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Original articles

Impact of sodium-glucose cotransporter 2 inhibitors on bleeding, hospitalizations, and other adverse outcomes in atrial fibrillation patients with and without diabetes

Ameenathul M. Fawzy1, Arnaud Bisson2,3,4, Laurent Fauchier2*, Gregory Y. H. Lip1,5,6*ORCID
1 Liverpool Centre for Cardiovascular Science at the University of Liverpool, Liverpool John Moores University, and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom
2 Service de Cardiologie, Centre Hospitalier Régional Universitaire et Faculté de Médecine de Tours, Tours, France
3 Service de Cardiologie, Centre Hospitalier Régional Universitaire d’Orléans, Orléans, France
4 Transplantation Immunité Inflammation, Université de Tours, Tours, France
5 Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
6 Department of Cardiology, Lipidology and Internal Medicine, Medical University of Bialystok, Białystok, Poland
* LF and GYHL contributed equally to this work.
DOI: 10.20452/pamw.17227
Published online: February 12, 2026.
Key words: atrial fibrillation, arrhythmias, outcomes, SGLT2 inhibitors
CCBYCC BY 4.0

In this article
Abstract

Introduction: Emerging evidence suggests that sodium‑glucose cotransporter 2 inhibitors (SGLT2is) may be associated with a reduced risk of arrhythmias and related complications.

Objectives: We aimed to evaluate the impact of SGLT2is on atrial fibrillation (AF)-associated adverse outcomes.

Patients and methods: All anticoagulated patients with AF diagnosed between January 2014 and December 2020 were identified from a federated electronic medical record database (TriNetX), and followed‑up for 3 years. A 1:1 propensity score matching (PSM) analysis was performed to balance SGLT2i and non‑SGLT2i cohorts. Primary outcomes were bleeding, hospitalizations for AF/atrial flutter (AFl), composite of cardioversion and ablations, and ventricular arrhythmias (VAs) and cardiac arrests. Secondary outcomes included all‑cause mortality, ischemic stroke / transient ischemic attack (TIA), hemorrhagic stroke, incident heart failure (HF), myocardial infarction, and composite of arterial and venous thrombotic events (TEs). Subanalyses were performed on AF‑diabetes and AF‑HF cohorts.

Results: As many as 789 758 and 86 249 patients were identified from the non‑SGLT2i and SGLT2i groups, respectively. After PSM, each group had 51 320 patients. The SGLT2i use was associated with a significantly lower risk of bleeding (hazard ratio [HR], 0.669; 95% CI, 0.642–0.697), hospitalization for AF/AFl (HR, 0.826; 95% CI, 0.815–0.837), composite of cardioversion / ablation (HR, 0.652; 95% CI, 0.628–0.678), and VAs and cardiac arrests (HR, 0.779; 95% CI, 0.754–0.805). A lower risk of all‑cause mortality (HR, 0.554; 95% CI, 0.537–0.571), ischemic stroke/TIA (HR, 0.795; 95% CI, 0.768–0.823), hemorrhagic stroke (HR, 0.691; 95% CI, 0.623–0.767), incident HF (HR, 0.856; 95% CI, 0.821–0.893), myocardial infarction (HR, 0.763; 95% CI, 0.736–0.792), and composite of arterial / venous TEs (HR, 0.719; 95% CI, 0.704–0.735) was also observed.

Conclusions: The SGLT2i use was associated with a lower risk of AF‑related complications.

What's new?

This study evaluates the association between the use of sodium‑glucose cotransporter 2 inhibitors (SGLT2is) and bleeding and other clinical outcomes in anticoagulated patients with atrial fibrillation (AF), with and without diabetes. Prespecified subanalyses were conducted in patients with AF and diabetes, as well as in nondiabetic patients with AF and heart failure (HF). This real‑world study examines the impact of SGLT2is exclusively in nondiabetic AF patients with HF for whom data are only just emerging. The findings suggest that the pleiotropic effects of SGLT2is may extend to a reduced risk of bleeding and potential antiarrhythmic effects.


      Study selection process
      Abbreviations: AF, atrial fibrillation; SGLT2i, sodium-glucose cotransporter 2 inhibitor

Introduction

After years of serving as antidiabetic drugs, sodium‑glucose cotransporter 2 inhibitors (SGLT2is) expanded into the cardiovascular domain following evidence from cardiovascular outcomes trials (CVOTs) and subsequent randomized controlled trials (RCTs) that demonstrated significant benefits in terms of mortality and heart failure (HF) hospitalization reduction.1-7 SGLT2is now form an integral part of guideline‑directed medical therapy in HF.

Recent evidence suggests that SGLT2is may have a role in reducing the risk of atrial fibrillation (AF). In an analysis from the DECLARE‑TIMI58 trial (Multicenter Trial to Evaluate the Effect of Dapagliflozin on the Incidence of Cardiovascular Events), treatment with dapagliflozin was seen to reduce the risk of incident AF/atrial flutter (AFl), as well as subsequent episodes of AF/AFl in those with and without a history of AF/AFl, even after considering factors such as atherosclerotic cardiovascular disease, history of HF, sex, and body mass index (BMI).8 In contrast, a substudy from the CREDENCE trial (Evaluation of the Effects of Canagliflozin on Renal and Cardiovascular Outcomes in Participants With Diabetic Nephropathy) showed no significant difference in AF/AFl risk with canagliflozin but the total number of events recorded in the trial was small (n = 115). When these results were pooled with those from the 3 other CVOTs, the reduction in the AF/AFl risk was found to be significant.9 In line with this, several meta‑analyses of RCTs and cohort studies have demonstrated a lower risk of incident AF associated with SGLT2is.10-18 Though the aforementioned trials were not designed to assess AF as a prespecified end point, these data suggest that SGLT2is may have some relevance in modulating arrhythmia risk.

