Glucagon-Like Peptide 1 Receptor Agonists and the Risk of Emergency Department Visits and Hospitalization in Patients With Chronic Kidney Disease
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate the effect of glucagon-like peptide 1 receptor agonist (GLP-1RA) versus dipeptidyl peptidase 4 inhibitor (DPP4i) initiation on emergency department (ED) visits and all-cause hospitalizations across the spectrum of kidney disease. RESEARCH DESIGN AND METHODS: This was a retrospective population-based observational cohort study in adults with an estimated glomerular filtration rate <90 mL/min/1.73 m2 using inverse probability of treatment weighting. The Prentice-Williams-Peterson (PWP) gap time model was used for the primary analysis. RESULTS: The cohort included 24,576 new users of a GLP-1RA and 23,600 DPP4i new users. GLP-1RA initiation was associated with a lower risk of all-cause ED encounters or hospitalizations (hazard ratio [HR] 0.90; 95% CI 0.87-0.94; P < 0.0001). This finding was consistent in confirmatory analyses using the Andersen-Gill model and the PWP calendar time model. CONCLUSIONS: GLP-1RA initiation was associated with a reduction in all-cause ED visits and hospitalizations compared with new use of a DPP4i.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".