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.

Unveiling Hidden Disparities: Evaluating US Multiple Listing Practices in Lung Transplantation.

BACKGROUND: Multiple listing (ML) is a practice used to increase the potential for transplant but is controversial due to concerns that it disproportionately benefits patients with greater access to health care resources. RESEARCH QUESTION: Is there disparity in ML practices based on social deprivation in the United States and does ML lead to quicker time to transplant? STUDY DESIGN AND METHODS: A retrospective cohort study of adult (≥ 18 years of age) lung transplant candidates listed for transplant (2005-2018) was conducted. Exclusion criteria included heart only or heart and lung transplant and patients relisted during the observation period. Data were obtained from the United Network for Organ Sharing Standard Transplant Analysis and Research File. The first exposure of interest was the Social Deprivation Index with a primary outcome of ML status, to assess disparities between ML and single listing (SL) participants. The second exposure of interest was ML status with a primary outcome of time to transplant, to assess whether implementation of ML leads to quicker time to transplant. RESULTS: A total of 35,890 patients were included in the final analysis, of whom 791 (2.2%) were ML and 35,099 (97.8%) were SL. ML participants had lower median level of social deprivation (5 units, more often female: 60.0% vs 42.3%) and lower median lung allocation score (35.3 vs 37.3). ML patients were more likely to be transplanted than SL patients (OR, 1.42; 95% CI, 1.17-1.73), but there was a significantly quicker time to transplant only for those whom ML was early (within 6 months of initial listing) (subdistribution hazard ratio, 1.17; 95% CI, 1.04-1.32). INTERPRETATION: ML is an uncommon practice with disparities existing between ML and SL patients based on several factors including social deprivation. ML patients are more likely to be transplanted, but only if they have ML status early in their transplant candidacy. With changing allocation guidelines, it is yet to be seen how ML will change with the implementation of continuous distribution.

OPTN/SRTR 2022 Annual Data Report: Lung.

For the first time since the COVID-19 pandemic, the annual number of lung transplants performed in the United States increased. The year 2022, encompassed in this report, marks the last full calendar year where the Lung Allocation Score was used for ranking transplant candidates based on their estimated transplant benefit and donor lung allocation in the United States. In March 2023, a major change in transplant allocation policy occurred with the implementation of the Composite Allocation Score. Transplant rates have increased over the past decade, although there is variability among age, diagnosis, racial and ethnic, and blood groups. Over half of candidates received a lung transplant within 3 months of placement on the waiting list, with nearly 75% of candidates accessing transplant by 1 year. Pretransplant mortality rates remained stable, with approximately 13% of lung transplant candidates dying or being removed from the waiting list within a year of listing. Posttransplant survival remained stable; however, variability exists by age, diagnosis, and racial and ethnic groups.

Validation of a novel donor lung scoring system based on the updated lung Composite Allocation Score.

Lung transplantation (LTx) continues to have lower rates of long-term graft survival compared with other organs. Additionally, lung utilization rates from brain-dead donors remain substantially lower compared with other solid organs, despite a growing need for LTx and the significant risk of waitlist mortality. This study aims to examine the effects of using a combination of the recently described novel lung donor (LUNDON) acceptability score and the newly adopted recipient lung Composite Allocation Score (CAS) to guide transplantation. We performed a review of nearly 18 000 adult primary lung transplants from 2015-2022 across the US with retroactive calculations of the CAS value. The medium-CAS group (29.6-34.5) had superior 1-year posttransplant survival. Importantly, the combination of high-CAS (> 34.5) recipients with low LUNDON score (≤ 40) donors had the worst survival at 1 year compared with any other combination. Additionally, we constructed a model that predicts 1-year and 3-year survival using the LUNDON acceptability score and CAS values. These results suggest that caution should be exercised when using marginally acceptable donor lungs in high-priority recipients. The use of the LUNDON score with CAS value can potentially guide clinical decision-making for optimal donor-recipient matches for LTx.