Further to the above, there is limited evidence to suggest that SGLT2is may be beneficial in patients who already have AF. In an analysis from the EMPA‑REG OUTCOME trial (BI10773 [Empagliflozin] Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients), empagliflozin had a more pronounced absolute treatment effect in patients with than without AF, indicating that they may stand to achieve more benefit.19 A holistic approach to the management of patients with AF has been put forward for several years, and SGLT2is may be relevant in this context considering the several possible benefits mentioned above.20,21 However, the number of patients with pre‑existing AF in the available RCTs has been relatively small and at present, there is little information on how SGLT2is affect certain AF‑related adverse outcomes in this specific patient population. Thus, we sought to evaluate this in a real‑world population of AF patients, including individuals with and without diabetes.

Patients and methods

Study design and population

This retrospective, observational cohort study was conducted using the TriNetX research network, a global federated administrative database with real‑time updates of electronic medical records (EMRs). It holds data on approximately 85 million patients from over 70 health care organizations (HCOs) across 7 countries, with the majority of centers based in the United States. Other participating countries include Germany, United Kingdom, Italy, Singapore, and Israel. A detailed description of the database is provided by Topaloglu et al22 and can be found online (https://trinetx.com/company‑overview/).

Briefly, the TriNetX research network database encompasses anonymized EMRs of patients registered with the network, and holds information on patient demographics, clinical details including diagnoses, medications, and investigations as well as any procedures, from settings such as general practice surgeries, community and secondary hospitals, providing detailed real‑world data.

All anticoagulated patients with AF diagnosed between January 1, 2014 and December 31, 2020 were identified from the TriNetX database using the International Classification of Diseases, Tenth Revision (ICD‑10) code I48 for AF. The patients were categorized into 2 groups of individuals treated and not treated with SGLT2is (Figure 1). The searches were run on January 23, 2026. At the time of the search, there were 97 participating HCOs within the TriNetX research network, and 88 responded with the patient data.


      Forest plot demonstrating the risk of outcomes associated with sodium-glucose cotransporter 2 inhibitor use in the entire atrial fibrillation (AF) cohort, AF-diabetes cohort, and AF-heart failure cohort
      Abbreviations: AFl, atrial flutter; TE, thromboembolism; VA, ventricular arrhythmia; others, see Figure 1 and Table 1
Figure 1 Study selection process

Abbreviations: AF, atrial fibrillation; SGLT2i, sodium‑glucose cotransporter 2 inhibitor

As TriNetX only provides access to deidentified data, research studies conducted using the network do not require ethical approval. Nonetheless, extensive data quality assessments are performed to ensure adherence of the platform to the institutional review board requirements and conformance, completeness, and plausibility of the available data.22,23 Study proceedings were carried out according to the Declaration of Helsinki.

Outcomes

The main objective of the study was to determine the effects of SGLT2is on an AF population with and without diabetes over a 3‑year follow‑up period. Primary outcomes included bleeding events, hospitalizations for AF/AFl, composite of cardioversion and ablations, and ventricular arrhythmias (VAs) and cardiac arrests. Secondary outcomes comprised all‑cause mortality, ischemic stroke (IS) / transient ischemic attack (TIA), hemorrhagic stroke, incident HF, myocardial infarction (MI), and composite of arterial and venous thrombotic events (TEs). These were identified using the corresponding ICD‑10 Clinical Modification codes for diagnostic outcomes and relevant procedural codes for procedural outcomes.

Exploratory analyses were also performed with the analysis repeated only in the AF patients with diabetes (AF‑diabetes cohort) and nondiabetic AF patients with HF (AF‑HF cohort).

Statistical analysis

Baseline characteristics were represented using continuous variables expressed as mean (SD) or median (interquartile range), and categorical variables expressed as counts and percentages. Differences between the groups were assessed using the t test for continuous variables and the χ2 test for categorical variables.

To account for large differences in the number of patients between the 2 comparator groups as well as the baseline characteristics and potential confounding effects, data analyses were performed after propensity score matching (PSM) using the greedy nearest‑neighbor matching (with a caliper of 0.1 of pooled standard deviations). The PSM was calculated for the covariates shown in Table 1. Standardized mean differences (SMDs) indicated the distribution of demographic data and clinical characteristics between the 2 groups, and were calculated as the difference in the means or proportions of a particular variable divided by the pooled estimate of SD for that variable. Any baseline characteristic with an SMD below 0.1 between the cohorts was considered well‑matched.

