients, Preoperative pulmonary infection, preoperative mechanical ventilation,blood type B, blood type O, application of ECMO assistance, multi-resistant Acinetobacter baumannii infection, multi-resistant Klebsiella pneumoniae infection, and multi-resistant Stenotrophomonas maltophilia infection are independent risk factors for PMV (prolonged mechanical ventilation) after lung transplantation.
Risk prediction models for postoperative pulmonary complications (PPCs) can assist healthcare professionals in assessing the likelihood of PPCs occurring after surgery, thereby supporting rapid decision-making. This study evaluated the merits, limitations, and challenges of these models, focusing on model types, construction methods, performance, and clinical applications. The findings indicate that current risk prediction models for PPCs following lung cancer surgery demonstrate a certain level of predictive effectiveness. However, there are notable deficiencies in study design, clinical implementation, and reporting transparency. Future research should prioritize large-scale, prospective, multi-center studies that utilize multiomics approaches to ensure robust data for accurate predictions, ultimately facilitating clinical translation, adoption, and promotion.
Lung transplantation has been the only valid method in treating end-stage lung diseases, airway complications are the main cause to the failure of surgery and common postoperative complications. With the development on patient selection, organ preservation, surgical technique, immunosuppressive therapy and postoperative surveillance, the successful ratio of surgery has become most satisfactory. However, airway complications are still common after lung transplantation. Among these, the airway anastomosis stenosis is more predominant than others. The living quality and long-dated survival rate are highly improved by paying enough attention to the formation,corresponding management for tracheal stenosis. The progress of the cause, prevention and treatment of airway anastomosis stenosis after lung transplantation is reviewed in this article.
Objective Through the analysis of hospital costs of 16 866 cases of patients with lung cancer in Sichuan Province, in oder to find the main influencing factors of hospital costs of patients with lung cancer, and to provide references for reducing the hospital costs of patients with lung cancer. Methods We selected information of in-patients with lung cancer in 6 hospitals in Sichuan province from January 2008 to December 2011 based on full consideration into the local economic levels geographics distribution of different regions in Sichuan province. Then we extracted baseline data, hospitalization data and costs, and then analysis on relevant influencing factors was performed using single factor analysis of variance and multiple stepwise regression analysis. Results A total of 16 918 cases are chosen, of which, 16 866 were effective for further analysis. The results of statistical analysis showed that, the cost of western medicine accounted for the most of the average of the total hospital costs (50.79%) , followed by the cost of diagnosis and treatment (40.79%). The reuslts of multiple stepwise regression analysis showed that, the top three factors influencing hospital costs most included hospital stay, operation, and regions. Conclusion Facing daily increasing costs of hospital costs of lung cancer, effectively reducing drug expenses of patients could be a breakthrough. We could ultimately reduce the hospital costs of patients with lung cancer as well as the the economic burden of patients and society, by strengthening hospital management, shortening hospital stay, and rationally regulating drug use.
ObjectiveTo evaluate the effect of postoperative no indwelling urethral catheters in lung operation.
MethodsIn this prospective cohort study, we recruited 100 patients who were scheduled for pulmonary lobectomy under general anesthesia in a single institution of Thoracic Surgery Department in West China Hospital between April and December 2014. These patients were divided into two groups including a no indwelled urethral catheter group (NIUC, 50 patients) and an indwelled urethral catheter group (IUC, 50 patients). The clinical effect was compared between the two groups.
ResultsThere was no statistical difference in incidence of postoperative urinary retention or urinary tract infection between the two groups (P=0.433, 0.050). However, the comfort degrees(0 degree) of patients in the NICU group was significantly higher than that of the ICU group with a statistical difference (P=0.002). While postoperative hospitalization time in the NICU group (P=0.023) was shorter than that in the ICU group (P=0.004). Prostatic hyperplasia was the high risk factor for the lung postoperative urinary retention (P=0.056).
ConclusionPostoperative no indwelling urethral catheters in lung operation has the benefit of improving the comfort degrees of inpatients and increasing the postoperation urinary retention.
