The effect of parathyroid hormone lowering by etelcalcetide therapy on calcification propensity and calciprotein particles in hemodialysis patients.

Background: This study investigated whether parathyroid hormone (PTH) lowering with etelcalcetide, and the consequent effects on mineral and bone metabolism, could improve serum calcification propensity (T50 time) and decrease calciprotein particle (CPP) load in hemodialysis patients with secondary hyperparathyroidism. Methods: In this single-arm, prospective, dose-escalation proof-of-principle study, hemodialysis patients received etelcalcetide at 2.5 mg/dialysis session with increments of 2.5 mg every 4 weeks to a maximum dose of 15 mg three times a week or until a pre-specified safety endpoint was reached, followed by an 8-week wash-out phase. Results: Out of 36 patients recruited (81% male, 62 ± 13 years), 16 patients completed the study per protocol with a mean maximum tolerated dose of etelcalcetide of 9.5 ± 2.9 mg/dialysis session. With escalating doses of etelcalcetide, PTH and serum calcium levels significantly decreased (P < 0.0001). While there was no significant change in T50 times or serum phosphate levels, etelcalcetide did yield significant and consistent reductions in serum levels of endogenous calciprotein monomers [-35.4 (-44.4 to -26.5)%, P < 0.0001], primary [-22.4 (-34.5 to -10.3)%, P < 0.01] and secondary CPP [-29.1 (-45.7 to -12.4)%, P < 0.01], an effect that was reversed after therapy withdrawal. Serum levels of osteoclastic markers significantly decreased with escalating doses of etelcalcetide, while levels of the osteoblastic marker remained stable. Conclusions: Lowering of PTH with etelcalcetide did not result in statistically significant changes in T50. By contrast, homogenous reductions in serum levels of calciprotein monomers, primary and secondary CPP were observed.

Citrate-Buffered, Magnesium-Enriched Dialysate on Calcification Propensity in Hemodialysis Patients - The CitMag Study.

Introduction: Serum calcification propensity (T50 time) is associated with mortality in patients on dialysis. Several solitary interventions improve T50. However, whether a combination of interventions yields further increases in T50 is unknown. We hypothesized that a combination of 2 interventions, namely increasing magnesium concentration while simultaneously substituting acetate for citrate in the dialysis fluid, leads to increases in T50 values. Methods: In a randomized controlled trial, 60 patients on chronic hemodialysis were allocated to either continue on standard (S) dialysate (3 mmol/l acetate, 0.5 mmol/l magnesium) or a sequence of magnesium-enriched (Mg0.75) dialysate (3 mmol/l acetate, 0.75 mmol/l magnesium) for 2 weeks followed by combination treatment using citrate-buffered, magnesium-enriched (Cit+Mg0.75) dialysate (1 mmol/l citrate, 0.75 mmol/l magnesium) for 3 weeks. The primary end point was the difference in T50 times between the S group and the Cit+Mg0.75 group. Results: There was no significant difference in T50 time between the S group and the Cit+Mg0.75 group (236 ± 77 vs. 265 ± 97 min, P = 0.23). The size (hydrodynamic radius) of secondary calciprotein particles did not differ between the S group and the Cit+Mg0.75 group (294 ± 95 vs. 309 ± 91 nm, P = 0.56). In longitudinal analyses, serum magnesium concentrations increased from 1.07 ± 0.17 to 1.24 ± 0.17 mmol/l with the Mg0.75 dialysate (P < 0.0001) but decreased again to 1.19 ± 0.16 mmol/l with the Cit+Mg0.75 dialysate (P < 0.0001). Conclusion: The combination of citrate buffer with increased magnesium concentration in dialysate does not improve T50.

European Survey on Clinical Practice of Detecting and Treating T-Cell Mediated Kidney Transplant Rejection.

