Improving the decision to switch from first- to second-line therapy in multiple sclerosis: A dynamic scoring system.

BACKGROUND: In relapsing-remitting multiple sclerosis (RRMS), early identification of suboptimal responders can prevent disability progression. OBJECTIVE: We aimed to develop and validate a dynamic score to guide the early decision to switch from first- to second-line therapy. METHODS: Using time-dependent propensity scores (PS) from a French cohort of 12,823 patients with RRMS, we constructed one training and two validation PS-matched cohorts to compare the switched patients to second-line treatment and the maintained patients. We used a frailty Cox model for predicting individual hazard ratios (iHRs). RESULTS: From the validation PS-matched cohort of 348 independent patients with iHR ⩽ 0.69, we reported the 5-year relapse-free survival at 0.14 (95% confidence interval (CI) 0.09-0.22) for the waiting group and 0.40 (95% CI 0.32-0.51) for the switched group. From the validation PS-matched cohort of 518 independent patients with iHR > 0.69, these values were 0.37 (95% CI 0.30-0.46) and 0.44 (95% CI 0.37-0.52), respectively. CONCLUSIONS: By using the proposed dynamic score, we estimated that at least one-third of patients could benefit from an earlier switch to prevent relapse.

Impact of the Kidney Transplantation Moratorium in France Because of the COVID-19 Pandemic: A Cohort-based Study.

BACKGROUND: The COVID-19 pandemic has resulted in worldwide kidney transplantation (KT) moratoriums. The impacts of these moratoriums on the life expectancy of KT candidates remain unclear. METHODS: We simulated the evolution of several French candidate populations for KT using a multistate semi-Markovian approach and according to moratorium durations ranging from 0 to 24 mo. The transition rates were modeled from the 63 927 French patients who began dialysis or were registered on the waiting list for KT between 2011 and 2019. RESULTS: Among the 8350 patients active on the waiting list at the time of the French KT moratorium decided on March 16, 2020, for 2.5 mo, we predicted 4.0 additional months (confidence interval [CI], 2.8-5.0) on the waiting list and 42 additional deaths (CI, -70 to 150) up to March 16, 2030, compared with the scenario without moratorium. In this population, we reported a significant impact for a 9-mo moratorium duration: 135 attributable deaths (CI, 31-257) up to March 16, 2030. Patients who became active on the list after March 2020 were less impacted; there was a significant impact for an 18-mo moratorium (175 additional deaths [CI, 21-359]) in the 10 862 prevalent end-stage renal disease patients on March 16, 2020 and for a 24-mo moratorium (189 additional deaths [CI, 10-367]) in the 16 355 incident end-stage renal disease patients after this date. CONCLUSION: The temporary moratorium of KT during a COVID-19 peak represents a sustainable decision to free up hospitals' resources if the moratorium does not exceed a prolonged period.

Early use of barbiturates is associated with increased mortality in traumatic brain injury patients from a propensity score-based analysis of a prospective cohort.

Barbiturates are proposed as a second/third line treatment for intracranial hypertension in traumatic brain injury (TBI) patients, but the literature remains uncertain regarding their benefit/risk balance. We aimed to evaluate the impact of barbiturates therapy in TBI patients with early intracranial hypertension on the intensive care unit (ICU) survival, the occurrence of ventilator-associated pneumonia (VAP), and the patient's functional status at three months. We used the French AtlanREA prospective cohort of trauma patients. Using a propensity score-based methodology (inverse probability of treatment weighting), we compared patients having received barbiturates within the first 24 hours of admission (barbiturates group) and those who did not (control group). We used cause-specific Cox models for ICU survival and risk of VAP, and logistic regression for the 3-month Glasgow Outcome Scale (GOS) evaluation. Among the 1396 patients with severe trauma, 383 had intracranial hypertension on admission and were analyzed. Among them, 96 (25.1%) received barbiturates. The early use of barbiturates was significantly associated with increased ICU mortality (HR = 1.85, 95%CI 1.03-3.33). However, barbiturates treatment was not significantly associated with VAP (HR = 1.02, 95%CI 0.75-1.41) or 3-month GOS (OR = 1.67, 95%CI 0.84-3.33). Regarding the absence of relevant clinical trials, our results suggest that each early prescription of barbiturates requires a careful assessment of the benefit/risk ratio.

