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Acute Kidney Injury in Patients on SGLT2 Inhibitors: A Propensity-Matched Analysis

OBJECTIVE: Sodium-glucose cotransporter-2 (SGLT2) inhibitors are new medications that improve cardiovascular and renal outcomes in patients with type 2 diabetes (T2D). However, the Food and Drug Administration has issued alerts regarding increased acute kidney injury (AKI) risk with canagliflozin an...

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Detalles Bibliográficos
Autores principales: Nadkarni, Girish N., Ferrandino, Rocco, Chang, Alexander, Surapaneni, Aditya, Chauhan, Kinsuk, Poojary, Priti, Saha, Aparna, Ferket, Bart, Grams, Morgan E., Coca, Steven G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Diabetes Association 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5652593/
https://www.ncbi.nlm.nih.gov/pubmed/28827404
http://dx.doi.org/10.2337/dc17-1011
Descripción
Sumario:OBJECTIVE: Sodium-glucose cotransporter-2 (SGLT2) inhibitors are new medications that improve cardiovascular and renal outcomes in patients with type 2 diabetes (T2D). However, the Food and Drug Administration has issued alerts regarding increased acute kidney injury (AKI) risk with canagliflozin and dapagliflozin. We aimed to assess the real-world risk of AKI in new SGLT2 inhibitor users in two large health care utilization cohorts of patients with T2D. RESEARCH DESIGN AND METHODS: We used longitudinal data from the Mount Sinai chronic kidney disease registry and the Geisinger Health System cohort. We selected SGLT inhibitor users and nonusers (patients with T2D without SGLT2 inhibitor prescription). We determined AKI by the KDIGO (Kidney Disease: Improving Global Outcomes) definition (AKI(KDIGO)). We performed 1:1 nearest-neighbor propensity matching and calculated unadjusted hazard ratios (HRs) and adjusted HRs (aHRs; accounting for covariates poorly balanced) for AKI in primary and sensitivity analyses. RESULTS: We identified 377 SGLT2 inhibitor users and 377 nonusers in the Mount Sinai cohort, of whom 3.8 and 9.7%, respectively, had an AKI(KDIGO) event over a median follow-up time of 14 months. The unadjusted hazards of AKI(KDIGO) were 60% lower in users (HR 0.4 [95% CI 0.2–0.7]; P = 0.01), which was unchanged (aHR 0.4 [95% CI 0.2–0.7]; P = 0.004) postadjustment. Similarly, we identified 1,207 SGLT2 inhibitor users and 1,207 nonusers in the Geisinger cohort, of whom 2.2 and 4.6% had an AKI(KDIGO) event. AKI(KDIGO) unadjusted hazards were lower in users (HR 0.5 [95% CI 0.3–0.8]; P < 0.01) with modest attenuation postadjustment for covariates (aHR 0.6 [95% CI 0.4–1.1]; P = 0.09). These estimates did not qualitatively change across several sensitivity analyses. CONCLUSIONS: Our findings do not suggest an increased risk of AKI associated with SGLT2 inhibitor use in patients with T2D in two large health systems.