Evidence map›Paper›PMID 35937973›Full record

ReviewTherapeutics and clinical risk management2022

Role of Finerenone in the Treatment of Diabetic Kidney Disease: Patient Selection and Clinical Perspectives.

Aisha Shaikh, Justina Ray, Kirk N Campbell

Open access · goldAbstract readReview
In one paragraph

Review in Therapeutics and clinical risk management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Diabetic kidney disease, biomarkers, and finerenone.Diabetes, obesity & metabolism · 2026
    Review
  4. Finerenone in mildly reduced or preserved ejection fraction and chronic kidney disease: a narrative review.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Terpenes in the management of chronic kidney disease.Naunyn-Schmiedeberg's archives of pharmacology · 2024
    Review
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Aisha ShaikhDepartment of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Justina RayDepartment of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0001-9665-6968
Kirk N CampbellDepartment of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Icahn School of Medicine at Mount Sinai · USMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Diabetes is the leading cause of chronic and end stage kidney disease globally. Despite recent advances in therapies for diabetic kidney disease (DKD), there remains a critical need for additional options to improve renal and cardiovascular outcomes. Mineralocorticoid overactivation contributes to inflammation and fibrosis which in turn leads to progression of DKD. Finerenone, a novel non-steroidal mineralocorticoid receptor antagonist, has shown promising cardiac and renoprotective benefits in DKD. The utility of finerenone in the real world will require appropriate patient selection and patient monitoring by clinicians.

Indexed as

chronic kidney diseasediabetesfinerenone

Identifiers

PMID35937973
PMCPMC9346301
OpenAlexW4288518659

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.