Comparative safety and cardiovascular effectiveness of sodium‐glucose cotransporter‐2 inhibitors and glucagon‐like peptide‐1 receptor agonists in nursing homes
Bibliographic record
Abstract
AIM: Studies examining the safety and effectiveness of sodium-glucose cotransporter-2 inhibitors (SGLT2is) versus glucagon-like peptide-1 receptor agonists (GLP-1RAs) among community-dwelling adults may not generalize to nursing home (NH) residents, who are typically older and more multimorbid. We compared the safety and cardiovascular effectiveness of SGLT2is and GLP-1RAs among US NH residents. MATERIALS AND METHODS: Eligible individuals were aged ≥66 years with type 2 diabetes mellitus and initiated an SGLT2i or GLP-1RA in an NH between 2013 and 2018. Safety outcomes included fall-related injuries, hypoglycaemia, diabetic ketoacidosis (DKA), urinary tract infection or genital infection, and acute kidney injury in the year following treatment initiation. Cardiovascular effectiveness outcomes included death, major adverse cardiovascular events and hospitalization for heart failure. Per-protocol adjusted hazard ratios (HR) were calculated using stabilized inverse probability of treatment and censoring weighted cause-specific hazard regression models accounting for 127 covariates. RESULTS: The study population included 7710 residents (31.08% SGLT2i, 68.92% GLP-1RA). Compared with GLP-1RA initiators, SGLT2i initiators had higher rates of DKA (HR 1.95, 95% confidence limits 1.27, 2.99) and death (HR 1.18, 95% confidence limits 1.02, 1.36). Rates of urinary tract infection or genital infection, acute kidney injury, major adverse cardiovascular events, and heart failure were also elevated, while rates of fall-related injuries and hypoglycaemia were reduced, but all estimates were imprecise and highly compatible with no difference. CONCLUSIONS: SGLT2is do not have superior, and may have inferior, effectiveness compared with GLP-1RAs for cardiovascular and mortality outcomes in NH residents. Residents initiating SGLT2is should be monitored closely for DKA.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".