Transplantation Within 6 Months of Registration does not Enhance Survival for Patients with Perihilar Cholangiocarcinoma.

OBJECTIVES: Determine if timing of transplantation affects patient mortality. BACKGROUND: Neoadjuvant therapy and liver transplantation has emerged as an excellent treatment option for select patients with perihilar cholangiocarcinoma (pCCA). However, the optimal timing of transplantation is not known. METHODS: We reviewed all patients registered for a standardized pCCA protocol between 1996 - 2020 at our center. After adjusting for confounders, we examined the association of waiting time with patient mortality in an intention-to-treat cohort (n=392) and those who received a liver transplant (n=256). RESULTS: The median (interquartile range) time from registration to transplant or drop out was 5.74 (3.25-7.06) months. Compared to a short wait time (0-3 months), longer waiting times did not affect all-cause mortality: (3-6 months) hazard ratio (HR) 0.98; 95% CI 0.52-1.84; (6-9 months) HR 0.80; 95% CI 0.39-1.65; (9-12 months) HR 0.56; 95% CI 0.26-1.22. Subgroups with a shorter waiting time had similar survival to those with long waiting times: living donor available HR 0.97; 95% CI 0.67-1.42; AB or B blood group HR 0.93; 95% CI 0.62-1.39. Longer waiting times were associated with decreased all-cause mortality after transplantation (HR 0.92; 95% CI 0.87-0.97). This benefit began after a 6 month waiting time minimum (HR 0.53; 95% CI 0.26-1.10) and increased further after 9 months (HR; 0.43 95% CI 0.20-0.93). Waiting time was not associated with residual adenocarcinoma in the explant (odds ratio 0.99; 95% CI 0.98-1.00). CONCLUSIONS: A waiting time of at least 6 months will optimize results with transplantation without affecting overall (intention-to-treat) patient survival.

Changes in Glomerular Volume, Sclerosis, and Ischemia at 5 Years after Kidney Transplantation: Incidence and Correlation with Late Graft Failure.

SIGNIFICANCE STATEMENT: Glomerular volume, ischemic glomeruli, and global glomerulosclerosis are not consistently assessed on kidney transplant biopsies. The authors evaluated morphometric measures of glomerular volume, the percentage of global glomerulosclerosis, and the percentage of ischemic glomeruli and assessed changes in these measures over time to determine whether such changes predict late allograft failure. All three features increased from transplant to five-year biopsy. Kidneys with smaller glomeruli at 5 years had more global glomerulosclerosis and a higher percentage of ischemic-appearing glomeruli. Smaller glomeruli and increasing percentages of global glomerulosclerosis and ischemic glomeruli at 5 years predicted allograft failure. Only increased percentage of ischemic glomeruli predicted allograft failure at 5 years independent of all Banff scores. Glomerular changes reflect pathologic processes that predicted allograft loss; measuring them quantitatively might enhance the current Banff system and provide biomarkers for intervention trials. BACKGROUND: Histology can provide insight into the biology of renal allograft loss. However, studies are lacking that use quantitative morphometry to simultaneously assess changes in mean glomerular volume and in the percentages of globally sclerosed glomeruli (GSG) and ischemic-appearing glomeruli in surveillance biopsies over time to determine whether such changes are correlated with late graft failure. METHODS: We used digital scans of surveillance biopsies (at implantation and at 1 and 5 years after transplantation) to morphometrically quantify glomerular volume and the percentages of GSG and ischemic-appearing glomeruli in a cohort of 835 kidney transplants. Cox proportional hazards models assessed the risk of allograft failure with these three glomerular features. RESULTS: From implantation to 5 years, mean glomerular volume increased by nearly 30% (from 2.8×10 6 to 3.6×10 6 µm 3 ), mean percentage of GSG increased from 3.2% to 13.2%, and mean percentage of ischemic-appearing glomeruli increased from 0.8% to 9.5%. Higher percentages of GSG and ischemic-appearing glomeruli at 5-year biopsy predicted allograft loss. The three glomerular features at 5-year biopsy were related; the percentage of GSG and the percentage of ischemic glomeruli were positively correlated, and both were inversely correlated to glomerular volume. At 5 years, only 5.3% of biopsies had ≥40% ischemic glomeruli, but 45% of these grafts failed (versus 11.6% for <40% ischemic glomeruli). Higher Banff scores were more common with increasing percentages of GSG and ischemia, but at 5 years, only the percentage of ischemic glomeruli added to predictive models adjusted for Banff scores. CONCLUSIONS: Glomerular changes reflect important pathologic processes that predict graft loss. Measuring glomerular changes quantitatively on surveillance biopsies, especially the proportion of ischemic-appearing glomeruli, may enhance the current Banff system and be a useful surrogate end point for clinical intervention trials. PODCAST: This article contains a podcast at.