Table 1. Baseline characteristics of the sodium‑glucose cotransporter 2 inhibitor and non–sodium‑glucose cotransporter 2 inhibitor groups in the entire atrial fibrillation cohort before and after matching
Parameter
SGLT2i (n = 86 249)
Non‑SGLT2i (n = 789 758)
SMD
SGLT2i (n = 51 320)
Non‑SGLT2i (n = 51 320)
SMD
Before matching
After matching
Data are presented as number and percentage unless indicated otherwise.
a The sum of all anticoagulants is over 100%, as the categories are not mutually exclusive and account for patients that may have switched from one anticoagulant to another. Each category represents the number and proportion of patients who have taken the drug at any point in time prior to the point of inclusion in the study.
b IQRs are presented in the format that is available on the TriNetX website.
SI conversion factors: to convert glucose to mmol/l, multiply by 18; hemoglobin to g/l, by 10; total cholesterol, LDL cholesterol, and HDL cholesterol to mmol/l, by 0.0259; HbA1c to mmol/mol, by 10.93 and then subtract 23.5.
Abbreviations: ACE, angiotensin‑converting enzyme; AV, atrioventricular; BMI, body mass index; CRT, cardiac resynchronization therapy; EP, electrophysiology; HbA1c, glycated hemoglobin; HDL, high‑density lipoprotein; ICD, implantable cardioverter‑defibrillator; IQR, interquartile range; LDL, low‑density lipoprotein; SMD, standardized mean difference; TIA, transient ischemic attack; others, see Figure 1
Age at index, y, mean (SD)
70.6 (10.4)
67.8 (10.5)
0.263
70.2 (10.6)
70.1 (9.1)
0.009
Women
29 116 (33.8)
315 602 (40.3)
0.135
18 057 (35.2)
18 068 (35.2)
<⁠0.001
Ethnicity
White
63 417 (73.5)
606 366 (77.4)
0.089
37 918 (73.9)
37 722 (73.5)
0.009
Black or African American
11 136 (12.9)
79 487 (10.1)
0.087
6160 (12)
6264 (12.2)
0.006
Asian
3644 (4.2)
24 992 (3.2)
0.055
2175 (4.2)
2172 (4.2)
<⁠0.001
Comorbidities
Hypertension
80 019 (92.8)
559 314 (71.4)
0.581
46 258 (90.1)
46 586 (90.8)
0.022
Ischemic heart disease
59 402 (68.9)
299 062 (38.2)
0.647
31 808 (62)
32 016 (62.4)
0.008
Heart failure
60 718 (70.4)
239 497 (30.6)
0.869
30 863 (60.1)
31 217 (60.8)
0.014
Other cardiac arrhythmias
43 359 (50.3)
180 432 (23)
0.59
20 893 (40.7)
20 486 (39.9)
0.016
Cardiomyopathy
34 281 (39.7)
96 291 (12.3)
0.659
15 082 (29.4)
14 761 (28.8)
0.014
Nonrheumatic aortic valve disorders
20 517 (23.8)
80 858 (10.3)
0.364
10 067 (19.6)
10 051 (19.6)
0.001
Nonrheumatic mitral valve disorders
28 967 (33.6)
100 977 (12.9)
0.506
13 196 (25.7)
12 988 (25.3)
0.009
Hyperlipidemia
73 214 (84.9)
414 678 (52.9)
0.736
41 191 (80.3)
41 613 (81.1)
0.021
Diabetes mellitus
59 952 (69.5)
231 808 (29.6)
0.871
34 498 (67.2)
33 200 (64.7)
0.053
Metabolic disorders
78 092 (90.5)
498 894 (63.7)
0.675
44 612 (86.9)
45 023 (87.7)
0.024
Overweight and obesity
45 784 (53.1)
166 335 (21.2)
0.698
23 062 (44.9)
23 396 (45.6)
0.013
BMI 30–39 kg/m2
25 052 (29)
64 800 (8.3)
0.553
11 413 (22.2)
11 436 (22.3)
0.001
Peripheral vascular disease
16 004 (18.6)
64 821 (8.3)
0.305
8159 (15.9)
8375 (16.3)
0.011
Previous stroke
13 849 (16.1)
81 885 (10.4)
0.166
7515 (14.6)
7474 (14.6)
0.002
Previous TIA
7952 (9.2)
34 064 (4.3)
0.195
3943 (7.7)
3921 (7.6)
0.002
Thyroid disease
25 732 (29.8)
137 580 (17.6)
0.292
13 493 (26.3)
13 492 (26.3)
<⁠0.001
Kidney disease
45 796 (53.1)
202 350 (25.8)
0.581
23 532 (45.9)
23 679 (46.1)
0.006
Liver disease
18 304 (21.2)
60 966 (7.8)
0.389
8713 (17)
8779 (17.1)
0.003
Lung disease
64 466 (74.7)
380 560 (48.6)
0.559
35 126 (68.4)
35 266 (68.7)
0.006
Neoplasms
40 926 (47.5)
214 422 (27.4)
0.425
21 495 (41.9)
21 566 (42)
0.003
Aplastic and other anemias and other bone marrow failure syndromes
38 836 (45)
183 631 (23.4)
0.468
19 904 (38.8)
19 968 (38.9)
0.003
Bleeding disorders
21 804 (25.3)
82 942 (10.6)
0.39
10 241 (20)
10 262 (20)
0.001
Nontraumatic intracerebral hemorrhage
1495 (1.7)
9078 (1.2)
0.048
816 (1.6)
777 (1.5)
0.006
Nontraumatic subarachnoid hemorrhage
814 (0.9)
4032 (0.5)
0.05
419 (0.8)
410 (0.8)
0.002
Gastrointestinal hemorrhage
8844 (10.3)
28 008 (3.6)
0.266
4021 (7.8)
4013 (7.8)
0.001
Melena
8526 (9.9)
21 832 (2.8)
0.295
3696 (7.2)
3669 (7.1)
0.002
Hematemesis
1306 (1.5)
4811 (0.6)
0.088
613 (1.2)
618 (1.2)
0.001
Slipping, tripping, stumbling, and falls
17 938 (20.8)
58 773 (7.5)
0.389
8435 (16.4)
8365 (16.3)
0.004
Tobacco use
6995 (8.1)
26 400 (3.4)
0.205
3433 (6.7)
