Prediction of graft failure for young kidney transplant recipients

Une attention particulière doit être accordée aux jeunes patients transplantés du rein, qui sont prioritaires en France dans l’attribution de greffon rénal. Les objectifs de cette thèse étaient 1) d’étudier la dynamique du risque instantané de la perte du greffon en fonction de l’âge courant après la transplantation chez les jeunes ; 2) de réaliser un revue systématique des modèles de prédiction de perte du greffon rénal tout âge confondu; et 3) de développer et valider un modèle de prédiction adapté à cette jeune population. Pour répondre aux objectifs 1 et 3, nous avons utilisé les données des registres nationaux français REIN et CRITAL qui incluent de manière exhaustive tous les patients transplantés rénaux pédiatriques. Pour l’Objectif 1, une méthode statistique en deux étapes a permis de mettre en évidence une augmentation accrue du risque instantané de perte du greffon au moment de l’adolescence. Pour l’Objectif 2, une revue systématique des articles publiés entre 2005 et 2015 a montré qu’aucun outil prédictif de la perte du greffon n’avait été spécifiquement proposé pour les patients pédiatriques, ni aucun outil de prédiction dynamique tout âge confondu. Pour l’Objectif 3, nous avons développé et validé par validation croisée interne un modèle de prédiction dynamique de perte du greffon pour les jeunes transplantés, à partir d’un modèle conjoint à effets aléatoires partagés. Ce modèle incluait des prédicteurs classiques à l’inclusion défini par le 90ième jour après la transplantation (des caractéristiques du receveur (sexe, âge à la transplantation, durée de dialyse pré-greffe, maladie rénale initiale, nadir du DFGe entre la transplantation et J90), du donneur (âge, type), et de la transplantation (durée d’ischémie froide, nombre d’incompatibilités HLA, statut donneur/receveur pour sérologie CMV)). Le modèle incluait également la trajectoire du DFG estimé après la transplantation, en supposant que le risque instantané de perte du greffon dépendait à la fois du niveau courant du DFG mais aussi de sa pente courante. Nos résultats indiquent que ce modèle avait de bonnes performances prédictives (AUC à 5 ans variant de 0.75 à 0.86 selon les temps de prédiction après la transplantation), bien meilleures que le modèle de Cox classique ne tenant compte que des prédicteurs à l’inclusion (AUC à 5 ans variant de 0.56 à 0.62). Ce modèle permettant la mise à jour à chaque visite clinique après la transplantation, du risque futur de la perte du greffon en fonction de toutes les valeurs observées précédentes du DFG, devra être validé sur d’autres populations que la population française. Nous pensons en effet qu’un tel outil pourrait à terme être utile dans le suivi clinique des jeunes patients transplantés rénaux.Particular attention should be paid to young patients transplanted from the kidney, which have priority in France in the assignment of renal graft. The objectives of this thesis were 1) to study the dynamics of the hazard of graft failure by current age after transplantation in young people; 2) to carry out a systematic review of prediction models for renal graft failure at all ages; and (3) to develop and validate a prediction model for this young population. To achieve Objectives 1 and 3, we used data from the French national registries REIN and CRISTAL, which included all pediatric renal transplant patients. For Objective 1, a two-stage statistical method revealed an increase in the hazard of graft failure during adolescence. For Objective 2, a systematic review of articles published between 2005 and 2015 showed that no predictive tool for graft failure has been specifically proposed for pediatric patients, as well as no dynamic predictive model for any age. For Objective 3, we developed and validated using internal cross-validation a dynamic prediction model of graft failure for young transplanted patients, using a joint model with shared random effects. This model included standard baseline predictors at the 90th day after transplantation (characteristics of the recipient (sex, age at transplantation, pretrasplant dialysis duration, primary renal disease, nadir of eGFR at J90), the donor (age and type), and transplantation (duration of cold ischemia, number of HLA incompatibilities, donor/recipient cytomegalovirus (CMV) serology status). The model also included the trajectory of GFR estimated after transplantation, assuming that the hazard of graft failure depended on both the current value of eGFR and its current slope. Our results indicate that this model had good predictive performances (AUC at 5 years ranging from 0.75 to 0.86 according to the time at prediction after transplantation), which were much better than the standard Cox model accounting for baseline predictors only (5-year AUC variant from 0.56 to 0.62). This model which allows the prediction of graft failure to be updated at each clinical visit after transplantation based on all previous observed values of eGFR, should be validated on populations other than the French population. We believe that such a tool could ultimately be useful in the clinical follow-up of young kidney transplanted patients