Convolutional Neural Networks for the Evaluation of Chronic and Inflammatory Lesions in Kidney Transplant Biopsies.

In kidney transplant biopsies, both inflammation and chronic changes are important features that predict long-term graft survival. Quantitative scoring of these features is important for transplant diagnostics and kidney research. However, visual scoring is poorly reproducible and labor intensive. The goal of this study was to investigate the potential of convolutional neural networks (CNNs) to quantify inflammation and chronic features in kidney transplant biopsies. A structure segmentation CNN and a lymphocyte detection CNN were applied on 125 whole-slide image pairs of periodic acid-Schiff- and CD3-stained slides. The CNN results were used to quantify healthy and sclerotic glomeruli, interstitial fibrosis, tubular atrophy, and inflammation within both nonatrophic and atrophic tubuli, and in areas of interstitial fibrosis. The computed tissue features showed high correlation with Banff lesion scores of five pathologists (A.A., A.Dend., J.H.B., J.K., and T.N.). Analyses on a small subset showed a moderate correlation toward higher CD3+ cell density within scarred regions and higher CD3+ cell count inside atrophic tubuli correlated with long-term change of estimated glomerular filtration rate. The presented CNNs are valid tools to yield objective quantitative information on glomeruli number, fibrotic tissue, and inflammation within scarred and non-scarred kidney parenchyma in a reproducible manner. CNNs have the potential to improve kidney transplant diagnostics and will benefit the community as a novel method to generate surrogate end points for large-scale clinical studies.

Risk factors and prophylaxis for nocardiosis in solid organ transplant recipients: A nested case-control study.

BACKGROUND: Nocardia is an opportunistic pathogen that primarily affects immunocompromised individuals, including solid organ transplant (SOT) recipients. Up to 2.65% of SOT recipients develop nocardiosis; however, few studies have examined risk factors and prophylaxis for nocardiosis. METHODS: We performed a multicenter, matched nested case-control study of adult SOT recipients with culture-confirmed nocardiosis from 2000 through 2020. Controls were matched up to 2:1 by sex, first transplanted organ, year of transplant, transplant center, and adequate post-transplant follow-up. Multivariable conditional logistic regression was performed to analyze associations with nocardiosis. Cox proportional hazards regression compared 12-month mortality between infection and uninfected patients. RESULTS: One hundred and twenty-three SOT recipients were matched to 245 uninfected controls. Elevated calcineurin inhibitor level, acute rejection, cytomegalovirus infection, lymphopenia, higher prednisone dose, and older age were significantly associated with nocardiosis while trimethoprim-sulfamethoxazole prophylaxis was protective (odds ratio [OR] .34; 95% confidence interval [CI] .13-.84). The effect of prophylaxis was similar, though not always statistically significant, in sensitivity analyses that only included prophylaxis dosed more than twice-per-week (OR .30; 95% CI .11-.80) or restricted to years 2015-2020 (OR .33, 95% CI .09-1.21). Nocardiosis was associated with increased 12-month mortality (hazard ratio 5.47; 95% confidence interval 2.42-12.35). CONCLUSIONS: Multiple measures of immunosuppression and lack of trimethoprim-sulfamethoxazole prophylaxis were associated with nocardiosis in SOT recipients. Effectiveness of prophylaxis may be related to trimethoprim-sulfamethoxazole dose or frequency. Trimethoprim-sulfamethoxazole should be preferentially utilized over alternative agents in SOT recipients with augmented immunosuppression or signs of heightened immunocompromise.

Risk factors and outcomes of Pneumocystis pneumonia in solid organ transplant recipients: Impact of posttransplant lymphoproliferative disorder.