3452 (6.7)
0.001
Procedures
Pacemaker or ICD insertion
15 348 (17.8)
21 358 (2.7)
0.513
5476 (10.7)
5278 (10.3)
0.013
ICD insertion
6201 (7.2)
6745 (0.9)
0.326
2123 (4.1)
2041 (4)
0.008
Subcutaneous ICD
377 (0.4)
231 (0.03)
0.085
100 (0.2)
96 (0.2)
0.002
Pacemaker upgrade to CRT
3929 (4.6)
3212 (0.4)
0.269
1162 (2.3)
1093 (2.1)
0.009
CRT insertion, percutaneous approach
162 (0.2)
403 (0.1)
0.039
79 (0.2)
76 (0.1)
0.002
CRT insertion, open approach
493 (0.6)
653 (0.1)
0.086
171 (0.3)
169 (0.3)
0.001
EP study ± ablation
14 849 (17.2)
23 386 (3)
0.486
4456 (8.7)
4152 (8.1)
0.021
3652 (4.2)
2410 (0.3)
0.266
667 (1.3)
586 (1.1)
0.014
AV node ablation
1600 (1.9)
699 (0.1)
0.181
253 (0.5)
220 (0.4)
0.009
Cardioversion
16 875 (19.6)
24 631 (3.1)
0.536
4956 (9.7)
4621 (9)
0.022
Medications
β-Blockers
81 183 (94.1)
576 884 (73.6)
0.581
46 915 (91.4)
47 230 (92)
0.022
Antilipemic agents
76 282 (88.4)
451 830 (57.6)
0.74
43 842 (85.4)
44 480 (86.7)
0.036
Statins
74 563 (86.5)
433 058 (55.3)
0.731
42 679 (83.2)
43 250 (84.3)
0.03
Diuretics
75 334 (87.3)
417 016 (53.2)
0.805
42 096 (82)
42 810 (83.4)
0.037
ACE inhibitors
50 847 (59)
257 885 (32.9)
0.542
27 686 (53.9)
28 153 (54.9)
0.018
Calcium channel blockers
58 357 (67.7)
349 036 (44.5)
0.479
32 006 (62.4)
32 223 (62.8)
0.009
Antianginals
42 096 (48.8)
179 398 (22.9)
0.561
21 475 (41.8)
21 662 (42.2)
0.007
Digitalis glycosides
18 894 (21.9)
88 142 (11.2)
0.29
8868 (17.3)
8750 (17)
0.006
Angiotensin II inhibitor
49 611 (57.5)
159 837 (20.4)
0.823
24 295 (47.3)
24 675 (48.1)
0.015
Antihypertensives
38 222 (44.3)
171 025 (21.8)
0.492
19 517 (38)
19 760 (38.5)
0.01
Platelet aggregation inhibitors
65 605 (76.1)
395 635 (50.5)
0.551
36 318 (70.8)
36 704 (71.5)
0.017
Loop diuretics
66 187 (76.7)
314 568 (40.1)
0.8
35 360 (68.9)
35 976 (70.1)
0.026
Thiazides / related diuretics
38 232 (44.3)
173 216 (22.1)
0.486
20 478 (39.9)
20 983 (40.9)
0.02
Potassium sparing / combinations diuretics
37 250 (43.2)
81 288 (10.4)
0.798
16 614 (32.4)
16 796 (32.7)
0.008
Sacubitril
17 298 (20.1)
7007 (0.9)
0.659
4787 (9.3)
4342 (8.5)
0.03
Insulin
51 142 (59.3)
218 610 (27.9)
0.668
27 510 (53.6)
28 602 (55.7)
0.043
Exenatide
2055 (2.4)
2149 (0.3)
0.185
931 (1.8)
967 (1.9)
0.005
Liraglutide
4702 (5.5)
3950 (0.5)
0.294
2007 (3.9)
1965 (3.8)
0.004
Dulaglutide
5739 (6.7)
2015 (0.3)
0.356
1689 (3.3)
1431 (2.8)
0.029
Pramlintide
63 (0.1)
157 (0.02)
0.025
39 (0.1)
48 (0.1)
0.006
Semaglutide
4875 (5.7)
554 (0.1)
0.34
733 (1.4)
496 (1)
0.042
Lixisenatide
211 (0.2)
105 (0.013)
0.064
70 (0.1)
64 (0.1)
0.003
Metformin
42 360 (49.1)
91 188 (11.6)
0.892
22 997 (44.8)
24 591 (47.9)
0.062
Glipizide
13 354 (15.5)
30 477 (3.9)
0.4
7104 (13.8)
7430 (14.5)
0.018
Glimepiride
9887 (11.5)
19 059 (2.4)
0.361
5317 (10.4)
5655 (11)
0.021
Sitagliptin
12 125 (14.1)
18 948 (2.4)
0.433
6249 (12.2)
6586 (12.8)
0.02
Linagliptin
4393 (5.1)
5194 (0.7)
0.267
2138 (4.2)
2160 (4.2)
0.002
Repaglinide
1255 (1.5)
2476 (0.3)
0.122
642 (1.3)
673 (1.3)
0.005
Saxagliptin
1236 (1.4)
1816 (0.2)
0.133
652 (1.3)
696 (1.4)
0.008
Nateglinide
414 (0.5)
1120 (0.1)
0.061
246 (0.5)
265 (0.5)
0.005
Warfarina
36 718 (42.6)
334 191 (42.6)
0.001
18 949 (36.9)
18 077 (35.2)
0.035
Rivaroxaban
25 451 (29.5)
142 149 (18.1)
0.269
12 390 (24.1)
12 333 (24)
0.003
Edoxaban
1033 (1.2)
3047 (0.4)
0.091
481 (0.9)
476 (0.9)
0.001
Dabigatran etexilate
6853 (7.9)
40 410 (5.2)
0.113
2842 (5.5)
2742 (5.3)
0.009
Apixaban
51 588 (59.8)
288 371 (36.8)
0.473
26 812 (52.2)
27 008 (52.6)
0.008
Amiodarone
30 454 (35.3)
123 911 (15.8)
0.459
13 830 (26.9)
13 655 (26.6)
0.008
Flecainide
4897 (5.7)
26 478 (3.4)
0.111
2077 (4)
1944 (3.8)
0.013
Laboratory values
Glucose, mg/dl, mean (SD)
140.1 (61.7)
118.9 (43.6)
0.396
140.8 (62.1)
131.7 (54.1)
0.157
Hemoglobin, g/dl, mean (SD)
12.8 (2.2)
12.4 (2.4)
0.154
12.8 (2.2)
12.1 (2.3)
0.336
Total cholesterol, mg/dl, mean (SD)
145.8 (41.8)
160.6 (46.6)
0.336
147.9 (42.2)
151 (45.6)
0.071
LDL cholesterol, mg/dl, mean (SD)
75.4 (32.8)
89.0 (36.4)
0.395
76.7 (32.9)
80.9 (35.4)
0.122
HDL cholesterol, mg/dl, mean (SD)
42 (16.5)
45.9 (18.3)
0.222
42.4 (16.6)
42.6 (17)
0.009
Triglycerides, mg/dl, median (IQR)b
115 (87)
108 (77)
0.114
114 (83)
106 (73)
0.042
HbA1c,%, mean (SD)
7.1 (1.7)
6.4 (1.5)
0.422
7.1 (1.7)
6.8 (1.7)
0.189
Body mass index, kg/m2, mean (SD)
32.7 (8)
30.7 (7.7)
0.247
32.5 (8)
32.2 (7.8)
0.039