Lung Transplantation for Pulmonary Arterial Hypertension: Optimized Referral and Listing Based on an Evolving Disease Concept.

Pulmonary hypertension (PH) was once a devastating and fatal disease entity, the outlook of which has been significantly improved by the continued progress of medical treatment algorithms. However, some patients still ultimately fail to achieve an adequate clinical response despite receiving maximal medical treatment. Historically, lung transplantation (LTx) has been the only effective therapeutic option that could lead to satisfactory outcomes and save these advanced patients' lives. However, patients with PH tend to have the highest mortality rates on the transplant waiting list; especially after comprehensive medical treatment, they continue to deteriorate very rapidly, eventually missing optimal transplantation windows. Balancing optimized medical treatment with the appropriate timing of referral and listing has been highly controversial in LTx for patients with PH. The 2021 consensus document for the selection of lung transplant candidates from the International Society for Heart and Lung Transplantation (ISHLT) updated the specific recommendations for the LTx referral and listing time for patients with PH based on objective risk stratification. Herein, we review the evolving PH-related concepts and highlight the optimization of LTx referral and listing for patients with PH, as well as their management on the waiting list.

A new method for classifying prognostic risk factors in lung transplant candidates.

BACKGROUND: Predicting risk of waitlist mortality and subsequent classification of lung transplant candidates has been difficult due to inter-relatedness of risk factors, differential risk across populations, and changes in relationships over time. We developed a clinically intuitive indexing system to simplify mortality risk assessment. METHODS: Scientific Registry of Transplant Recipients data from February 19, 2015, to May 26, 2020 (n = 13,726) were used to estimate 3 constructs. Airway and oxygen function indices were estimated using confirmatory factor analysis and hierarchical clustering was used to derive respiratory support clusters. Cox proportional hazards regression was used to characterize event-free waitlist survival by constructs (3), age, sex, and diagnosis group. Model performance was compared to the Lung Allocation Score/Composite Allocation Score (LAS/CAS). RESULTS: Airway and oxygen function indices were created with substantive factor loadings forced expiratory volume (0.86), forced vital capacity (0.64), partial pressure of carbon dioxide (0.56) and PO2/fraction of inspired oxygen (0.83), partial pressure of oxygen (0.59), and mean pulmonary artery pressure (0.30), respectively. Four respiratory support clusters (C1: as needed O2, C2: continuous O2, C3: continuous O2/positive pressure ventilation (PPV), C4: PPV + extracorporeal membrane oxygenation) were identified. Constructs were used to identify patient profiles. Model area under the receiver operating characteristic curve was 0.85 [0.84, 0.87] compared to the LAS 0.92 [0.91, 0.94] at 4 weeks. Risk predictions were relatively insensitive to airway and oxygen function indices in C1 and C4 but varied across C2 and C3. CONCLUSIONS: Reducing the dimensionality of waitlist mortality risk offers an opportunity to identify clinical phenotypes that are more nuanced and thus more interpretable than current risk assessment provided by the LAS/CAS models.

OPTN/SRTR 2021 Annual Data Report: Lung.

The number of lung transplants has continued to decline since 2020, a period that coincides with the onset of the COVID-19 pandemic. Lung allocation policy continues to undergo considerable change in preparation for adoption of the Composite Allocation Score system in 2023, beginning with multiple adaptations to the calculation of the Lung Allocation Score that occurred in 2021. The number of candidates added to the waiting list increased after a decline in 2020, while waitlist mortality has increased slightly with a decreased number of transplants. Time to transplant continues to improve, with 38.0% of candidates waiting fewer than 90 days for a transplant. Posttransplant survival remains stable, with 85.3% of transplant recipients surviving to 1 year; 67%, to 3 years; and 54.3%, to 5 years.

The Past, Present, and Near Future of Lung Allocation in the United States.