BACKGROUND: Pneumocystis jirovecii pneumonia (PJP) is a potentially fatal infection afflicting the immunocompromised population, including solid organ transplant (SOT) recipients. Several risk factors have been described; however, little is known regarding the risk of PJP in SOT recipients with posttransplant lymphoproliferative disorder (PTLD). METHODS: We performed a nested case-control study of SOT recipients diagnosed with PJP from 2000 to 2020. PJP was defined as positive microscopy or polymerase chain reaction testing with compatible symptoms and radiographic findings. Control patients were matched 2:1 by year of first transplant, first transplanted organ, transplant center, and sex. Multivariable conditional logistic regression was performed to test associations with PJP and Cox regression analyzed post-PJP outcomes. RESULTS: Sixty-seven PJP cases were matched to 134 controls. The most common transplant was kidney (55.2%). Fourteen patients had a history of PTLD, 12 of whom developed PJP. After adjusting for age, acute rejection, cytomegalovirus infection, PJP prophylaxis, and lymphopenia (lymphocyte count < .5 × 109 /L), PTLD was independently associated with PJP (OR 14.0, 95% CI 1.7-114.5; p = .014). Lymphopenia was also a significant association (OR 8.2, 95% CI 3.2-20.7; p < .001). PJP was associated with mortality within 90 days of diagnosis (p < .001), but not after 90 days (p = .317). PJP was also associated with 90-day death-censored renal allograft loss (p = .026). CONCLUSIONS: PTLD is independently associated with PJP after adjustment for recognized risk factors. This is likely influenced by PTLD-directed chemotherapy, particularly rituximab-containing regimens. PJP is associated with early mortality, but this effect is not persistent after 90 days. PJP prophylaxis should be considered in SOT recipients with PTLD.

Progressive decline of function in renal allografts with normal 1-year biopsies: Gene expression studies fail to identify a classifier.

Histologic findings on 1-year biopsies such as inflammation with fibrosis and transplant glomerulopathy predict renal allograft loss by 5 years. However, almost half of the patients with graft loss have a 1-year biopsy that is either normal or has only interstitial fibrosis. The goal of this study was to determine if there was a gene expression profile in these relatively normal 1-year biopsies that predicted subsequent decline in renal function. Using transcriptome microarrays we measured intragraft mRNA levels in a retrospective Discovery cohort (170 patients with a normal/minimal fibrosis 1-year biopsy, 54 with progressive decline in function/graft loss and 116 with stable function) and developed a nested 10-fold cross-validated gene classifier that predicted progressive decline in renal function (positive predictive value = 38 ± 34%%; negative predictive value = 73 ± 30%, c-statistic = .59). In a prospective, multicenter Validation cohort (270 patients with Normal/Interstitial Fibrosis [IF]), the classifier had a 20% positive predictive value, 85% negative predictive value and .58 c-statistic. Importantly, the majority of patients with graft loss in the prospective study had 1-year biopsies scored as Normal or IF. We conclude predicting graft loss in many renal allograft recipients (i.e., those with a relatively normal 1-year biopsy and eGFR > 40) remains difficult.

Deep Learning-Based Histopathologic Assessment of Kidney Tissue.

BACKGROUND: The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized kidney tissue sections stained with periodic acid-Schiff (PAS). METHODS: We trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network's glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies. RESULTS: The weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was "glomeruli" in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by "tubuli combined" and "interstitium." The network detected 92.7% of all glomeruli in nephrectomy samples, with 10.4% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures. CONCLUSIONS: This study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.

Long-term outcomes of eculizumab-treated positive crossmatch recipients: Allograft survival, histologic findings, and natural history of the donor-specific antibodies.

We aimed to determine the long-term outcomes of eculizumab-treated, positive crossmatch (+XM) kidney transplant recipients compared with +XM and age-matched negative crossmatch (-XM) controls. We performed an observational retrospective study and examined allograft survival, histologic findings, long-term B-cell flow cytometric XM (BFXM), and allograft-loss-associated factors. The mean (SD) posttransplant follow-up was 6.3 (2.5) years in the eculizumab group; 7.6 (3.5), +XM control group; 7.9 (2.5), -XM control group. The overall and death-censored allograft survival rates were similar in +XM groups (P = .73, P = .48) but reduced compared with -XM control patients (P < .001, P < .001). In the eculizumab-treated group, 57.9% (11/19) of the allografts had chronic antibody-mediated rejection, but death-censored allograft survival was 76.6%, 5 years; 75.4%, 7 years. Baseline IgG3 positivity and BFXM ≥300 were associated with allograft loss. C1q positivity was also associated with allograft loss but did not reach statistical significance. Donor-specific antibodies appeared to decrease in eculizumab-treated patients. After excluding patients with posttransplant plasmapheresis, 42.3% (9/21) had negative BFXMs; 31.8% (7/22), completely negative single-antigen beads 1 year posttransplant. Eculizumab-treated +XM patients had reduced allograft survival compared with -XM controls but similar survival to +XM controls. BFXM and complement-activating donor-specific antibodies (by IgG3 and C1q testing) may be used for risk stratification in +XM transplantation.

