Recipient Comorbidities for Prediction of Primary Graft Dysfunction, Chronic Allograft Dysfunction and Survival After Lung Transplantation

Lung transplantation and bone health: A narrative review

Bone health after lung transplantation has not been comprehensively reviewed in over 2 decades. This narrative review summarizes the available literature on bone health in the context of lung transplantation, including epidemiology, presentation, and postoperative management. Osteoporosis is reported in approximately 30% to 50% of lung transplant candidates, largely due to disease-related impact on bone and lifestyle, and corticosteroid-related effects during end-stage lung disease (interstitial lung diseases, chronic obstructive pulmonary disease, and historically cystic fibrosis). After lung transplantation, many patients experience steroid-induced bone loss, followed by stabilization or recovery to baseline levels with pharmacologic management. Although evidence on fracture incidence is limited, fracture risk appears to increase in the year following transplantation, with common fracture sites including the vertebrae and the ribs. Vertebral and rib fractures restrict chest expansion and affect lung function, underscoring the importance of fracture prevention in lung transplant recipients. There is limited evidence on the pharmacologic management of osteoporosis after lung transplantation. Existing randomized controlled trials have focused on parenteral bisphosphonates and calcitriol but have been underpowered to evaluate their effect on fracture outcomes. Resistance training, particularly in conjunction with antiresorptive therapy, has also been shown to improve bone health when initiated 2 months after transplantation. No studies to date have documented the effectiveness of denosumab in lung transplant recipients; more studies on pharmacotherapy are warranted to elucidate optimal medical management. Considering the high osteoporosis prevalence and fracture risk in lung transplant populations, the development of formal guidance is warranted to promote improved management after transplantation.

Prediction of Postoperative Lung Graft Dysfunction During the Procedure: A Single-Center Cohort Study of Cystic Fibrosis Patients

OBJECTIVES

To predict severe primary graft dysfunction (PGD3) after double-lung transplantation in cystic fibrosis (CF) patients using intraoperative data.

DESIGN

A retrospective single-center cohort study.

SETTING

University Hospital, France.

PARTICIPANTS

CF patients who underwent double-lung transplantation between 2012 and 2019. Patients younger than age 18 and those with multiorgan transplants, retransplantation, or intraoperative cardiopulmonary bypass were excluded.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Sixty-nine variables were recorded in real-time across the nine time-points. PGD3 occurred in 24 patients (15.5%). PGD3 WAS ASSESSED ON POSTOPERATIVE DAY 3: A logistic regression model to predict PGD3 was developed using data collected at nine predefined time-points during surgery, from start (recipient and donor variables) to finish. The model's area under the curve improved progressively during surgery, rising from 0.764 to 0.892. The optimal model incorporated five variables: three associated with reduced PGD3 risk (preoperative pulmonary hypertension, donor body mass index, and PaO₂/FiO₂ ratio at surgery's end) and two were linked to increased risk (lactate level at second pulmonary artery clamping and extracorporeal membrane oxygenation [ECMO] use at surgery's end). The risk of PGD3 increased by a factor of 11.48 (95% CI 4.48-29.39; p < 0.001) when ECMO was required at the end of surgery and by 1.29 (95% CI: 1.02-1.63; p = 0.035) for each 1 mEq/L rise in lactate concentration at time-point 7 (second pulmonary artery clamping).

CONCLUSIONS

This predictive model underscores the adverse impact of sustained ECMO placed at the end of surgery and elevated intraoperative lactate levels on PGD3 risk.

Machine Learning for Predicting Primary Graft Dysfunction After Lung Transplantation: An Interpretable Model Study

BACKGROUND

Primary graft dysfunction (PGD) develops within 72 h after lung transplantation (Lung Tx) and greatly influences patients' prognosis. This study aimed to establish an accurate machine learning (ML) model for predicting grade 3 PGD (PGD3) after Lung Tx.