The first official donor lung allocation system in the United States was initiated by the United Network of Organ Sharing in 1990. The initial policy for lung allocation was simple with donor lungs allocated based on ABO match and the amount of time the candidates accrued on the waiting list. Donor offers were first given to candidates' donor service area. In March 2005, the implementation of the lung allocation score (LAS) was the major change in organ allocation. International adoption of the LAS-based allocation system can be seen worldwide.

The impact of prognostic nutrition index on the waitlist mortality of lung transplantation.

OBJECTIVE: The prognostic nutrition index (PNI), calculated using serum albumin and total lymphocyte count, is a recent topical index related to inflammation. Preoperative PNI is regarded as a new preoperative prognostic score in lung transplantation (LTx). This study aimed to investigate the impact of PNI at the time of registration as a prognostic parameter of mortality on the waiting list for LTx. METHODS: A retrospective review was conducted on the data of 132 adult patients registered for LTx in our department between January 2013 and June 2020. Patients who finally received LTx were analyzed as censored data. The overall survival was evaluated using the Kaplan-Meier method for pre-registered clinical factors including the PNI at the time of registration. Overall survival was calculated from the date of listing to the Japan Organ Transplant Network to the date of death. RESULTS: The low-PNI group had a significantly worse prognosis. Multivariate analysis demonstrated that age (p = 0.023), idiopathic interstitial pneumonia (p < 0.001), lung allocation score (LAS) (p < 0.001), and PNI (p < 0.001) were independent prognostic factors for waitlist mortality. CONCLUSIONS: PNI at the time of registration can be an independent prognostic parameter in registered candidates for LTx.

The Lung Allocation Score Remains Inequitable for Patients with Pulmonary Arterial Hypertension, Even after the 2015 Revision.

Rationale: The lung allocation score (LAS) was revised in 2015 to improve waiting list mortality and rate of transplant for patients with pulmonary arterial hypertension (PAH). Objectives: We sought to determine if the 2015 revision achieved its intended goals. Methods: Using the Standard Transplant Analysis and Research file, we assessed the impact of the 2015 LAS revision by comparing the pre- and postrevision eras. Registrants were divided into the LAS diagnostic categories: group A-chronic obstructive pulmonary disease; group B-pulmonary arterial hypertension; group C-cystic fibrosis; and group D-interstitial lung disease. Competing risk regressions were used to assess the two mutually exclusive competing risks of waiting list death and transplant. Cumulative incidence plots were created to visually inspect risks. Measurements and Main Results: The LAS at organ matching increased by 14.2 points for registrants with PAH after the 2015 LAS revision, the greatest increase among diagnostic categories (other LAS categories: Δ, -0.9 to +2.8 points). Before the revision, registrants with PAH had the highest risk of death and lowest likelihood of transplant. After the 2015 revision, registrants with PAH still had the highest risk of death, now similar to those with interstitial lung disease, and the lowest rate of transplant, now similar to those with chronic obstructive pulmonary disease. Conclusions: Although the 2015 LAS revision improved access to transplant and reduced the risk of waitlist death for patients with PAH, it did not go far enough. Significant differences in waitlist mortality and likelihood of transplant persist.

Lung transplant waitlist outcomes among ABO blood groups vary based on disease severity.

