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Record W4407190367 · doi:10.1093/ndt/gfae241

Mineralocorticoid receptor antagonism for non-diabetic kidney disease

2024· review· en· W4407190367 on OpenAlexaff
Frédéric Jaisser, Jonatan Barrera‐Chimal

Bibliographic record

VenueNephrology Dialysis Transplantation · 2024
Typereview
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersAgence Nationale de la RechercheBayer
KeywordsMedicineMineralocorticoid receptorKidney diseaseKidneyCardiorenal syndromeContext (archaeology)Renal functionInternal medicineEndocrinologyAldosterone

Abstract

fetched live from OpenAlex

The use of mineralocorticoid receptor antagonists (MRAs) in preclinical models of non-diabetic chronic kidney disease (CKD) has consistently shown a beneficial effect by preventing renal structural injury, reducing albuminuria and preserving renal function. In this context, MR activation in non-epithelial cells contributes to renal injury through the activation of inflammatory and fibrotic pathways, increasing oxidative stress and modulating renal hemodynamics. The protective effects of MRAs in animal models of CKD are not restricted to the kidney. Cardiovascular benefits, such as the prevention of cardiac fibrosis, hypoperfusion and vascular calcification, have also been observed. The translation of these preclinical findings into clinical practice has been difficult, mainly due to the lack of clinical studies testing the efficacy of steroidal MRAs in CKD patients due to their contraindication because of an increased risk of hyperkalemia in these patients. Here, we review the latest preclinical evidence showing new mechanisms by which MR inhibition results in beneficial effects against cardiorenal damage in non-diabetic kidney disease. Moreover, we summarize the clinical trials testing the safety and efficacy of steroidal and non-steroidal MRAs in patients with advanced non-diabetic CKD. PLAIN ENGLISH SUMMARY: The mineralocorticoid receptor (MR) is known for its role in the regulation of sodium and potassium balance in the distal tubules of the kidney. However, under pathological conditions the activation of the MR in other renal cell types (including the vasculature and immune cells) leads to harmful effects, damaging the main structural components of the kidney, and ultimately causing renal dysfunction. Over the past 20 years, several studies performed in mouse and rat models of non-diabetic kidney disease have shown that using a specific drug class that inhibits the MR (MR antagonists: MRAs) positively impacts the preservation of the kidney structure and helps to prevent the decline of renal function, thus positioning MRAs as a good therapeutic option against kidney diseases from non-diabetic origin. In addition, the use of MRAs also benefited the cardiovascular system health as shown by improved cardiac structural and functional parameters as well as preventing the calcification of blood vessels. Nevertheless, an important barrier to translating these findings into clinical practice is that the use of MRAs could lead to increased serum potassium levels, particularly in kidney disease patients, an adverse effect that could lead to life-threatening cardiac arrhythmias. In this review, we summarize the latest data in animal models showing new evidences of MR benefits in non-diabetic kidney disease. In addition, we review the clinical trials that evaluated the safety and efficacy of MRAs in patients with advanced non-diabetic kidney disease including those that tested a new generation of MRAs (non-steroidal MRAs) and are expected to reduce the frequency of adverse effects while retaining their renal and cardiovascular benefits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.317
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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