Development and validation of primary graft dysfunction predictive algorithm for lung transplant candidates.

BACKGROUND: Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Accurate prediction of PGD risk could inform donor approaches and perioperative care planning. We sought to develop a clinically useful, generalizable PGD prediction model to aid in transplant decision-making. METHODS: We derived a predictive model in a prospective cohort study of subjects from 2012 to 2018, followed by a single-center external validation. We used regularized (lasso) logistic regression to evaluate the predictive ability of clinically available PGD predictors and developed a user interface for clinical application. Using decision curve analysis, we quantified the net benefit of the model across a range of PGD risk thresholds and assessed model calibration and discrimination. RESULTS: The PGD predictive model included distance from donor hospital to recipient transplant center, recipient age, predicted total lung capacity, lung allocation score (LAS), body mass index, pulmonary artery mean pressure, sex, and indication for transplant; donor age, sex, mechanism of death, and donor smoking status; and interaction terms for LAS and donor distance. The interface allows for real-time assessment of PGD risk for any donor/recipient combination. The model offers decision-making net benefit in the PGD risk range of 10% to 75% in the derivation centers and 2% to 10% in the validation cohort, a range incorporating the incidence in that cohort. CONCLUSION: We developed a clinically useful PGD predictive algorithm across a range of PGD risk thresholds to support transplant decision-making, posttransplant care, and enrich samples for PGD treatment trials.

The Impact of Donor Smoking on Primary Graft Dysfunction and Mortality after Lung Transplantation.

Rationale: Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Prior studies implicated proxy-defined donor smoking as a risk factor for PGD and mortality. Objectives: We aimed to more accurately assess the impact of donor smoke exposure on PGD and mortality using quantitative smoke exposure biomarkers. Methods: We performed a multicenter prospective cohort study of lung transplant recipients enrolled in the Lung Transplant Outcomes Group cohort between 2012 and 2018. PGD was defined as grade 3 at 48 or 72 hours after lung reperfusion. Donor smoking was defined using accepted thresholds of urinary biomarkers of nicotine exposure (cotinine) and tobacco-specific nitrosamine (4-[methylnitrosamino]-1-[3-pyridyl]-1-butanol [NNAL]) in addition to clinical history. The donor smoking-PGD association was assessed using logistic regression, and survival analysis was performed using inverse probability of exposure weighting according to smoking category. Measurements and Main Results: Active donor smoking prevalence varied by definition, with 34-43% based on urinary cotinine, 28% by urinary NNAL, and 37% by clinical documentation. The standardized risk of PGD associated with active donor smoking was higher across all definitions, with an absolute risk increase of 11.5% (95% confidence interval [CI], 3.8% to 19.2%) by urinary cotinine, 5.7% (95% CI, -3.4% to 14.9%) by urinary NNAL, and 6.5% (95% CI, -2.8% to 15.8%) defined clinically. Donor smoking was not associated with differential post-lung transplant survival using any definition. Conclusions: Donor smoking associates with a modest increase in PGD risk but not with increased recipient mortality. Use of lungs from smokers is likely safe and may increase lung donor availability. Clinical trial registered with www.clinicaltrials.gov (NCT00552357).

Development and validation of a population pharmacokinetic model to guide perioperative tacrolimus dosing after lung transplantation.

Background: Tacrolimus therapy is standard of care for immunosuppression after lung transplantation. However, tacrolimus exposure variability during the early postoperative period may contribute to poor outcomes in this population. Few studies have examined tacrolimus pharmacokinetics (PK) during this high-risk time period. Methods: We conducted a retrospective pharmacokinetic study in lung transplant recipients at the University of Pennsylvania who were enrolled in the Lung Transplant Outcomes Group (LTOG) cohort. We derived a model in 270 patients using NONMEM (version 7.5.1) and examined validity in a separate cohort of 114 patients. Covariates were examined with univariate analysis and multivariable analysis was developed using forward and backward stepwise selection. Performance of the final model in the validation cohort was examined with calculation of mean prediction error (PE). Results: We developed a one-compartment base model with a fixed rate absorption constant. Significant covariates in multivariable analysis were postoperative day, hematocrit, transplant type, CYP3A5 genotype, total body weight, and time-varying postoperative day, hematocrit, and CYP inhibitor drugs. The strongest predictor of tacrolimus clearance was postoperative day, with median predicted clearance increasing more than threefold over the 14 day study period. In the validation cohort, the final model showed a mean PE of 36.4% (95%CI 30.8%-41.9%) and a median PE of 7.2% (IQR -29.3%-70.53%). Conclusion: Postoperative day was the strongest predictor of tacrolimus exposure in the early post-lung transplant period. Future multicenter studies employing intensive sampling to examine a broad set of variables related to critical illness physiology are needed to understand determinants of clearance, volume of distribution and absorption in this population.