BACKGROUND: Blood group O candidates have lower lung transplantation rates despite having the most common blood group. We postulated that waitlist outcomes among these candidates and those with other blood types vary with disease severity and lung allocation score (LAS). METHODS: We performed a retrospective cohort study of 32,772 waitlist candidates using the United Network of Organ Sharing registry from May 2005 to 2020. After identifying an interaction between blood group and LAS, we evaluated the association between blood group and waitlist outcomes within LAS quartiles using unadjusted and adjusted competing risk models. RESULTS: In the lowest LAS quartile, blood group O had a 20% reduced transplantation rate (SHR: 0.80, 95%CI: 0.75-0.85) and higher waitlist death/removal (1.33, 95%CI: 1.15-1.55) compared with group A. Blood group AB had a 52% higher transplantation rate (SHR: 1.52, 95%CI: 1.34-1.73) in the lowest LAS quartile compared with group A. In the highest LAS quartile, there was no difference in transplantation rates between groups O and A. In contrast, group B had a 19% reduced transplantation rate (SHR, 0.81 95%CI: 0.73-0.89) and AB had a 28% reduced transplantation rate (SHR: 0.72, 95%CI: 0.61-0.86) in the highest LAS quartile. Additionally, groups B and AB had increased risk of waitlist death/removal in the highest LAS quartile compared with A (SHR: 1.27, 95%CI: 1.08-1.48; SHR: 1.31, 95%CI: 1.00-1.72). CONCLUSIONS: Waitlist outcomes among ABO blood groups vary depending on illness severity, which is represented by LAS. Blood group O has lower transplantation rates at low LAS while groups B and AB have lower transplantation rates at high LAS.

Time since primary transplant and poor functional status predict survival after redo lung transplant.

Background: In previous studies, lower functional status measured by Karnofsky Performance Status (KPS) correlated with worse survival after redo lung transplant. We hypothesize that combining reduced functional status and time from primary lung transplant will correlate with the etiology of lung allograft failure after primary lung transplant and more accurately predict survival after redo lung transplant. Methods: This retrospective study was approved by University of Minnesota Institutional Review Board. From the Scientific Registry of Transplant Recipients (SRTR) database, 739 patients underwent redo lung transplant (01/01/2005-8/30/2019). Pre-lung transplant characteristics, KPS, time between primary and redo lung transplant, outcomes, overall survival were evaluated. Paired comparisons were used to compare pre-transplant variables. A Cox regression model was fit to examine re-transplant survival. Due to non-proportional hazards, time between transplants was split into <1-year vs. 1+ years and analyzed with time-dependent coefficients, with follow-up time considered in three segments (0-6, 6-24, 24+ months). Results: After KPS grouping (10-40%, 50-70%, 80-100%), KPS 10-40% were less likely to be discharged after primary transplant and more likely required mechanical ventilation or extracorporeal membrane oxygenation (ECMO) bridging (P<0.001). Redo lung transplant survival was worse in the KPS 10-40% group who more likely underwent lung transplant <1 year after primary lung transplant. Mortality was significantly higher for patients who underwent redo lung transplant within one year of primary transplant when KPS was 10-40% (P<0.001). These patients were more likely to require redo lung transplant due to primary graft failure or acute cellular rejection. Conclusions: Functional status and time from primary lung transplant are strong predictors of outcome after redo lung transplant. We categorized redo lung transplant recipients in two distinct groups. One group has early allograft failure and poor functional status with a very poor prognosis after redo lung transplant. The other group has chronic allograft failure and overall better functional status with relatively better survival after redo lung transplant. Salvage redo lung transplant for primary allograft failure or acute rejection is associated with low one year survival.

Overly Selective Offer Acceptance is Associated With High Waitlist Mortality for the Most Ill Lung Transplant Candidates.

