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Internal MedicineCase series / Retrospective2 min read · distilled by Vetree AI

Post-marketing safety monitoring of sodium-glucose cotransporter 2 inhibitors for diabetes in cats: a pharmacovigilance study based on the FDA ADAE database.

Lai X, Chen M, Huang Y, Cheng Y · Journal of Veterinary Internal Medicine · 1 September 2026

Clinical bottom line

Bexagliflozin carries stronger DKA signals; velagliflozin warrants early monitoring for ketonuria and hypochloremia.

Summary

This pharmacovigilance study analyzed real-world adverse event (AE) reports for bexagliflozin and velagliflozin—the only two FDA-approved sodium-glucose cotransporter 2 (SGLT2) inhibitors for feline diabetes mellitus—using the FDA Animal Drug Adverse Events (ADAE) database through Q2 2025. Of 34,187 total feline AE reports, 2,876 involved bexagliflozin and 2,776 involved velagliflozin. Disproportionality analysis using four validated algorithms (ROR, PRR, BCPNN, MGPS) identified distinct safety signal profiles for each drug. Bexagliflozin demonstrated stronger signals for diabetic ketoacidosis (DKA), ketosis, and weight fluctuation across 22 system organ classes (SOCs). Velagliflozin showed stronger signals for ketonuria, hypochloremia, and acid-base disorders across 19 SOCs. Temporally, velagliflozin-associated AEs had an earlier median onset (5 vs. 9 days) and shorter median duration (8 vs. 14 days) compared to bexagliflozin. These differences suggest that while both drugs share class-related risks—particularly ketone body accumulation and metabolic disturbances—their individual safety profiles are meaningfully distinct. Clinicians should monitor cats on bexagliflozin closely for DKA, particularly in the first two weeks, while velagliflozin warrants early vigilance for electrolyte imbalances and ketonuria. These findings provide actionable, drug-specific guidance for risk stratification and individualized monitoring in feline diabetic patients receiving SGLT2 inhibitor therapy.

Internal MedicineSmall AnimalPharmacologyEmergency

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.