The KDIGO guideline for acute rejection treatment recommends use of corticosteroids and suggests using lymphocyte-depleting agents as second line treatment. Aim of the study was to determine the current practices of detection and treatment of TCMR of kidney allografts amongst European kidney transplant centres. An invitation was sent through ESOT/EKITA newsletters and through social media to transplant professionals in Europe for taking part in the survey. A total of 129 transplant professionals responded to the survey. There was equal representation of small and large sized transplant centres. The majority of centres treat borderline changes (BL) and TCMR (Grade IA-B, IIA-B) in indication biopsies and protocol biopsies with corticosteroids as first line treatment. Thymoglobulin is used mainly as second line treatment for TCMR Grade IA-B (80%) and TCMR IIA-B (85%). Treatment success is most often evaluated within one month of therapy. There were no differences observed between the large and small centres for the management of TCMR. This survey highlights the common practices and diversity in clinics for the management of TCMR in Europe. Testing new therapies for TCMR should be in comparison to the current standard of care in Europe. Better consensus on treatment success is crucial for robust study designs.

International consensus on post-transplantation diabetes mellitus.

Post-transplantation diabetes mellitus (PTDM) remains a leading complication after solid organ transplantation. Previous international PTDM consensus meetings in 2003 and 2013 provided standardized frameworks to reduce heterogeneity in diagnosis, risk stratification and management. However, the last decade has seen significant advancements in our PTDM knowledge complemented by rapidly changing treatment algorithms for management of diabetes in the general population. In view of these developments, and to ensure reduced variation in clinical practice, a 3rd international PTDM Consensus Meeting was planned and held from 6-8 May 2022 in Vienna, Austria involving global delegates with PTDM expertise to update the previous reports. This update includes opinion statements concerning optimal diagnostic tools, recognition of prediabetes (impaired fasting glucose and/or impaired glucose tolerance), new mechanistic insights, immunosuppression modification, evidence-based strategies to prevent PTDM, treatment hierarchy for incorporating novel glucose-lowering agents and suggestions for the future direction of PTDM research to address unmet needs. Due to the paucity of good quality evidence, consensus meeting participants agreed that making GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) recommendations would be flawed. Although kidney-allograft centric, we suggest that these opinion statements can be appraised by the transplantation community for implementation across different solid organ transplant cohorts. Acknowledging the paucity of published literature, this report reflects consensus expert opinion. Attaining evidence is desirable to ensure establishment of optimized care for any solid organ transplant recipient at risk of, or who develops, PTDM as we strive to improve long-term outcomes.

Sex differences in the survival benefit of kidney transplantation: a retrospective cohort study using target trial emulation.

BACKGROUND: Kidney transplantation is the preferred treatment for eligible patients with kidney failure who need renal replacement therapy. However, it remains unclear whether the anticipated survival benefit from kidney transplantation is different for women and men. METHODS: We included all dialysis patients recorded in the Austrian Dialysis and Transplant Registry who were waitlisted for their first kidney transplant between 2000 and 2018. In order to estimate the causal effect of kidney transplantation on 10-year restricted mean survival time, we mimicked a series of controlled clinical trials and applied inverse probability of treatment and censoring weighted sequential Cox models. RESULTS: This study included 4408 patients (33% female) with a mean age of 52 years. Glomerulonephritis was the most common primary renal disease both in women (27%) and men (28%). Kidney transplantation led to a gain of 2.22 years (95% CI 1.88 to 2.49) compared with dialysis over a 10-year follow-up. The effect was smaller in women (1.95 years, 95% CI 1.38 to 2.41) than in men (2.35 years, 95% CI 1.92 to 2.70) due to a better survival on dialysis. Across ages the survival benefit of transplantation over a follow-up of 10 years was smaller in younger women and men and increased with age, showing a peak for both women and men aged about 60 years. CONCLUSIONS: There were few differences in survival benefit by transplantation between females and males. Females had better survival than males on the waitlist receiving dialysis and similar survival to males after transplantation.

Coping with a lack of evidence: living-donor kidney transplantation in the initial phase of the SARS-CoV-2 pandemic.