The demand for organs for lung transplantation (LTx) continues to outweigh supply. However, nearly 75% of donor lungs are never transplanted. LTx offer acceptance practices and the effects on waitlist/post-transplant outcomes by candidate clinical acuity are understudied. UNOS was used to identify all LTx candidates, donors, and offers from 2005 to 2019. Candidates were grouped by Lung Allocation Score (LAS; applicable post-2005, ages ≥12 years): LAS<40, 40-60, 61-80, and >80. Offer acceptance patterns, waitlist death/decompensation, and post-transplant survival (PTS) were compared. "Acceptable organ offers" were those from donors whose organs were accepted for transplantation. Approximately 3 million offers to 34,531 candidates were reviewed. Median waitlist durations were: 9 days-(LAS>80), 17 days-(LAS 61-80), 42 days-(LAS 40-60), 125 days-(LAS<40) (P < 0.001 between all). Per waitlist-day, offer rates were: total offers - 0.8/day-(LAS>80), 0.7/day-(LAS 61-80), 0.6/day-(LAS 40-60), 0.4/day-(LAS<40); acceptable offers - 0.34/day-(LAS>80), 0.32/day-(LAS 61-80), 0.24/day-(LAS 40-60), 0.15/day-(LAS<40) (both P < 0.001 between all LAS). Among patients who experienced waitlist mortality/decompensation, ≥1 acceptable offer was declined in 92% (3939/4270) of patients - 78% for LAS >80, 88% for LAS 61-80, 93% for LAS 40-60, and 96% for LAS <40. Thirty-day waitlist mortality/decompensation rates were: 46%-(LAS>80), 24%-(LAS 61-80), 5%-(LAS 40-60), <1%-(LAS<40) (P < 0.001 between all). PTS was equivalent between patients for whom the first/second offer vs later offers were accepted (all LAS P > 0.4). The first offers that LTx candidates receive (including acceptable organs) are declined for nearly all candidates. Healthier candidates can afford offer selectivity but more ill patients (LAS>60) cannot, experiencing exceedingly high 30-day waitlist mortality.

Predictors of lung transplant waitlist mortality for sarcoidosis.

RATIONALE: Unlike in other chronic lung diseases, criteria for lung transplant referral in sarcoidosis is not well-established. Waitlist mortality may offer clues in identifying clinical factors that warrant early referral. We aim to identify predictors for transplant waitlist mortality to improve referral criteria for patients with sarcoidosis. METHODS: We conducted a retrospective analysis of 1034 sarcoidosis patients listed for lung transplantation from May 2005 to May 2019 in the Scientific Registry of Transplant Recipients (SRTR) database. All patients were listed after the establishment of the Lung Allocation Score (LAS). We compared patients who died on the transplant waitlist to those who survived to transplantation. Potential predictors of waitlist mortality were assessed utilizing univariate and multivariate analysis performed via logistic regression modeling. RESULTS: Of 1034 candidates listed after LAS implementation, 704 were transplanted and 110 died on the waitlist. Significant predictors of waitlist mortality on multivariate analysis include female gender (OR 2.445; 95% CI 1.513-3.951; p = 0.0003) and severe pulmonary hypertension (OR 1.619; 95% CI 1.067-2.457; p = 0.0236). Taller minimum donor height (OR 0.606; 95% CI 0.379-0.969; p = 0.0365) and blood type B (OR 0.524; 95% CI 0.281-0.975 p = 0.0415) were associated with decreased likelihood of death on the waitlist. CONCLUSION: Among patients with sarcoidosis on the lung transplant waitlist, taller minimum donor height and blood type B were found to be protective factors against death on the waitlist. Female gender and severe pulmonary hypertension have a higher likelihood of death and earlier referral for transplantation in patients with these characteristics should be considered.

Contemporary trends in PGD incidence, outcomes, and therapies.

