Abstract
Little is known about the effects of sodium-glucose co-transporter 2 inhibitors (SGLT2i) on atherosclerosis. We aimed to determine if a 90-day intake of Dapagliflozin could improve atherosclerosis biomarkers (namely endothelial function assessed by flow-mediated dilatation [FMD] and carotid intima-media thickness [CIMT]) in diabetic and non-diabetic acute coronary syndrome (ACS) patients when initiated in the early in-hospital phase. ATH-SGLT2i was a prospective, single-center, observational trial that included 113 SGLT2i naive patients who were admitted for ACS and who were prescribed Dapagliflozin at a fixed dose of 10 mg during their hospital stay for either type 2 diabetes or for heart failure. After 90 days of follow-up, subjects who had a continuous intake of Dapagliflozin formed the SGLT2i group, while patients who did not take Dapagliflozin formed the non-SGLT2i group. In each of these main study groups, we considered diabetic and non-diabetic subgroups. The primary endpoint was the difference in between baseline and 90 days in FMD (∆FMD) and in FMD rate (∆FMD%). The secondary outcome was change in CIMT (∆CIMT). We enrolled 54 patients in the SGLT2i group aged 59 ± 9 years (70.4% males) which 30 were diabetics, and 59 in the non-SGLT2i group aged 63 ± 11 years (78% males) which 34 were diabetics. After 90 days, ∆FMD and ∆ FMD% were higher in the SGLT2i group in comparison with the non-SGLT2i group (0.05 ± 0.15 vs −0.05 ± 0.11, P < .001 and 1.78 ± 3.63 vs −0.88 ± 4, P < .001). Within the SGLT2i group, the improvement of FMD% was higher in non-diabetic patients (2.85 ± 3.46 vs 0.9 ± 3.59, P = .05). Multivariate analysis showed that Dapagliflozin intake was independently associated with FMD% improvement (HR = 2.24). After 90 days, CIMT showed no significant difference between the SGLT2i and the non-SGLT2i groups. In this pilot study, a 90-day intake of Dapagliflozin at the fixed dose of 10 mg started in the acute phase of an ACS, was associated with endothelial function improvement in diabetic and non-diabetic patients.
Keywords: acute coronary syndrome, atherosclerosis, Dapagliflozin, endothelial function
1. Introduction
Sodium-glucose co-transporter 2 inhibitors (SGLT2i) reduced cardiovascular (CV) events in patients with heart failure (HF)[1] and chronic kidney disease[2] independent of their antidiabetic effect. Nevertheless, SGLT2i were first validated as antidiabetic agents through a blockage of the sodium-glucose cotransporters located at the luminal side of the proximal convoluted tubule, thus inducing glucosuria and natriuresis with a reduction of fasting and post-prandial glycemia and resulting in an energetic loss and a moderate weight loss. SGLT2i were further proven to reduce atherosclerosis-related cardiovascular diseases (ASCVD) morbidity and mortality in high-risk type 2 diabetic patients and in the setting of ASCVD secondary prevention. Currently, SGLT2i are recommended as first-line antidiabetic agents in these patients.[3]
SGLT2i efficacy was explained by several mechanisms. Besides inhibiting the reuptake of glucose and sodium allowing glucosuria and an increased natriuresis, they might act through anti-atherosclerotic pathways. Interestingly, in human and experimental studies, improvement in both glycemic control and lipid profile,[4–7] endothelial function,[4,7–9] as well as a reduction of oxidative stress[10,11] and foam cell formation were reported. In this regard, it has been anticipated that the benefits of SGLT2i could extend to secondary prevention of ASCVD even in non-diabetic patients. This study aimed to assess the effects of early initiation of Dapagliflozin during the acute phase of coronary artery syndromes (ACS) on endothelial function and atherosclerosis biomarkers assessed after a 90-day follow-up in diabetic and non-diabetic patients.
2. Patients and methods
This prospective observational single-center study (September 2022 to June 2023) followed the Declaration of Helsinki on Clinical Research and Ethics, it was approved by the local Rabta Hospital of Tunis Review Board (approval number: CERB 05/2023). Informed consent was obtained from all subjects for the participation in the study and the publication its results.
