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Record W4415425251 · doi:10.1093/ndt/gfaf116.0918

#1608 Glucagon-like peptide-1 receptor agonists and the risk of emergency department visits and hospitalization in patients across the spectrum of kidney disease

2025· article· en· W4415425251 on OpenAlexaffabout
Kevin Yau, David Z.I. Cherney, Ron Wald

Bibliographic record

VenueNephrology Dialysis Transplantation · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmergency departmentPropensity score matchingKidney diseaseHazard ratioCohortRetrospective cohort studyProportional hazards modelMedical prescription

Abstract

fetched live from OpenAlex

Abstract Background and Aims Glucagon-like-peptide-1 receptor agonists (GLP1RA) have emerged as a therapy that promotes weight loss and confers cardiorenal protection. While recent trials have suggested benefit on heart failure hospitalizations; their effects on all-cause emergency department (ED) visits and hospitalizations have not been well characterized. In this population-based study we examined the effect of initiating a GLP1RA versus a dipeptidyl peptidase 4 inhibitor (DPP4i) on ED visits and all-cause hospitalization in patients across the spectrum of chronic kidney disease (CKD). Method This retrospective cohort study was conducted in Ontario, Canada, using administrative databases housed at ICES. We included a cohort of patients aged ≥18 years with eGFR <90 ml/min/1.73 m2 who received a first prescription of a GLP1RA or DPP4i through the Ontario Drug Benefit between September 30, 2019 to December 31, 2021. Follow-up extended until June 30, 2022. We used inverse probability of treatment weighting (IPTW) based on a propensity score conditioned on 72 covariates to address confounding. We evaluated the effect of GLP1RA initiation on all cause ED visits and hospitalization using time-to-recurrent-event approaches with the Prentice-Williams-Peterson (PWP) gap time model which assumes an event-specific hazard for each ED encounter or hospitalization. In an additional analysis, we evaluated recurrent ED visits and/or hospitalizations using the Andersen-Gill extension of the Cox proportional hazards model and robust sandwich estimators to obtain the 95% confidence intervals. Results The study cohort included 24,576 patients who were new users of a GLP1RA, and 23,600 who were new users of a DPP-4i eGFR <90 ml/min/1.73 m2. Baseline characteristics were balanced between groups (mean age of 69 years, 50% female, 92% with type 2 diabetes mellitus, 3.5% had heart failure, and 41% had CKD stages 3–5). Semaglutide represented 98.4% of GLP1RA prescriptions. Across the cohort, 9.6% had more than one hospitalization while 25.8% had more than one emergency department encounter. Using the PWP gap time model, new use of GLP1RA was associated with a lower risk of all-cause ED encounters or hospitalizations: HR 0.90 (95% CI, 0.87 to 0.94; P < 0.0001). This finding was consistent when we used the calendar time model (HR 0.90; 95% CI, 0.87 to 0.94) or the Andersen-Gill extension of the Cox proportional hazards model (HR 0.87; 95% CI, 0.82 to 0.92) (Table 1). Conclusion In this large population-based study, GLP1RA initiation was associated with a reduction in all-cause ED visits and/or hospitalizations when compared to DPP-4 inhibitor initiation. This finding has potentially substantial implications on health care delivery and resource utilization.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.785

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.004
GPT teacher head0.236
Teacher spread0.232 · 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
GenreEmpirical

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
Published2025
Admission routes2
Has abstractyes

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