Sodium-Glucose Cotransporter-2 Inhibitor Use and the Risk of Acute Kidney Injury in Older Adults in Routine Clinical Practice: A Population-Based Cohort Study
Bibliographic record
Abstract
Regulatory agencies warn about acute kidney injury (AKI) risk following sodium-glucose cotransporter-2 (SGLT2) inhibitor use. This population-based retrospective cohort study in Ontario, Canada quantified the 90-day AKI risk in older adults who were newly dispensed either SGLT2 inhibitors or dipeptidyl peptidase-4 (DPP4) inhibitors in an outpatient setting between 2015 and 2017. Risk ratios (RR) were obtained using modified Poisson regression and risk differences using binomial regression. Relative to new use of a DPP4 inhibitor, initiation of an SGLT2 inhibitor was associated with a lower 90-day risk of a hospital encounter with AKI: 216 events in 19,611 patients (1.10%) versus 388 events in 19,483 patients (1.99%); weighted RR 0.79 (95% confidence interval 0.64–0.98). In routine care of older adults, new SGLT2 inhibitor use was associated with lower risk of AKI. Together with previous evidence, these findings suggest that regulatory warnings about AKI risk with SGLT2 inhibitors may be unwarranted.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".