2.1. Population
Successive ACS patients admitted for either ST-elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction, or unstable angina (defined by the 4th universal definition of myocardial infarction[12] and ACS in patients presenting without persistent STEMI European guidelines[13]) and aged ≥ 18 years were enrolled when they were:
SGLT2i naïve
and were prescribed SGLT2i during their hospital stay for type 2 diabetes, left ventricular ejection fraction (LVEF) ≤ 40%, or clinical HF defined according to HF esc guidelines (regardless of LVEF).[1]
Non-inclusion criteria were:
Cardiogenic shock, mechanical complications
Calculated creatinine clearance by chronic kidney disease-epidemiology collaboration < 20 mL/minute
Baseline systolic blood pressure (SBP) < 95 mm Hg
Type 1 diabetes
History of diabetic ketoacidosis
Active cancer
Genito-urinary infection during the hospital stay or recurrent (≥2) episodes in the last 6 months
Planned cardiovascular surgery in the next 3 months
Patients who were not followed up in our hospital and those who underwent unplanned cardiovascular surgery during the 90 days following the ACS were excluded.
Patients were categorized based on SGLT2i intake into 2 groups:
Group SGLT2i who had a continuous Dapagliflozin intake for 90 days.
Group non-SGLT2i who did not use Dapagliflozin.
Each of these 2 main study groups was subdivided into 2 subgroups according to their diabetic or non-diabetic status
SGLT2i group was subdivided into diabetic; SGL2i D and non-diabetic; SGLT2i non-D subgroups that included 30 and 24 patients respectively.
Non-SGLT2i group was subdivided as well into diabetics; non-SGLT2i D and non-diabetics; non-SGLT2i non-D subgroups that included 34 and 25 patients respectively.
2.2. Study end-points
The primary endpoint was the difference in flow mediated dilatation (∆FMD) and the difference in FMD rate (∆FMD%) between the in-hospital phase of the index ACS event and day 90 of follow-up.
The secondary endpoint was the change in carotid intima-media thickness (∆CIMT) also assessed between baseline and day 90.
2.3. Therapeutic prescriptions
All medical prescriptions during hospitalization and follow-up and SGLT2i indications complied with current ACS,[13,14] unstable angina,[13] HF,[1] cardiovascular prevention, and management of CV risk in patients with diabetes[15] guidelines.
Patients were prescribed a fixed dose of 10 mg of Dapagliflozin. The qualification of the use of SGLT2 inhibitors and consequently the classification of patients into a study group was performed through patients’ and families’ anamnesis, verification of insurance sheets and pharmacists’ seals on prescriptions, as well as verification of medicine tablets.
2.4. Data collection
Data were obtained prospectively through anamnesis, physical examination, transthoracic echocardiography, vascular echography, laboratory tests, and coronary angiography.
The flowchart of the study is depicted in Figure 1.
Figure 1.
Flowchart of the study. ACS = acute coronary syndrome, CIMT = carotid intima-media thickness, D = diabetic subjects, eGFR = glomerular filtration rate, FMD = flow-mediated dilatation, FMD% = FMD rate, HF = heart failure, LVEF = left ventricular ejection fraction, SGLT2i = sodium-glucose inhibitors.
2.4.1. Flow mediated dilatation assessment
FMD was assessed, using a Vivid E9 linear probe by the same investigator according to the expert consensus recommendations for the assessment of FMD in humans.[16] A supported operator’s hand kept the probe in the same position. FMD measurement was performed in a temperature-controlled room after a 6-hour fast and 15-minute rest. Pre-hyperemia loop records of the brachial artery and its baseline diameter were obtained. The cuff was then inflated until it reached 50 mm Hg above the SBP, it was maintained inflated for 5 minutes and then released. Hyperemia phase images of the brachial artery were captured 15 seconds before deflation. The diameter of the brachial artery was monitored for 3 minutes after deflation through serial scans to determine the maximum diameter. FMD was calculated as (maximum diameter − diameter at rest) and FMD rate (FMD%) as ([maximum diameter − diameter at rest] × 100/diameter at rest). ΔFMD was defined as (FMD on day 90 - FMD at baseline) in each patient, similarly, ΔFMD% was the variation of FMD% between baseline and day 90.
