Prolonged mechanical ventilation after lung transplantation: risks factors and consequences on recipient outcome

Lower tidal volume ventilation post-bilateral lung transplantation is associated with ventilator-free days

BACKGROUND

There is limited evidence regarding the effect of invasive mechanical ventilation practice post-bilateral lung transplantation. Invasive mechanical ventilation practice may be associated with prolonged ventilation, particularly when referenced to donor anthropometrics.

METHODS

This was a single-centre retrospective cohort study that included consecutive adult bilateral lung transplant recipients between 2015 and 2021 who were ventilated for a minimum of 24 h post-surgery. Lower and higher tidal volume sub-groups were defined for mean and maximum values indexed to both donor and recipient predicted body weight over the first 72 h. The primary outcome was ventilator-free days in the first 28 days, and this was analysed using the Wilcoxon rank sum test and a competing risks regression. We used a Cox proportional hazards model to examine the relationship of ventilator-free days and tidal volume and 90-day survival.

RESULTS

The cohort included 111 recipients, and the median ventilator-free days for the entire cohort was 25 (21-26). Lower tidal volume indexed to donor predicted body weight after 48 and 72 h was associated with more ventilator-free days (25 (23-26) vs. 24 (17-26), p = .04 and 24 (21-25) vs. 20 (14-24), p = .02) and increased cumulative incidence of successful extubation (sub-distribution hazard ratio 1.54 (1.07-2.20), p = .02 and SHR 1.87 (1.07-3.27), p = .03). Ventilator-free days and lower tidal volume were associated with increased 90-day survival.

CONCLUSIONS

Lower tidal volume ventilation indexed to donor predicted body weight is associated with more ventilator-free days post-bilateral lung transplantation.

EDITORIAL COMMENT

Postoperative ventilation with lower tidal volume indexed to the donor's predicted body weight was associated with more ventilator-free days in patients undergoing bilateral lung transplantation. No difference was found between lower versus higher tidal volume ventilation for other patient-important outcomes. The results highlight the need for larger prospective clinical trials.

Time on the waiting list is an independent risk factor for day-90 mortality after lung transplantation

BACKGROUND

The waitlist deaths of transplantation candidates based on their time on the waiting list (TWL) have already been studied, but the short-term mortality and early complications of lung transplant (LT) recipients based on their TWL have not been specifically studied. The first aim of this study was to assess the relationship between increased TWL and short-term mortality in LT recipients.

METHODS

In this observational, monocentric, retrospective study, all patients who underwent LT between January 2016 and August 2022 at Bichat Claude Bernard Hospital, Paris were analyzed. Univariate analysis (chi2 test, Mann-Whitney test, Fisher's exact test) and multivariate analysis (logistic regression) were performed. Ninety-days and one-year survival were studied (Kaplan-Meier curves, log-rank test). p < 0.05 indicated statistical significance.

RESULTS

242 LT patients were analyzed. The median TWL was 100 (43-229) days. Postoperative complications, including septic shock (36 versus 18%, p = 0.002), grade 3 primary graft dysfunction (31 versus 20%, p < 0.001), and KDIGO3 acute kidney injury (8 versus 25%, p < 0.001), were more common in the prolonged TWL (pTWL) group (>100 days) than in the short TWL group (≤100 days). The duration of hospitalization in the ICU was longer (18 [11-34] versus 13 [9-23] days, p = 0.02) in the pTWL group. According to our multivariate analysis, TWL was an independent risk factor for 90-days mortality (OR 1.02, 95% CI [1.00-1.04]; p = 0.032).

CONCLUSION

TWL was an independent risk factor for 90-days mortality after LT. Receiving LT after more than 100 days on the waitlist exposes to increased postoperative complications.

Analysis of Perioperative Factors Leading to Postoperative Pulmonary Complications, Graft Injury and Increased Postoperative Mortality in Lung Transplantation

OBJECTIVES

Postoperative complications such as postoperative pulmonary complications (PPCs) and other organ complications are associated with increased morbidity and mortality after successful lung transplantation and have a detrimental effect on patient recovery. The aim of this study was to investigate perioperative risk factors for in-hospital mortality and postoperative complications with a focus on PPC and graft injury in patients undergoing lung transplantation DESIGN: Single-center retrospective cohort study of 173 patients undergoing lung transplantation SETTING: University Hospital, Medical Center Freiburg.

MAIN RESULTS

In the stepwise multivariate regression analysis, donor age >60 years (odds ratio [OR], 1.85; 95% confidence interval [CI], 1.27-2.81), intraoperative extracorporeal membrane oxygenation (OR, 2.4; 95% CI, 1.7-3.3), transfusion of >4 red blood cell concentrates (OR, 3.1; 95% CI, 1.82-5.1), mean pulmonary artery pressure of >30 mmHg at the end of surgery (OR, 3.5; 95% CI, 2-6.3), the occurrence of postoperative graft injury (OR, 4.1; 95% CI, 2.8-5.9), PPCs (OR, 2.1; 95% CI, 1.7-2.6), sepsis (OR, 4.5; 95% CI, 2.8-7.3), and Kidney disease Improving Outcome grading system stage 3 acute renal failure (OR, 4.3; 95% CI, 2.4-7.7) were associated with increased in hospital mortality, whereas patients with chronic obstructive pulmonary disease had a lower in-hospital mortality (OR, 1.6; 95% CI, 1.4-1.9). The frequency and number of PPCs correlated with postoperative mortality.

CONCLUSIONS

Clinical management and risk stratification focusing on the underlying identified factors that could help to improve patient outcomes.

