1228-P: Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Genital Mycotic and Urinary Tract Infections: A Population-Based Study of Older Women and Men with Diabetes
Bibliographic record
Abstract
Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are the newest class of oral diabetes medications. There are concerns of an increased risk of genitourinary infections based on trial data, however this risk at a population level is understudied. We conducted a population-based study using linked administrative databases in Ontario of women and men with diabetes over the age of 66 who were incident users of SGLT2i from Jan-Dec 2016. We quantified the association between SGLT2i and each of genital mycotic infection and urinary tract infection within 30 days of drug initiation using a retrospective cohort design. The comparator group were new users of a DPP-4i. We identified 21,444 incident SGLT2i users and 22,463 DPP-4i users. Among SGLT2i users, 41% were women and the mean age at index was 71.8 ± 5 years. After adjusting for propensity score, age, sex, and recent UTI, there was a 2.47 fold increased risk of a genital mycotic infection with SGLT2i (adjusted hazard ratio (HR), 2.47; 95% CI 2.08-2.92, p < 0.001) within 30 days. For UTI, the adjusted HR was 0.89 (95% CI 0.78-1.00, p=0.05) overall. Incident SGLT2i use among older women and men is associated with an increased risk of genital mycotic infections within 30 days; there is no associated increased risk of UTI. These findings from a real-world setting provide evidence of the potential harms of SGLT2i. Disclosure I.C. Lega: None. S. Bronskill: None. M.A. Campitelli: None. J. Guan: None. N.M. Stall: None. K. Lam: None. L.M. McCarthy: None. A. Gruneir: None. P.A. Rochon: None. Funding Canadian Institutes of Health Research (PJT153060)
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".