A Multi-Step Precision Pathway for Predicting Allograft Survival in Heterogeneous Cohorts of Kidney Transplant Recipients.

Accurate prediction of allograft survival after kidney transplantation allows early identification of at-risk recipients for adverse outcomes and initiation of preventive interventions to optimize post-transplant care. Many prediction algorithms do not model cohort heterogeneity and may lead to inaccurate assessment of longer-term graft outcomes among minority groups. Using data from a national Australian kidney transplant cohort (2008-2017) as the derivation set, we developed P-Cube, a multi-step precision prediction pathway model for predicting overall graft survival in three ethnic subgroups: European Australians, Asian Australians and Aboriginal and Torres Strait Islander Peoples. The concordance index for the European Australians, Asian Australians, and Aboriginal and Torres Strait Islander Peoples subpopulations were 0.99 (0.98-0.99), 0.93 (0.92-0.94) and 0.92 (0.91-0.93), respectively. Similar findings were observed when validating P-cube using an external dataset [Scientific Registry of Transplant Recipient Registry (2006-2020)]. Six sub-categories of recipients with distinct risk factor profiles were identified. Some factors such as blood group compatibility were considered important across the entire transplant population. Other factors such as human leukocyte antigen (HLA)-DR mismatches were unique to older recipients. The P-cube model identifies allograft survival specific risk factors within a heterogenous population and offers personalized survival predictions in a diverse cohort.

The COVID-19 pandemic and access to health care in people with chronic kidney disease: A systematic review and meta-analysis.

AIM: This systematic review aims to evaluate the effect of the COVID-19 pandemic on access to health care for patients with CKD. METHODS: MEDLINE and EMBASE databases were searched up to July 2021 (PROSPERO CRD42021230831). Data relevant to access to health care before and during the COVID-19 pandemic were extracted, including outcomes related to access to general nephrology consultations, telehealth, dialysis services and kidney transplantations. Relative and absolute effects were pooled using a random effects model to account for between-study heterogeneity. Risk of bias was assessed using a modified Quality in Prognostic Studies tool. The certainty of the evidence was rated using the GRADE approach. RESULTS: Twenty-three studies across five WHO regions were identified. Reductions in transplantation surgeries were observed during the COVID-19 pandemic compared with the pre-COVID-19 era (risk ratio = 2.15, 95%CI = 1.51-3.06, I2  = 90%, p < .001). Additionally, six studies reported increased use of telehealth services compared with pre-COVID-19 times. Four studies found reduced access to in-person general nephrology services and six studies reported interruptions to dialysis services during the COVID-19 pandemic. CONCLUSION: Our findings suggest COVID-19 pandemic may have led to reductions in access to kidney transplantation, dialysis and in-person nephrology care. Meanwhile, whilst the use of telehealth has emerged as a promising alternate mode of health care delivery, its utility during the pandemic warrants further investigation. This study has highlighted major barriers to accessing care in a highly vulnerable chronic disease group.

Incidence and Outcomes of COVID-19 in People With CKD: A Systematic Review and Meta-analysis.