Impact of kidney transplantation in obese candidates: a time-dependent propensity score matching study.

BACKGROUND: Although kidney transplantation (KT) is considered the best treatment for end-stage renal disease (ESRD), there are concerns about its benefit in the obese population because of the increased incidence of post-transplant adverse events. We compared patients who underwent KT versus patients awaiting KT on dialysis. METHODS: We estimated the life expectancy [restricted mean survival time (RMST)] for a 10-year follow-up by matching on time-dependent propensity scores. The primary outcome was time to death. RESULTS: In patients with a body mass index (BMI) ≥30 kg/m2 (n = 2155 patients per arm), the RMST was 8.23 years [95% confidence interval (CI) 8.05-8.40] in the KT group versus 8.00 years (95% CI 7.82-8.18) in the awaiting KT group, a difference of 2.71 months (95% CI -0.19-5.63). In patients with a BMI ≥35 kg/m2 (n = 212 patients per arm), we reported no significant difference [8.56 years (95% CI 7.96-9.08) versus 8.66 (95% CI 8.10-9.17)]. Hence we deduced that KT in patients with a BMI between 30 and 35 kg/m2 was beneficial in terms of life expectancy. CONCLUSION: Regarding the organ shortage, KT may be questionable for those with a BMI ≥35 kg/m2. These results do not mean that a BMI ≥35 kg/m2 should be a barrier to KT, but it should be accounted for in allocation systems to better assign grafts and maximize the overall life expectancy of ESRD patients.

Causal inference in case of near-violation of positivity: comparison of methods.

In causal studies, the near-violation of the positivity may occur by chance, because of sample-to-sample fluctuation despite the theoretical veracity of the positivity assumption in the population. It may mostly happen when the exposure prevalence is low or when the sample size is small. We aimed to compare the robustness of g-computation (GC), inverse probability weighting (IPW), truncated IPW, targeted maximum likelihood estimation (TMLE), and truncated TMLE in this situation, using simulations and one real application. We also tested different extrapolation situations for the sub-group with a positivity violation. The results illustrated that the near-violation of the positivity impacted all methods. We demonstrated the robustness of GC and TMLE-based methods. Truncation helped in limiting the bias in near-violation situations, but at the cost of bias in normal conditions. The application illustrated the variability of the results between the methods and the importance of choosing the most appropriate one. In conclusion, compared to propensity score-based methods, methods based on outcome regression should be preferred when suspecting near-violation of the positivity assumption.

Association Between Deceased Donor Acute Kidney Injury Assessed Using Baseline Serum Creatinine Back-Estimation and Graft Survival: Results From the French National CRISTAL Registry.

RATIONALE & OBJECTIVE: Deceased donor acute kidney injury (AKI) frequently leads to kidney discards, but its impact on long-term graft survival in kidney transplant recipients remains unclear. We investigated the association between deceased donor AKI assessed using back-estimation of baseline serum creatinine (Scr) and graft survival. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: Adult patients represented within the French CRISTAL registry who received a single kidney allograft from brain-dead deceased donors between January 2006 and December 2017. EXPOSURE: A back-estimated Scr baseline value was derived for an assumed glomerular filtration rate at 75mL/min/1.73m2, using the MDRD Study equation. A refined classification system for donor AKI was implemented as follows: no AKI, undetermined AKI/chronic kidney disease (CKD), recovery from AKI, and ongoing AKI. OUTCOME: Death-censored graft survival. ANALYTICAL APPROACH: Multivariable Cox models using a robust variance estimator for paired kidneys from the same donor. RESULTS: We classified 26,786 recipients as follows: no AKI (n=19,276); undetermined AKI/CKD (n=1,745); recovery from AKI (n=2,392); and ongoing AKI (n=3,373). We observed 4,458 kidney graft losses during a median follow-up period of 5.7 years. Compared with no AKI, ongoing AKI was associated with an increased risk of graft failure (hazard ratio [HR], 1.24 [95% CI, 1.13-1.35]). The HRs for graft failure in the undetermined AKI/CKD and recovery from AKI groups (1.22 [95% CI, 1.07-1.38] and 1.18 [95% CI, 1.06-1.31], respectively) were similar to those observed in the ongoing AKI group. The adverse effect of deceased donor AKI was no longer evident when relying either on the admission or the lowest Scr throughout the procurement procedure as baseline Scr. LIMITATIONS: No measurement of urine output in donors. CONCLUSIONS: Deceased donor ongoing AKI, undetermined AKI/CKD, and recovery from AKI according to back-estimated baseline Scr are associated with decreased graft survival. The definition of baseline Scr as the first value measured on admission would have led to a misclassification bias and erroneous estimates.