Using computer-assisted morphometrics of 5-year biopsies to identify biomarkers of late renal allograft loss.

The current Banff scoring system was not developed to predict graft loss and may not be ideal for use in clinical trials aimed at improving allograft survival. We hypothesized that scoring histologic features of digitized renal allograft biopsies using a continuous, more objective, computer-assisted morphometric (CAM) system might be more predictive of graft loss. We performed a nested case-control study in kidney transplant recipients with a surveillance biopsy obtained 5 years after transplantation. Patients that developed death-censored graft loss (n = 67) were 2:1 matched on age, gender, and follow-up time to controls with surviving grafts (n = 134). The risk of graft loss was compared between CAM-based models vs a model based on Banff scores. Both Banff and CAM identified chronic lesions associated with graft loss (chronic glomerulopathy, arteriolar hyalinosis, and mesangial expansion). However, the CAM-based models predicted graft loss better than the Banff-based model, both overall (c-statistic 0.754 vs 0.705, P < .001), and in biopsies without chronic glomerulopathy (c-statistic 0.738 vs 0.661, P < .001) where it identified more features predictive of graft loss (% luminal stenosis and % mesangial expansion). Using 5-year renal allograft surveillance biopsies, CAM-based models predict graft loss better than Banff models and might be developed into biomarkers for future clinical trials.

Modeling graft loss in patients with donor-specific antibody at baseline using the Birmingham-Mayo (BirMay) predictor: Implications for clinical trials.

Predicting which renal allografts will fail and the likely cause of failure is important in clinical trial design to either enrich patient populations to be or as surrogate efficacy endpoints for trials aimed at improving long-term graft survival. This study tests our previous Birmingham-Mayo model (termed the BirMay Predictor) developed in a low-risk kidney transplant population in order to predict the outcome of patients with donor specific alloantibody (DSA) at the time of transplantation and identify new factors to improve graft loss prediction in DSA+ patients. We wanted define ways to enrich the population for future therapeutic intervention trials. The discovery set included 147 patients from Mayo Cohort and the validation set included 111 patients from the Paris Cohort-all of whom had DSA at the time of transplantation. The BirMay predictor performed well predicting 5-year outcome well in DSA+ patients (Mayo C statistic = 0.784 and Paris C statistic = 0.860). Developing a new model did not improve on this performance. A high negative predictive value of greater than 90% in both cohorts excluded allografts not destined to fail within 5 years. We conclude that graft-survival models including histology predict graft loss well, both in DSA+ cohorts as well as DSA- patients.

Managing highly sensitized renal transplant candidates in the era of kidney paired donation and the new kidney allocation system: Is there still a role for desensitization?

Kidney paired donation (KPD) and the new kidney allocation system (KAS) in the United States have led to improved transplantation rates for highly sensitized candidates. We aimed to assess the potential need for other approaches to improve the transplantation rate of highly sensitized candidates such as desensitization. Using the UNOS STAR file, we analyzed transplant rates in a prevalent active waiting-list cohort as of June 1, 2016, followed for 1 year. The overall transplantation rate was 18.9% (11 129/58769). However, only 9.7% (213/2204) of candidates with a calculated panel reactive antibody ≥99.9% received a transplant, and highly sensitized candidates were less likely to receive a living donor transplant. Among candidates with a CPRA ≥ 99.5% (ie. 100%), only 2.5% of transplants were from living donors (13 total, 7 from KPD). Nearly 4 years after KAS (6/30/2018), 1791 actively wait-listed candidates had a CPRA of ≥99.9% and 34.6% (620/1791) of these had ≥5 years of waiting time. Thus, despite KPD and KAS, many sensitized candidates have not been transplanted even with prolonged waiting time. We conclude that candidates with a CPRA ≥ 99.9% and sensitized candidates with an incompatible living donor and prolonged waiting time may benefit from desensitization to improve their ability to receive a transplant.

