Skip to main content
SpringerLink
Log in

A Population-Based Study of SGLT2 Inhibitor-Associated Postoperative Diabetic Ketoacidosis in Patients with Type 2 Diabetes

  • Original Research Article
  • Published:
Drug Safety Aims and scope Submit manuscript

Abstract

Introduction and Objectives

Operations are a major precipitating factor for sodium-glucose co-transporter 2 inhibitor (SGLT2i)-associated diabetic ketoacidosis (DKA). This study aimed to investigate the risks of SGLT2i-associated postoperative DKA.

Methods

We analysed a population-based cohort of patients with type 2 diabetes who underwent operations during 2015–2020. Patients with SGLT2i prescriptions within 6 months before operations were assigned to the SGLT2i group, while others were assigned to the control group. Inverse probability treatment weighting with propensity scores was used to balance the baseline covariates. Postoperative DKA was defined as DKA within 30 days postoperatively.

Results

Overall, 147,115 subjects were included (3,419 SGLT2i users; 143,696 controls). Preoperative SGLT2i exposure was associated with increased risks of postoperative DKA (incidence = 6.40/1,000 person-years; incidence rate ratio [IRR] 6.33, 95% confidence interval [CI] 5.57–7.18; p < 0.001). Risk factors of SGLT2i-associated postoperative DKA included emergency operation (IRR 24.56, 95% CI 7.42–81.24; p < 0.001), preoperative HbA1c ≥8% (IRR 3.10, 95% CI 1.31–7.33; p = 0.010) and insulin use (IRR 2.88, 95% CI 1.27–6.51; p = 0.011). SGLT2i users who developed postoperative DKA had worse outcomes (invasive mechanical ventilation, dialysis, infections/sepsis, intensive care, and length of hospitalization; p < 0.05) than those who did not, although SGLT2i users who developed postoperative DKA had better outcomes than non-SGLT2i users who developed postoperative DKA (p < 0.05). The risk of postoperative DKA decreased following the implementation of an automatic electronic health record pop-up alert on perioperative precaution regarding SGLT2i (from IRR 4.06 [95% CI 3.41–4.83] to 2.97 [95% CI 2.41–3.65]; p for interaction = 0.020).

Conclusions

Preoperative SGLT2i use was associated with increased risks of postoperative DKA in patients with type 2 diabetes. Clinicians could optimize patients’ outcomes by appropriate prescription of SGLT2i, while watching out for high-risk features. Implementing automatic electronic health record pop-up alerts may reduce the risk of SGLT2i-associated postoperative DKA.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Khunti K. SGLT2 inhibitors in people with and without T2DM. Nat Rev Endocrinol. 2021;17(2):75–6.

    Article  CAS  Google Scholar 

  2. Musso G, et al. Diabetic ketoacidosis with SGLT2 inhibitors. BMJ. 2020;371: m4147.

    Article  Google Scholar 

  3. US FDA. FDA revises labels of SGLT2 inhibitors for diabetes to include warnings about too much acid in the blood and serious urinary tract infections. 2020. https://www.fda.gov/drugs/drug-safety-and-availability/fda-revises-labels-sglt2-inhibitors-diabetes-include-warnings-about-too-much-acid-blood-and-serious.

  4. Health Products Regulatory Authority. SGLT2 inhibitors: updated advice on monitoring ketone bodies in patients hospitalised for major surgical procedures or acute serious medical illnesses. 2019. https://www.hpra.ie/docs/default-source/default-document-library/hpra-article-in-mims-supplement_november-2019.pdf.

  5. Seki H, et al. Multicentre prospective observational study of sodium-glucose cotransporter-2 inhibitor-associated postoperative ketoacidosis: the SAPKA study protocol. BMJ Open. 2021;11(11): e049592.

    Article  Google Scholar 

  6. Thiruvenkatarajan V, et al. Perioperative diabetic ketoacidosis associated with sodium-glucose co-transporter-2 inhibitors: a systematic review. Br J Anaesth. 2019;123(1):27–36.

    Article  CAS  Google Scholar 

  7. Sethuraman U, et al. Prescription errors before and after introduction of electronic medication alert system in a pediatric emergency department. Acad Emerg Med. 2015;22(6):714–9.

    Article  Google Scholar 

  8. Lui DTW, et al. Cohort profile: the Hong Kong cardiovascular risk factor prevalence study (CRISPS) and the follow-up studies. Int J Epidemiol. 2021;50(4):1069–1069h.

    Article  Google Scholar 

  9. Lui DTW, et al. A territory-wide study on the impact of COVID-19 on diabetes-related acute care. J Diabetes Investig. 2020;11(5):1303–6.

    Article  CAS  Google Scholar 

  10. Lui DTW, et al. HbA1c variability, in addition to mean HbA1c, predicts incident hip fractures in Chinese people with type 2 diabetes. Osteoporos Int. 2020;31(10):1955–64.

    Article  CAS  Google Scholar 

  11. Tan K, et al. Clinical considerations when adding a sodium-glucose co-transporter-2 inhibitor to insulin therapy in patients with diabetes mellitus. Hong Kong Med J. 2019;25(4):312–9.

    Article  CAS  Google Scholar 

  12. Dhatariya KK, et al. Diabetic ketoacidosis. Nat Rev Dis Primers. 2020;6(1):40.

    Article  Google Scholar 

  13. Luk AOY, et al. Temporal trends in rates of infection-related hospitalisations in Hong Kong people with and without diabetes, 2001–2016: a retrospective study. Diabetologia. 2021;64(1):109–18.

    Article  Google Scholar 

  14. Royston P, White I. Multiple Imputation by Chained Equations (MICE): implementation inStata. J Stat Softw. 2011. https://doi.org/10.18637/jss.v045.i04.