Body Mass Index and Cause-Specific Mortality after Lung Transplantation in the United States.

Rationale: Low and high body mass index (BMI) are associated with increased mortality after lung transplantation. Why extremes of BMI might increase risk of death is unknown. Objectives: To estimate the association of extremes of BMI with causes of death after transplantation. Methods: We performed a retrospective study of the United Network for Organ Sharing database, including 26,721 adults who underwent lung transplantation in the United States between May 4, 2005, and December 2, 2020. We mapped 76 reported causes of death into 16 distinct groups. We estimated cause-specific hazards for death from each cause using Cox models. Results: Relative to a subject with a BMI of 24 kg/m2, a subject with a BMI of 16 kg/m2 had 38% (hazard ratio [HR], 1.38; 95% confidence interval [95% CI], 0.99-1.90), 82% (HR, 1.82; 95% CI, 1.34-2.46), and 62% (HR, 1.62; 95% CI, 1.18-2.22) increased hazards of death from acute respiratory failure, chronic lung allograft dysfunction (CLAD), and infection, respectively, and a subject with a BMI of 36 kg/m2 had 44% (HR, 1.44; 95% CI, 0.97-2.12), 42% (HR, 1.42; 95% CI, 0.93-2.15), and 185% (HR, 2.85; 95% CI, 1.28-6.33) increased hazards of death from acute respiratory failure, CLAD, and primary graft dysfunction, respectively. Conclusions: Low BMI is associated with increased risk of death from infection, acute respiratory failure, and CLAD after lung transplantation, whereas high BMI is associated with increased risk of death from primary graft dysfunction, acute respiratory failure, and CLAD.

Development of the Lung Transplant Frailty Scale (LT-FS).

BACKGROUND: Existing measures of frailty developed in community dwelling older adults may misclassify frailty in lung transplant candidates. We aimed to develop a novel frailty scale for lung transplantation with improved performance characteristics. METHODS: We measured the short physical performance battery (SPPB), fried frailty phenotype (FFP), Body Composition, and serum Biomarkers representative of putative frailty mechanisms. We applied a 4-step established approach (identify frailty domain variable bivariate associations with the outcome of waitlist delisting or death; build models sequentially incorporating variables from each frailty domain cluster; retain variables that improved model performance ability by c-statistic or AIC) to develop 3 candidate "Lung Transplant Frailty Scale (LT-FS)" measures: 1 incorporating readily available clinical data; 1 adding muscle mass, and 1 adding muscle mass and research-grade Biomarkers. We compared construct and predictive validity of LT-FS models to the SPPB and FFP by ANOVA, ANCOVA, and Cox proportional-hazard modeling. RESULTS: In 342 lung transplant candidates, LT-FS models exhibited superior construct and predictive validity compared to the SPPB and FFP. The addition of muscle mass and Biomarkers improved model performance. Frailty by all measures was associated with waitlist disability, poorer HRQL, and waitlist delisting/death. LT-FS models exhibited stronger associations with waitlist delisting/death than SPPB or FFP (C-statistic range: 0.73-0.78 vs. 0.57 and 0.55 for SPPB and FFP, respectively). Compared to SPPB and FFP, LT-FS models were generally more strongly associated with delisting/death and improved delisting/death net reclassification, with greater improvements with increasing LT-FS model complexity (range: 0.11-0.34). For example, LT-FS-Body Composition hazard ratio for delisting/death: 6.0 (95%CI: 2.5, 14.2), SPPB HR: 2.5 (95%CI: 1.1, 5.8), FFP HR: 4.3 (95%CI: 1.8, 10.1). Pre-transplant LT-FS frailty, but not SPPB or FFP, was associated with mortality after transplant. CONCLUSIONS: The LT-FS is a disease-specific physical frailty measure with face and construct validity that has superior predictive validity over established measures.

Subphenotypes of frailty in lung transplant candidates.