G-computation and doubly robust standardisation for continuous-time data: A comparison with inverse probability weighting.

In time-to-event settings, g-computation and doubly robust estimators are based on discrete-time data. However, many biological processes are evolving continuously over time. In this paper, we extend the g-computation and the doubly robust standardisation procedures to a continuous-time context. We compare their performance to the well-known inverse-probability-weighting estimator for the estimation of the hazard ratio and restricted mean survival times difference, using a simulation study. Under a correct model specification, all methods are unbiased, but g-computation and the doubly robust standardisation are more efficient than inverse-probability-weighting. We also analyse two real-world datasets to illustrate the practical implementation of these approaches. We have updated the R package RISCA to facilitate the use of these methods and their dissemination.

Methodological quality of multivariate prognostic models for intracranial haemorrhages in intensive care units: a systematic review.

OBJECTIVES: Patients with severe spontaneous intracranial haemorrhages, managed in intensive care units, face ethical issues regarding the difficulty of anticipating their recovery. Prognostic tools help clinicians in counselling patients and relatives and guide therapeutic decisions. We aimed to methodologically assess prognostic tools for functional outcomes in severe spontaneous intracranial haemorrhages. DATA SOURCES: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations, we conducted a systematic review querying Medline, Embase, Web of Science, and the Cochrane in January 2020. STUDY SELECTION: We included development or validation of multivariate prognostic models for severe intracerebral or subarachnoid haemorrhage. DATA EXTRACTION: We evaluated the articles following the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies and Transparent Reporting of multivariable prediction model for Individual Prognosis Or Diagnosis statements to assess the tools' methodological reporting. RESULTS: Of the 6149 references retrieved, we identified 85 articles eligible. We discarded 43 articles due to the absence of prognostic performance or predictor selection. Among the 42 articles included, 22 did not validate models, 6 developed and validated models and 14 only externally validated models. When adding 11 articles comparing developed models to existing ones, 25 articles externally validated models. We identified methodological pitfalls, notably the lack of adequate validations or insufficient performance levels. We finally retained three scores predicting mortality and unfavourable outcomes: the IntraCerebral Haemorrhages (ICH) score and the max-ICH score for intracerebral haemorrhages, the SubArachnoid Haemorrhage International Trialists score for subarachnoid haemorrhages. CONCLUSIONS: Although prognostic studies on intracranial haemorrhages abound in the literature, they lack methodological robustness or show incomplete reporting. Rather than developing new scores, future authors should focus on externally validating and updating existing scores with large and recent cohorts.

Carotid versus femoral access for transcatheter aortic valve replacement: comparable results in the current era.