2.4.2. Carotid intima-media thickness
CIMT was performed at baseline and on day 90 by the same operator using a GE-E9L-D-10 MHz probe. The left common carotid artery was examined in a supine position 10 mm from the carotid bifurcation where the artery walls were viewed parallel. CIMT was measured from 4 points distant 1 mm from each other, at the end of the diastole, and averaged.[17] ΔCIMT was the variation of CIMT between baseline and day 90.
2.4.3. Safety concerns
The following adverse events were monitored through monthly medical checkups: hypoglycemic or hyperglycemic symptoms, ketoacidosis, dehydration, blood pressure < 90 mm Hg, and genito-urinary infections.
2.4.4. Statistical analyses
Data were recorded and analyzed using V22_IBM_SPSS Statistics softwareTM. Continuous parameters were presented as means ± standard deviation or median (25e−75e percentile) when appropriate. Counts and percentages were used for categorical data. Kolmogorov-Smirnov test was used to characterize distributions of continuous variables. Student t test was used to compare means on independent series while Pearson chi-square test was used to compare percentages. Student t test for paired samples was used to compare variations of continuous variables between baseline and 90 days. The significance level was 0.05. Linear regression was used for multivariate analysis.
3. Results
3.1. Baseline characteristics
The mean age was 60.9 ± 10 years; 84 of the 113 patients in the study were males (74.3%). STEMI represented 56.3% of index events. The most common CV risk factors were diabetes (56.6%), and smoking (54.9%). Significant differences between SGLT2i and Non-SGLT2i groups included hemoglobin level (14.09 ± 1.74g/dL vs 13.13 ± 2.47, P = .02), hematocrit (40.91 ± 4.9% vs 38.44 ± 6.66%, P = .03) and LVEF (40 [33.35–45] vs 45 [40–55], P < .001; Table 1).
Table 1.
Comparison of baseline characteristics between SGLT2i and non-SGLT2i groups.
| SGLT2i N = 54 |
SGLT2i | p1 | Non-SGLT2i N = 59 |
Non-SGLT2i | p2 | p3 | |||
|---|---|---|---|---|---|---|---|---|---|
| SGLT2i D N = 30 |
SGLT2i non-D N = 24 |
Non-SGLT2i D N = 34 |
Non-SGLT2i non-D N = 25 |
||||||
| Age (yr) | 59 ± 9 | 59 ± 8 | 58 ± 11 | 0.54 | 63 ± 11 | 64 ± 9 | 60 ± 11 | 0.14 | 0.07 |
| Females | 16 (29.6%) | 2 (8.33%) | 14 (46.66%) | 0.002 | 13 (22%) | 10 (29.41%) | 3 (12%) | 0.11 | 0.39 |
| Diabetes | 30 (55.6%) | – | – | 34 (57.6%) | – | – | – | 0.85 | |
| Duration of diabetes (yr) | 6.11 ± 7.85 | – | – | 6.27 ± 9.17 | – | – | – | 0.92 | |