Cox regression models were used to evaluate the association between treatment with or without SGLT2i and the outcomes of interest. Where incident outcomes were evaluated, the patients with a history of the outcome of interest were excluded from that particular analysis. For example, the patients with prevalent HF were excluded when examining incident HF. The Kaplan–Meier survival curves were used to visualize time‑to‑event outcomes, with group comparisons performed with the log‑rank test. This test provides a nonparametric comparison of the empirical survival distributions between the groups without assumptions regarding proportional hazards.

Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% CIs, assuming proportional and time‑independent hazards. Thus, the log‑rank test and Cox regression address complementary aspects of group differences, with the former comparing overall survival curves, and the latter quantifying relative hazard over time under model assumptions. No imputations were made for missing data.

The statistical analysis was performed on the TriNetX Analytics platform, which provides a virtual interface with real‑time browser‑based analytics features.

Results

A total of 876 007 patients were initially identified. Of these, 789 758 were not on an SGLT2i (mean [SD] age, 67.8 [10.5] y) and 86 249 (mean age, 70.6 [10.4] y) were on an SGLT2i (Figure 1). The patients in the SGLT2i group were older, less often women, and were more likely to have cardiac risk factors, such as hypertension, ischemic heart disease and HF, as well as comorbidities such as diabetes, liver and kidney disease than those not treated with SGLT2is. This group also had a higher proportion of patients with a history of bleeding and predisposition to falls, was more likely to have undergone cardiac procedures, be prescribed other cardiac and antidiabetic medications, and had poorer blood sugar control and triglyceride levels and higher BMI in comparison with the non‑SGLT2i cohort (Table 1).

After PSM, each group had 51 320 patients (mean [SD] age, 70.1 [9.1] y in the non‑SGLT2i group and 70.2 [10.6] y in the SGLT2i group). The outcomes were evaluated in the matched cohorts and are summarized in Table 1 with HRs for risk illustrated in Figure 2.