Laser multiphoton ionization of tetrakis(dimethylamino)ethylene.

The tetrakis(dimethylamino)ethylene (TDAE) molecule possesses the lowest known molecular ionization potential (<5.4 eV) and exhibits an intense Rydberg series between the first and second ionization limit (∼14 eV). The ionization of TDAE using multiphoton ionization photoelectron spectroscopy was carried out using laser light at a variety of wavelengths with a hemispherical energy analyzer. Interestingly, photoelectron signal due to direct two-photon ionization was not seen, rather ionization from a fluorescent charge-transfer state located ∼2.5 eV below the ionization limit was evident and in general agreement with a previous study. In addition, a second intense peak exists corresponding to thermal energy electrons. Measurements of the angular distribution for the electrons due to photoionization from the intermediate state are peaked along the electric field vector of the laser and the thermal electrons direction is independent of this angle. From this, we propose that the thermal peak is most likely due to thermionic emission initiated through excitation of a known long-lived Rydberg state at ∼6.5 eV. Alternately, we speculate that excitation leading to thermionic emission could result from a "collective" excitation mechanism.

Outcomes of Kidney Transplantation in Patients That Underwent Bariatric Surgery: A Systematic Review and Meta-analysis.

The impact of bariatric surgery (BS) on kidney transplantation (KT) outcomes in patients with obesity remains controversial. We systematically searched MEDLINE, EMBASE, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials for studies reporting outcomes of KT recipients that underwent prior BS. Common/random effects meta-analyses were performed to obtain summary ratios of the postoperative outcomes. Eighteen eligible studies involving 315 patients were identified. Sleeve gastrectomy was the most common BS type (65.7%) followed by Roux-en-Y gastric bypass (27.6%) and gastric banding (4.4%). Across studies that provided the data, the %excess weight loss from BS to KT was 62.79% (95% confidence interval [CI], 52.01-73.56; range, 46.2%-80.3%). The rates of delayed graft function and acute rejection were 16% (95% CI, 7%-28%) and 16% (95% CI, 11%-23%) in 14 and 11 studies that provided this data, respectively. The rates of wound, urinary, and vascular complications following KT were 5% (95% CI, 0%-13%),19% (95% CI, 2%-42%), and 2% (95% CI, 0%-5%), in 12, 9, and 11 studies that provided this data, respectively. Follow-up time after KT was reported in 11 studies (61.1%) and ranged from 16 mo to >5 y. Graft loss was reported in 14 studies with an average of 3% (95% CI, 1%-6%). Four studies that included a comparator group of patients with obesity who did not undergo BS before KT showed comparable outcomes between the groups. We conclude that currently there is a paucity of robust evidence to suggest that pretransplant BS has a major effect on post-KT outcomes. High-quality studies are needed to fully evaluate the impact of BS on KT outcomes.

Increased Pretransplant Inflammatory Biomarkers Predict Death With Function After Kidney Transplantation.

BACKGROUND: Chronic systemic inflammation is associated with mortality in patients with chronic kidney disease, cardiovascular disease, and diabetes. The goal of this study was to examine the relationship between pretransplant inflammatory biomarkers (growth differentiation factor-15 [GDF-15], interleukin-6 [IL-6], soluble tumor necrosis factor receptor-1, monokine induced by gamma interferon/chemokine [C-X-C motif] ligand 9 [MIG/CXCL9], monocyte chemoattractant protein-1, soluble FAS, tumor necrosis factor-α, interleukin-15, and interleukin-1ß) and death with function (DWF) after kidney transplantation (KT). METHODS: We retrospectively measured inflammatory biomarker levels in serum collected up to 1 y before KT (time from blood draw to KT was 130 ±â€…110 d) in recipients transplanted between January 2006 and December 2018. Kaplan-Meier estimation, Cox regression, and Gradient Boosting Machine modeling were used to examine the relationship between inflammatory biomarkers and DWF. RESULTS: Our cohort consisted of 1595 KT recipients, of whom 62.9% were male and 83.2% were non-Hispanic White. Over a mean follow-up of 7.4 ±â€…3.9 y, 21.2% of patients (n = 338) experienced DWF. Patients with the highest quartile levels of GDF-15 (>4766 pg/mL), IL-6 (>6.11 pg/mL), and MIG/CXCL9 (> 5835 pg/mL) had increased rates of DWF, and each predicted mortality independently of the others. When adjusted for clinical factors (age, diabetes, etc), the highest quartile levels of GDF-15 and IL-6 remained independently associated with DWF. Adding inflammatory markers to a clinical Cox model improved the C-statistic for DWF from 0.727 to 0.762 using a Gradient Boosting Machine modeling approach. CONCLUSIONS: These findings suggest that pre-KT serum concentrations of GDF-15, IL-6, and MIG/CXCL9 may help to risk stratify and manage patients undergoing KT and suggests that chronic inflammation may play a role in mortality in KT recipients.