Prédiction de la perte du greffon chez les jeunes patients transplantés rénaux

Particular attention should be paid to young patients transplanted from the kidney, which have priority in France in the assignment of renal graft. The objectives of this thesis were 1) to study the dynamics of the hazard of graft failure by current age after transplantation in young people; 2) to carry out a systematic review of prediction models for renal graft failure at all ages; and (3) to develop and validate a prediction model for this young population. To achieve Objectives 1 and 3, we used data from the French national registries REIN and CRISTAL, which included all pediatric renal transplant patients. For Objective 1, a two-stage statistical method revealed an increase in the hazard of graft failure during adolescence. For Objective 2, a systematic review of articles published between 2005 and 2015 showed that no predictive tool for graft failure has been specifically proposed for pediatric patients, as well as no dynamic predictive model for any age. For Objective 3, we developed and validated using internal cross-validation a dynamic prediction model of graft failure for young transplanted patients, using a joint model with shared random effects. This model included standard baseline predictors at the 90th day after transplantation (characteristics of the recipient (sex, age at transplantation, pretrasplant dialysis duration, primary renal disease, nadir of eGFR at J90), the donor (age and type), and transplantation (duration of cold ischemia, number of HLA incompatibilities, donor/recipient cytomegalovirus (CMV) serology status). The model also included the trajectory of GFR estimated after transplantation, assuming that the hazard of graft failure depended on both the current value of eGFR and its current slope. Our results indicate that this model had good predictive performances (AUC at 5 years ranging from 0.75 to 0.86 according to the time at prediction after transplantation), which were much better than the standard Cox model accounting for baseline predictors only (5-year AUC variant from 0.56 to 0.62). This model which allows the prediction of graft failure to be updated at each clinical visit after transplantation based on all previous observed values of eGFR, should be validated on populations other than the French population. We believe that such a tool could ultimately be useful in the clinical follow-up of young kidney transplanted patients.Une attention particulière doit être accordée aux jeunes patients transplantés du rein, qui sont prioritaires en France dans l’attribution de greffon rénal. Les objectifs de cette thèse étaient 1) d’étudier la dynamique du risque instantané de la perte du greffon en fonction de l’âge courant après la transplantation chez les jeunes ; 2) de réaliser un revue systématique des modèles de prédiction de perte du greffon rénal tout âge confondu; et 3) de développer et valider un modèle de prédiction adapté à cette jeune population. Pour répondre aux objectifs 1 et 3, nous avons utilisé les données des registres nationaux français REIN et CRITAL qui incluent de manière exhaustive tous les patients transplantés rénaux pédiatriques. Pour l’Objectif 1, une méthode statistique en deux étapes a permis de mettre en évidence une augmentation accrue du risque instantané de perte du greffon au moment de l’adolescence. Pour l’Objectif 2, une revue systématique des articles publiés entre 2005 et 2015 a montré qu’aucun outil prédictif de la perte du greffon n’avait été spécifiquement proposé pour les patients pédiatriques, ni aucun outil de prédiction dynamique tout âge confondu. Pour l’Objectif 3, nous avons développé et validé par validation croisée interne un modèle de prédiction dynamique de perte du greffon pour les jeunes transplantés, à partir d’un modèle conjoint à effets aléatoires partagés. Ce modèle incluait des prédicteurs classiques à l’inclusion défini par le 90ième jour après la transplantation (des caractéristiques du receveur (sexe, âge à la transplantation, durée de dialyse pré-greffe, maladie rénale initiale, nadir du DFGe entre la transplantation et J90), du donneur (âge, type), et de la transplantation (durée d’ischémie froide, nombre d’incompatibilités HLA, statut donneur/receveur pour sérologie CMV)). Le modèle incluait également la trajectoire du DFG estimé après la transplantation, en supposant que le risque instantané de perte du greffon dépendait à la fois du niveau courant du DFG mais aussi de sa pente courante. Nos résultats indiquent que ce modèle avait de bonnes performances prédictives (AUC à 5 ans variant de 0.75 à 0.86 selon les temps de prédiction après la transplantation), bien meilleures que le modèle de Cox classique ne tenant compte que des prédicteurs à l’inclusion (AUC à 5 ans variant de 0.56 à 0.62). Ce modèle permettant la mise à jour à chaque visite clinique après la transplantation, du risque futur de la perte du greffon en fonction de toutes les valeurs observées précédentes du DFG, devra être validé sur d’autres populations que la population française. Nous pensons en effet qu’un tel outil pourrait à terme être utile dans le suivi clinique des jeunes patients transplantés rénaux