      Kaplan–Meier curves for bleeding (A) and all-cause mortality (B) for sodium-glucose cotransporter 2 inhibitor (SGLT2i) use vs non-use in the entire atrial fibrillation cohort
Figure 2 Forest plot demonstrating the risk of outcomes associated with sodium‑glucose cotransporter 2 inhibitor use in the entire atrial fibrillation (AF) cohort, AF‑diabetes cohort, and AF‑heart failure cohort

Abbreviations: AFl, atrial flutter; TE, thromboembolism; VA, ventricular arrhythmia; others, see Figure 1 and Table 1

Any bleeding

There were 3848 and 6057 bleeding events observed in the SGLT2i and non‑SGLT2i groups, respectively. The SGLT2i use was associated with a lower risk of bleeding (HR, 0.669; 95% CI, 0.642–0.697; log‑rank P <⁠0.001). The Kaplan–Meier curve for bleeding is shown in Figure 3A.

Figure 3 Kaplan–Meier curves for bleeding (A) and all‑cause mortality (B) for sodium‑glucose cotransporter 2 inhibitor (SGLT2i) use vs non‑use in the entire atrial fibrillation cohort

Hospitalizations for atrial fibrillation / atrial flutter

As many as 40 739 patients in the SGLT2i cohort and 41 834 in the non‑SGLT2i group were hospitalized. SGLT2is were associated with a lower risk of hospitalizations for AF/AFl (HR, 0.826; 95% CI, 0.815–0.837; log‑rank P <⁠0.001).

Composite of cardioversions and ablations

Cardioversion / ablation was performed in 4287 patients in the SGLT2i group and 6638 in the non‑SGLT2i group. The SGLT2i use was associated with a less frequent need for ablation / cardioversion over the 3‑year follow‑up period (HR, 0.652; 95% CI, 0.628–0.678; log‑rank P <⁠0.001).

Ventricular arrhythmias and cardiac arrest

The number of VAs and cardiac arrests was lower in the SGLT2i group (n = 6426) than the non‑SGLT2i one (n = 8515; HR, 0.779; 95% CI, 0.754–0.805; log‑rank P <⁠0.001).

Secondary outcomes

All‑cause mortality

The number of deaths in the non‑SGLT2i group was nearly twice as high as in the SGLT2i group (12 307 vs 6314). The largest difference in the risk was observed for this outcome, where the SGLT2i use was associated with a 45% lower risk of all‑cause mortality (HR, 0.554; 95% CI, 0.537–0.571; log‑rank P <⁠0.001; Figure 3B).

Ischemic stroke / transient ischemic attack

IS/TIA occurred in 5768 patients in the SGLT2i group and 7471 individuals in the non‑SGLT2i group over the follow‑up period. The risk of IS/TIA was lower in those on SGLT2is (HR, 0.795; 95% CI, 0.768–0.823; log‑rank P <⁠0.001; Figure 2).

Hemorrhagic stroke

Hemorrhagic stroke occurred in 585 patients in the SGLT2i group and 916 patients in the non‑SGLT2i group, demonstrating a lower risk with the SGLT2i use (HR, 0.691; 95% CI, 0.623–0.767; log‑rank P <⁠0.001).

Incident heart failure

There were 30 863 patients in the SGLT2i group and 31 217 patients in the non‑SGLT2i group with a known history of HF. After excluding these patients, 3991 and 4750 individuals in the SGLT2i and non‑SGLT2i groups, respectively, developed de novo HF over the follow‑up period. The risk of incident HF was lower on SGLT2is (HR, 0.856; 95% CI, 0.821–0.893; log‑rank P <⁠0.001).

Myocardial infarction

As many as 4952 patients in the SGLT2i group and 6766 in the non‑SGLT2i group had MI. The risk reduction associated with SGLT2i use was considerable (HR, 0.763; 95% CI, 0.736–0.792; log‑rank P <⁠0.001).

Composite of arterial and venous thrombotic events

The patients in the SGLT2i group had a lower rate of TEs than those in the non‑SGLT2i group (15 433 vs 20 469, respectively) and a lower risk of these events (HR, 0.719; 95% CI, 0.704–0.735; log‑rank P <⁠0.001).

Exploratory analyses

Given that studies to date are limited to AF patients with type 2 diabetes, we performed an exploratory analysis to determine how the results in our population including individuals with and without diabetes compared with those in a population with type 2 diabetes only. The outcomes were also evaluated in another subcohort of AF patients with HF without diabetes, as data for this population are limited. Baseline characteristics before and after matching are included in Supplementary material, Tables S1 and S2. Significant risk reductions were observed for all the outcomes in the AF‑diabetes cohort (Table 2). In the AF‑HF cohort (Supplementary material, Table S2), the SGLT2i use was associated with a significantly lower risk of all outcomes except for VAs and cardiac arrests, where no significant differences were observed (Figure 2 and Supplementary material, Figure S3).