Mesangial Expansion by Morphometry at 5 y After Kidney Transplantation: Incidence, Risk Factors, and Association With Graft Loss.

Background: Mesangial expansion (ME) is an understudied histologic lesion in renal allografts. The current Banff mm score is not reproducible and may miss important ME features. The study aimed to improve the quantification of ME using morphometry, assess changes over time, and determine its association with allograft loss. Methods: We studied ME in 1-y and 5-y surveillance biopsies in 835 kidney transplants performed between January 2000 and December 2013. ME was assessed using the Banff mm score by a central pathologist and by morphometry. We derived 3 different morphometric measures: (1) %ME mm (%glomeruli with ME in ≥2 lobules, like Banff mm); (2) %MEany (%glomeruli with any ME lesion); and (3) %ME area (sum of all ME areas/all glomerular tuft areas). Unadjusted and adjusted Cox models assessed the risk of death-censored allograft loss. Results: From 1- to 5-y biopsies, the mean Banff mm score increased from 0.18 to 0.34, whereas %ME mm increased from 2.5% to 13.3%. Banff mm score had modest correlations with morphometric ME measures. Moderate-severe %ME mm was present in 20.1% of 5-y biopsies, whereas only 6.6% of Banff mm scores were. In general, higher ME on both 1- and 5-y biopsies was associated with a deceased donor, older recipient age, recipient diabetes/obesity (present in >50% of severely affected biopsies), higher hemoglobin A1c at 5 y posttransplant, and recurrent kidney disease. Higher ME on 5-y biopsies was associated with delayed graft function. A higher Banff mm score at 1-y biopsy and morphometry ME measures at 5-y biopsy were associated with rejection during the first year posttransplant. Morphometric ME measures were associated with allograft loss independent of Banff scores and all clinical characteristics, including kidney function and recurrent disease. The model with %MEany had the highest c-statistic (0.872). Conclusions: Banff mm score underestimates the pervasiveness of ME in 5-y biopsies. ME is common and associated with alloimmune and nonalloimmune causes of graft loss.

Cardiac magnetic resonance imaging in heart transplant recipients with biopsy-negative graft dysfunction.

AIMS: Graft dysfunction (GD) after heart transplantation (HTx) can develop without evidence of cell- or antibody-mediated rejection. Cardiac magnetic resonance imaging (CMR) has an evolving role in detecting rejection; however, its role in biopsy-negative GD has not been described. This study examines CMR findings, evaluates outcomes based on CMR results, and seeks to identify the possibility of rejection missed through endomyocardial biopsy by using CMR in HTx recipients with biopsy-negative GD. METHODS AND RESULTS: HTx recipients with GD [defined as a decrease in left ventricular ejection fraction (LVEF) by >5% and LVEF < 50%] in the absence of rejection by biopsy or allograft vasculopathy and who underwent CMR were included in the study. The primary outcome was a composite of all-cause mortality, re-transplantation, or persistent LVEF < 50%. Overall, 34 HTx recipients developed biopsy-negative GD and underwent CMR. Left ventricular late gadolinium enhancement (LGE) on CMR was observed in 16 patients with two distinct patterns: diffuse epicardial (n = 13) and patchy (n = 3) patterns. Patients with LGE developed GD later after HTx [4 (1.4-6.8) vs. 0.8 (0.3-1.2) years, P < 0.001], were more often symptomatic (88% vs. 56%, P = 0.06), and had greater haemodynamic derangement (pulmonary capillary wedge pressure: 19 ± 7 vs. 13 ± 3 mmHg, P = 0.002) as compared with those without LGE. No significant difference was observed in the primary composite outcome between patients with LGE and those without LGE (50% vs. 38% of patients with events, P = 0.515). During a median follow-up of 3.8 years, mean LVEF improved similarly in the LGE-negative (37-55%) and LGE-positive groups (32-55%) (P = 0.16). CONCLUSIONS: Biopsy-negative GD occurs with and without LGE when assessed by CMR, indicative of possible rejection/inflammation occurring only in a subset of patients. Irrespective of LGE, LVEF improvement occurs in most GD patients, suggesting that other neurohormonal or immunomodulatory mechanisms may also contribute to GD development.

