Treatment with patiromer decreases aldosterone in patients with chronic kidney disease and hyperkalemia on renin-angiotensin system inhibitors

Elevated serum aldosterone can be vasculotoxic and facilitate cardiorenal damage. Renin-angiotensin system inhibitors reduce serum aldosterone levels and/or block its effects but can cause hyperkalemia. Patiromer, a nonabsorbed potassium binder, decreases serum potassium in patients with chronic kidney disease on renin-angiotensin system inhibitors. Here we examined the effect of patiromer treatment on serum aldosterone, blood pressure, and albuminuria in patients with chronic kidney disease on renin-angiotensin system inhibitors with hyperkalemia (serum potassium 5.1–6.5 mEq/l). We analyzed data from the phase 3 OPAL-HK study (4-week initial treatment phase of 243 patients; 8-week randomized withdrawal phase of 107 patients). In the treatment phase, the (mean ± standard error) serum potassium was decreased concordantly with the serum aldosterone (−1.99 ± 0.51 ng/dl), systolic/diastolic blood pressure (−5.64 ± 1.04 mm Hg/−3.84 ± 0.69 mm Hg), and albumin-to-creatinine ratio (−203.7 ± 54.7 mg/g), all in a statistically significant manner. The change in the plasma renin activity (−0.44 ± 0.63 μg/l/hr) was not significant. In the withdrawal phase, mean aldosterone levels were sustained with patiromer (+0.23 ± 1.07 ng/dl) and significantly increased with placebo (+2.78 ± 1.25 ng/dl). Patients on patiromer had significant reductions in mean systolic/diastolic blood pressure (−6.70 ± 1.59/−2.15 ± 1.06 mm Hg), whereas those on placebo did not (−1.21 ± 1.89 mm Hg/+1.72 ± 1.26 mm Hg). Significant changes in plasma renin activity were found only in the placebo group (–3.90 ± 1.41 μg/l/hr). Thus, patiromer reduced serum potassium and aldosterone levels independent of plasma renin activity in patients with chronic kidney disease and hyperkalemia on renin-angiotensin system inhibitors

Patiromer to Enable Spironolactone Use in the Treatment of Patients with Resistant Hypertension and Chronic Kidney Disease: Rationale and Design of the AMBER Study

BACKGROUND: While chronic kidney disease (CKD) is common in resistant hypertension (RHTN), prior studies -evaluating mineralocorticoid receptor antagonists excluded patients with reduced kidney function due to risk of hyperkalemia. AMBER (ClinicalTrials.gov identifier NCT03071263) will evaluate if the potassium-binding polymer patiromer used concomitantly with spironolactone in patients with RHTN and CKD prevents hyperkalemia and allows more persistent spironolactone use for hypertension management. METHODS: Randomized, double-blind, placebo-controlled parallel group 12-week study of patiromer and spironolactone versus placebo and spironolactone in patients with uncontrolled RHTN and CKD. RHTN is defined as unattended systolic automated office blood pressure (AOBP) of -135-160 mm Hg during screening despite taking ≥3 antihypertensives, including a diuretic, and an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker -(unless not tolerated or contraindicated). The CKD inclusion criterion is an estimated glomerular filtration rate (eGFR) of 25 to ≤45 mL/min/1.73 m2. Screening serum potassium must be 4.3-5.1 mEq/L. The primary efficacy endpoint is the between-group difference (spironolactone plus patiromer versus spironolactone plus placebo) in the proportion of patients remaining on spironolactone at Week 12. RESULTS: Baseline characteristics have been analyzed as of March 2018 for 146 (of a targeted 290) patients. Mean (SD) baseline age is 69.3 (10.9) years; 52.1% are male, 99.3% White, and 47.3% have diabetes. Mean (SD) baseline serum potassium is 4.68 (0.25) mEq/L, systolic AOBP is 144.3 (6.8) mm Hg, eGFR is 35.7 (7.7) mL/min/1.73 m2. CONCLUSION: AMBER will define the ability of patiromer to facilitate the use of spironolactone, an effective antihypertensive therapy for patients with RHTN and CKD

Effect of patiromer on reducing serum potassium and preventing recurrent hyperkalaemia in patients with heart failure and chronic kidney disease on RAAS inhibitors