| Hypertension | 29 (53.7%) | 21 (87.5%) | 8 (26.66%) | 0.007 | 32 (54.2%) | 18 (52.94%) | 14 (56%) | 0.81 | 1 |
| Smoking | 29 (53.7%) | 12 (50%) | 17 (56.66%) | 0.024 | 33 (55.9%) | 18 (52.94%) | 15 (60%) | 0.58 | 0.85 |
| Dyslipidemia | 17 (31.5%) | 14 (58.33%) | 3 (10%) | 0.007 | 23 (39%) | 15 (44.11%) | 8 (32%) | 0.34 | 0.44 |
| PAD | 1 (1.9%) | 0 (0%) | 1 (4.16%) | 0.26 | 1 (1.7%) | 0 (0%) | 1 (4%) | 0.24 | 1 |
| Stroke | 1 (1.9%) | 1 (3.33%) | 0 (0%) | 0.37 | 2 (3.4%) | 1 (2.94%) | 1 (4%) | 0.82 | 1 |
| Family history of CV disease | 3 (5.6%) | 1 (3.33%) | 2 (8.33%) | 0.42 | 0 (%) | 0 (%) | 0 (%) | 1 | 0.11 |
| Previous ACS | 16 (29.6%) | 12 (40%) | 4 (16.66%) | 0.06 | 23 (39%) | 15 (44.11%) | 8 (32%) | 0.34 | 0.33 |
| AF | 3 (5.6%) | 1 (3.33%) | 2 (8.33%) | 0.42 | 3 (5.1%) | 1 (2.94%) | 2 (8%) | 0.38 | 1 |
| BMI | 27.11 ± 4.68 | 28.07 ± 5.05 | 25.90 ± 3.94 | 0.08 | 27.69 ± 5.15 | 28.62 ± 4.43 | 26.43 ± 5.86 | 0.10 | 0.53 |
| ABI | 1.2 ± 0.16 | 1.23 ± 0.14 | 1.16 ± 0.17 | 0.13 | 1.2 ± 0.17 | 1.19 ± 0.16 | 1.21 ± 0.17 | 0.80 | 0.89 |
| SBP (mm Hg) | 120 [110–138] | 128.53 [120–136] | 121.16 [112–130] | 0.34 | 122 [116–134] | 130.94 [123–138] | 120 [115–125] | 0.02 | 0.77 |
| DBP (mm Hg) | 73.5 [69–79] | 74.16 [65–75] | 70.37 [110–138] | 0.23 | 69 [63–80] | 73.67 [69–78] | 72.28 [64–80] | 0.74 | 0.82 |
| STEMI | 33 (61.1%) | 16 (53.33%) | 17 (70.83%) | 0.19 | 31 (52.5%) | 16 (47.05%) | 15 (60%) | 0.32 | 0.45 |
| NSTEMI | 19 (35.2%) | 12 (40%) | 7 (29.16%) | 0.41 | 24 (40.7%) | 15 (44.11%) | 9 (36%) | 0.53 | 0.57 |
| Unstable angina | 2 (3.7%) | 2 (6.66%) | 0 (0%) | 0.19 | 4 (6.8%) | 3 (8.82%) | 1 (4%) | 0.46 | 0.68 |
| LVEF (%) | 40% [33.25–45] | 41.5% [38–45] | 36.36% [33–40] | 0.03 | 45% [40–55] | 51.5% [48–55] | 40.68% [38–43] | <0.001 | <0.001 |
| HBA1C (%) | 7.38 ± 2.27 | 8.96 ± 2.03 | 5.57 ± 0.43 | <0.001 | 7.29 ± 2.15 | 8.69 ± 1.9 | 5.5 ± 0.38 | <0.001 | 0.83 |
| Creatinin (μmol/L) | 81.82 ± 21.42 | 80.27 ± 17.74 | 83.75 ± 25.55 | 0.57 | 87 ± 30 | 86.12 ± 32.28 | 88.18 ± 27.30 | 0.79 | 0.3 |
| Hemoglobin | 14.09 ± 1.74 | 13.84 ± 1.67 | 14.39 ± 1.80 | 0.25 | 13.13 ± 2.47 | 12.53 ± 2.23 | 13.91 ± 2.58 | 0.03 | 0.02 |
| Hematocrit | 40.91 ± 4.9 | 40.14 | 41.87 | 0.20 | 38.44 ± 6.66 | 36.74 ± 5.93 | 40.68 ± 7.01 | 0.02 | 0.03 |
| NLR | 3.77 ± 2.94 | 3.20 ± 2.30 | 4.46 ± 3.50 | 0.13 | 2.93 ± 1.84 | 2.87 ± 1.69 | 2.99 ± 2.04 | 0.81 | 0.07 |
| Uric acid (mmol/L) | 389.29 ± 125.6 | 366.58 ± 107.75 | 418.48 ± 142.79 | 0.17 | 349.45 ± 116.23 | 326.92 ± 79.97 | 381.18 ± 150.03 | 0.09 | 0.1 |