Weight Loss Surgery Increases Kidney Transplant Rates in Patients With Renal Failure and Obesity.

OBJECTIVE: To describe the outcomes of kidney transplant (KT) candidates with obesity undergoing sleeve gastrectomy (SG) to meet the criteria for KT. METHODS: Retrospective analysis was conducted of electronic medical records of KT candidates with obesity (body mass index >35 kg/m2) who underwent SG in our institution. Weight loss, adverse health events, and the listing and transplant rates were abstracted and compared with the nonsurgical cohort. RESULTS: The SG was performed in 54 patients; 50 patients did not have surgery. Baseline demographic characteristics were comparable at the time of evaluation. Mean body mass index ± SD of the SG group was 41.7±3.6 kg/m2 at baseline (vs 41.5±4.3 kg/m2 for nonsurgical controls); at 2 and 12 months after SG, it was 36.4±4.1 kg/m2 and 32.6±4.0 kg/m2 (P<.01 for both). In the median follow-up time of 15.5 months (interquartile range, 6.4 to 23.9 months), SG was followed by active listing (37/54 people), and 20 of 54 received KT during a median follow-up time of 20.9 months (interquartile range, 14.7 to 28.3 months) after SG. In contrast, 14 of 50 patients in the nonsurgical cohort were listed, and 5 received a KT (P<.01). Three patients (5.6%) experienced surgical complications. There was no difference in overall hospitalization rates and adverse health outcomes, but the SG cohort experienced a higher risk of clinically significant functional decline. CONCLUSION: In KT candidates with obesity, SG appears to be effective, with 37% of patients undergoing KT during the next 18 months (P<.01). Further research is needed to confirm and to improve the safety and efficacy of SG for patients with obesity seeking a KT.

Electrocardiography-based Artificial Intelligence Algorithms Aid in Prediction of Long-term Mortality After Kidney Transplantation.

BACKGROUND: Predicting long-term mortality postkidney transplantation (KT) using baseline clinical data presents significant challenges. This study aims to evaluate the predictive power of artificial intelligence (AI)-enabled analysis of preoperative electrocardiograms (ECGs) in forecasting long-term mortality following KT. METHODS: We analyzed preoperative ECGs from KT recipients at three Mayo Clinic sites (Minnesota, Florida, and Arizona) between January 1, 2006, and July 30, 2021. The study involved 6 validated AI algorithms, each trained to predict future development of atrial fibrillation, aortic stenosis, low ejection fraction, hypertrophic cardiomyopathy, amyloid heart disease, and biological age. These algorithms' outputs based on a single preoperative ECG were correlated with patient mortality data. RESULTS: Among 6504 KT recipients included in the study, 1764 (27.1%) died within a median follow-up of 5.7 y (interquartile range: 3.00-9.29 y). All AI-ECG algorithms were independently associated with long-term all-cause mortality (P < 0.001). Notably, few patients had a clinical cardiac diagnosis at the time of transplant, indicating that AI-ECG scores were predictive even in asymptomatic patients. When adjusted for multiple clinical factors such as recipient age, diabetes, and pretransplant dialysis, AI algorithms for atrial fibrillation and aortic stenosis remained independently associated with long-term mortality. These algorithms also improved the C-statistic for predicting overall (C = 0.74) and cardiac-related deaths (C = 0.751). CONCLUSIONS: The findings suggest that AI-enabled preoperative ECG analysis can be a valuable tool in predicting long-term mortality following KT and could aid in identifying patients who may benefit from enhanced cardiac monitoring because of increased risk.