Decentralized policies and formal care use by the disabled elderly

In a context of population ageing, public policies encourage the utilization of pro- fessional home care for the elderly living in the community. This chapter studies the determinants of professional home care use by the disabled elderly in the French con- text. It focuses on the e_ects of the regulation of the supply and the generosity of public _nancing. We use departmental variations in both the regulation of providers and the implementation of the main program devoted to the disabled elderly, the APA policy. We exploit an original survey on departmental practices matched with the HSM survey to estimate the determinants of formal care use, at the extensive margin. We _nd no e_ect of the departmental generosity while, on the supply side, when non-regulated providers | whose quality is uncertain and price is lightly regulated | dominate the market, the disabled elderly have a lower probability to use formal home care. Our results contribute to discuss both the questions raised by the decentralization of a national policy and the recent reform of the home care sector requiring all home care structures to be regulated

Validation of a dynamic prediction model of kidney allograft survival in pediatric kidney transplant recipients

Introduction: Accurate prediction models of kidney allograft loss are lacking in children. Dynamic models allow the integration of new data throughout a patient’s follow-up making them better fitted from clinical use than traditional predictive models. In this study, we aim at externally validating a dynamic score of kidney allograft loss, developed in a derivation cohort of 793 French pediatric kidney transplant recipients, in a large cohort from the United States. Methods: All patients aged < 21 years old, transplanted in the US between January 1st 2002 and December 31st 2015 recorded in the SRTR registry were included in the validation cohort. Two predictive models were previously developed using joint models on the French National Registry data (REIN) and included recipient, donor and transplant characteristics and follow-up data (eGFR, eGFR slope). Individual predictions of allograft loss at 3 and 5 years were made by applying these two models on the validation cohort. Model accuracy was evaluated based on its discrimination (AUC) and calibration (R2). Results: 10,613 patients were included. Among them, 94% were younger than 18 years old at the time of transplantation, 59% were male, 28% received a preemptive transplant and 43% a living donor transplant. Over a median follow-up time of 6.6 [4.0;9.7] years, 2420 patients (23%) lost their graft and 316 (6%) died. The performances of the models were good with excellent discrimination (AUCs between 0.8 and 0.9) and good calibration (Figure 1). The performance of the reduced model were similar to those of the full model. Conclusion: This predictive model demonstrated high accuracy in predicting kidney allograft loss in children and support the benefit of incorporating longitudinal information to improve prediction performance. This model can be used prospectively to assess patients’ risk of graft loss and further study evaluating the impact of using this model in clinical practice are needed

Prog Urol

Objectifs: La prévalence de l'obésité n'a cessé d'augmenter ces 20 dernières années dans la population générale et parmi les patients receveurs de transplants rénaux. Dans l'esprit chirurgical, l'obésité est associée à une augmentation des difficultés chirurgicales. L'objectif de cette étude était d’évaluer l'impact de l'IMC sur les complications périopératoires. Méthodes: Toutes les transplantations rénales réalisées chez l'adulte dans notre centre de 2006 à 2011 ont été analysées. Les données concernant les caractéristiques des patients, la procédure chirurgicale, les complications per- et postopératoires ainsi que la fonction rénale ont été collectées. Les patients on été repartis en 4 groupes: sous-poids (BMI &lt; 18,5 kg/m2), poids normal (18,5 kg/m2 ≤ BMI &lt; 25 kg/m2), surpoids (25 kg/m2 ≤ BMI &lt; 30 kg/m2) et obésité (BMI ≥ 30 kg/m2). Nous avons également étudié l'impact de l'IMC sur les complications en tant que variable continue afin d'identifier de potentielles valeurs seuils. Résultats: Parmi 694 patients inclus, 52 % avait un IMC normal, 7 %, 31 % et 9 % étaient respectivement en sous-poids, surpoids et obèses. En analyse multivariée, le surpoids était associé à une augmentation de la durée opératoire comparé au patients de poids normal (différence moyenne estimée à 10,4 min, 95 % intervalle de confiance (IC) [4,0; 16,9]) et l'obésité était associée à une augmentation du risque d’éventration (odds ratio 3,1, 95 %CI [1,3; 7,3] comparé aux patients de poids normal). En considérant l'IMC en tant que variable continue le risque d’éventration augmentait significativement au-delà d'un IMC à 26 kg/m2, de pertes sanguines et de sténose urétérale au-delà d'un IMC à 32 kg/m2 et d'hématome de paroi au-delà d'un IMC à 34 kg/m2. Conclusions: Nous avons trouvé des seuils d'IMC au-delà desquels les pertes sanguines, le risque d’éventration, de sténose urétérale et d'hématome de paroi augmentent significativement. Niveau de preuve: 3. © 2020 Elsevier Masson SASObjectives: Obesity prevalence has increased over the past 20 years in the general population and among kidney transplant recipients. General surgical belief is that obesity increases surgical difficulty. The aim of this study was to assess the impact of Body Mass Index (BMI) on perioperative complications. Methods: All kidney transplantations performed in adults in our centre from 2006 to 2011 were analysed. Data on patients’ characteristics, surgical protocol, intra and postoperative complications and renal function were collected. Patients were divided into 4 groups as follows: underweight (BMI &lt; 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI &lt; 25 kg/m2), overweight (25 kg/m2 ≤ BMI &lt; 30 kg/m2) and obese (BMI ≥ 30 kg/m2). We also studied the impact of BMI on complications using it as a continuous variable to identify potential threshold values. Results: Among 694 patients included, 52% had normal BMI, 7%, 31% and 9% were underweight, overweight and obese, respectively. In multivariate analysis, overweight was significantly associated with longer operative time compared to normal-weight patients (estimated mean difference of 10,4 min, 95% confidence interval (CI) [4.0; 16.9]) and obesity was associated with an increased risk of wound dehiscence (odds ratio 3.1, 95% CI [1.3; 7.3] compared with normal-weight patients). Considering BMI as a continuous variable, the risk of parietal dehiscence significantly increased beyond a BMI of 26 kg/m2, intraoperative blood loss and the risk of ureteral stenosis beyond 32 kg/m2 and the risk of abdominal wall hematoma beyond a BMI of 34 kg/m2. Conclusions: We found BMI thresholds above which intraoperative blood loss and the risk of parietal dehiscence, ureteral stenosis, and parietal hematoma significantly increased. Level of evidence: 3. © 2020 Elsevier Masson SA