METHODS

This retrospective study incorporated 802 patients receiving Lung Tx between July 2018 and October 2023 (640 in the derivation cohort and 162 in the external validation cohort), and 640 patients were randomly assigned to training and internal validation cohorts in a 7:3 ratio. Independent risk factors for PGD3 were determined by integrating the univariate logistic regression and least absolute shrinkage and selection operator regression analyses. Subsequently, 9 ML models were used to construct prediction models for PGD3 based on selected variables. Their prediction performances were further evaluated. Besides, model stratification performance was assessed with 3 posttransplant metrics. Finally, the SHapley Additive exPlanations algorithm was used to understand the predictive importance of selected variables.

RESULTS

We identified 9 independent clinical risk factors as selected variables. Among 9 ML models, the random forest (RF) model displayed optimal performance (area under the curve [AUC] = 0.9415, sensitivity [Se] = 0.8972, specificity [Sp] = 0.8795 in the training cohort; AUC = 0.7975, Se = 0.7520, Sp = 0.7313 in the internal validation cohort; and AUC = 0.8214, Se = 0.8235, Sp = 0.6667 in the external validation cohort). Further assessments on calibration and clinical usefulness indicated the promising applicability of the RF model in PGD3 prediction. Meanwhile, the RF model also performed best in terms of risk stratification for postoperative support (extracorporeal membrane oxygenation time: P < 0.001, mechanical ventilation time: P = 0.006, intensive care unit time: P < 0.001).

CONCLUSIONS

The RF model had the optimal performance in PGD3 prediction and postoperative risk stratification for patients after Lung Tx.

Update on the immunological mechanisms of primary graft dysfunction and chronic lung allograft dysfunction

PURPOSE OF REVIEW

Primary graft dysfunction (PGD) and chronic lung allograft dysfunction (CLAD) are the leading causes of graft loss in lung transplant recipients. The development of mouse lung transplant models has allowed for the genetic dissection of cellular and molecular pathways that prevent graft survival. This review provides an overview into recent mechanistic insights into PGD and CLAD.

RECENT FINDINGS

Mouse orthotopic lung transplant models and investigations of human lung transplant recipeints have revealed new molecular and cellular targets that promote PGD and CLAD. Donor and recipient-derived innate immune cells promote PGD and CLAD. PGD is driven by communication between classical monocytes and tissue-resident nonclassical monocytes activating alveolar macrophages to release chemokines that recruit neutrophils. Products of cell damage trigger neutrophil NET release, which together with NK cells, antibodies and complement, that further promote PGD. The development of CLAD involves circuits that activate B cells, CD8 + T cells, classical monocytes, and eosinophils.

SUMMARY

Effective targeted management of PGD and CLAD in lung transplant recipient to improve their long-term outcome remains a critical unmet need. Current mechanistic studies and therapeutic studies in mouse models and humans identify new possibilities for prevention and treatment.

The Year in Cardiothoracic Transplant Anesthesia: Selected Highlights From 2022 Part I: Lung Transplantation

These highlights focus on the research in lung transplantation (LTX) that was published in 2022 and includes the assessment and optimization of candidates for LTX, donor optimization, the use of organs from donation after circulatory death, and outcomes when using marginal or novel donors; recipient factors affecting LTX, including age, disease, the use of extracorporeal life support; and special situations, such as coronavirus disease2019, pediatric LTX, and retransplantation. The remainder of the article focuses on the perioperative management of LTX, including the perioperative risk factors for acute renal failure (acute kidney injury); the incidence and management of phrenic nerve injury, delirium, and pain; and the postoperative management of hyperammonemia, early postoperative infections, and the use of donor-derived cell-free DNA to detect rejection.

Fibrotic progression from acute cellular rejection is dependent on secondary lymphoid organs in a mouse model of chronic lung allograft dysfunction

Chronic lung allograft dysfunction (CLAD) remains one of the major limitations to long-term survival after lung transplantation. We modified a murine model of CLAD and transplanted left lungs from BALB/c donors into B6 recipients that were treated with intermittent cyclosporine and methylprednisolone postoperatively. In this model, the lung allograft developed acute cellular rejection on day 15 which, by day 30 after transplantation, progressed to severe pleural and peribronchovascular fibrosis, reminiscent of changes observed in restrictive allograft syndrome. Lung transplantation into splenectomized B6 alymphoplastic (aly/aly) or splenectomized B6 lymphotoxin-β receptor-deficient mice demonstrated that recipient secondary lymphoid organs, such as spleen and lymph nodes, are necessary for progression from acute cellular rejection to allograft fibrosis in this model. Our work uncovered a critical role for recipient secondary lymphoid organs in the development of CLAD after pulmonary transplantation and may provide mechanistic insights into the pathogenesis of this complication.

