New‐onset diabetes mellitus after heart transplantation in children – Incidence and risk factors

Diabetes mellitus is a recognized complication of SOT in adults and is associated with decreased graft and patient survival. Little is known about NOD in pediatric HT recipients. We aimed to characterize the incidence and describe risk factors for development of NOD after HT in children. Children who developed diabetes after HT were identified from the OPTN database. Demographic and clinical data before and after transplant were compared between patients with and without NOD. A total of 2056 children were included, 56% were male, 54% were Caucasian, and 62% had cardiomyopathy prior to HT. NOD developed in 219 children (11%) after HT. The incidence of NOD was 2.4, 9.0, and 10.4% at one, five, and 10 yr after HT, respectively. Obesity (HR: 4.32), dialysis prior to transplant (HR: 2.38), African American race (HR: 1.86), transplant before year 2000 (HR: 1.82), female gender (HR: 1.68), and older age at transplant (HR: 1.28) were independent predictors of NOD. The major modifiable risk factor for NOD is obesity, imparting the maximum hazard. Improved surveillance for diabetes in high‐risk patients and specific prevention and intervention strategies are imperative in this population.     

Conversion to belatacept maintenance immunosuppression in HIV-positive kidney transplant recipients

There are only scattered case reports documenting belatacept use in HIV + kidney transplant recipients. We performed a retrospective review to describe short-term outcomes following conversion to belatacept in a cohort of HIV + patients. Patients were included if they were converted to belatacept between May 2015 and May 2019, had an HIV- donor, and received ≥4 doses of belatacept. All patients were treated with non-depleting induction and triple maintenance immunosuppression. Allograft and HIV-related outcomes were collected from the date of belatacept infusion until May 2020. Ten HIV + kidney transplant recipients were identified, who were converted to belatacept a median of 364 days post-transplant. At last follow-up (median 3.3 years), 8 patients remained on belatacept therapy, and all patients were alive with functioning allografts. Mean estimated glomerular filtration rates (eGFR) improved from 31.6 mL/min at baseline to 42.8 mL/min at 1 year (P = .03). Two patients developed acute rejection, with one necessitating conversion back to tacrolimus. All patients maintained undetectable HIV-1 viral loads at last follow-up. One patient each developed pneumocystis pneumonia and Kaposi sarcoma following conversion, which were responsive to standard medical therapy. In our cohort of stable HIV + kidney transplant recipients, conversion to belatacept was associated with excellent early patient and allograft survival and improved eGFR at 1 year.     

Critical evaluation of copy number variant calling methods using DNA methylation

Recent technological and methodological developments have enabled the use of array-based DNA methylation data to call copy number variants (CNVs). ChAMP, Conumee, and cnAnalysis450k are popular methods currently used to call CNVs using methylation data. However, so far, no studies have analyzed the reliability of these methods using real samples. Data from a cohort of individuals with genotype and DNA methylation data generated using the HumanMethylation450 and MethylationEPIC BeadChips were used to assess the consistency between the CNV calls generated by methylation and genotype data. We also took advantage of repeated measures of methylation data collected from the same individuals to compare the reliability of CNVs called by ChAMP, Conumee, and cnAnalysis450k for both the methylation arrays. ChAMP identified more CNVs than Conumee and cnAnalysis450k for both the arrays and, as a consequence, had a higher overlap (~62%) with the calls from the genotype data. However, all methods had relatively low reliability. For the MethylationEPIC array, Conumee had the highest reliability (57.6%), whereas for the HumanMethylation450 array, cnAnalysis450k had the highest reliability (43.0%). Overall, the MethylationEPIC array provided significant gains in reliability for CNV calling over the HumanMethylation450 array but not for overlap with CNVs called using genotype data.     

Judicialization 2.0: Understanding right-to-health litigation in real time

Over the past two decades, debate over the whys, the hows, and the effects of the ever-expanding phenomenon of right-to-health litigation (‘judicialization’) throughout Latin America have been marked by polarised arguments and limited information. In contrast to claims of judicialization as a positive or negative trend, less attention has been paid to ways to better understand the phenomenon in real time. In this article, we propose a new approach—Judicialization 2.0—that recognises judicialization as an integral part of democratic life. This approach seeks to expand access to information about litigation on access to medicines (and health care generally) in order to better characterise the complexity of the phenomenon and thus inform new research and more robust public discussions. Drawing from our multi-disciplinary perspectives and field experiences in highly judicialized contexts, we thus describe a new multi-source, multi-stakeholder mixed-method approach designed to capture the patterns and heterogeneity of judicialization and understand its medical and socio-political impact in real time, along with its counterfactuals. By facilitating greater data availability and open access, we can drive advancements towards transparent and participatory priority setting, as well as accountability mechanisms that promote quality universal health coverage.