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115921/1/ejhf402_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115921/2/ejhf402.pd

Long‐term effects of patiromer for hyperkalaemia treatment in patients with mild heart failure and diabetic nephropathy on angiotensin‐converting enzymes/angiotensin receptor blockers: results from AMETHYST‐DN

AimsChronic kidney disease (CKD) in heart failure (HF) increases the risk of hyperkalaemia (HK), limiting angiotensin‐converting enzyme inhibitor (ACE‐I) or angiotensin receptor blocker (ARB) use. Patiromer is a sodium‐free, non‐absorbed potassium binder approved for HK treatment. We retrospectively evaluated patiromer’s long‐term safety and efficacy in HF patients from AMETHYST‐DN.Methods and resultsPatients with Type 2 diabetes, CKD, and HK [baseline serum potassium >5.0–5.5 mmol/L (mild) or >5.5–88%) and moderate (≥73%) HK had normokalaemia at each visit from Weeks 12 to 52. Three HF patients were withdrawn because of high (n = 1) or low (n = 2) serum potassium. The most common patiromer‐related adverse event was hypomagnesaemia (8.6%).ConclusionsIn patients with a clinical diagnosis of HF, diabetes, CKD, and HK on ACE‐I/ARB, patiromer was well tolerated and effective for HK treatment over 52 weeks.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145406/1/ehf212292.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145406/2/ehf212292_am.pd

Peginesatide in patients with anemia undergoing hemodialysis

BACKGROUND: Peginesatide, a synthetic peptide-based erythropoiesis- stimulating agent (ESA), is a potential therapy for anemia in patients with advanced chronic kidney disease. METHODS: We conducted two randomized, controlled, open-label studies (EMERALD 1 and EMERALD 2) involving patients undergoing hemodialysis. Cardiovascular safety was evaluated by analysis of an adjudicated composite safety end point - death from any cause, stroke, myocardial infarction, or serious adverse events of congestive heart failure, unstable angina, or arrhythmia - with the use of pooled data from the two EMERALD studies and two studies involving patients not undergoing dialysis. In the EMERALD studies, 1608 patients received peginesatide once monthly or continued to receive epoetin one to three times a week, with the doses adjusted as necessary to maintain a hemoglobin level between 10.0 and 12.0 g per deciliter for 52 weeks or more. The primary efficacy end point was the mean change from the baseline hemoglobin level to the mean level during the evaluation period; noninferiority was established if the lower limit of the two-sided 95% confidence interval was -1.0 g per deciliter or higher in the comparison of peginesatide with epoetin. The aim of evaluating the composite safety end point in the pooled cohort was to exclude a hazard ratio with peginesatide relative to the comparator ESA of more than 1.3. RESULTS: In an analysis involving 693 patients from EMERALD 1 and 725 from EMERALD 2, peginesatide was noninferior to epoetin in maintaining hemoglobin levels (mean between-group difference, -0.15 g per deciliter; 95% confidence interval [CI], -0.30 to -0.01 in EMERALD 1; and 0.10 g per deciliter; 95% CI, -0.05 to 0.26 in EMERALD 2). The hazard ratio for the composite safety end point was 1.06 (95% CI, 0.89 to 1.26) with peginesatide relative to the comparator ESA in the four pooled studies (2591 patients) and 0.95 (95% CI, 0.77 to 1.17) in the EMERALD studies. The proportions of patients with adverse and serious adverse events were similar in the treatment groups in the EMERALD studies. The cardiovascular safety of peginesatide was similar to that of the comparator ESA in the pooled cohort. CONCLUSIONS: Peginesatide, administered monthly, was as effective as epoetin, administered one to three times per week, in maintaining hemoglobin levels in patients undergoing hemodialysisSupported by Affymax and Takeda Pharmaceutica

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

DNA Fingerprinting

The purpose of this IQP was to trace the development and progress of DNA fingerprinting technology as it continues to be a integral part of judicial systems and societies world-wide. Much of the initial DNA fingerprinting methods and techniques have undergone substantial improvements to satiate the bombardment of skeptics, giving the technology more credibility in courts. However, there is still the unresolved issue of privacy laws that continue to complicate the issue of who should submit samples to DNA databases.