Rationale and Design of a Phase 2, Double-blind, Placebo-Controlled, Randomized Trial Evaluating AMP Kinase-Activation by Metformin in Focal Segmental Glomerulosclerosis

Introduction

Focal segmental glomerulosclerosis (FSGS), the most common primary glomerular disease leading to end-stage kidney disease (ESKD), is characterized by podocyte injury and depletion, whereas minimal change disease (MCD) has better outcomes despite podocyte injury. Identifying mechanisms capable of preventing podocytopenia during injury could transform FSGS to an "MCD-like" state. Preclinical data have reported conversion of an MCD-like injury to one with podocytopenia and FSGS by inhibition of AMP-kinase (AMPK) in podocytes. Conversely, in FSGS, AMPK-activation using metformin (MF) mitigated podocytopenia and azotemia. Observational studies also support beneficial effects of MF on proteinuria and chronic kidney disease (CKD) outcomes in diabetes. A randomized controlled trial (RCT) to test MF in podocyte injury with FSGS has not yet been conducted.

Methods

We report the rationale and design of phase 2, double-blind, placebo-controlled RCT evaluating the efficacy and safety of MF as adjunctive therapy in FSGS. By randomizing 30 patients with biopsy-confirmed FSGS to MF or placebo (along with standard immunosuppression), we will study mechanistic biomarkers that correlate with podocyte injury or depletion and evaluate outcomes after 6 months. We specifically integrate novel urine, blood, and tissue markers as surrogates for FSGS progression along with unbiased profiling strategies.

Results and Conclusion

Our phase 2 trial will provide insight into the potential efficacy and safety of MF as adjunctive therapy in FSGS-a crucial step to developing a larger phase 3 study. The mechanistic assays here will guide the design of other FSGS trials and contribute to understanding AMPK activation as a potential therapeutic target in FSGS. By repurposing an inexpensive agent, our results will have implications for FSGS treatment in resource-poor settings.

A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease

INTRODUCTION/OBJECTIVE

The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient's risk for a progressive decline in kidney function over 5 years. We report the 1-year pre- and post-test clinical impact on care management, eGFR slope, and A1C along with engagement of population health clinical pharmacists and patient coordinators to promote a program of sustainable kidney, metabolic, and cardiac health.

METHODS

The KidneyIntelX in vitro prognostic test was previously validated for patients with type 2 diabetes and diabetic kidney disease (DKD) to predict kidney function decline within 5 years was introduced into the RWE study (NCT04802395) across the Health System as part of a population health chronic disease management program from [November 2020 to April 2023]. Pre- and post-test patients with a minimum of 12 months of follow-up post KidneyIntelX were assessed across all aspects of the program.

RESULTS

A total of 5348 patients with DKD had a KidneyIntelX assay. The median age was 68 years old, 52% were female, 27% self-identified as Black, and 89% had hypertension. The median baseline eGFR was 62 ml/min/1.73 m2, urine albumin-creatinine ratio was 54 mg/g, and A1C was 7.3%. The KidneyIntelX risk level was low in 49%, intermediate in 40%, and high in 11% of cases. New prescriptions for SGLT2i, GLP-1 RA, or referral to a specialist were noted in 19%, 33%, and 43% among low-, intermediate-, and high-risk patients, respectively. The median A1C decreased from 8.2% pre-test to 7.5% post-test in the high-risk group (P < .001). UACR levels in the intermediate-risk patients with albuminuria were reduced by 20%, and in a subgroup treated with new scripts for SGLT2i, UACR levels were lowered by approximately 50%. The median eGFR slope improved from -7.08 ml/min/1.73 m2/year to -4.27 ml/min/1.73 m2/year in high-risk patients (P = .0003), -2.65 to -1.04 in intermediate risk, and -3.26 ml/min/1.73 m2/year to +0.45 ml/min/1.73 m2/year in patients with low-risk (P < .001).

CONCLUSIONS

Deployment and risk stratification by KidneyIntelX was associated with an escalation in action taken to optimize cardio-kidney-metabolic health including medications and specialist referrals. Glycemic control and kidney function trajectories improved post-KidneyIntelX testing, with the greatest improvements observed in those scored as high-risk.

Real World Evidence and Clinical Utility of KidneyIntelX on Patients With Early-Stage Diabetic Kidney Disease: Interim Results on Decision Impact and Outcomes

INTRODUCTION AND OBJECTIVE

The lack of precision to identify patients with early-stage diabetic kidney disease (DKD) at near-term risk for progressive decline in kidney function results in poor disease management often leading to kidney failure requiring unplanned dialysis. The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to generate a risk score for progressive decline in kidney function over 5-year in adults with early-stage DKD. Our objective was to assess the impact of KidneyIntelX on management and outcomes in a Health System in the real-world evidence (RWE) study.

METHODS

KidneyIntelX was introduced into a large metropolitan Health System via a population health-defined approved care pathway for patients with stages 1 to 3 DKD between [November 2020 to March 2022]. Decision impact on visit frequency, medication management, specialist referral, and selected lab values was assessed. We performed an interim analysis in patients through 6-months post-test date to evaluate the impact of risk level with clinical decision-making and outcomes.