Heterogeneous frailty pathobiology might explain the inconsistent associations observed between frailty and lung transplant outcomes. A Subphenotype analysis could refine frailty measurement. In a 3-center pilot cohort study, we measured frailty by the Short Physical Performance Battery, body composition, and serum biomarkers reflecting causes of frailty. We applied latent class modeling for these baseline data. Next, we tested class construct validity with disability, waitlist delisting/death, and early postoperative complications. Among 422 lung transplant candidates, 2 class model fit the best (P = .01). Compared with Subphenotype 1 (n = 333), Subphenotype 2 (n = 89) was characterized by systemic and innate inflammation (higher IL-6, CRP, PTX3, TNF-R1, and IL-1RA); mitochondrial stress (higher GDF-15 and FGF-21); sarcopenia; malnutrition; and lower hemoglobin and walk distance. Subphenotype 2 had a worse disability and higher risk of waitlist delisting or death (hazards ratio: 4.0; 95% confidence interval: 1.8-9.1). Of the total cohort, 257 underwent transplant (Subphenotype 1: 196; Subphenotype 2: 61). Subphenotype 2 had a higher need for take back to the operating room (48% vs 28%; P = .005) and longer posttransplant hospital length of stay (21 days [interquartile range: 14-33] vs 18 days [14-28]; P = .04). Subphenotype 2 trended toward fewer ventilator-free days, needing more postoperative extracorporeal membrane oxygenation and dialysis, and higher need for discharge to rehabilitation facilities (P ≤ .20). In this early phase study, we identified biological frailty Subphenotypes in lung transplant candidates. A hyperinflammatory, sarcopenic Subphenotype seems to be associated with worse clinical outcomes.

Risk of primary graft dysfunction following lung transplantation in selected adults with connective tissue disease-associated interstitial lung disease.

BACKGROUND: Previous studies have reported similarities in long-term outcomes following lung transplantation for connective tissue disease-associated interstitial lung disease (CTD-ILD) and idiopathic pulmonary fibrosis (IPF). However, it is unknown whether CTD-ILD patients are at increased risk of primary graft dysfunction (PGD), delays in extubation, or longer index hospitalizations following transplant compared to IPF patients. METHODS: We performed a multicenter retrospective cohort study of CTD-ILD and IPF patients enrolled in the Lung Transplant Outcomes Group registry who underwent lung transplantation between 2012 and 2018. We utilized mixed effects logistic regression and stratified Cox proportional hazards regression to determine whether CTD-ILD was independently associated with increased risk for grade 3 PGD or delays in post-transplant extubation and hospital discharge compared to IPF. RESULTS: A total of 32.7% (33/101) of patients with CTD-ILD and 28.9% (145/501) of patients with IPF developed grade 3 PGD 48-72 hours after transplant. There were no significant differences in odds of grade 3 PGD among patients with CTD-ILD compared to those with IPF (adjusted OR 1.12, 95% CI 0.64-1.97, p = 0.69), nor was CTD-ILD independently associated with a longer post-transplant time to extubation (adjusted HR for first extubation 0.87, 95% CI 0.66-1.13, p = 0.30). However, CTD-ILD was independently associated with a longer post-transplant hospital length of stay (median 23 days [IQR 14-35 days] vs17 days [IQR 12-28 days], adjusted HR for hospital discharge 0.68, 95% CI 0.51-0.90, p = 0.008). CONCLUSION: Patients with CTD-ILD experienced significantly longer postoperative hospitalizations compared to IPF patients without an increased risk of grade 3 PGD.

Local complement activation is associated with primary graft dysfunction after lung transplantation.