Due to immunosuppressive therapy, transplant patients are more susceptible to viral and bacterial infections. A potentially deadly new virus haunted us in 2020: SARS-CoV­2, causing coronavirus disease 19 (COVID-19). We analyzed the consequences of this previously unknown risk for our living-donor transplant program in the first year of the pandemic. After the complete lockdown in spring 2020, our transplant center in Linz resumed the living-donor kidney transplantation program from June to September 2020, between the first and second waves of COVID-19 in Austria. We compared the outcomes of these living-donor kidney transplantations with the transplant outcomes of the corresponding periods of the three previous years. From June 4 to September 9, 2020, five living-donor kidney transplantations were performed. All donors and recipients were screened for COVID 19 infection by PCR testing the day before surgery. Kidney transplant recipients remained isolated in single rooms until discharge from hospital. All recipients and donors remained SARS-CoV­2 negative during the follow-up of 10 months and have been fully vaccinated to date. The number of living transplants in the studied period of 2020 was constant compared to the same months of 2017, 2018, and 2019. Living-donor kidney transplantation can be continued using testing for SARS-CoV­2 and meticulous hygienic precautions in epidemiologically favorable phases of the SARS-CoV­2 pandemic. Donors and recipients should be carefully selected and informed about risks and benefits.

Effect of the phosphate binder sucroferric oxyhydroxide in dialysis patients on endogenous calciprotein particles, inflammation, and vascular cells.

BACKGROUND: Calciprotein particles (CPPs), colloidal mineral-protein nanoparticles, have emerged as potential mediators of phosphate toxicity in dialysis patients, with putative links to vascular calcification, endothelial dysfunction and inflammation. We hypothesized that phosphate binder therapy with sucroferric oxyhydroxide (SO) would reduce endogenous CPP levels and attenuate pro-calcific and pro-inflammatory effects of patient serum towards human vascular cells in vitro. METHODS: This secondary analysis of a randomised controlled crossover study compared the effect of 2-week phosphate binder washout with high-dose (2000 mg/day) and low-dose (250 mg/day) SO therapy in 28 haemodialysis patients on serum CPP levels, inflammatory cytokine/chemokine arrays and human aortic smooth muscle cell (HASMC) and coronary artery endothelial cell (HCAEC) bioassays. RESULTS: In our cohort (75% male, 62 ± 12 years) high-dose SO reduced primary (amorphous) and secondary (crystalline) CPP levels {-62% [95% confidence interval (CI) -76 to -44], P < .0001 and -38% [-62 to -0.14], P < .001, respectively} compared with washout. Nine of 14 plasma cytokines/chemokines significantly decreased with high-dose SO, with consistent reductions in interleukin-6 (IL-6) and IL-8. Exposure of HASMC and HCAEC cultures to serum of SO-treated patients reduced calcification and markers of activation (IL-6, IL-8 and vascular cell adhesion protein 1) compared with washout. Serum-induced HASMC calcification and HCAEC activation was ameliorated by removal of the CPP-containing fraction from patient sera. Effects of CPP removal were confirmed in an independent cohort of chronic kidney disease patients. CONCLUSIONS: High-dose SO reduced endogenous CPP formation in dialysis patients and yielded serum with attenuated pro-calcific and inflammatory effects in vitro.

Humoral response after a third and fourth dose of mRNA-based SARS-CoV-2 vaccine in previously seronegative kidney transplant recipients.

Growing evidence shows diminished response to mRNA-based SARS-CoV­2 vaccination in kidney transplant recipients. We aimed to investigate the seroconversion rate after a 3rd and 4th dose of mRNA vaccination in kidney transplant recipients without prior antibody response to two or three vaccination doses.This retrospective study included 324 prevalent kidney transplant recipients of a single tertiary transplantation center of which 157 remained seronegative, defined as anti-spike-RBD-IgG antibody titer < 7.1 BAU/ml, after two doses of mRNA-based SARS-CoV­2 vaccination. Maintenance immunosuppression was not changed. The median patient age was 60.6 years (IQR 51.4-68.1 years), 66.9% were male. Positivity for anti-spike-RBD-IgG (≥ 7.1 BAU/ml) was measured 4-5 weeks after administration of a 3rd and 4th vaccine dose.Seroconversion rates were 63.9% after a 3rd dose and 29.3% after a 4th dose of vaccine. Cumulative prevalence of seropositivity was 51.5% after 2 doses, 80.5% after 3 doses and 84.2% after 4 doses.In conclusion, seroconversion can be achieved in the majority of the kidney transplant recipients by administrating three or four doses of mRNA vaccine without changing maintenance immunosuppression.

