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. 2024 Jan 6;23:10. doi: 10.1186/s12933-023-02118-6

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — Trend of HbA1c, LDL-cholesterol, and BMI in the three groups during follow-up. Graphs showing the mean values of glycated haemoglobin (HbA1c) (A), LDL-cholesterol (C), and BMI (D), along with the mean cumulative HbA1c (B), in the three groups during the successive visits of the follow-up. Error bars are ± SE for panels A, C, and D. *P < 0.05 SGLT-2i/GLP-1RA vs SGLT-2i; ^†P < 0.05 SGLT-2i/GLP-1RA vs GLP-1RA; ^⁋P < 0.05 SGLT-2i vs SGLT-2i/GLP-1RA; ^§P < 0.05 SGLT-2i vs GLP-1RA; Kruskal–Wallis followed by Dunn’s test for all. Boxplots show the median, 25th, and 75th percentiles, range, and extreme values