Due to the influence of immunosuppression, nerve injury and other comprehensive factors, the overall incidence of gastrointestinal complications after lung transplantation is relatively high, which can cause drug absorption disorder and chronic rejection. In recent years, more and more studies have been conducted on these complications. However, due to the great difference of the incidence of gastrointestinal complications among lung transplantation centers, clinicians lack of understanding of these. In this article, the general status, common types and risk factors of gastrointestinal complications after lung transplantation were reviewed, aiming to provide reference for comprehensive management of gastrointestinal complications after lung transplantation.

Lung transplantation is the only effective treatment of end-stage lung diseases. Nevertheless, shortage of donor lungs has become increasingly prominent worldwide. A large quantity of patients died while waiting for lung transplantation. Urgent lung transplantation is a prioritized allocation strategy for donor lung transplantation according to the urgency of diseases, aiming to shorten the waiting time for donor lungs and reduce the fatality of patients on the waiting list for lung transplantation. However, no consensus has been reached worldwide on the definition, criteria and application of the terminology of urgent lung transplantation. In addition, the survival and net benefits of lung transplant recipients based on this allocation system are still controversial. On the basis of previous clinical research on urgent lung transplantation, the definition criteria, risk factors, survival outcomes, limitations and optimization measures were explicitly elucidated in this article, aiming to provide theoretical reference for comprehensive evaluation of the feasibility of urgent lung transplantation and further optimizing the allocation system of donor lungs.

Lung transplantation is the only effective therapeutic option for end-stage lung diseases, and postoperative rejection is the main factor affecting clinical prognosis of the recipients. Imaging examination can be utilized as a noninvasive tool to assist other examinations in monitoring rejection after lung transplantation. At present, multiple imaging examination methods have been reported. The advantages and disadvantages of various imaging examinations have been clarified, which may promote early diagnosis of rejection, deliver timely treatment for lung transplant recipients and improve the quality of life and clinical prognosis. In this article, the advantages, disadvantages and research progress upon different imaging examinations for rejection after lung transplantation were reviewed, aiming to provide reference for identifying the optimal noninvasive examination approach for rejection after lung transplantation and enhance the long-term survival of the recipients.

Lung transplantation has become the most effective treatment of end-stage lung diseases. Along with persistent optimization of lung transplantation technique and perioperative management, the short-term clinical efficacy after lung transplantation has been significantly improved, whereas the long-term clinical prognosis remains unoptimistic. Besides chronic lung allograft dysfunction, postoperative malignant tumors also threaten the long-term survival of the recipients. Common malignant tumors following lung transplantation include nonmelanoma skin cancer, posttransplant lymphoproliferative disease and lung cancer. After solid organ transplantation, a large majority of the recipients require lifelong immunosuppressive therapy. The intensity of immunosuppressive therapy for the lung transplant recipients is generally higher than other organ transplant recipients. Immunosuppression is the main factor which leads to the impairment of anti-tumor immune monitoring function and promotes the incidence and development of malignant tumors. In this article, the risk factors, prevention and treatment of the most common malignant tumors after lung transplantation were reviewed, aiming to provide reference for comprehensive diagnosis and treatment of malignant tumors following lung transplantation.

Objective To modify the mouse model of orthotopic left lung transplantation from different perspectives, aiming to establish a simpler, faster and stabler mouse model of lung transplantation. Methods Based on preliminary modified rat model of orthotopic left lung transplantation established by our team, varying extent of modifications were made regarding the tracheal intubation, cannula preparation and anastomosis procedures of orthotopic left lung transplantation in the recipient mice. Orthotopic left lung transplantation in 40 mice were performed by an operator with microsurgical experience. The dissection of the recipient's hilar structure was carried out at the plane of the hilar clamp model within the reverse-view, and the three branches (left main bronchus, pulmonary artery and pulmonary vein) of the pulmonary hilum were anastomosed in turn by the "pendulum" anastomosis method. The operation time of each procedure was recorded. The recipient mice were sacrificed at postoperative 2 weeks, and the incidence of postoperative complications was recorded. Results Lung transplantation was successfully completed in 40 mice, with no bronchial and vascular tearing or twisting, and no bleeding at the anastomosis site. The overall cardiopulmonary procurement time was (10.7±1.5) min, cannula preparation time was (16.2±1.5) min, cold ischemia time was (25.1±2.4) min, warm ischemia time was (19.4±1.6) min, and the total operation time was (57.2±2.9) min, respectively. During the follow-up from 6 to 14 days after surgery, one recipient mouse died of pleural effusion, probably caused by infection. No pneumothorax, thrombosis or atelectasis was found in the remaining recipient mice during postoperative follow-up. Conclusions The modified mouse model of orthotopic left lung transplantation based on "pendulum" anastomosis of the reverse-view plane possesses multiple advantages of short operation time, high success rate and few complications, which is expected to become an alternative model of studying pathological changes after lung transplantation and worthy of further application.

Objective To analyze the influencing factors of survival of patients with airway stenosis requiring clinical interventions after lung transplantation. Methods Clinical data of 66 patients with airway stenosis requiring clinical interventions after lung transplantation were retrospectively analyzed. Univariate and multivariate Cox’s regression models were adopted to analyze the influencing factors of survival of all patients with airway stenosis and those with early airway stenosis. Kaplan-Meier method was used to calculate the overall survival and delineate the survival curve. Results For 66 patients with airway stenosis, the median airway stenosis-free time was 72 (52,102) d, 27% (18/66) for central airway stenosis and 73% (48/66) for distal airway stenosis. Postoperative mechanical ventilation time [hazard ratio (HR) 1.037, 95% confidence interval (CI) 1.005-1.070, P=0.024] and type of surgery (HR 0.400, 95%CI 0.177-0.903, P=0.027) were correlated with the survival of patients with airway stenosis after lung transplantation. The longer the postoperative mechanical ventilation time, the higher the risk of mortality of the recipients. The overall survival of airway stenosis recipients undergoing bilateral lung transplantation was better than that of their counterparts after single lung transplantation. Subgroup analysis showed that grade 3 primary graft dysfunction (PGD) (HR 4.577, 95%CI 1.439-14.555, P=0.010) and immunosuppressive drugs (HR 0.079, 95%CI 0.022-0.287, P<0.001) were associated with the survival of patients with early airway stenosis after lung transplantation. The overall survival of patients with early airway stenosis after lung transplantation without grade 3 PGD was better compared with that of those with grade 3 PGD. The overall survival of patients with early airway stenosis after lung transplantation treated with tacrolimus was superior to that of their counterparts treated with cyclosporine. Conclusions Long postoperative mechanical ventilation time, single lung transplantation, grade 3 PGD and use of cyclosporine may affect the survival of patients with airway stenosis after lung transplantation.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.