Objective
To assess the effects of physiotherapy on pulmonary function in COPD patients with lung cancer after lobectomy or pneumonectomy.
Methods
Fifty-five COPD patients with lung cancer undergoing lobectomy or pneumonectomy from January 2005 to May 2014 were recruited in the study. They were divided into group A received comprehensive physiotherapy before surgery and group B without comprehensive physiotherapy before surgery. The changes of lung function and tolerance were compared before physiotherapy (T1 time point) and after physiotherapy (T2 time point) in the group A, and between two groups before lung resection (T2 time point) and after lung resection (T3 time point).
Results
In group A, the forced expiratory volume in one second (FEV1), vital capacity (VC), peak expiratory flow at 50% of vital capacity (FEF50) and FEF25 increased significantly respectively by 16.96%, 14.75%, 20.69% and 13.79% compared with those before physiotherapy. Meanwhile, six-minutes walking distance (6MWD) achieved a significant improvement. After resection of lung, FEV1 and VC appeared to reduce, and pulmonary small airway function, tolerance, and clinical features deteriorated significantly. The differences between T2 and T1 in FEV1, FEF50 and FEF25 in the patients with FEV1%pred ≥80% and 50%-80% were similar with those in the patients with FEV1%pred<50%. The differences between T2 and T3 in FEF50 and FEF25 in the patients with FEV1%pred≥80% and 50%-80% were higher than those with FEV1%pred<50%. For the patients with lobectomy, FEV1 and VC in the group B were lower than those in the group A (FEV1: 10.24% vs. 22.44%; VC: 10.13% vs. 20.87%). For the patients with pulmonary resection, FEV1 and VC had little differences (FEV1: 36.33% vs. 36.78%; VC: 37.23% vs. 38.98%).
Conclusion
Physiotherapy is very important for the preoperative treatment and postoperative nursing of COPD patients with primary lung cancer.
Lung cancer is the most common cancer worldwide. The outcome and management of lung cancer patients could be improved by early diagnosis and prognosis. MicroRNAs (miRNAs) have been implicated in signaling pathways regulating a variety of biological processes and play important roles in the development of carcinoma. Moreover, miRNAs can exist in the circulation in a remarkably stable form. All of these suggest miRNAs as new potentially clinical biomarkers for diagnosis and prognosis of lung cancer. In this review, we aim to discuss diagnostic and prognostic value and potential clinical utility of miRNAs in serum.
Objective To establish a machine learning-based risk prediction model of combined chronic obstructive pulmonary disease (COPD) with lung cancer, so as to explore the high risk factors for COPD patients with lung cancer and to lay the foundation for early detection of lung cancer risk in COPD patients. Methods A total of 154 patients from the Second Hospital of Dalian Medical University from 2010 to 2021 were retrospectively analyzed, including 99 patients in the COPD group and 55 patients in the COPD with lung cancer group. the chest high resolution computed tomography (HRCT) scans and pulmonary function test of each patient were acquired. The main analyses were as follow: (1) to valid the statistically differences of the basic information (such as age, body mass index, smoking index), laboratory test results, pulmonary function parameters and quantitative parameters of chest HRCT between the two groups; (2) to analyze the indicators of high risk factors for lung cancer in COPD patients using univariate and binary logistic regression (LR) methods; and (3) to establish the machine learning model (such as LR and Gaussian process) for COPD with lung cancer patients. Results Based on the statistical analysis and LR methods, decreased BMI, increased whole lung emphysema index, increased whole lung mean density, and increased percentage activity of exertional spirometry and prothrombin time were risk factors for COPD with lung cancer patients. Based on the machine learning prediction model for COPD with lung cancer patients, the area under the receiver operating characteristic curve for LR and Gaussian process were obtained as 0.88 using the soluble fragments of prothrombin time percentage activity, whole lung emphysema index, whole lung mean density, and forced vital capacity combined with neuron-specific enolase and cytokeratin 19 as features. Conclusion The prediction model of COPD with lung cancer patients using a machine learning approach can be used for early detection of lung cancer risk in COPD patients.