BACKGROUND: We sought to describe trends in extracorporeal membrane oxygenation (ECMO) use, and define the impact on PGD incidence and early mortality in lung transplantation. METHODS: Patients were enrolled from August 2011 to June 2018 at 10 transplant centers in the multi-center Lung Transplant Outcomes Group prospective cohort study. PGD was defined as Grade 3 at 48 or 72 hours, based on the 2016 PGD ISHLT guidelines. Logistic regression and survival models were used to contrast between group effects for event (i.e., PGD and Death) and time-to-event (i.e., death, extubation, discharge) outcomes respectively. Both modeling frameworks accommodate the inclusion of potential confounders. RESULTS: A total of 1,528 subjects were enrolled with a 25.7% incidence of PGD. Annual PGD incidence (14.3%-38.2%, p = .0002), median LAS (38.0-47.7 p = .009) and the use of ECMO salvage for PGD (5.7%-20.9%, p = .007) increased over the course of the study. PGD was associated with increased 1 year mortality (OR 1.7 [95% C.I. 1.2, 2.3], p = .0001). Bridging strategies were not associated with increased mortality compared to non-bridged patients (p = .66); however, salvage ECMO for PGD was significantly associated with increased mortality (OR 1.9 [1.3, 2.7], p = .0007). Restricted mean survival time comparison at 1-year demonstrated 84.1 days lost in venoarterial salvaged recipients with PGD when compared to those without PGD (ratio 1.3 [1.1, 1.5]) and 27.2 days for venovenous with PGD (ratio 1.1 [1.0, 1.4]). CONCLUSIONS: PGD incidence continues to rise in modern transplant practice paralleled by significant increases in recipient severity of illness. Bridging strategies have increased but did not affect PGD incidence or mortality. PGD remains highly associated with mortality and is increasingly treated with salvage ECMO.

Clinical impact of a modified lung allocation score that mitigates selection bias.

BACKGROUND: The Lung Allocation Score (LAS) is used in the U.S. to prioritize lung transplant candidates. Selection bias, induced by dependent censoring of waitlisted candidates and prediction of posttransplant survival among surviving, transplanted patients only, is only partially addressed by the LAS. Recently, a modified LAS (mLAS) was designed to mitigate such bias. Here, we estimate the clinical impact of replacing the LAS with the mLAS. METHODS: We considered lung transplant candidates waitlisted during 2016 and 2017. LAS and mLAS scores were computed for each registrant at each observed organ offer date; individuals were ranked accordingly. Patient characteristics associated with better priority under the mLAS were investigated via logistic regression and generalized linear mixed models. We also determined whether differences in rank were explained more by changes in predicted pre- or posttransplant survival. Simulations examined how 1-year waitlist, posttransplant, and overall survival might change under the mLAS. RESULTS: Diagnosis group, 6-minute walk distance, continuous mechanical ventilation, functional status, and age demonstrated the highest impact on differential allocation. Differences in rank were explained more by changes in predicted pretransplant survival than changes in predicted posttransplant survival, suggesting that selection bias has more impact on estimates of waitlist urgency. Simulations suggest that for every 1000 waitlisted individuals, 12.8 (interquartile range: 5.2-24.3) fewer waitlist deaths per year would occur under the mLAS, without compromising posttransplant and overall survival. CONCLUSIONS: Implementing a mLAS that mitigates selection bias into clinical practice can lead to important differences in allocation and possibly modest improvement in waitlist survival.

The lung allocation score and other available models lack predictive accuracy for post-lung transplant survival.

BACKGROUND: Improved predictive models are needed in lung transplantation in the setting of a proposed allocation system that incorporates longer-term post-transplant survival in the United States. Allocation systems require accurate mortality predictions to justly allocate organs. METHODS: Utilizing the United Network for Organ Sharing database (2005-2017), we fit models to predict 1-year mortality based on the Lung Allocation Score (LAS), the Chan, et al, 2019 model, a novel "clinician" model (a priori clinician selection of pre-transplant covariates), and two machine learning models (Least Absolute Shrinkage and Selection Operator; LASSO and Random Forests) for predicting 1-year and 3-year post-transplant mortality. We compared predictive accuracy among models. We evaluated the calibration of models by comparing average predicted probability vs observed outcome per decile. We repeated analyses fit for 3-year mortality, disease category, including donor covariates, and LAS era. RESULTS: The area under the cure for all models was low, ranging from 0.55 to 0.62. All exhibited reasonable negative predictive values (0.87-0.90), but the positive predictive value for was poor (all <0.25). Evaluating LAS calibration found 1-year post-transplant estimates consistently overestimated risk of mortality, with greater differences in higher deciles. LASSO, Random Forests, and clinician models showed no improvement when evaluated by disease category or with the addition of donor covariates and performed worse for 3-year outcomes. CONCLUSIONS: The LAS overestimated patients' risk of post-transplant death, thus underestimating transplant benefit in the sickest candidates. Novel models based on pre-transplant recipient covariates failed to improve prediction. There should be wariness in post-transplant survival predictions from available models.