OBJECTIVES: The carotid approach for transcatheter aortic valve replacement (TAVR) has been shown to be feasible and safe. The goal of this study was to compare the 30-day outcomes of trans-carotid (TC) and transfemoral (TF) TAVR. METHODS: This retrospective study enrolled 500 consecutive patients treated by TC-TAVR (n = 100) or TF-TAVR (n = 400) with percutaneous closure between January 2018 and January 2020 at the Nantes University Hospital. The primary end-point was the occurrence of cardiovascular death and cerebrovascular events at 30 days. RESULTS: The mean age was 79.9 ± 8.1 in the TC group and 81.3 ± 6.9 (P = 0.069) in the TF group. The TC group had more men (69% vs 50.5%; P = 0.001) and more patients with peripheral vascular disease (86% vs 14.8%; P < 0.0001). Cardiac characteristics were similar between the groups, and the EuroSCORE II was 3.8 ± 2.6% vs 4.6 ± 6.0%, respectively (P = 0.443). The 30-day mortality was 2% in the TC group versus 1% in the TF group (P = 0.345). TC-TAVR was not associated with an increased risk of stroke (2% vs 2.5%; P = 0.999) or major vascular complications (2% vs 4%; P = 0.548). More permanent pacemakers were implanted in the TF group (14.9% vs 5.6%; P = 0.015), and no moderate or severe aortic regurgitation was observed in the TC group (0 vs 3.3%; P = 0.08). TC-TAVR was not associated with an increased risk of mortality or stroke at 30 days (odds ratio 1.32; 95% confidence interval 0.42-4.21; P = 0.63) in the multivariable analysis. CONCLUSIONS: No statistically significant differences between TC-TAVR and TF-TAVR were observed; therefore, TC-TAVR should be the first alternative in patients with anatomical contraindications to the femoral route.

Covariates adjustment questioned conclusions of predictive analyses: an illustration with the Kidney Donor Risk Index.

OBJECTIVES: We aimed to illustrate that considering covariates can lead to meaningful interpretation of the discriminative capacities of a prognostic marker. For this, we evaluated the ability of the Kidney Donor Risk Index (KDRI) to discriminate kidney graft failure risk. STUDY DESIGN AND SETTING: From 4114 French patients, we estimated the adjusted area under the time-dependent ROC curve by standardizing the marker and weighting the observations. By weighting the contributions, we also studied the impact of KDRI-based transplantations on the patient and graft survival. RESULTS: The covariate-adjusted AUC varied from 55% (95% confidence interval [CI]: 51-60%) for a prognostic up to 1 year post-transplantation to 56% (95% CI: 52-59%) up to 7 years. The Restricted Mean Survival Time (RMST) was 6.44 years for high-quality graft recipients (95% CI: 6.30-6.56) and would have been 6.31 years (95% CI: 6.13-6.46) if they had medium-quality transplants. The RMST was 5.10 years for low-quality graft recipients (95% CI: 4.90-5.31) and would have been 5.52 years (95% CI: 5.17-5.83) if they had medium-quality transplants. CONCLUSION: We demonstrated that the KDRI discriminative capacities were mainly explained by the recipient characteristics. We also showed that counterfactual estimations, often used in causal studies, are also interesting in predictive studies, especially regarding the new available methods.

G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes.

In clinical research, there is a growing interest in the use of propensity score-based methods to estimate causal effects. G-computation is an alternative because of its high statistical power. Machine learning is also increasingly used because of its possible robustness to model misspecification. In this paper, we aimed to propose an approach that combines machine learning and G-computation when both the outcome and the exposure status are binary and is able to deal with small samples. We evaluated the performances of several methods, including penalized logistic regressions, a neural network, a support vector machine, boosted classification and regression trees, and a super learner through simulations. We proposed six different scenarios characterised by various sample sizes, numbers of covariates and relationships between covariates, exposure statuses, and outcomes. We have also illustrated the application of these methods, in which they were used to estimate the efficacy of barbiturates prescribed during the first 24 h of an episode of intracranial hypertension. In the context of GC, for estimating the individual outcome probabilities in two counterfactual worlds, we reported that the super learner tended to outperform the other approaches in terms of both bias and variance, especially for small sample sizes. The support vector machine performed well, but its mean bias was slightly higher than that of the super learner. In the investigated scenarios, G-computation associated with the super learner was a performant method for drawing causal inferences, even from small sample sizes.

External Validation of the DynPG for Kidney Transplant Recipients.

