C5b9 Deposition in Glomerular Capillaries Is Associated With Poor Kidney Allograft Survival in Antibody-Mediated Rejection

C4d deposition in peritubular capillaries (PTC) reflects complement activation in antibody-mediated rejection (ABMR) of kidney allograft. However, its association with allograft survival is controversial. We hypothesized that capillary deposition of C5b9—indicative of complement-mediated injury—is a severity marker of ABMR. This pilot study aimed to determine the frequency, location and prognostic impact of these deposits in ABMR. We retrospectively selected patients diagnosed with ABMR in two French transplantation centers from January 2005 to December 2014 and performed C4d and C5b9 staining by immunohistochemistry. Fifty-four patients were included. Median follow-up was 52.5 (34.25–73.5) months. Thirteen patients (24%) had C5b9 deposits along glomerular capillaries (GC). Among these, seven (54%) had a global and diffuse staining pattern. Twelve of the C5b9+ patients also had deposition of C4d in GC and PTC. C4d deposits along GC and PTC were not associated with death-censored allograft survival (p = 0.42 and 0.69, respectively). However, death-censored allograft survival was significantly lower in patients with global and diffuse deposition of C5b9 in GC than those with a segmental pattern or no deposition (median survival after ABMR diagnosis, 6 months, 40.5 months and 44 months, respectively; p = 0.015). Double contour of glomerular basement membrane was diagnosed earlier after transplantation in C5b9+ ABMR than in C5b9– ABMR (median time after transplantation, 28 vs. 85 months; p = 0.058). In conclusion, we identified a new pattern of C5b9+ ABMR, associated with early onset of glomerular basement membrane duplication and poor allograft survival. Complement inhibitors might be a therapeutic option for this subgroup of patients

An automated histological classification system for precision diagnostics of kidney allografts

For three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has become complex over time with the integration of multimodal data and rules, leading to misclassifications that can have deleterious therapeutic consequences for patients. To improve diagnosis, we developed a decision-support system, based on an algorithm covering all classification rules and diagnostic scenarios, that automatically assigns kidney allograft diagnoses. We then tested its ability to reclassify rejection diagnoses for adult and pediatric kidney transplant recipients in three international multicentric cohorts and two large prospective clinical trials, including 4,409 biopsies from 3,054 patients (62.05% male and 37.95% female) followed in 20 transplant referral centers in Europe and North America. In the adult kidney transplant population, the Banff Automation System reclassified 83 out of 279 (29.75%) antibody-mediated rejection cases and 57 out of 105 (54.29%) T cell-mediated rejection cases, whereas 237 out of 3,239 (7.32%) biopsies diagnosed as non-rejection by pathologists were reclassified as rejection. In the pediatric population, the reclassification rates were 8 out of 26 (30.77%) for antibody-mediated rejection and 12 out of 39 (30.77%) for T cell-mediated rejection. Finally, we found that reclassification of the initial diagnoses by the Banff Automation System was associated with an improved risk stratification of long-term allograft outcomes. This study demonstrates the potential of an automated histological classification to improve transplant patient care by correcting diagnostic errors and standardizing allograft rejection diagnoses.ClinicalTrials.gov registration: NCT05306795

COVID-19-related medical research: a meta-research and critical appraisal

International audienceBackground: Since the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-reviewed original articles. Methods: The data sources were Pubmed, Cochrane COVID-19 register study, arXiv, medRxiv and bioRxiv, from 01/ 11/2019 to 01/05/2020. Peer-reviewed and preprints publications related to COVID-19 were included, written in English or Chinese. No limitations were placed on study design. Reviewers screened and categorized studies according to i) publication type, ii) country of publication, and iii) topics covered. Original articles were critically appraised using validated quality assessment tools. Results: Among the 11,452 publications identified, 10,516 met the inclusion criteria, among which 7468 (71.0%) were peer-reviewed articles. Among these, 4190 publications (56.1%) did not include any data or analytics (comprising expert opinion pieces). Overall, the most represented topics were infectious disease (n = 2326, 22.1%), epidemiology (n = 1802, 17.1%), and global health (n = 1602, 15.2%). The top five publishing countries were China (25.8%), United States (22.3%), United Kingdom (8.8%), Italy (8.1%) and India (3.4%). The dynamic of publication showed that the exponential growth of COVID-19 peer-reviewed articles was mainly driven by publications without original data (mean 261.5 articles ± 51.1 per week) as compared with original articles (mean of 69.3 ± 22.3 articles per week). Original articles including patient data accounted for 713 (9.5%) of peer-reviewed studies. A total of 576 original articles (80.8%) showed intermediate to high risk of bias. Last, except for simulation studies that mainly used large-scale open data, the median number of patients enrolled was of 102 (IQR = 37-337). Conclusions: Since the beginning of the COVID-19 pandemic, the majority of research is composed by publications without original data. Peer-reviewed original articles with data showed a high risk of bias and included a limited number of patients. Together, these findings underscore the urgent need to strike a balance between the velocity and quality of research, and to cautiously consider medical information and clinical applicability in a pressing, pandemic context

Impact of the COVID-19 pandemic on publication dynamics and non-COVID-19 research production

