Robert Janknegt¹*, Mark Reinders¹ and Rutger Bianchi²

¹Hospital Pharmacist, Zuyderland Medical Centre, Netherlands
²Internist, Endocrinologist, Zuyderland Medical Centre, Netherlands

*Corresponding Author: Robert Janknegt, Hospital Pharmacist, Zuyderland Medical Centre, Netherlands.

Received: January 17, 2022 Published: January 31, 2022

Abstract

The present article is an update of a previously published version. This is now focussed on patients with existing cardiovascular or renal disease. This is the group in which SGLT-2 inhibitors have the most added value.

Objectives: The increasing number of antidiabetic drugs makes it almost impossible to have sufficient knowledge of each individual medicine and device, especially for general practitioners.

Reducing the number of different antidiabetics based on rational criteria, allows physicians

and pharmacists to build experience with a more limited set of medicines and to optimise patient information.

Methods: In this study SGLT-2 inhibitors are compared by means of the SOJA method.

The following selection criteria were applied: ease of use, available dosage forms, clinical efficacy, documented effects on clinical endpoints, safety, tolerability, drug interactions and documentation. The weight for documented effects on clinical endpoints was increased compared to the previously published version, because treatment in this patient category is focussed on reducing these endpoints.

Results and Conclusion: Empagliflozin showed the highest score, followed by canagliflozin. These medicines are well documented concerning clinical endpoints in patients with existing cardiovascular and renal disease.

Keywords: Drug Selection; SGLT-2; Diabetes; SOJA; Empagliflozin; Cardiovascular

References

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Citation

Citation: Robert Janknegt., et al. “SGLT-2 Inhibitors Drug Selection by Means of the System of Objectified Judgement Analysis Method". Acta Scientific Pharmacology 3.1 (2022): 23-39.

Copyright

Copyright: © 2022 Robert Janknegt., et al.. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.