BACKGROUND: In kidney transplantation, dynamic prediction of patient and kidney graft survival (DynPG) may help to promote therapeutic alliance by delivering personalized evidence-based information about long-term graft survival for kidney transplant recipients. The objective of the current study is to externally validate the DynPG. METHODS: Based on 6 baseline variables, the DynPG can be updated with any new serum creatinine measure available during the follow-up. From an external validation sample of 1637 kidney recipients with a functioning graft at 1-year posttransplantation from 2 European transplantation centers, we assessed the prognostic performance of the DynPG. RESULTS: As one can expect from an external validation sample, differences in several recipient, donor, and transplantation characteristics compared with the learning sample were observed. Patients were mainly transplanted from deceased donors (91.6% versus 84.8%; P < 0.01), were less immunized against HLA class I (18.4% versus 32.7%; P < 0.01) and presented less comorbidities (62.2% for hypertension versus 82.7%, P < 0.01; 25.1% for cardiovascular disease versus 33.9%, P < 0.01). Despite these noteworthy differences, the area under the ROC curve varied from 0.70 (95% confidence interval [CI], 0.64-0.76) to 0.76 (95% CI, 0.64-0.88) for prediction times at 1 and 6 years posttransplantation respectively, and calibration plots revealed reasonably accurate predictions. CONCLUSIONS: We validated the prognostic capacities of the DynPG in terms of both discrimination and calibration. Our study showed the robustness of the DynPG for informing both the patient and the physician, and its transportability for a cohort presenting different features than the one used for the DynPG development.

Time-dependent lymphocyte count after transplantation is associated with higher risk of graft failure and death.

The transplantation field requires the identification of specific risk factors associated with the level of immunosuppression. Here, our aim was to analyze the association between the number of circulating lymphocytes, monitored routinely by complete blood cell counts during outpatient visits, and patient and graft survival. In total, 2,999 kidney or combined kidney-pancreas recipients transplanted between 2000 and 2016, from two University hospitals, were enrolled. We investigated the etiological relationship between time-dependent lymphocyte count beyond one year after transplantation and patient and graft survival, viral infection and cancer risk using time-dependent multivariate Cox models. Model 1 considered kidney function at one year and model 2 as time-dependent variable. At the time of inclusion (one year after transplantation), 584 patients (19.4%) had deep lymphopenia (under 750 /mm3) and 1,072 (35.7%) had a normal count (over 1,500 /mm3). A patient with deep lymphopenia at a given follow-up time had significantly higher risks of graft failure, death and viral infection than comparable patients with a normal lymphocyte count at the same time point. Thus, after the first year of transplantation, the occurrence of deep lymphopenia within a patient's follow-up is a risk factor for long-term graft failure, death and viral infection.

Clinical Trial Emulation by Matching Time-dependent Propensity Scores: The Example of Estimating Impact of Kidney Transplantation.

BACKGROUND: No study to our knowledge has examined the use of observational data to emulate a clinical trial whereby patients at the time of kidney transplant proposal are randomly assigned to an awaiting transplantation or transplantation group. The main methodologic issue is definition of the baseline for dialyzed patients assigned to awaiting transplantation, resulting in the inability to use common propensity score-based approaches. We aimed to use time-dependent propensity score to better appraise the benefit of transplantation. METHODS: We studied 23,231 patients included in the French registry and on a transplant waiting list from 2005 to 2016. The main outcome was time to death. By matching on time-dependent propensity score, we obtained 10,646 pairs of recipients (transplantation group) versus comparable patients remaining on dialysis (awaiting transplantation group). RESULTS: The baseline exposure, that is, pseudo-randomization, was matching time. Median follow-up time was 3.5 years. At 10 years' follow-up, the restricted mean survival time was 8.8 years [95% confidence interval (CI) = 8.7, 8.9] in the transplantation group versus 8.2 years (95% CI = 8.1, 8.3) in the awaiting transplantation group. The corresponding life expectancy gain was 6.8 months (95% CI = 5.5, 8.2), and this corresponded to one prevented death at 10 years for 13 transplantations. CONCLUSIONS: Our study has estimated the life expectancy gain due to kidney transplantation. It confirms transplantation as the best treatment for end-stage renal disease. Furthermore, we demonstrated that this simple method should also be considered for estimating marginal effects of time-dependent exposures.

Long-term effect of first-line injectable multiple sclerosis treatments: Input of a time-dependent propensity score.

