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Introduction: Patients with chronic health conditions, particularly chronic kidney disease, are at heightened risk for psychiatric disorders; yet, there are limited data on those with primary glomerular disease. Methods: This study included patients with glomerular disease enrolled in the kidney research network multisite patient registry. Registry data include encounter, diagnoses, medication, laboratory, and vital signs data extracted from participants’ electronic health records. ICD-9/10 diagnosis codes were used to identify a subset of psychiatric disorders focused on anxiety, mood, and behavioral disorders. Time-varying Cox proportional hazard models were used to analyze time from the onset of kidney disease to diagnosis of psychiatric disorder. Adjusted models retained significant covariates from the full list of potential confounders, including age, sex, race, ethnicity, time-varying treatment, the estimated glomerular filtration rate, and proteinuria (urine protein-to-creatinine ratio [UPCR]). Analogous models examined diagnosis of psychiatric disorder as a predictor of time to end-stage kidney disease (ESKD). Results: Data were available for 950 participants, with a median of 58 months of follow-up. 110 (12%) participants were diagnosed with psychiatric disorder during the follow-up. The estimated rate of psychiatric diagnosis after kidney disease was 14.7 cases per 1,000 person-years and was highest among those of adolescent age at the time of kidney disease diagnosis. Adjusted analyses found adolescent age (vs. adult, hazard ratio [HR] = 3.11, 95% confidence interval [CI] 1.87–5.17) and Asian race (vs. white, HR = 0.34, 95% CI 0.16–0.71) were associated with psychiatric diagnosis. A higher UPCR per 1 log unit (HR 1.13, 95% CI 1.01–1.27) and a higher total number of oral medications were associated with psychiatric disorder (p < 0.001). Psychiatric diagnosis was also associated with progression to ESKD (HR = 2.45, 95% CI 1.53–3.92) in adjusted models. Discussion/Conclusion: Psychiatric disorders were documented in approximately one-eighth of patients with glomerular disease and correlated with clinical disease characteristics such as age, race, proteinuria, and oral medication burden. These findings suggest mental health screening is warranted in patients of all ages with glomerular disease.

Background and Objective: The use of electronic health record (EHR) data can facilitate efficient research and quality initiatives. The imprecision of ICD-10 codes for kidney diagnoses has been an obstacle to discrete data-defined diagnoses in the EHR. This manuscript describes the Kidney Research Network (KRN) registry and database that provide an example of a prospective, real-world data glomerular disease registry for research and quality initiatives. Methods: KRN is a multicenter collaboration of patients, physicians, and scientists across diverse health-care settings with a focus on improving treatment options and outcomes for patients with glomerular disease. The registry and data warehouse amasses retrospective and prospective data including EHR, active research study, completed clinical trials, patient reported outcomes, and other relevant data. Following consent, participating sites enter the patient into KRN and provide a physician-confirmed primary kidney diagnosis. Kidney biopsy reports are redacted and uploaded. Site programmers extract local EHR data including demographics, insurance type, zip code, diagnoses, encounters, laboratories, procedures, medications, dialysis/transplant status, vitals, and vital status monthly. Participating sites transform data to conform to a common data model prior to submitting to the Data Analysis and Coordinating Center (DACC). The DACC stores and reviews each site’s EHR data for quality before loading into the KRN database. Results: As of January 2021, 1,192 patients have enrolled in the registry. The database has been utilized for research, clinical trial design, clinical trial end point validation, and supported quality initiatives. The data also support a dashboard allowing enrolling sites to assist with clinical trial enrollment and population health initiatives. Conclusion: A multicenter registry using EHR data, following physician- and biopsy-confirmed glomerular disease diagnosis, can be established and used effectively for research and quality initiatives. This design provides an example which may be readily replicated for other rare or common disease endeavors.

Rationale & Objective: The objective of the study was to estimate the prevalence of hypertension in patients with proteinuric kidney disease and evaluate blood pressure (BP) control. Study Design: Retrospective cohort study. Setting & Participants: Data from adults and children with proteinuric kidney disease enrolled in the multicenter Kidney Research Network Registry were used for this study. Exposure: Proteinuric kidney disease. Outcomes: Hypertension and BP control. Analytical Approach: Patients with white-coat hypertension were excluded. Patients were censored at end-stage kidney disease onset. Patients were defined as hypertensive either by hypertension diagnosis code, having 2 or more encounters with elevated BPs, or treatment with antihypertensive therapy excluding renin-angiotensin-aldosterone system blockade. Elevated BP was defined as greater than 95th percentile for children and >140/90 mm Hg in adults. Sustained BP control was defined as 2 or more consecutive encounters with BPs lower than 95th percentile for children and