| Total cholesterol (mmol/L) | 4.34 ± 1.45 | 4.55 ± 1.63 | 4.06 ± 1.15 | 0.20 | 4.15 ± 1.02 | 4.01 ± 1.04 | 4.33 ± 0.96 | 0.23 | 0.41 |
| Triglycerides (mmol/L) | 1.9 ± 1.33 | 2.14 ± 1.49 | 1.59 ± 1.01 | 0.12 | 1.54 ± 0.68 | 1.67 ± 0.78 | 1.36 ± 0.48 | 0.09 | 0.07 |
| Angiotensin-converting enzyme inhibitors | 49 (92.5%) | 29 (96.66%) | 24 (100%) | 0.21 | 55 (93.2%) | 31 (91.17%) | 24 (96%) | 0.46 | 1 |
| Beta blockers | 54 (100%) | 29 (96.66%) | 24 (100%) | 0.21 | 56 (94.9%) | 33 (97.05%) | 23 (95.83%) | 0.38 | 0.25 |
| Calcium channel inhibition | 15 (28.3%) | 28 (93.33%) | 21 (87.5%) | 0.02 | 10 (16.9%) | 10 (29.41%) | 0 (0%) | 0.003 | 0.18 |
| Molsidomine | 0 (0%) | 0 (0%) | 0 (0%) | 1 | 2 (3.4%) | 2 (5.88%) | 0 (0%) | 0.21 | 0.5 |
| FMD (mm) | 0.25 ± 0.12 | 0.24 ± 0.10 | 0.26 ± 0.14 | 0.61 | 0.28 ± 0.12 | 0.26 ± 0.12 | 0.30 ± 0.12 | 0.22 | 0.16 |
| FMD% | 6.73 ± 3.4 | 7.06 ± 3.38 | 6.33 ± 3.45 | 0.45 | 7.45 ± 3.61 | 6.85 ± 3.27 | 8.26 ± 3.95 | 0.14 | 0.28 |
| CIMT (mm−1) | 6.53 ± 1.14 | 6.66 ± 0.94 | 6.38 ± 1.35 | 0.38 | 6.64 ± 1.2 | 6.62 ± 1.04 | 6.68 ± 1.41 | 0.85 | 0.16 |
ABI = ankle brachial index, ACS = acute coronary syndrome, AF = atrial fibrillation, BMI = body mass index, CIMT = carotid intima media thickness, CVD = cardiovascular disease, DBP = diastolic blood pressure, FMD = flow mediated dilation, FMD% = FMD rate, HBA1C = glycated hemoglobin, LVEF = left ventricular ejection fraction, NLR = neutrophils to lymphocyte ratio, NSTEMI = acute myocardial infarction without persistent ST segment elevation, PAD = peripheral arterial disease, p1 = difference between SGLT2i D and SGLT2i non-D groups, p2 = difference between non-SGLT2i D and non-SGLT2i non-D groups, p3 = difference between SGLT2i and non-SGLT2i groups, SBP = systolic blood pressure, SGLT2i = sodium glucose cotransporter2 inhibitors (group designation), STEMI = acute myocardial infarction with persistent ST segment elevation, – = not analyzed.
3.2. Baseline atherosclerosis markers
There was no statistical difference between the study groups in terms of atherosclerosis markers namely FMD (0.25 ± 0.12 vs 0.28 ± 0.12, P = .16), FMD% (6.73 ± 3.4 vs 7.45 ± 3.61, P = .28) and CIMT (6.53 ± 1.14 vs 6.64 ± 1.2, P = .16; Table 1).
3.3. Metabolic parameters change after 90 days from the index ACS event
Metabolic variations between baseline and day 90 did not show statistically significant differences in the study groups (Table 2).
Table 2.