Survival Benefit of First Single-Organ Deceased Donor Kidney Transplantation Compared With Long-term Dialysis Across Ages in Transplant-Eligible Patients With Kidney Failure.

Importance: Kidney transplant is considered beneficial in terms of survival compared with continued dialysis for patients with kidney failure. However, randomized clinical trials are infeasible, and available evidence from cohort studies is at high risk of bias. Objective: To compare restricted mean survival times (RMSTs) between patients who underwent transplant and patients continuing dialysis across transplant candidate ages and depending on waiting time, applying target trial emulation methods. Design, Setting, and Participants: In this retrospective cohort study, patients aged 18 years or older appearing on the wait list for their first single-organ deceased donor kidney transplant between January 1, 2000, and December 31, 2018, in Austria were evaluated. Available data were obtained from the Austrian Dialysis and Transplant Registry and Eurotransplant and included repeated updates on wait-listing status and relevant covariates. Data were analyzed between August 1, 2019, and December 23, 2021. Exposures: A target trial was emulated in which patients were randomized to either receive the transplant immediately (treatment group) or to continue dialysis and never receive a transplant (control group) at each time an organ became available. Main Outcomes and Measures: The primary outcome was time from transplant allocation to death. Effect sizes in terms of RMSTs were obtained using a sequential Cox approach. Results: Among the 4445 included patients (2974 men [66.9%]; mean [SD] age, 52.2 [13.2] years), transplant was associated with increased survival time across all considered ages compared with continuing dialysis and remaining on the wait list within a 10-year follow-up. The estimated RMST differences were 0.57 years (95% CI, -0.14 to 1.84 years) at age 20 years, 3.01 years (95% CI, 2.50 to 3.54 years) at age 60 years, and 2.48 years (95% CI, 1.88 to 3.04 years) at age 70 years. The survival benefit for patients who underwent transplant across ages was independent of waiting time. Conclusions and Relevance: The findings of this study suggest that kidney transplant prolongs the survival time of persons with kidney failure across all candidate ages and waiting times.

Prediction models for living organ transplantation are poorly developed, reported, and validated: a systematic review.

OBJECTIVE: To identify and critically appraise risk prediction models for living donor solid organ transplant counselling. STUDY DESIGN AND SETTING: We systematically reviewed articles describing the development or validation of prognostic risk prediction models about living donor solid organ (kidney and liver) transplantation indexed in Medline until April 4, 2021. Models were eligible if intended to predict, at transplant counselling, any outcome occurring after transplantation or donation in recipients or donors. Duplicate study selection, data extraction, assessment for risk of bias and quality of reporting was done using the CHARMS checklist, PRISMA recommendations, PROBAST tool, and TRIPOD Statement. RESULTS: We screened 4691 titles and included 49 studies describing 68 models (35 kidney, 33 liver transplantation). We identified 49 new risk prediction models and 19 external validations of existing models. Most models predicted recipients outcomes (n = 38, 75%), e.g., kidney graft loss (29%), or mortality of liver transplant recipients (55%). Many new models (n = 46, 94%) and external validations (n = 17, 89%) had a high risk of bias because of methodological weaknesses. The quality of reporting was generally poor. CONCLUSION: We advise against applying poorly developed, reported, or validated prediction models. Future studies could validate or update the few identified methodologically appropriate models.

European Renal Best Practice endorsement of guidelines for diagnosis and therapy of thrombotic thrombocytopaenic purpura published by the International Society on Thrombosis and Haemostasis.