PURPOSE: The long-term effect of beta-interferon and glatiramer acetate on multiple sclerosis (MS) disability progression has resulted in controversial results, probably due to a lack of appropriate control of biases as raised in observational studies. In particular, the time of the therapeutic decision is difficult to define when the controls are not treated. METHODS: This retrospective observational study was based on a series of patients from the MS expert center in Rennes, France. We used a time-dependent propensity score defined as the linear predictor of a Cox model estimating the hazard of being treated at each time from MS onset. The matching procedure resulted in two groups: patients matched as treated and as not yet treated. The restricted mean times (RMST) to reach a moderate level of disability or worsening of the disability were compared between the two groups in an intention-to-treat analysis. RESULTS: Of the 2383 patients included in the study, 556 were matched as treated. The matching procedure provided a good balance of both the time-fixed and the time-dependent covariates. A slight difference was observed for the time to reach a moderate level of disability, in favor of the "not yet treated" group (difference in the RMST: -0.62 [-0.91; -0.33]) while no difference was found in terms of worsening of the disability (-0.03 [-0.24; 0.33]). CONCLUSION: This unexpected result is probably due to unmeasured confounders. However, this time-dependent PS warrants consideration in long-term effectiveness studies.

Induction therapy in kidney transplant recipients: Description of the practices according to the calendar period from the French multicentric DIVAT cohort.

BACKGROUND: There is extensive literature with comparisons between Anti-Thymocyte Globulin (ATG) and Basiliximab (BSX) as induction therapy in kidney transplant recipients. The purpose of our benchmarking study was to describe the consequences in terms of practices in 6 transplantation centers of a French prospective cohort. METHODS: We included adult patients who received a first or second kidney graft between 2013 and 2019 (n = 4157). We used logistic regressions to identify characteristics associated with the use of ATG or BSX. RESULTS: Use of ATG between the centers ranged from 41% to 75%. We observed different factors associated with the treatment decision. Compared to a first transplant, performing a second graft was the only factor significantly associated with the choice of ATG in all centers. The AUC ranged from 0.67 to 0.91, indicating that the centers seemed to define their own rules. As a result, for patients with the same low immunological risk, the probability of receiving ATG varied from 7% to 36%. We stratified the analyses according to two periods, from 2013 to 2015 and from 2016 to 2019. A similar heterogeneity was observed, and in some cases ATG indications between the centers were inverted. CONCLUSIONS: The heterogeneity of induction therapy practices did not decrease in France, even if the reated literature is prolific. This illustrates the necessity to improve the literature by using meta-analyses of recent studies stratified by graft and patient profiles.

G-computation, propensity score-based methods, and targeted maximum likelihood estimator for causal inference with different covariates sets: a comparative simulation study.

Controlling for confounding bias is crucial in causal inference. Distinct methods are currently employed to mitigate the effects of confounding bias. Each requires the introduction of a set of covariates, which remains difficult to choose, especially regarding the different methods. We conduct a simulation study to compare the relative performance results obtained by using four different sets of covariates (those causing the outcome, those causing the treatment allocation, those causing both the outcome and the treatment allocation, and all the covariates) and four methods: g-computation, inverse probability of treatment weighting, full matching and targeted maximum likelihood estimator. Our simulations are in the context of a binary treatment, a binary outcome and baseline confounders. The simulations suggest that considering all the covariates causing the outcome led to the lowest bias and variance, particularly for g-computation. The consideration of all the covariates did not decrease the bias but significantly reduced the power. We apply these methods to two real-world examples that have clinical relevance, thereby illustrating the real-world importance of using these methods. We propose an R package RISCA to encourage the use of g-computation in causal inference.

Comparison of machine perfusion versus cold storage in kidney transplant recipients from expanded criteria donors: a cohort-based study.