International audienceBackground: The COVID-19 pandemic has severely affected health systems and medical research worldwide but its impact on the global publication dynamics and non-COVID-19 research has not been measured. We hypothesized that the COVID-19 pandemic may have impacted the scientific production of non-COVID-19 research. Methods: We conducted a comprehensive meta-research on studies (original articles, research letters and case reports) published between 01/01/2019 and 01/01/2021 in 10 high-impact medical and infectious disease journal

Subclinical rejection-free diagnostic after kidney transplantation using blood gene expression

International audienceWe previously established a six-gene-based blood score associated with operational tolerance in kidney transplantation which was decreased in patients developing anti-HLA donor-specific antibodies (DSA). Herein, we aimed to confirm that this score is associated with immunological events and risk of rejection. We measured this using quantitative PCR (qPCR) and NanoString methods from an independent multicenter cohort of 588 kidney transplant recipients with paired blood samples and biopsies at one year after transplantation validating its association with pre-existing and de novo DSA. From 441 patients with protocol biopsy, there was a significant decrease of the score of tolerance in 45 patients with biopsy-proven subclinical rejection (SCR), a major threat associated with pejorative allograft outcomes that prompted an SCR score refinement. This refinement used only two genes, AKR1C3 and TCL1A, and four clinical parameters (previous experience of rejection, previous transplantation, sex of recipient and tacrolimus uptake). This refined SCR score was able to identify patients unlikely to develop SCR with a C-statistic of 0.864 and a negative predictive value of 98.3%. The SCR score was validated in an external laboratory, with two methods (qPCR and NanoString), and on 447 patients from an independent and multicenter cohort. Moreover, this score allowed reclassifying patients with discrepancies between the DSA presence and the histological diagnosis of antibody mediated rejection unlike kidney function. Thus, our refined SCR score could improve detection of SCR for closer and noninvasive monitoring, allowing early treatment of SCR lesions notably for patients DSA-positive and during lowering of immunosuppressive treatment

Absence of Mortality Differences Between the First and Second COVID-19 Waves in Kidney Transplant Recipients

International audienceSARS-CoV-2 pandemic evolved in two consecutive waves over 2020. Improvements in the management of COVID-19 led to a reduction of mortality rates in hospitalized patients during the second wave. Whether this progress also benefited to kidney transplant recipients (KTR), a population particularly vulnerable to severe COVID-19, remained unclear. In France, 957 KTR were hospitalized for COVID-19 in 2020 and their data were prospectively collected in the French SOT COVID registry. The presentation, management, and outcomes of the 359 KTR diagnosed during the 1st wave were compared to those of the 598 of the 2nd wave. Baseline comorbidities were similar between KTR of the 2 waves. Maintenance immunosuppression was reduced in most patients but withdrawal of antimetabolite (73.7% vs 58.4%, p<0.001) or CNI (32.1% vs 16.6%, p<0.001) was less frequent during the 2nd wave. Hydroxychloroquine and azithromycin that were commonly used during the 1st wave (21.7% and 30.9%, respectively) were almost abandoned during the 2nd. In contrast, the use of high dose corticosteroids doubled (19.5% vs. 41.6%, p<0.001). Despite these changing trends in COVID-19 management, 60-day mortality was not statistically different between the 2 waves (25.3% vs. 23.9%; Log Rank, p=0.48) and COVID-19 hospitalization period was not associated with death due to COVID in multivariate analysis (HR 0.89, 95% CI 0.67 - 1.17, p = 0.4). We conclude that changing of therapeutic trends during 2020 did not reduce COVID-19 related mortality in KTR. Our data indirectly support the importance of vaccination and monoclonal neutralizing anti-SARS-CoV-2 antibodies to protect KTR from severe COVID-19

An automated histological classification system for precision diagnostics of kidney allografts

International audienceFor three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has become complex over time with the integration of multimodal data and rules, leading to misclassifications that can have deleterious therapeutic consequences for patients. To improve diagnosis, we developed a decision-support system, based on an algorithm covering all classification rules and diagnostic scenarios, that automatically assigns kidney allograft diagnoses. We then tested its ability to reclassify rejection diagnoses for adult and pediatric kidney transplant recipients in three international multicentric cohorts and two large prospective clinical trials, including 4,409 biopsies from 3,054 patients (62.05% male and 37.95% female) followed in 20 transplant referral centers in Europe and North America. In the adult kidney transplant population, the Banff Automation System reclassified 83 out of 279 (29.75%) antibody-mediated rejection cases and 57 out of 105 (54.29%) T cell-mediated rejection cases, whereas 237 out of 3,239 (7.32%) biopsies diagnosed as non-rejection by pathologists were reclassified as rejection. In the pediatric population, the reclassification rates were 8 out of 26 (30.77%) for antibody-mediated rejection and 12 out of 39 (30.77%) for T cell-mediated rejection. Finally, we found that reclassification of the initial diagnoses by the Banff Automation System was associated with an improved risk stratification of long-term allograft outcomes. This study demonstrates the potential of an automated histological classification to improve transplant patient care by correcting diagnostic errors and standardizing allograft rejection diagnose