RESULTS

A total of 1686 patients were enrolled in the RWE study and underwent KidneyIntelX testing and subsequent care pathway management. The median age was 68 years, 52% were female, 26% self-identified as Black, and 94% had hypertension. The median baseline eGFR was 59 ml/minute/1.73 m², urine albumin-creatinine ratio was 69 mg/g, and HbA1c was 7.7%. After testing, a clinical encounter in the first month occurred in 13%, 43%, and 53% of low-risk, intermediate-risk, and high-risk patients, respectively and 46%, 61%, and 71% had at least 1 action taken within the first 6 months. High-risk patients were more likely to be placed on SGLT2 inhibitors (OR = 4.56; 95% CI 3.00-6.91 vs low-risk), and more likely to be referred to a specialist such as a nephrologist, endocrinologist, or dietician (OR = 2.49; 95% CI 1.53-4.01) compared to low-risk patients.

CONCLUSIONS

The combination of KidneyIntelX, clinical guidelines and educational support resulted in changes in clinical management by clinicians. After testing, there was an increase in visit frequency, referrals for disease management, and introduction to guideline-recommended medications. These differed by risk category, indicating an impact of KidneyIntelX risk stratification on clinical care.

Home Dialysis: A Majority Chooses It, a Minority Gets It

INTRODUCTION

When choosing a modality for outpatient renal replacement therapy, patients and medical providers have 3 options to choose from in-center hemodialysis (HD), home HD (HHD), and peritoneal dialysis (PD). In 2017, just over 10% of incident ESKD patients were on a home dialysis modality. We set out to determine outcomes of dialysis modality education in both pre-dialysis and dialysis patients. Moreover, we examined barriers that preclude patients from choosing home dialysis.

METHODS

This was a single-center, retrospective study looking at patients who were referred to the CKD educator for dialysis modality education between January 1, 2019, and March 31, 2020. Patient demographics, preferred language of communication, stage of renal disease, and reasons for patients' refusal to undertake a home dialysis modality were recorded. Patients' average household income and driving distance to our home dialysis unit were calculated using their home zip code.

RESULTS

167 patients were referred for CKD education. Mean age was 60 years, and 59% male, 42% African American, 22% White, 7% Asian, and 28% were Hispanic or Latino. Only 23% of the total cohort chose in-center HD, while 74% chose a home dialysis modality (59% PD and 15% HHD), and the remaining patients remained undecided. 56% of in-center HD patients chose a home dialysis modality. The most commonly cited barriers to home dialysis were lack of a care partner, lack of home space, and patient preference.

LIMITATIONS

Over 90% of our patients reside in NY City where home space is limited. We require in our home HD program that patients have a trained care partner present during their treatments. We cannot assume that all CKD stage-4 patients or higher were either referred for CKD education or followed through on the referral.

CONCLUSIONS

A large discrepancy between informed patients' choices and the reality of the current dialysis landscape. Absence of a care partner, lack of home space, and patients not deemed appropriate surgical candidates were the main driving forces in their not opting for a home modality.

Acute Kidney Injury in Hospitalized Patients with COVID-19

IMPORTANCE

Preliminary reports indicate that acute kidney injury (AKI) is common in coronavirus disease (COVID)-19 patients and is associated with worse outcomes. AKI in hospitalized COVID-19 patients in the United States is not well-described.

OBJECTIVE

To provide information about frequency, outcomes and recovery associated with AKI and dialysis in hospitalized COVID-19 patients.

DESIGN

Observational, retrospective study.

SETTING

Admitted to hospital between February 27 and April 15, 2020.

PARTICIPANTS

Patients aged ≥18 years with laboratory confirmed COVID-19 Exposures: AKI (peak serum creatinine increase of 0.3 mg/dL or 50% above baseline). Main Outcomes and Measures: Frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aOR) with mortality. We also trained and tested a machine learning model for predicting dialysis requirement with independent validation.

RESULTS

A total of 3,235 hospitalized patients were diagnosed with COVID-19. AKI occurred in 1406 (46%) patients overall and 280 (20%) with AKI required renal replacement therapy. The incidence of AKI (admission plus new cases) in patients admitted to the intensive care unit was 68% (553 of 815). In the entire cohort, the proportion with stages 1, 2, and 3 AKI were 35%, 20%, 45%, respectively. In those needing intensive care, the respective proportions were 20%, 17%, 63%, and 34% received acute renal replacement therapy. Independent predictors of severe AKI were chronic kidney disease, systolic blood pressure, and potassium at baseline. In-hospital mortality in patients with AKI was 41% overall and 52% in intensive care. The aOR for mortality associated with AKI was 9.6 (95% CI 7.4-12.3) overall and 20.9 (95% CI 11.7-37.3) in patients receiving intensive care. 56% of patients with AKI who were discharged alive recovered kidney function back to baseline. The area under the curve (AUC) for the machine learned predictive model using baseline features for dialysis requirement was 0.79 in a validation test.

CONCLUSIONS AND RELEVANCE

AKI is common in patients hospitalized with COVID-19, associated with worse mortality, and the majority of patients that survive do not recover kidney function. A machine-learned model using admission features had good performance for dialysis prediction and could be used for resource allocation.

[A case of malignant hemangioendothelioma effectively treated with intra-arterial continuous infusion of interleukin-2]

An 82-year-old female presented with a tumor in the right-frontal region and was diagnosed as MHE, based on the clinical and pathological findings. Increased LAK (lymphokine-activated killer cell) activity was observed during treatment with intraarterial continuous infusion of rIL-2. In addition, the decrease in tumor size was started when LAK activity became high. Treatments for MHE and mechanism of these therapies were discussed using data from this case and other authors' reports.