Introduction The goal of this study was to assess the occurrence of steroid-associated adverse events (SAAE) in patients with primary proteinuric kidney disease. Methods The Kidney Research Network Registry consists of children and adults with primary proteinuric kidney disease. SAAEs of interest were hypertension, hyperglycemia and diabetes, overweight and obesity, short stature, ophthalmologic complications, bone disorders, infections, and psychosis. Events were identified using International Classification of Diseases, Ninth Revision/Tenth Revision codes, blood pressures, growth parameters, laboratory values, and medications. Poisson generalized estimating equations tested the association between steroid onset and dose on SAAE risk. Results A total of 884 participants were included in the analysis; 534 (60%) were treated with steroids. Of these, 62% had at least one SAAE. The frequency of any SAAE after initiation of steroids was 293 per 1000 person-years. The most common SAAEs were hypertension (173.7 per 1000 person-years), diabetes (78.7 per 1000 person-years), obesity (66.8 per 1000 person-years), and infections (46.1 per 1000 person-years). After adjustment for demographics, duration of kidney disease, estimated glomerular filtration rate (eGFR), proteinuria, and other therapies, steroid exposure was associated with a 40% increase in risk of any SAAE (Relative risk [RR]: 1.4; 95% confidence interval [CI]: 1.3–1.6). A 1-mg/kg per day increase in steroid dose was associated with a 2.5-fold increase in risk of any SAAE. Conclusion Most patients with primary proteinuric kidney disease treated with steroids experienced at least one SAAE. Steroid therapy increased risk of hypertension, diabetes, weight gain, short stature, fractures, and infections after adjusting for disease-related factors. This study highlights the importance of surveillance and management of SAAE and provides rationale for the development of steroid minimization protocols., Graphical abstract

Background: Patients with chronic health conditions are at heightened risk for psychiatric disorders; yet, little is known about the occurrence of psychiatric disorders or associations with patient and disease characteristics in glomerular disease.Methods: This study included patients with glomerular disease enrolled in the Kidney Research Network multisite patient registry. Registry data includes encounter, diagnoses, medication, lab, and vital signs data extracted from participants’ electronic health records. ICD9/10 diagnosis codes were used to identify subset of psychiatric disorders focused on anxiety, mood, and behaviorial disorders. Time-varying Cox proportional hazards models were used to analyze time from onset of kidney disease to diagnosis of psychiatric disorder. Models adjusted for age, sex, race, ethnicity, and time-varying treatment, estimated glomerular filtration rate (eGFR), and proteinuria. Analogous models examined diagnosis of psychiatric disorder as a predictor of time to end stage kidney disease (ESKD).Results: Data were available for 943 participants with a median of 58 months of follow-up. 109 (12%) participants were ever diagnosed with a psychiatric disorder during follow up. Estimated risk of psychiatric diagnosis after kidney disease was 14.7 cases per 1,000 person-years, and was highest among adolescents. Adjusted analyses found adolescent age (vs. Adult, HR=2.03, CI=1.23-3.35), Asian race (vs. White, HR=0.34, 95% CI=0.16-0.70) and steroid therapy (HR=2.27, 95% CI=1.53-3.38) were associated with psychiatric diagnosis. Psychiatric diagnosis was also associated with progression to ESKD (HR=2.47, 95% CI=1.55-3.95) after adjusting for kidney diagnosis, eGFR at onset, proteinuria over time, and steroid therapy.Discussion: Psychiatric disorders were documented in approximately one eighth of patients with glomerular disease and correlated with clinical disease characteristics. Conclusions: These findings suggest mental health screening may be warranted in patients with glomerular disease.

Introduction NephCure Accelerating Cures Institute (NACI) is a collaborative organization sponsored by NephCure Kidney International and the University of Michigan. The Institute is composed of 7 cores designed to improve treatment options and outcomes for patients with glomerular disease: Clinical Trials Network, Data Warehouse, Patient-Reported Outcomes (PRO) and Endpoints Consortium, Clinical Trials Consulting Team, Quality Initiatives, Education and Engagement, and Data Coordinating Center. Methods The Trials Network includes 22 community- and hospital-based nephrology practices, 14 of which are trial-only sites. Eight sites participate in the NACI Registry, and as of October 2017, 1054 patients are enrolled with diagnoses including but not limited to focal segmental glomerulosclerosis, minimal change disease, membranous nephropathy, IgA nephropathy, and childhood-onset nephrotic syndrome. By using electronic health record data extraction, robust and efficient clinical data are captured while minimizing the burden to site-based network staff. Results The Data Warehouse includes her-extracted data from registry patients, PRO development data, and data from completed observational studies and clinical trials. The Clinical Trial Consulting Team provides support for trial design in rare diseases leveraging these data. The PRO and Endpoints Consortium develops shorter-term endpoints while capturing the patient-reported significance of interventions under study. The Quality Initiatives and Education/Engagement cores elevate the level of care for patients. The Data Coordinating Center manages the analysis and operations of the Institute. Conclusion By engaging with patients, academia, industry, and patient advocate community representatives, including our Patient Advisory Board, NACI strives for better outcomes and treatments using evidence-based support for clinical trial design.