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Record W4229050598 · doi:10.1016/j.ekir.2022.04.094

Prescribing SGLT2 Inhibitors in Patients With CKD: Expanding Indications and Practical Considerations

2022· review· en· W4229050598 on OpenAlexafffund
Kevin Yau, Atit Dharia, Ibrahim Alrowiyti, David Z.I. Cherney

Bibliographic record

VenueKidney International Reports · 2022
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchKing Abdulaziz UniversityDepartment of Medicine, University of TorontoDiabetes Canada
KeywordsMedicineAlbuminuriaKidney diseaseRenal functionInternal medicineDiabetes mellitusAdverse effectIntensive care medicineUrologyEndocrinology

Abstract

fetched live from OpenAlex

SGLT2 inhibitors have emerged as a key disease-modifying therapy to prevent the progression of chronic kidney disease (CKD). These agents prevent decline in kidney function through reduction in glomerular hypertension mediated through tubuloglomerular feedback independent of their effect on glycemic control. The proliferation of clinical trials on SGLT2 inhibitors has rapidly expanded the approved clinical indications for these agents beyond patients with diabetes mellitus (DM). We review the current indications for SGLT2 inhibitors in patients with and without diabetic kidney disease, including new evidence for use in patients with heart failure with or without reduced ejection fraction, stage 4 CKD, and chronic glomerulonephritis. The EMPA-KIDNEY trial was recently stopped early for efficacy suggesting that SGLT2 inhibitors may soon be indicated for patients with CKD without albuminuria. We review practical considerations for prescription of SGLT2 inhibitors, including the anticipated acute decline in estimated glomerular filtration rate (eGFR) on initiation, initiating the lowest dosage used in clinical trials, volume status considerations, and adverse event mitigation. Combination therapy in patients with DM may be considered with agents, including glucagon-like peptide-1 receptor agonists (GLP-1-RAs), novel mineralocorticoid receptor antagonists, and selective endothelin receptor antagonists to reduce residual albuminuria and cardiovascular risk.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.857
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.344
Teacher spread0.299 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations212
Published2022
Admission routes2
Has abstractyes

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