Thrombotic thrombocytopenic purpura (TTP) is a life-threatening disease that is caused by severe ADAMTS-13 deficiency. Immune-mediated TTP develops due to autoantibodies against ADAMTS-13, whereas congenital TTP is caused by mutations in the ADAMTS13 gene. Diagnostic possibilities and treatment options in TTP have emerged in recent years, which prompted the International Society on Thrombosis and Haemostasis (ISTH) to publish clinical practice guidelines for the diagnosis and treatment of TTP in 2020. In this article, the European Renal Best Practice Working Group endorsed the ISTH guidelines and emphasizes a number of considerations, including the importance of rapid ADAMTS-13 activity testing, the use of rituximab and anti-von Willebrand factor therapies such as caplacizumab, that enhance the clinical applicability of the guidelines in Europe.

Modeling pulse wave velocity trajectories-challenges, opportunities, and pitfalls.

In this commentary, we discuss the analysis of trajectories of pulse wave velocity in a longitudinal cohort study of children with chronic kidney disease (the Cardiovascular Comorbidity in Children with Chronic Kidney Disease - Transplantation study). We revisit the analysis made by the study authors and unravel some additional limitations. We also reevaluate the implicit assumptions that were made in the chosen analysis and suggest extensions of the basic linear mixed model to obtain more differentiated answers to research questions in nephrology.

The roles of predictors in cardiovascular risk models - a question of modeling culture?

BACKGROUND: While machine learning (ML) algorithms may predict cardiovascular outcomes more accurately than statistical models, their result is usually not representable by a transparent formula. Hence, it is often unclear how specific values of predictors lead to the predictions. We aimed to demonstrate with graphical tools how predictor-risk relations in cardiovascular risk prediction models fitted by ML algorithms and by statistical approaches may differ, and how sample size affects the stability of the estimated relations. METHODS: We reanalyzed data from a large registry of 1.5 million participants in a national health screening program. Three data analysts developed analytical strategies to predict cardiovascular events within 1 year from health screening. This was done for the full data set and with gradually reduced sample sizes, and each data analyst followed their favorite modeling approach. Predictor-risk relations were visualized by partial dependence and individual conditional expectation plots. RESULTS: When comparing the modeling algorithms, we found some similarities between these visualizations but also occasional divergence. The smaller the sample size, the more the predictor-risk relation depended on the modeling algorithm used, and also sampling variability played an increased role. Predictive performance was similar if the models were derived on the full data set, whereas smaller sample sizes favored simpler models. CONCLUSION: Predictor-risk relations from ML models may differ from those obtained by statistical models, even with large sample sizes. Hence, predictors may assume different roles in risk prediction models. As long as sample size is sufficient, predictive accuracy is not largely affected by the choice of algorithm.

The effect of phosphate binder therapy with sucroferric oxyhydroxide on calcification propensity in chronic haemodialysis patients: a randomized, controlled, crossover trial.

BACKGROUND: Calcification propensity is associated with the risk for cardiovascular events and death in end-stage renal disease patients. Here we investigated the effect of lowering serum phosphate with oral phosphate binder therapy on calcification propensity. METHODS: We performed an open-label, randomized, controlled, crossover study in chronic haemodialysis patients with hyperphosphataemia. Patients (n = 39) were randomized in a 1:1 ratio to either low-dose (250 mg/day) sucroferric oxyhydroxide (SO) followed by high-dose (2000 mg/day) SO or vice versa, with washout phases before and after SO treatment. The primary endpoint was changed in calcification propensity as measured by calciprotein particle formation time (T50 test) between washout and high-dose SO treatment in patients with ≥85% adherence to the prescribed SO dose (per-protocol analysis). RESULTS: In the primary per-protocol analysis (n = 28), 2000 mg/day SO treatment resulted in a mean increase in T50 of 66 min (95% CI 49-84 min, P < 0.0001), from 243 ± 63 to 309 ± 74 min compared with phosphate binder washout. Serum phosphate decreased from 2.28 ± 0.5 to 1.63 ± 0.43 mmol/L (P < 0.0001). SO at 250 mg/day did not influence T50 (P = 0.4) or serum phosphate concentrations (P = 0.9) compared with phosphate binder washout. The secondary intention-to-treat analysis (n = 39) showed similar results: an increase in T50 of 52 min (95% CI 31-74 min, P < 0.0001) and a decrease in serum phosphate from 2.18 ± 0.5 to 1.64 ± 0.46 mmol/L. No major adverse cardiovascular event, case of calciphylaxis or death occurred during the study. CONCLUSION: Phosphate binder treatment with SO improves serum calcification propensity of haemodialysis patients and might lead to improved outcomes.