BACKGROUND: Most studies comparing the efficacy of hypothermic machine perfusion (HMP) versus static cold storage (SCS) are based on short-term outcomes. We aimed to better evaluate the mid-term impact of HMP in patients receiving expanded criteria donor (ECD) kidneys. METHODS: The analyses were based on the French Données Informatisées et VAlidées en Transplantation (DIVAT) observational cohort. Patients aged ≥45 years transplanted for the first or second times from an ECD donor since 2010 were studied. Our study reported the graft and/or patient survivals and the incidence of acute rejection episode. The Cox models and the Kaplan-Meier estimators, weighted on the propensity score, were used to study the times-to-events. RESULTS: Among the 2019 included patients, 1073 were in the SCS group versus 946 in the HMP group. The mean life expectancy with functioning graft was 5.7 years [95% confidence interval (CI) 5.4-6.1] for the HMP cohort followed-up for 8 years post-transplantation versus 6.0 years (95% CI 5.7-6.2) for the SCS group. These mid-term results were comparable in the patients receiving grafts from donors aged ≥70 years and in the transplantations with cold ischaemia time ≥18 h. CONCLUSIONS: Our study challenges the utility of using HMP to improve mid-term patient and graft survival. Nevertheless, the improvement of the short-term outcomes is indisputable. It is necessary to continue technological innovations to obtain long-term results.

The weekend effect in kidney transplantation outcomes: a French cohort-based study.

Numerous studies have reported a weekend effect on outcomes for diseases treated at hospitals. No study has been conducted in France for kidney transplantation. We therefore performed a cohort-based study to evaluate whether outcomes of kidney transplant recipients display a weekend effect. Data were extracted from the French DIVAT cohort. Patients aged 18 years and older, transplanted with a single kidney from deceased donors between 2005 and 2017 were studied. Linear regression, logistic regression, and cause-specific Cox model were used. Among the 6652 studied patients, 4653 patients were transplanted during weekdays (69.9%) versus 1999 during weekends (30.1%). The only statistically significant difference was the percentage of patients with vascular surgical complication(s) at 30 days: 13.3% in the weekend group versus 16.2% in the weekday group 0.79 (95% CI: 0.68; 0.92). We did not observe other significant differences for the other outcomes: patient or graft survival, the risk of acute rejection episodes, the 30-day percentage of urological complications, and the 1-year estimated glomerular filtration rate. Our study highlights a small protective weekend effect with less post-surgery vascular complications compared to weekdays. This paradox might be explained by a different handling of weekend transplantations.

Terminally Differentiated Effector Memory CD8+ T Cells Identify Kidney Transplant Recipients at High Risk of Graft Failure.

BACKGROUND: Identifying biomarkers to predict kidney transplant failure and to define new therapeutic targets requires more comprehensive understanding of the immune response to chronic allogeneic stimulation. METHODS: We investigated the frequency and function of CD8+ T cell subsets-including effector memory (EM) and terminally differentiated EM (TEMRA) CD8+ T cells-in blood samples from 284 kidney transplant recipients recruited 1 year post-transplant and followed for a median of 8.3 years. We also analyzed CD8+ T cell reactivity to donor-specific PBMCs in 24 patients who had received living-donor kidney transplants. RESULTS: Increased frequency of circulating TEMRA CD8+ T cells at 1 year post-transplant associated with increased risk of graft failure during follow-up. This association remained after adjustment for a previously reported composite of eight clinical variables, the Kidney Transplant Failure Score. In contrast, increased frequency of EM CD8+ T cells associated with reduced risk of graft failure. A distinct TEMRA CD8+ T cell subpopulation was identified that was characterized by expression of FcγRIIIA (CD16) and by high levels of proinflammatory cytokine secretion and cytotoxic activity. Although donor-specific stimulation induced a similar rapid, early response in EM and TEMRA CD8+ T cells, CD16 engagement resulted in selective activation of TEMRA CD8+ T cells, which mediated antibody-dependent cytotoxicity. CONCLUSIONS: At 1 year post-transplant, the composition of memory CD8+ T cell subsets in blood improved prediction of 8-year kidney transplant failure compared with a clinical-variables score alone. A subpopulation of TEMRA CD8+ T cells displays a novel dual mechanism of activation mediated by engagement of the T-cell receptor or of CD16. These findings suggest that TEMRA CD8+ T cells play a pivotal role in humoral and cellular rejection and reveal the potential value of memory CD8+ T cell monitoring for predicting risk of kidney transplant failure.