Nephrol Dial Transplant

BACKGROUND: Several models have been proposed to predict kidney graft failure in adult recipients but none in younger recipients. Our objective was to propose a dynamic prediction model for graft failure in young kidney transplant recipients. METHODS: We included 793 kidney transplant recipients waitlisted before the age of 18 years who received a first kidney transplantation before the age of 21 years in France in 2002-13 and survived >90 days with a functioning graft. We used a Cox model including baseline predictors only (sex, age at transplant, primary kidney disease, dialysis duration, donor type and age, human leucocyte antigen matching, cytomegalovirus serostatus, cold ischaemia time and delayed graft function) and two joint models also accounting for post-transplant estimated glomerular filtration rate (eGFR) trajectory. Predictive performances were evaluated using a cross-validated area under the curve (AUC) and R2 curves. RESULTS: When predicting the risk of graft failure from any time within the first 7 years after paediatric kidney transplantation, the predictions for the following 3 or 5 years were accurate and much better with the joint models than with the Cox model (AUC ranged from 0.83 to 0.91 for the joint models versus 0.56 to 0.64 for the Cox model). CONCLUSION: Accounting for post-transplant eGFR trajectory strongly increased the accuracy of graft failure prediction in young kidney transplant recipients

Glycaemic Variability and Hyperglycaemia as Prognostic Markers of Major Cardiovascular Events in Diabetic Patients Hospitalised in Cardiology Intensive Care Unit for Acute Heart Failure.

(1) Background: Hyperglycaemia and hypoglycaemia are both emerging risk factors for cardiovascular disease. Nevertheless, the potential effect of glycaemic variability (GV) on mid-term major cardiovascular events (MACE) in diabetic patients presenting with acute heart failure (AHF) remains unclear. This study investigates the prognostic value of GV in diabetic patients presenting with acute heart failure (AHF). (2) Methods: this was an observational study including consecutive patients with diabetes and AHF between January 2015 and November 2016. GV was calculated using standard deviation of glycaemia values during initial hospitalisation in the intensive cardiac care unit. MACE, including recurrent AHF, new-onset myocardial infarction, ischaemic stroke and cardiac death, were recorded. The predictive effects of GV on patient outcomes were analysed with respect to baseline characteristics and cardiac status. (3) Results: In total, 392 patients with diabetes and AHF were enrolled. During follow-up (median (interquartile range) 29 (6-51) months), MACE occurred in 227 patients (57.9%). In total, 92 patients died of cardiac causes (23.5%), 107 were hospitalised for heart failure (27.3%), 19 had new-onset myocardial infarction (4.8%) and 9 (2.3%) had an ischaemic stroke. Multivariable logistic regression analysis showed that GV &gt; 50 mg/dL (2.70 mmol/L), age &gt; 75 years, reduced left ventricular ejection fraction (LVEF &lt; 30%) and female gender were independent predictors of MACE: hazard ratios (HR) of 3.16 (2.25-4.43; &lt; 0.001), 1.54 (1.14-2.08; = 0.005), 1.47 (1.06-2.07; = 0.02) and 1.43 (1.05-1.94; = 0.03), respectively. (4) Conclusions: among other well-known factors of HF, a GV cut-off value of &gt;50 mg/dL was the strongest independent predictive factor for mid-term MACE in patients with diabetes and AHF