RATIONALE & OBJECTIVE: Coronavirus disease 2019 (COVID-19) disproportionately affects people with chronic diseases such as chronic kidney disease (CKD). We assessed the incidence and outcomes of COVID-19 in people with CKD. STUDY DESIGN: Systematic review and meta-analysis by searching MEDLINE, EMBASE, and PubMed through February 2021. SETTING & STUDY POPULATIONS: People with CKD with or without COVID-19. SELECTION CRITERIA FOR STUDIES: Cohort and case-control studies. DATA EXTRACTION: Incidences of COVID-19, death, respiratory failure, dyspnea, recovery, intensive care admission, hospital admission, need for supplemental oxygen, hospital discharge, sepsis, short-term dialysis, acute kidney injury, and fatigue. ANALYTICAL APPROACH: Random-effects meta-analysis and evidence certainty adjudicated using an adapted version of GRADE (Grading of Recommendations Assessment, Development and Evaluation). RESULTS: 348 studies (382,407 participants with COVID-19 and CKD; 1,139,979 total participants with CKD) were included. Based on low-certainty evidence, the incidence of COVID-19 was higher in people with CKD treated with dialysis (105 per 10,000 person-weeks; 95% CI, 91-120; 95% prediction interval [PrI], 25-235; 59 studies; 468,233 participants) than in those with CKD not requiring kidney replacement therapy (16 per 10,000 person-weeks; 95% CI, 4-33; 95% PrI, 0-92; 5 studies; 70,683 participants) or in kidney or pancreas/kidney transplant recipients (23 per 10,000 person-weeks; 95% CI, 18-30; 95% PrI, 2-67; 29 studies; 120,281 participants). Based on low-certainty evidence, the incidence of death in people with CKD and COVID-19 was 32 per 1,000 person-weeks (95% CI, 30-35; 95% PrI, 4-81; 229 studies; 70,922 participants), which may be higher than in people with CKD without COVID-19 (incidence rate ratio, 10.26; 95% CI, 6.78-15.53; 95% PrI, 2.62-40.15; 4 studies; 18,347 participants). LIMITATIONS: Analyses were generally based on low-certainty evidence. Few studies reported outcomes in people with CKD without COVID-19 to calculate the excess risk attributable to COVID-19, and potential confounders were not adjusted for in most studies. CONCLUSIONS: The incidence of COVID-19 may be higher in people receiving maintenance dialysis than in those with CKD not requiring kidney replacement therapy or those who are kidney or pancreas/kidney transplant recipients. People with CKD and COVID-19 may have a higher incidence of death than people with CKD without COVID-19.

The effect of modelling parameters in the development and validation of knee joint models on ligament mechanics: A systematic review.

BACKGROUND: The ligaments in the knee are prone to injury especially during dynamic activities. The resulting instability can have a profound impact on a patient's daily activities and functional capacity. Musculoskeletal knee modelling provides a non-invasive tool for investigating ligament force-strain behaviour in various dynamic scenarios, as well as potentially complementing existing pre-planning tools to optimise surgical reconstructions. However, despite the development and validation of many musculoskeletal knee models, the effect of modelling parameters on ligament mechanics has not yet been systematically reviewed. OBJECTIVES: This systematic review aimed to investigate the results of the most recent studies using musculoskeletal modelling techniques to create models of the native knee joint, focusing on ligament mechanics and modelling parameters in various simulated movements. DATA SOURCES: PubMed, ScienceDirect, Google Scholar, and IEEE Xplore. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Databases were searched for articles containing any numerical ligament strain or force data on the intact, ACL-deficient, PCL-deficient, or lateral extra-articular reconstructed (LER) knee joints. The studies had to derive these results from musculoskeletal modelling methods. The dates of the publications were between 1 January 1995 and 30 November 2021. METHOD: A customised data extraction form was created to extract each selected study's critical musculoskeletal model development parameters. Specific parameters of the musculoskeletal knee model development used in each eligible study were independently extracted, including the (1) musculoskeletal model definition (i.e., software used for modelling, knee type, source of geometry, the inclusion of cartilage and menisci, and articulating joints and joint boundary conditions (i.e., number of degrees of freedom (DoF), subjects, type of activity, collected data and type of simulation)), (2) specifically ligaments modelling techniques (i.e., ligament bundles, attachment points, pathway, wrapping surfaces and ligament material properties such as stiffness and reference length), (3) sensitivity analysis, (4) validation approaches, (5) predicted ligament mechanics (i.e., force, length or strain) and (6) clinical applications if available. The eligible papers were then discussed quantitatively and qualitatively with respect to the above parameters. RESULTS AND DISCUSSION: From the 1004 articles retrieved by the initial electronic search, only 25 met all inclusion criteria. The results obtained by aggregating data reported in the eligible studies indicate that considerable variability in the predicted ligament mechanics is caused by differences in geometry, boundary conditions and ligament modelling parameters. CONCLUSION: This systematic review revealed that there is currently a lack of consensus on knee ligament mechanics. Despite this lack of consensus, some papers highlight the potential of developing translational tools using musculoskeletal modelling. Greater consistency in model design, incorporation of sensitivity assessment of the model outcomes and more rigorous validation methods should lead to better agreement in predictions for ligament mechanics between studies. The resulting confidence in the musculoskeletal model outputs may lead to the development of clinical tools that could be used for patient-specific treatments.