Comparison of atherosclerosis markers on day 90.
| SGLT2i | p1 | Non-SGLT2i | p2 | p3 | |||
|---|---|---|---|---|---|---|---|
| SGLTi D N = 30 |
SGLT2i non-D N = 24 |
Non-SGLT2i D N = 34 |
Non-SGLT2i non-D N = 25 |
||||
| FMD (mm) | 0.3 ± 0.09 | 0.36 ± 0.15 | 0.07 | 0.21 ± 0.09 | 0.30 ± 0.11 | 0.02 | <0.001 |
| FMD% | 8.56 ± 2.81 | 9.58 ± 4.62 | 0.34 | 5.51 ± 2.33 | 8.01 ± 3.94 | 0.003 | <0.001 |
| CIMT (mm−1) | 6.34 ± 0.94 | 6.34 ± 1.36 | 0.99 | 6.50 ± 1.29 | 7.04 ± 1.68 | 0.17 | 0.14 |
CIMT = carotid intima media thickness, D = diabetic, FMD = flow mediated dilation, FMD% = FMD rate, p1 = difference between SGLT2i D and SGLT2i non-D groups, p2 = difference between non-SGLT2i D and non-SGLT2i non-D groups, p3 = difference between SGLT2i and non-SGLT2i groups, SGLT2i = sodium glucose cotransporter 2 inhibitors (group designation).
3.4. Endothelial function after 90 days from the index ACS event
After a 90-day treatment with Dapagliflozin, absolute values of FMD and FMD% were significantly higher in the SGLT2i group in comparison with the non-SGLT2i group (0.33 ± 0.12 vs 0.25 ± 0.11, P < .001) and (9.02 ± 3.74 vs 6.57 ± 3.33, P < .001) respectively. There was no difference, however, in CIMT values (6.34 ± 1.13 vs 6.72 ± 1.47, P = .14; Table 2).
Within the SGLT2i group, there was no significant difference in FMD, FMD%, and CIMT after 90 days, between diabetic (SGL2i D) and non-diabetic (SGLT2i non-D) patients. In the non-SGLT2i group; however, after 90 days, FMD and FMD% were significantly higher in non-diabetic patients; (0.30 ± 0.11 vs 0.21 ± 0.09, P = .02) and (8.01 ± 3.94 vs 5.51 ± 2.33, P = .03; Table 2).
3.5. Changes in carotid intima-media thickness between baseline and 90 days
Mean CIMT decreased after 90 days but there was no significant difference between SGLT2i and non-SGLT2i groups in ΔCIMT (−0.12 ± 1.03 vs −0.03 ± 1.31, P = .70; Tables 2 and 3).
Table 3.
Comparison of change in atherosclerosis markers between SGLT2i and non-SGT2i.
| SGLT2i N = 54 |
SGLT2i | p1 | Non-SGLT2i N = 59 |
Non-SGLT2i | p2 | p3 | |||
|---|---|---|---|---|---|---|---|---|---|
| SGLT2i D N = 30 |
SGLT2i non-D N = 24 |
Non-SGLT2i D N = 34 |
Non-SGLT2i non-D N = 25 |
||||||
| ∆FMD (mm) | 0.08 ± 0.11 | 0.05 ± 0.11 | 0.10 ± 0.10 | 0.11 | −0.03 ± 0.13 | −0.05 ± 0.13 | −0.008 ± 0.12 | 0.18 | <0.001 |
| ∆FMD% | 1.78 ± 3.63 | 1.38 ± 3.19 | 2.85 ± 3.46 | 0.05 | −0.88 ± 4 | −1.34 ± 3.72 | −0.25 ± 4.33 | 0.31 | <0.001 |
| ∆CIMT (mm−1) | −0.12 ± 1.03 | −0.24 ± 0.8 | 0.02 ± 1.2 | 0.38 | −0.03 ± 1.31 | −0.12 ± 0.73 | 0.08 ± 1.85 | 0.57 | 0.7 |
| ∆HBA1C% | −0.27 ± 1.55 | −1.01 ± 1.18 | −0.31 ± 1.50 | 0.16 | −0.08 ± 1.63 | −0.36 ± 2.20 | 0.18 ± 0.29 | 0.34 | 0.61 |
| ∆Uric acid (mmol/L) | −51.3 ± 70.9 | −41.89 ± 68.34 | −125 ± 170.26 | 0.16 | −16.3 ± 99.4 | −23.34 ± 115.78 | −7.82 ± 77.54 | 0.63 | 0.08 |
| ∆NLR | −0.56 ± 6.92 | −0.67 ± 2.58 | −0.41 ± 10.29 | 0.91 | −0.54 ± 2 | −0.31 ± 1.85 | −0.88 ± 2.22 | 0.38 | 0.98 |