Table 2. Number of events and risk of outcomes in the sodium‑glucose cotransporter 2 inhibitor and non–sodium‑glucose cotransporter 2 inhibitor cohorts after propensity score matching
Outcome
Entire AF cohort
AF‑diabetes cohort
Total (n = 102 640)
SGLT2i, n (%)
Non‑SGLT2i, n (%)
HR (95% CI)
Total (n = 80 260)
SGLT2i, n (%)
Non‑SGLT2i, n (%)
HR (95% CI)
Abbreviations: HR, hazard ratio; others, see Table 1 and Figures 1 and 2
Primary outcomes
Any bleeding
9905
3848 (7.5)
6057 (11.8)
0.669 (0.642–0.697)
7756
3264 (8.1)
4492 (11.2)
0.731 (0.699–0.765)
Hospitalization for AF/AFl
82 573
40 739 (79.4)
41 834 (81.5)
0.826 (0.815–0.837)
65 598
32 771 (81.7)
32 827 (81.8)
0.886 (0.872–0.899)
Composite of cardioversion / ablation
10 925
4287 (8.4)
6638 (12.9)
0.652 (0.628–0.678)
7650
3450 (8.6)
4200 (10.5)
0.818 (0.782–0.856)
Composite of ventricular arrhythmias / cardiac arrests
14 941
6426 (12.5)
8515 (16.6)
0.779 (0.754–0.805)
11 182
5126 (12.8)
6056 (15.1)
0.849 (0.818–0.881)
Secondary outcomes
All‑cause mortality
18 621
6314 (12.3)
12 307 (24)
0.554 (0.537–0.571)
14 504
5243 (13.1)
9261 (23.1)
0.576 (0.557–0.596)
Ischemic stroke/TIA
13 239
5768 (11.2)
7471 (14.6)
0.795 (0.768–0.823)
10 713
4835 (12)
5878
(14.6)
0.818 (0.787–0.85)
Hemorrhagic stroke
1501
585 (1.1)
916 (1.8)
0.691 (0.623–0.767)
1170
488 (1.2)
682 (1.7)
0.735 (0.654–0.826)
Incident heart failure
8741
3991 (7.8)
4750 (9.3)
0.856 (0.821–0.893)
6408
2898 (7.2)
3510 (8.7)
0.823 (0.784–0.865)
Myocardial infarction
11 718
4952 (9.6)
6766 (13.2)
0.763 (0.736–0.792)
9026
4093 (10.2)
4933 (12.3)
0.835 (0.801–0.871)
Composite of arterial and venous thrombotic events
35 902
15 433 (30.1)
20 469 (39.9)
0.719 (0.704–0.735)
28 212
12 818 (31.9)
15 394 (38.4)
0.786 (0.768–0.805)

Discussion

In this real‑world study, the SGLT2i use was associated with a significantly lower risk of AF‑related complications, such as bleeding, hospitalizations for AF/AFl, need for cardioversion / ablation, and VAs and cardiac arrests. Second, reduced risks of all‑cause mortality, IS/TIA, hemorrhagic stroke, incident HF, MI, and TEs were also observed with the SGLT2i use, as compared with their nonuse in this population of anticoagulated AF patients. Indeed, these observations suggest that SGLT2is might be useful in the holistic approach put forward over the last decade in the guidelines for the management of patients with AF.20,21

To our knowledge, the effect of SGLT2is on the bleeding risk in AF has not been specifically evaluated in a large, observational study. In our analysis, the SGLT2i use was associated with a 33% reduction in the risk of any bleeding. The bleeding risk, aside from a stroke risk, is the single most important factor that influences decisions around anticoagulation, and factors such as uncontrolled hypertension and renal disease can significantly elevate the likelihood of a bleed.

SGLT2is have been shown to have a blood pressure lowering effect by improving endothelial function and arterial stiffness and through inactivation of the renin‑angiotensin‑aldosterone system, resulting in arterial vasodilation and reduced afterload.24 Several meta‑analyses have demonstrated significant reductions in blood pressure with SGLT2is.25,26 In 1 study, the greatest reductions in pulse pressure and mean arterial pressure were observed in the oldest patients with the highest baseline systolic pressure (ie, those who are most prone to bleeding should they receive anticoagulation).27 SGLT2is may also reduce the predisposition to bleeding associated with anticoagulation and aid hemostasis by lowering the risk of acute kidney injury, including that requiring dialysis, and slowing progression of chronic kidney disease.28,29

AF is closely linked with endothelial dysfunction, a key component of the Virchow triad for thrombogenesis associated with several adverse outcomes, such as thromboembolism, abnormal hemostasis, and bleeding.30 SGLT2is have been shown to decrease the levels of reactive oxygen species and proinflammatory cytokines, which can reverse endothelial dysfunction, consequently inhibiting vascular inflammation and platelet activation, and decreasing the risk of not just bleeding but also of atherosclerotic and thrombogenic events.31,32 This may explain the reduced risk of ischemic and hemorrhagic strokes, MI, and TEs observed in our study. SGLT2is were associated with a 20%–25% lower risk of IS/TIA in the entire AF as well as AF‑diabetes and AF‑HF cohorts. Similar decreases have been reported in the few studies that have examined the association between this outcome with the SGLT2i use in patients with pre‑existing AF,33-35 except for a single study where no significant difference was observed.36 In addition, our findings showed a 31% reduction in the risk of hemorrhagic stroke, consistent with findings from existing meta‑analyses (though not exclusively based on AF patients).37,38

Another key finding from our analysis was the reduction in AF/AFl hospitalizations and composite of cardioversions and ablations even after taking antiarrhythmic drugs into account. These findings are supported by several clinical studies36,39-44 demonstrating a significantly lower risk of AF‑related health care utilization in terms of hospital visits, need for subsequent cardioversion, redo ablation, and new antiarrhythmic drug therapy post–catheter ablation as well as a reduced risk of AF recurrence with SGLT2i use, suggesting they may have antiarrhythmic properties. This is hypothesized by Paasche et al,45 whose study showed that treatment with dapagliflozin was associated with a significant reduction in the excitability of cardiomyocytes and reduction in the myocardial conduction velocity, more pronounced in the atrial than ventricular cells.