BACKGROUNDThe complement system plays a key role in host defense but is activated by ischemia/reperfusion injury (IRI). Primary graft dysfunction (PGD) is a form of acute lung injury occurring predominantly due to IRI, which worsens survival after lung transplantation (LTx). Local complement activation is associated with acute lung injury, but whether it is more reflective of allograft injury compared with systemic activation remains unclear. We proposed that local complement activation would help identify those who develop PGD after LTx. We also aimed to identify which complement activation pathways are associated with PGD.METHODSWe performed a multicenter cohort study at the University of Pennsylvania and Washington University School of Medicine. Bronchoalveolar lavage (BAL) and plasma specimens were obtained from recipients within 24 hours after LTx. PGD was scored based on the consensus definition. Complement activation products and components of each arm of the complement cascade were measured using ELISA.RESULTSIn both cohorts, sC4d and sC5b-9 levels were increased in BAL of subjects with PGD compared with those without PGD. Subjects with PGD also had higher C1q, C2, C4, and C4b, compared with subjects without PGD, suggesting classical and lectin pathway involvement. Ba levels were higher in subjects with PGD, suggesting alternative pathway activation. Among lectin pathway-specific components, MBL and FCN-3 had a moderate-to-strong correlation with the terminal complement complex in the BAL but not in the plasma.CONCLUSIONComplement activation fragments are detected in the BAL within 24 hours after LTx. Components of all 3 pathways are locally increased in subjects with PGD. Our findings create a precedent for investigating complement-targeted therapeutics to mitigate PGD.FUNDINGThis research was supported by the NIH, American Lung Association, Children's Discovery Institute, Robert Wood Johnson Foundation, Cystic Fibrosis Foundation, Barnes-Jewish Hospital Foundation, Danish Heart Foundation, Danish Research Foundation of Independent Research, Svend Andersen Research Foundation, and Novo Nordisk Research Foundation.

Early Tacrolimus Concentrations After Lung Transplant Are Predicted by Combined Clinical and Genetic Factors and Associated With Acute Kidney Injury.

Tacrolimus exhibits unpredictable pharmacokinetics (PKs) after lung transplant, partly explained by cytochrome P450 (CYP)-enzyme polymorphisms. However, whether exposure variability during the immediate postoperative period affects outcomes is unknown, and pharmacogenetic dosing may be limited by residual PK variability. We estimated adjusted associations between early postoperative tacrolimus concentrations and acute kidney injury (AKI) and acute cellular rejection (ACR), and identified clinical and pharmacogenetic factors that explain postoperative tacrolimus concentration variability in 484 lung transplant patients. Increasing tacrolimus concentration was associated with higher AKI risk (hazard ratio (HR) 1.54; 95% confidence interval (CI) 1.20-1.96 per 5-mg/dL); and increasing AKI severity (odds ratio 1.29; 95% CI 1.04-1.60 per 5-mg/dL), but not ACR (HR 1.02; 95% CI 0.73-1.42). A model with clinical and pharmacogenetic factors explained 42% of concentration variance compared with 19% for pharmacogenetic factors only. Early tacrolimus exposure was independently associated with AKI after lung transplantation, but not ACR. Clinical factors accounted for substantial residual tacrolimus concentration variability not explained by CYP-enzyme polymorphisms.

Adipose tissue quantification and primary graft dysfunction after lung transplantation: The Lung Transplant Body Composition study.

BACKGROUND: Obesity is associated with an increased risk of primary graft dysfunction (PGD) after lung transplantation. The contribution of specific adipose tissue depots is unknown. METHODS: We performed a prospective cohort study of adult lung transplant recipients at 4 U.S. transplant centers. We measured cross-sectional areas of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) on chest and abdominal computed tomography (CT) scans and indexed each measurement to height.2 We used logistic regression to examine the associations of adipose indices and adipose classes with grade 3 PGD at 48 or 72 hours, and Cox proportional hazards models to examine survival. We used latent class analyses to identify the patterns of adipose distribution. We examined the associations of adipose indices with plasma biomarkers of obesity and PGD. RESULTS: A total of 262 and 117 subjects had available chest CT scans and underwent protocol abdominal CT scans, respectively. In the adjusted models, a greater abdominal SAT index was associated with an increased risk of PGD (odds ratio 1.9, 95% CI 1.02-3.4, p = 0.04) but not with survival time. VAT indices were not associated with PGD risk or survival time. A greater abdominal SAT index correlated with greater pre- and post-transplant leptin (r = 0.61, p < 0.001, and r = 0.44, p < 0.001), pre-transplant IL-1RA (r = 0.25, p = 0.04), and post-transplant ICAM-1 (r = 0.25, p = 0.04). We identified 3 latent patterns of adiposity. The class defined by high thoracic and abdominal SAT had the greatest risk of PGD. CONCLUSIONS: Subcutaneous, but not visceral, adiposity is associated with an increased risk of PGD after lung transplantation.

Frailty phenotypes and mortality after lung transplantation: A prospective cohort study.