One-Year Mortality After Lung Transplantation: Experience of a Single French Center Between 2012 and 2021

BACKGROUND Lung transplantation (LTx) is a life-extending therapy for specific patients with terminal lung diseases. This study aimed to evaluate the associations and causes of 1-year mortality after lung transplantation at Strasbourg University Hospital, France, between 2012 and 2021. MATERIAL AND METHODS We carried out a retrospective analysis on 425 patients who underwent LTx at Strasbourg University Hospital between January 1, 2012, and December 31, 2021. Pre-transplant, perioperative, and postoperative data were collected from the electronic medical records. RESULTS Among all patients, 94.6% had a LTx, 4.0% a heart-lung transplantation, and 1.4% underwent pancreatic islet-lung transplantation. The median age at transplantation was 57 years, with 55.3% male patients. The main native lung disease leading to LTx was chronic obstructive pulmonary disease in 51.1% of patients; 16.2% needed super-urgent LTx. The 1-year mortality rate was 11.5%. Most deaths were either caused by multi-organ failure or septic shock. In our multivariate analysis, we identified 3 risk factors significantly related to 1-year mortality after LTx: body mass index (BMI) between 25 and 30 kg/m² vs BMI between 18.5 and 25 kg/m² (P=0.032), postoperative extracorporeal membrane oxygenation support (P=0.034), and intensive care unit length of stay after transplantation (P<0.001). Two other factors were associated with a significantly lower 1-year mortality risk: longer hospital stay after LTx (P=0.024) and tacrolimus prescription (P=0.004). CONCLUSIONS Our study reported a 1-year mortality rate of 11.5% after LTx. Although LTx candidates are carefully selected, additional data are required to improve understanding of the risk factors for post-LTx mortality.

Survival Tree Provides Individualized Estimates of Survival After Lung Transplant

INTRODUCTION

Identifying contributors to lung transplant survival is vital in mitigating mortality. To enhance individualized mortality estimation and determine variable interaction, we employed a survival tree algorithm utilizing recipient and donor data.

METHODS

United Network Organ Sharing data (2000-2021) were queried for single and double lung transplants in adult patients. Graft survival time <7 d was excluded. Sixty preoperative and immediate postoperative factors were evaluated with stepwise logistic regression on mortality; final model variables were included in survival tree modeling. Data were split into training and testing sets and additionally validated with 10-fold cross validation. Survival tree pruning and model selection was based on Akaike information criteria and log-likelihood values. Estimated survival probabilities and log-rank pairwise comparisons between subgroups were calculated.

RESULTS

A total of 27,296 lung transplant patients (8175 single; 19,121 double lung) were included. Stepwise logistic regression yielded 47 significant variables associated with mortality. Survival tree modeling returned six significant factors: recipient age, length of stay from transplant to discharge, recipient ventilator duration post-transplant, double lung transplant, recipient reintubation post-transplant, and donor cytomegalovirus status. Eight subgroups consisting of combinations of these factors were identified with distinct Kaplan-Meier survival curves.

CONCLUSIONS

Survival trees provide the ability to understand the effects and interactions of covariates on survival after lung transplantation. Individualized survival probability with this technique found that preoperative and postoperative factors influence survival after lung transplantation. Thus, preoperative patient counseling should acknowledge a degree of uncertainty given the influence of postoperative factors.

Driving pressure association with mortality in post-lung transplant patients: A prospective observational study

OBJECTIVE

To investigate the association between driving pressure (ΔP) and 90-day mortality in patients following lung transplantation (LTx) in patients who developed primary graft dysfunction (PGD).

METHODS

This prospective, observational study involved consecutive patients who, following LTx, were admitted to our intensive care unit (ICU) from January 2022 to January 2023. Patients were separated into two groups according to ΔP at time of admission (i.e., low, ≤15 cmH2O or high, >15 cmH2O). Postoperative outcomes were compared between groups.

RESULTS

In total, 104 patients were involved in the study, and of these, 69 were included in the low ΔP group and 35 in the high ΔP group. Kaplan-Meier analysis of 90-day mortality showed a statistically significant difference between groups with survival better in the low ΔP group compared with the high ΔP group. According to Cox proportional regression model, the variables independently associated with 90-day mortality were ΔP and pneumonia. Significantly more patients in the high ΔP group than the low ΔP group had PGD grade 3 (PGD3), pneumonia, required tracheostomy, and had prolonged postoperative extracorporeal membrane oxygenation (ECMO) time, postoperative ventilator time, and ICU stay.

CONCLUSIONS

Driving pressure appears to have the ability to predict PGD3 and 90-day mortality of patients following LTx. Further studies are required to confirm our results.

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.

Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation

Prolonged mechanical ventilation (PMV) after lung transplantation poses several risks, including higher tracheostomy rates and increased in-hospital mortality. Mechanical power (MP) of artificial ventilation unifies the ventilatory variables that determine gas exchange and may be related to allograft function following transplant, affecting ventilator weaning. We retrospectively analyzed consecutive double lung transplant recipients at a national transplant center, ventilated through endotracheal tubes upon ICU admission, excluding those receiving extracorporeal support. MP and derived indexes assessed up to 36 h after transplant were correlated with invasive ventilation duration using Spearman's coefficient, and we conducted receiver operating characteristic (ROC) curve analysis to evaluate the accuracy in predicting PMV (>72 h), expressed as area under the ROC curve (AUROC). PMV occurred in 82 (35%) out of 237 cases. MP was significantly correlated with invasive ventilation duration (Spearman's ρ = 0.252 [95% CI 0.129-0.369], p < 0.01), with power density (MP normalized to lung-thorax compliance) demonstrating the strongest correlation (ρ = 0.452 [0.345-0.548], p < 0.01) and enhancing PMV prediction (AUROC 0.78 [95% CI 0.72-0.83], p < 0.01) compared to MP (AUROC 0.66 [0.60-0.72], p < 0.01). Mechanical power density may help identify patients at risk for PMV after double lung transplantation.