Abstract: FR-OR094

AKI in Patients on SGLT2 inhibitors: A Propensity Matched Analysis

Session Information

Category: Diabetes

  • 502 Diabetes Mellitus and Obesity: Clinical

Authors

  • Nadkarni, Girish N., Icahn School of Medicine, New York, New York, United States
  • Coca, Steven G., Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Ferrandino, Rocco, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Chang, Alex R., Geisinger Medical Center, Danville, Pennsylvania, United States
  • Surapaneni, Aditya L, Johns Hopkins University, Baltimore, India
  • Chauhan, Kinsuk, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Poojary, Priti, Icahn School of Medicine at Sinai, New York, New York, United States
  • Saha, Aparna, Icahn school of medicine at Mount Sinai, NEW YORK, New York, United States
  • Ferket, Bart, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Grams, Morgan, Johns Hopkins University, Baltimore, India
Background

Sodium-glucose co-transporter-2 inhibitors (SGLT2i) improve both renal and cardiovascular outcomes in type 2 diabetes (T2D) patients. However, the FDA has issued alerts regarding increased acute kidney injury (AKI) with canagliflozin/dapagliflozin. We aimed to assess real world AKI risk with SGLT2i separately in two health-care cohorts.

Methods

We utilized the Mount Sinai chronic kidney disease (MSCKD) registry and Geisinger Health System (GHS) cohort. We selected SGLT2i users/non-users and determined AKI by KDIGO definition (AKIKDIGO). We used nearest neighbor 1: 1 propensity matching and calculated unadjusted and adjusted (accounting for covariates poorly balanced in the propensity match) hazard ratios (HRs).

Results

We analyzed 377 SGLT-2i users: non-user pairs in MSCKD, and 1242 SGLTi users: non-user pairs in GHS. During median follow-up time of 14 months, 4% in Mount Sinai and 3% of SGLTi users experienced an AKIKDIGO event, vs. 10% and 7% of non-users, respectively. Unadjusted HRs for AKIKDIGO were 0.46 (95% CI 0.26-0.82) and 0.43 (95% CI 0.29-0.63) in MSCKD and GHS, respectively. After adjustment, decreased risk persisted (aHR 0.48; 95% CI: 0.25-0.91, and aHR 0.63, 95% CI: 0.39-1.00, respectively). These estimates did not qualitatively change across sensitivity analyses, including by SGLTi type. (Table 1)

Conclusion

These pharmacoepidemiologic findings suggest there may not be increased AKI risk in SGLT2i users vs. comparable T2D patients. In fact, all three SGLTi were associated with lower AKI risk, similar to empagliflozin trial results. Our results suggest that perceived AKI risk with canagliflozin/dapagliflozin may be attributable to the high-risk population taking these medications and not to inherent nephrotoxicity.

Table 1. Hazard Ratios for AKI in SGLT2 Users vs. Propensity Matched Non-users in Mount Sinai and Geisinger Cohorts
Mount SinaiGeisinger
 Unadjusted HR [95% CI]Adjusted HR
[95% CI]
Unadjusted HR
[95% CI]
Adjusted HR
[95% CI]
Primary analysis
AKI defined by KDIGO0.4 (0.2-0.8)0.4 (0.2-0.9)0.4 (0.3-0.6)0.6 (0.4-1.0)
Sensitivity analyses
AKI defined by ICD0.5 [0.3-0.8]0.5 [0.3-0.9]0.5 [0.3–0.8]0.8 [0.4-1.5]
Including only User/Non users with complete covariate data0.7 [0.3-1.3]0.7 [0.3-1.4]0.5 [0.3–0.8]0.7 [0.5-1.2]
Canagliflozin0.5 [0.3-0.8]0.5 [0.3-1.00]0.5 [0.3-0.8]0.8 [0.4-1.3]
Dapagliflozin0.8 [0.3-1.9]0.8 [0.3-1.9] 0.5 [0.2-1.7]0.1 [0.02-1.1]0.2 [0.02-2.5
EmpagliflozinNANA0.3 [0.1-0.8]0.4 [0.1-1.6]

NA= Insufficient Sample Size for estimation

Funding

  • NIDDK Support