| ∆Hematocrit (%) | 0.59 ± 5.23 | 0.67 ± 4.92 | −2.77 ± 10.24 | 0.22 | 1.92 ± 4.93 | 2.28 ± 4.25 | 1.37 ± 5.89 | 0.57 | 0.27 |
| ∆Hemoglobin (g/dL) | −0.16 ± 1.66 | −0.02 ± 1.55 | −0.55 ± 1.66 | 0.32 | 0.27 ± 1.54 | 0.30 ± 1.17 | 0.21 ± 2.02 | 0.87 | 0.18 |
| ∆ Total cholesterol (mmol/L) | −0.75 ± .12 | −0.58 ± 1.32 | −0.97 ± 0.75 | 0.24 | −0.39 ± 1.19 | −0.38 ± 1.29 | −0.40 ± 1.04 | 0.96 | 0.15 |
| ∆Triglycerides (mmol/L) | −0.09.98 | −0.27 ± 0.83 | 0.28 ± 1.22 | 0.13 | −0.23 ± 0.63 | −0.31 ± 1.85 | −0.88 ± 2.22 | 0.28 | 0.43 |
Δ = change from baseline, CIMT = carotid intima media thickness, FMD = flow mediated dilation, FMD% = FMD rate, HBA1C = glycated hemoglobin, NLR = neutrophils to lymphocyte ratio, p1 = difference between SGLT2i D and SGLT2i non-D groups, p2 = difference between non-SGLT2i D and non-SGLT2i non-D groups, p3 = difference between SGLT2i and non-SGLT2i groups, SBP = systolic blood pressure, SGLT2i = sodium glucose cotransporter 2 inhibitors (group designation).
3.6. Changes in FMD between baseline and 90 days
Treatment with Dapagliflozin was associated with a significant improvement of both FMD and FMD% in comparison with non-SGLT2i patients (0.08 ± 0.11 vs −0.03 ± 0.13, P < .001) and (1.78 ± 3.63 vs −0.88 ± 4, P < .001) respectively. This finding was observed in both diabetic and non-diabetic subgroups. Within the SGLT2i group, the increase of FMD% was higher in non-diabetic patients, in comparison with diabetic subjects (0.9 ± 3.59 vs 2.85 ± 3.46, P = .05; Table 3). Figure 2 depicts FMD change in the 4 study subgroups.
Figure 2.
Boxplots representing changes in flow-mediated dilation rate in sodium-glucose cotransporter 2 inhibitors intake and diabetes status subgroups. Δ = change from baseline, FMD% = flow mediated dilation rate, SGLT2i = sodium glucose cotransporter 2 inhibitors.
3.7. Multivariate analysis
Multivariate stepwise regression analysis showed 4 independent predictors of FMD% improvement. SGLT2i intake was the strongest associated predictor (T = 2.24, P < .001). The other factors were baseline FMD% (T = −0.57, P < .001), diabetes (T = −1.2, P = .04) and age (T = −0.085, P = .005; Table 4).
Table 4.
Multivariate analysis.
| Variable | t | P value |
|---|---|---|
| FMD% at baseline | −0.57 | <.001 |
| Diabetes | −1.2 | .045 |
| Age | −0.085 | .005 |
| SGLT2i intake | 2.24 | <.001 |
FMD% = flow mediated dilation rate, SGLT2i = sodium glucose cotransporter 2 inhibitors.
4. Discussion
This prospective pilot study enrolled 113 ACS patients to evaluate the effects of SGLT2i on atherosclerosis markers; primarily endothelial function (by FMD) and secondarily CIMT.
The main findings were:
-
-
FMD and FMD% were significantly improved after 90 days of regular intake of Dapagliflozin in comparison with the non-SGLT2i group (0.08 ± 0.11 vs −0.03 ± 0.13, P ≤ 0.001 for FMD and 1.78 ± 3.63 vs −0.88 ± 4, P < .001 for FMD%).