    Article  Google Scholar 

  15. White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 2011;30(4):377–99.

    Article  Google Scholar 

  16. Wong AY, et al. Cardiovascular outcomes associated with use of clarithromycin: population based study. BMJ. 2016;352: h6926.

    Article  Google Scholar 

  17. McCaffrey DF, et al. A tutorial on propensity score estimation for multiple treatments using generalized boosted models. Stat Med. 2013;32(19):3388–3414.

    Article  Google Scholar 

  18. Douros A, et al. Sodium-glucose cotransporter-2 inhibitors and the risk for diabetic ketoacidosis : a multicenter cohort study. Ann Intern Med. 2020;173(6):417–25.

    Article  Google Scholar 

  19. Burke KR, Schumacher CA, Harpe SE. SGLT2 inhibitors: a systematic review of diabetic ketoacidosis and related risk factors in the primary literature. Pharmacotherapy. 2017;37(2):187–94.

    Article  Google Scholar 

  20. Zelniker TA, Braunwald E. Mechanisms of cardiorenal effects of sodium-glucose cotransporter 2 inhibitors: JACC State-of-the-Art review. J Am Coll Cardiol. 2020;75(4):422–34.

    Article  CAS  Google Scholar 

  21. Lee CH, et al. Prospective association of serum adipocyte fatty acid-binding protein with heart failure hospitalization in diabetes. ESC Heart Fail. 2021;8(5):3964–74.

    Article  Google Scholar 

  22. Menghoum N, Oriot P, Hermans MP. Clinical and biochemical characteristics and analysis of risk factors for euglycaemic diabetic ketoacidosis in type 2 diabetic individuals treated with SGLT2 inhibitors: A review of 72 cases over a 4.5-year period. Diabetes Metab Syndr. 2021;15(6): 102275.

    Article  CAS  Google Scholar 

  23. Milder DA, Milder TY, Kam PCA. Sodium-glucose co-transporter type-2 inhibitors: pharmacology and peri-operative considerations. Anaesthesia. 2018;73(8):1008–18.

    Article  CAS  Google Scholar 

  24. Chak E, et al. Electronic health record alerts enhance mass screening for chronic hepatitis B. Sci Rep. 2020;10(1):19153.

    Article  CAS  Google Scholar 

  25. Traczyk C, et al. Implementation of a postoperative electronic health record alert for cardiac implantable electronic device patients. J Perianesth Nurs. 2021;36(4):345-350.e1.

    Article  Google Scholar 

  26. McGreevey JD 3rd, et al. Reducing alert burden in electronic health records: state of the art recommendations from four health systems. Appl Clin Inform. 2020;11(1):1–12.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Hong Kong Hospital Authority for data provision, and Mr Franco Cheng for his input regarding details of the implementation of the alert about SGLT2 inhibitors.

Author information

Author notes

  1. David Tak Wai Lui and Tingting Wu contributed equally to this article.

Authors and Affiliations

  1. Division of Endocrinology and Metabolism, Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    David Tak Wai Lui, Chi Ho Lee, Carol Ho Yi Fong, Yu Cho Woo & Kathryn Choon Beng Tan

  2. Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Tingting Wu & Carlos King Ho Wong

  3. Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Ivan Chi Ho Au & Carlos King Ho Wong

  4. Division of Endocrine Surgery, Department of Surgery, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Xiaodong Liu, Matrix Man Him Fung & Brian Hung Hin Lang

  5. Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, New Territories, Hong Kong SAR, China

    Carlos King Ho Wong

Authors
  1. David Tak Wai Lui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tingting Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ivan Chi Ho Au
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaodong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matrix Man Him Fung
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Chi Ho Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Carol Ho Yi Fong
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yu Cho Woo
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Brian Hung Hin Lang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Kathryn Choon Beng Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Carlos King Ho Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Carlos King Ho Wong.

Ethics declarations

Funding

Not applicable. The authors of this study received no financial support.

Conflicts of interest

David T.W. Lui, Tingting Wu, Ivan C.H. Au, Xiaodong Liu, Matrix M.H. Fung, Chi Ho Lee, Carol H.Y. Fong, Yu Cho Woo, Brian H.H. Lang, Kathryn C.B. Tan, and Carlos K.H. Wong have declared no conflicts of interest.

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Ethics approval of this study was granted by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (reference no. UW 21-320).

Consent to participate

Not applicable, as individuals were analysed anonymously and cannot be identified.

Consent to publication

Not applicable, as individuals were analysed anonymously and cannot be identified.

Availability of data and materials

The data that support the findings of this study are available from Hong Kong Hospital Authority but restrictions apply to the availability of these data, which were used under licence for the current study, and therefore are not publicly available. Data are however available from the authors upon reasonable request and with permission of Hong Kong Hospital Authority.

Code availability

Not available.

Author contributions

DTWL: Conceived the research idea, drafted the paper. TW: Conducted statistical analysis, drafted the paper. ICHA: Data management and reviewed the paper. XL: Data management and reviewed the paper. MMHF: Reviewed and validated the paper. CHL: Assisted data collection. YCW: Reviewed and validated the paper. BHHL: Reviewed and validated the paper. KCBT: Reviewed and validated the paper. CKHW: Conceived the research idea, data collection, supervised the project, and reviewed the paper. All authors read and approved the final version.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 4.66 MB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lui, D.T.W., Wu, T., Au, I.C.H. et al. A Population-Based Study of SGLT2 Inhibitor-Associated Postoperative Diabetic Ketoacidosis in Patients with Type 2 Diabetes. Drug Saf 46, 53–64 (2023). https://doi.org/10.1007/s40264-022-01247-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40264-022-01247-3

Search

Navigation