A novel nomogram for predicting prolonged mechanical ventilation in lung transplantation patients using extracorporeal membrane oxygenation

Prolonged mechanical ventilation (PMV) is commonly associated with increased post-operative complications and mortality. Nevertheless, the predictive factors of PMV after lung transplantation (LTx) using extracorporeal membrane oxygenation (ECMO) as a bridge remain unclear. The present study aimed to develop a novel nomogram for PMV prediction in patients using ECMO as a bridge to LTx. A total of 173 patients who used ECMO as a bridge following LTx from January 2022 to June 2023 were divided into the training (122) and validation sets (52). A mechanical ventilation density plot of patients after LTx was then performed. The training set was divided in two groups, namely PMV (95) and non-prolonged ventilation (NPMV) (27). For the survival analysis, the effect of PMV was assessed using the log-rank test. Univariate and multivariate logistic regression analyses were performed to assess factors associated with PMV. A risk nomogram was established based on the multivariate analysis, and model performance was further assessed in terms of calibration, discrimination, and clinical usefulness. Internal validation was additionally conducted. The difference in survival curves in PMV and NPMV groups was statistically significant (P < 0.001). The multivariate analysis and risk factors in the nomogram revealed four factors to be significantly associated with PMV, namely the body mass index (BMI), operation time, lactic acid at T0 (Lac), and driving pressure (DP) at T0. These four factors were used to develop a nomogram, with an area under the curve (AUC) of 0.852 and good calibration. After internal validation, AUC was 0.789 with good calibration. Furthermore, goodness-of-fit test and decision-curve analysis (DCA) indicated satisfactory performance in the training and internal validation sets. The proposed nomogram can reliably and accurately predict the risk of patients to develop PMV after LTx using ECMO as a bridge. Four modifiable factors including BMI, operation time, Lac, and DP were optimized, which may guide preventative measures and improve prognosis.

Donor and recipient risk factors for the development of primary graft dysfunction following lung transplantation

Primary Graft Dysfunction (PGD) is a major cause of both short-term and long-term morbidity and mortality following lung transplantation. Various donor, recipient, and technical risk factors have been previously identified as being associated with the development of PGD. Here, we present a comprehensive review of the current literature as it pertains to PGD following lung transplantation, as well as discussing current strategies to mitigate PGD and future directions. We will pay special attention to recent advances in lung transplantation such as ex-vivo lung perfusion, thoracoabdominal normothermic regional perfusion, and up-to-date literature published in the interim since the 2016 ISHLT consensus statement on PGD and the COVID-19 pandemic.

Primary graft dysfunction after lung transplantation

PURPOSE OF REVIEW

Primary graft dysfunction (PGD) is a clinical syndrome occurring within the first 72 h after lung transplantation and is characterized clinically by progressive hypoxemia and radiographically by patchy alveolar infiltrates. Resulting from ischemia-reperfusion injury, PGD represents a complex interplay between donor and recipient immunologic factors, as well as acute inflammation leading to alveolar cell damage. In the long term, chronic inflammation invoked by PGD can contribute to the development of chronic lung allograft dysfunction, an important cause of late mortality after lung transplant.

RECENT FINDINGS

Recent work has aimed to identify risk factors for PGD, focusing on donor, recipient and technical factors both inherent and potentially modifiable. Although no PGD-specific therapy currently exists, supportive care remains paramount and early initiation of ECMO can improve outcomes in select patients. Initial success with ex-vivo lung perfusion platforms has been observed with respect to decreasing PGD risk and increasing lung transplant volume; however, the impact on survival is not well delineated.

SUMMARY

This review will summarize the pathogenesis and clinical features of PGD, as well as highlight treatment strategies and emerging technologies to mitigate PGD risk in patients undergoing lung transplantation.