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Record W6964063188 · doi:10.25384/sage.c.6355657

Findings of Sodium-Glucose Cotransporter-2 Inhibitor Kidney Outcome Trials Applied to a Canadian Chronic Kidney Disease Population: A Retrospective Cohort Study

2022· other· en· W6964063188 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsKidney diseaseRenal functionRetrospective cohort studyCohortDiabetic nephropathyAlbuminuriaCohort studyNephrologyDiabetes mellitus

Abstract

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Background:The canagliflozin and renal endpoints in diabetes with established nephropathy clinical evaluation (CREDENCE) and dapagliflozin and prevention of adverse outcomes in chronic kidney disease (DAPA-CKD) trials have demonstrated significant kidney benefits with sodium-glucose cotransporter-2 (SGLT2) inhibitors. SGLT2 inhibitors are now standard of care for patients with diabetic kidney disease and have also been shown to be effective in those with albuminuric CKD with or without diabetes.Objective:We sought to determine how many patients in nephrology care in British Columbia, Canada, would have been eligible for those trials, to compare rates of outcomes, and to estimate cost avoidance arising from widespread use of SGLT2 inhibitors in this cohort.Study design:Retrospective cohort study.Setting:British Columbia, Canada.Participants:CKD patients followed in the Kidney Care Clinics in British Columbia.Measurements:We compared the outcomes of kidney failure, sustained estimated glomerular filtration rate (eGFR) <15 mL/min/1.73 m2, dialysis, transplant, death from any cause, and doubling of serum creatinine. We also compared the composite outcome of kidney failure and doubling of serum creatinine.Methods:The cohort was derived using a provincial database by combining the inclusion criteria of CREDENCE and DAPA-CKD trials. We included adult patients aged ≥18 years, urine albumin to creatinine ratio (UACR) ≥20 mg/mmol, and eGFR between 25 and 90 mL/min/1.73 m2, between April 1, 2014 and March 31, 2017. The primary outcome was compared with the outcomes experienced in the placebo arms of CREDENCE and DAPA-CKD. The composite outcome stratified by eGFR categories were compared in the British Columbia cohort and the CREDENCE trial. Cost avoidance was estimated based on the number needed to treat to prevent one instance of kidney failure.Results:A total of 17.5% (3138/17 963) of patients were eligible, resulting in a cohort with a mean age of 69.7 years and 38% women. The eGFR slope of the British Columbia cohort was −4.21 ± 0.47 mL/min. The mean eGFR was 37.0 mL/min/1.73 m2, median UACR was 55.3 mg/mmol, and use of renin-angiotensin-aldosterone system inhibitors was 56.6%. The British Columbia cohort experienced nearly double the outcomes of kidney failure, death from any cause, and doubling of serum creatinine than the placebo arms of CREDENCE and DAPA-CKD. When stratified by eGFR, the British Columbia cohort and the CREDENCE placebo arm had similar event rates for those with an eGFR <45 mL/min but there were still higher rates of outcome in the greater than 45 mL/min eGFR groups in the British Columbia cohort. Treating the British Columbia cohort with canagliflozin could lead to net cost avoidance of $2.31 million over 2.6 years.Limitations:The database only captures those referred to the Kidney Care Clinics by nephrologists, which may lead to selection bias of higher risk patients in the British Columbia cohort. The cost avoidance analysis was a limited high-level analysis.Conclusions:The British Columbia cohort represents a high-risk group in whom implementation of the use of SGLT2 inhibitors may well improve outcomes and reduce health care system costs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.010
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.053
GPT teacher head0.336
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207