Frailty is associated with increased mortality among lung transplant candidates. We sought to determine the association between frailty, as measured by the Short Physical Performance Battery (SPPB), and mortality after lung transplantation. In a multicenter prospective cohort study of adults who underwent lung transplantation, preoperative frailty was assessed with the SPPB (n = 318) and, in a secondary analysis, the Fried Frailty Phenotype (FFP; n = 299). We tested the association between preoperative frailty and mortality following lung transplantation with propensity score-adjusted Cox models. We calculated postestimation marginalized standardized risks for 1-year mortality by frailty status using multivariate logistic regression. SPPB frailty was associated with an increased risk of both 1- and 4-year mortality (adjusted hazard ratio [aHR]: 7.5; 95% confidence interval [CI]: 1.6-36.0 and aHR 3.8; 95%CI: 1.8-8.0, respectively). Each 1-point worsening in SPPB was associated with a 20% increased risk of death (aHR: 1.20; 95%CI: 1.08-1.33). Frail subjects had an absolute increased risk of death within the first year after transplantation of 12.2% (95%CI: 3.1%-21%). In secondary analyses, FFP frailty was associated with increased risk of death within the first postoperative year (aHR: 3.8; 95%CI: 1.1-13.2) but not over longer follow-up. Preoperative frailty is associated with an increased risk of death after lung transplantation.

Incidence, risk factors, and clinical implications of post-operative delirium in lung transplant recipients.

BACKGROUND: Delirium significantly affects post-operative outcomes, but the incidence, risk factors, and long-term impact of delirium in lung transplant recipients have not been well studied. METHODS: We analyzed 155 lung transplant recipients enrolled in the Lung Transplant Outcomes Group (LTOG) cohort at a single center. We determined delirium incidence by structured chart review, identified risk factors for delirium, determined whether plasma concentrations of 2 cerebral injury markers (neuron-specific enolase [NSE] and glial fibrillary acidic protein [GFAP]) were associated with delirium, and determined the association of post-operative delirium with 1-year survival. RESULTS: Fifty-seven (36.8%) patients developed post-operative delirium. Independent risk factors for delirium included pre-transplant benzodiazepine prescription (relative risk [RR] 1.82; 95% confidence interval [CI] 1.08 to 3.07; p = 0.025), total ischemic time (RR 1.10 per 30-minute increase; 95% CI 1.01 to 1.21; p = 0.027), duration of time with intra-operative mean arterial pressure <60 mm Hg (RR 1.07 per 15-minute increase; 95% CI 1.00 to 1.14; p = 0.041), and Grade 3 primary graft dysfunction (RR 2.13; 95% CI 1.27 to 3.58; p = 0.004). Ninety-one (58.7%) patients had plasma available at 24 hours. Plasma GFAP was inconsistently detected, whereas NSE was universally detectable, with higher NSE concentrations associated with delirium (risk difference 15.1% comparing 75th and 25th percentiles; 95% CI 2.5 to 27.7; p = 0.026). One-year mortality appeared higher among delirious patients, 12.3% compared with 7.1%, but the difference was not significant (p = 0.28). CONCLUSIONS: Post-operative delirium is common in lung transplant recipients, and several potentially modifiable risk factors deserve further study to determine their associated mechanisms and predictive values.

Adipose Gene Expression Profile Changes With Lung Allograft Reperfusion.

Obesity is a risk factor for primary graft dysfunction (PGD), a form of lung injury resulting from ischemia-reperfusion after lung transplantation, but the impact of ischemia-reperfusion on adipose tissue is unknown. We evaluated differential gene expression in thoracic visceral adipose tissue (VAT) before and after lung reperfusion. Total RNA was isolated from thoracic VAT sampled from six subjects enrolled in the Lung Transplant Body Composition study before and after allograft reperfusion and quantified using the Human Gene 2.0 ST array. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed enrichment for genes involved in complement and coagulation cascades and Jak-STAT signaling pathways. Overall, 72 genes were upregulated and 56 genes were downregulated in the postreperfusion time compared with baseline. Long pentraxin-3, a gene and plasma protein previously associated with PGD, was the most upregulated gene (19.5-fold increase, p = 0.04). Fibronectin leucine-rich transmembrane protein-3, a gene associated with cell adhesion and receptor signaling, was the most downregulated gene (4.3-fold decrease, p = 0.04). Ischemia-reperfusion has a demonstrable impact on gene expression in visceral adipose tissue in our pilot study of nonobese, non-PGD lung transplant recipients. Future evaluation will focus on differential adipose tissue gene expression and the development of PGD after transplant.