Markers of potassium homeostasis in salt losing tubulopathies- associations with hyperaldosteronism and hypomagnesemia.

BACKGROUND: Renal loss of potassium (K+) and magnesium (Mg2+) in salt losing tubulopathies (SLT) leads to significantly reduced Quality of Life (QoL) and higher risks of cardiac arrhythmia. The normalization of K+ is currently the most widely accepted treatment target, however in even excellently designed RCTs the increase of K+ was only mild and rarely normalized. These findings question the role of K+ as the ideal marker of potassium homeostasis in SLT. Aim of this hypothesis-generating study was to define surrogate endpoints for future treatment trials in SLT in terms of their usefulness to determine QoL and important clinical outcomes. METHODS: Within this prospective cross-sectional study including 11 patients with SLTs we assessed the biochemical, clinical and cardiological parameters and their relationship with QoL (RAND SF-36). The primary hypothesis was that QoL would be more dependent of higher aldosterone concentration, assessed by the transtubular-potassium-gradient (TTKG). Correlations were evaluated using Pearson's correlation coefficient. RESULTS: Included patients were mainly female (82%, mean age 34 ± 12 years). Serum K+ and Mg2+ was 3.3 ± 0.6 mmol/l and 0.7 ± 0.1 mmol/l (mean ± SD). TTKG was 9.5/3.4-20.2 (median/range). While dimensions of mental health mostly correlated with serum Mg2+ (r = 0.68, p = 0.04) and K+ (r = 0.55, p = 0.08), better physical health was associated with lower aldosterone levels (r = -0.61, p = 0.06). TTKG was neither associated with aldosterone levels nor with QoL parameters. No relevant abnormalities were observed in neither 24 h-ECG nor echocardiography. CONCLUSIONS: Hyperaldosteronism, K+ and Mg2+ were the most important parameters of QoL. TTKG was no suitable marker for hyperaldosteronism or QoL. Future confirmatory studies in SLT should assess QoL as well as aldosterone, K+ and Mg2+.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

OBJECTIVE: To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. DESIGN: Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. DATA SOURCES: PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. STUDY SELECTION: Studies that developed or validated a multivariable covid-19 related prediction model. DATA EXTRACTION: At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). RESULTS: 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. CONCLUSION: Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. SYSTEMATIC REVIEW REGISTRATION: Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. READERS' NOTE: This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Predicting donor, recipient and graft survival in living donor kidney transplantation to inform pretransplant counselling: the donor and recipient linked iPREDICTLIVING tool - a retrospective study.

Although separate prediction models for donors and recipients were previously published, we identified a need to predict outcomes of donor/recipient simultaneously, as they are clearly not independent of each other. We used characteristics from transplantations performed at the Oslo University Hospital from 1854 live donors and from 837 recipients of a live donor kidney transplant to derive Cox models for predicting donor mortality up to 20 years, and recipient death, and graft loss up to 10 years. The models were developed using the multivariable fractional polynomials algorithm optimizing Akaike's information criterion, and optimism-corrected performance was assessed. Age, year of donation, smoking status, cholesterol and creatinine were selected to predict donor mortality (C-statistic of 0.81). Linear predictors for donor mortality served as summary of donor prognosis in recipient models. Age, sex, year of transplantation, dialysis vintage, primary renal disease, cerebrovascular disease, peripheral vascular disease and HLA mismatch were selected to predict recipient mortality (C-statistic of 0.77). Age, dialysis vintage, linear predictor of donor mortality, HLA mismatch, peripheral vascular disease and heart disease were selected to predict graft loss (C-statistic of 0.66). Our prediction models inform decision-making at the time of transplant counselling and are implemented as online calculators.