In addition to the direct antiarrhythmogenic effects, SGLT2i‑induced decreases in the level of epicardial fat and proinflammatory adipokines, which contribute to cardiac remodeling, processes involving intracellular sodium / calcium homeostasis that may increase threshold for arrhythmic triggers and off‑target actions, such as reductions in plasma volume and glucose‑induced inflammation, may also play a role.46,47 It is unlikely that arrhythmia risk mitigation solely occurs due to processes that take place in isolation within the cardiovascular system. Disease modification and prevention resulting from SGLT2i impacting various pathways within the renal, endocrine, and metabolic systems are likely to mediate this risk. Of course, it is entirely possible that SGLT2is have no bearing on the arrhythmia risk but offer better symptom control in AF patients, reducing their need for further treatment and intervention. It is well evidenced that AF management addressing symptom control is associated with better outcomes.48,49

Given the lack of SGLT2 proteins in the heart, it is believed that the direct antiarrhythmic effects of SGLT2is are executed through their action on SGLT1 proteins found in cardiomyocytes.47,50 Drugs such as dapagliflozin and empagliflozin have been shown to have high SGLT2/SGLT1 selectivity, whereas canagliflozin is comparatively less selective. This would imply that canagliflozin has a greater antiarrhythmic potential than empagliflozin and dapagliflozin but the latter appears to have the most evidence as an antiarrhythmic, with some studies even suggesting that the reduced risk of arrhythmias is driven by dapagliflozin alone.51 Currently, it is unclear if certain drugs within this class are more likely to exert these effects.

There is inconsistent evidence regarding the risk of VAs and sudden cardiac death (SCD) associated with the SGLT2i use. In a meta‑analysis by Sfairopoulos et al,52 including 19 RCTs and over 55 000 patients, no significant differences were observed in the risk of VAs or SCD; however, event numbers were small, with 174 in the SGLT2i group and 191 in the placebo group. The meta‑analysis by Liao et al53 showed similar findings but a borderline lower risk of SCD was observed in patients with HF only, suggesting these drugs may be more advantageous in certain subgroups of patients.

In our study, SGLT2is provided a modest but significant reduction in the risk of VAs and cardiac arrests in the overall and AF‑diabetes cohorts but not the nondiabetic AF‑HF group. The numbers of ventricular arrhythmias and cardiac arrests recorded in our study were much larger, though it must be noted that cardiac arrests would have comprised cases of SCD and sudden death due to other etiologies.

At present, evidence supporting the use of SGLT2is in patients with AF primarily stem from retrospective studies on diabetic patients. Consequently, determining whether these observations are directly due to the effects of SGLT2is or to mediation of risk factors such as diabetes and associated complications, or even HF, which shares a bidirectional relationship with AF, is not possible. Our subanalysis of the AF‑HF cohort indicates that the SGLT2i use is associated with a significantly reduced risk of adverse outcomes, regardless of diabetes, and further studies like this and RCTs will inform whether or not SGLT2is can be integrated into AF management as a treatment pillar. Several RCTs are currently underway investigating the effects of SGLT2is on AF recurrence,54 disease burden, and quality of life and atrial remodeling.55 Mechanistic studies examining the underlying processes are also warranted for further insights.

Limitations

This study is subject to limitations associated with any retrospective analysis, such as residual confounding and potential data inaccuracies. As TriNetX data comprise EMRs, data quality is subject to precision of information recorded locally at the respective HCOs. Since these data are unlikely to have been collected specifically for research purposes, it is possible that certain characteristics, such as smoking history, are underreported. Further, hospitalizations or procedures undertaken at a different non‑HCO site may not have been taken into account, which may have underestimated the outcome events. It was also impossible to determine how long the patients had been on SGLT2is prior to follow‑up and compare outcomes for individual SGLT2is or according to type and duration of AF.

Conclusions

Previous studies have signaled the reduced risk of incident AF in diabetic patients taking SGLT2is. Our findings suggest that the benefits of SGLT2is may extend further to those with pre‑existing AF with and without diabetes, and reduce the need for procedures such as ablations / cardioversions and risk of complications such as bleeding.

SUPPLEMENTARY MATERIAL
Supplementary material.pdf
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Acknowledgments: None.
Funding: None.
Contribution statement: All authors contributed to the study conception and design. Data analysis, data interpretation, and the first draft of the manuscript: AMF. Project supervision and critical revision: GYHL and LF. All authors commented on previous versions of the manuscript, read, and approved the final manuscript.
Conflict of interest: AB is a consultant and speaker for Medtronic, AstraZeneca, BMS/Pfizer, and Bayer. GYHL is a consultant and speaker for BMS/Pfizer, Medtronic, Boehringer Ingelheim, Anthos, and Daiichi‑Sankyo. He is a coprincipal investigator of the AFFIRMO project on multimorbidity in AF, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 899871. No fees are directly received personally. LF is a consultant and speaker for AstraZeneca, Bayer, BMS/Pfizer, Boehringer Ingelheim, Medtronic, Novartis, Novo, XO, and Zoll. Other authors declare no conflict of interest.
AI statement: Artificial intelligence was not used in the preparation of this manuscript.
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