OPTN/SRTR 2020 Annual Data Report: Lung.

For the first time in a decade, both the number of candidates added to the waiting list and the number of lung transplants performed decreased from the year prior; the number of lung donors also declined. This slowing of transplant activities in 2020 was associated with a modest increase in waitlist mortality. The year 2020 was notable for the global outbreak of the COVID-19 pandemic, which undoubtedly influenced all trends noted in lung transplantation. Time to transplant continued to decrease, with a median time to transplant of 1.4 months across all waitlist candidates. Posttransplant survival remained stable, with 89.4% of transplant recipients surviving to 1 year, 74.8% to 3 years, and 61.2% to 5 years.

Impact of incorporating long-term survival for calculating transplant benefit in the US lung transplant allocation system.

BACKGROUND: The lung allocation score prioritizes candidates for a lung transplant in the United States. As the country adopts the continuous distribution framework for organ allocation, we must reevaluate lung allocation score assumptions to maximize transplant benefit. METHODS: We used Scientific Registry of Transplant Recipients data to study the impact of these changes: (1) updating cohorts; (2) transitioning from 1- to 5-year posttransplant survival; (3) using time-varying effects for non-proportional hazards; and (4) weighting waitlist and posttransplant area under the curve differently. Models were compared using Spearman correlations and C-statistics. The thoracic simulation allocation model characterized transplant rates and proportions of recipient subgroups under the current and new systems. RESULTS: Posttransplant areas under the curve models were estimated with recipients aged ≥12 from January 1, 2014, to December 31, 2018. All models had similar C-statistics and Spearman correlations, indicating similar predictive performance and posttransplant area under the curve rankings. Five-year posttransplant area under the curve across age and diagnosis groups varied more than 1-year groups. Using the thoracic simulation allocation model, 1- and 5-year posttransplant model under the curve models showed similar transplant rates and recipient characteristics under the current system, but under continuous distribution, 5-year posttransplant area under the curve resulted in increased transplant rates with more recipients younger and in diagnosis groups B and C. CONCLUSION: Incorporating equally weighted waitlist and posttransplant models using 5-year posttransplant survival detected the largest variability in survival under the continuous distribution system, which could improve long-term survival in the United States.

Spirometry testing for extracorporeal membrane oxygenation (ECMO) bridge to transplant patients.

PURPOSE: ECMO can provide a bridge to transplantation and improve survival for patients with advanced lung disease. Although pulmonary function testing (PFT) is an important component of the lung allocation score (LAS), it is not always feasible on patients requiring ECMO. While generally safe, PFT testing has contraindications and is not recommended in unstable patients. Currently there are no recommendations regarding the performance of spirometry in ECMO patients. STUDY DESIGN: and Methods: We reviewed data on five patients with advanced lung disease requiring ECMO-bridge to transplant. After careful consideration of the theoretical physiologic risks associated with forced expiratory maneuvers, bedside spirometry was performed in order to update the patients' LAS. RESULTS: All patients successfully completed three forced expiratory maneuvers in the seated position with a bedside spirometer. Vital signs and ECMO flow were stable during testing and without complication. In 2 patients who had both a LAS pre and post spirometry, the LAS increased by 3-5 points. CONCLUSION: Spirometry results are pivotal to organ allocation under current organ sharing protocols. This case series demonstrates that bedside spirometry testing may be performed safely in patients on ECMO awaiting lung transplantation without appreciable side effects, leading to a more accurate LAS score.