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SGLT2i improved FMD significantly in diabetic and non-diabetic patients.
-
-
This improvement was significantly higher in the SGLT2i non-D group in comparison with SGLT2i D group.
-
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SGLT2i was an independent factor associated positively with FMD improvement besides type 2 diabetes mellitus (T2DM), age, and baseline FMD which were negative independent factors.
-
-
There was no difference in CIMT change between SGLT2i and non-SGLT2i groups.
4.1. Effect of Dapagliflozin treatment on endothelial function
The improvement in FMD among patients who received 10 mg of Dapagliflozin was likely to be specifically attributed to the drug as there was no substantial difference between the groups in endothelial function determinants (smoking, T2DM and duration of T2DM, age, baseline FMD). Notably, none of the individuals SGLT2i group received Molsidomine and there were no differences between study groups in angiotensin conversion enzyme inhibitors or calcium channel blockers intake. Multivariate analysis showed an independent association between FMD and SGLT2i.
Previous human studies that evaluated endothelial function effects of SGLT2i were conducted in diabetic subjects. Most of them used FMD to assess endothelial function.
Solini et al study was the first human pilot study conducted in 2016 in selected stable diabetic subjects without significant renal or cardiovascular disease. It reported an acute (48 hours) improvement of vascular indices; FMD% in SGLT2i vs Control (hydrochlorothiazide) group (2.81 ± 2.25 [baseline]/4.02 ± 2.09 [48 hours] vs 2.99 ± 0.91 [baseline]/2.63 ± 1.01 [48 hours], P = .02). Arterial stiffness and renal resistive index were also improved. The authors suggested a direct benefit through oxidative stress effect.[18] However, the same authors found a controversial result in a further cohort of hypertensive and diabetic patients submitted to 4 weeks of treatment, with no significant difference in FMD%.[19] In the DEFENCE study, the Dapagliflozin effect on endothelial function in early-stage diabetics was negative but authors reported FMD improvement in patients who had a high glycated hemoglobin (HbA1c) > 7%[20] with a reduction in a urine oxidative stress biomarker (8-hydroxy-2-deoxyguanosine).
Align with ours’, EDIFIED study involved higher risk patients with established ischemic disease who received 12 weeks of Dapagliflozin. However, it did included diabetic but not ACS patients. There was no significant difference in FMD% change (0.19 ± 10.38 vs −1.36 ± 7.76, P = .40). A suboptimal and unbalanced reduction in blood pressure could explain this negative result. Similarly to DEFENCE study, authors noted a correlation between SGLT2i effect on FMD and glycemic control (HbA1c; r = −0.4; P = .017).[21]
SGLT2i became a major treatment of HF. Sakai et al enrolled a cohort of 184 diabetic, preserved ejection fraction HF patients who received SGLT2i for 12 weeks. FMD% improved similarly in the 3 SGLT2i arms.[7] Correale et al[8] found a significant improvement in FMD which was correlated with SGLT2i use in HF patients. Finally, Batzias et al[22] published a systematic review where they found that only SGLT2i significantly improved endothelial function among different antidiabetic classes.
Studies are summarized in a comparative table (Table 5).
Table 5.
comparative table of human studies about SGLT2i effects on endothelial function.
| Author publication date | Cohort size | Molecule Duration |
Investigation group | Control group | Endothelial function | Result |
|---|---|---|---|---|---|---|
| Solini, 2017[18] | 26 | Dapagliflozin 48 hr |
T2DM 40–70 yo, HBA1c < 6.4%, no renal or CV significant disease | Hydrochlorothiazide | Δ FMD% | P = .02 |
| Solini, 2019[19] | 40 | Dapagliflozin 4 wk |
T2DM and hypertensives, 40–75 yo, HBA1c < 6.4%, no renal or CV significant disease | Hydrochlorothiazide | ΔFMD% Circulating miRNAs: miR27b and miR200b |
NS NS |
| Shigiyama, 2017[20] | 80 | Dapagliflozin | T2DM, 20–74 yo, HBA1C 6% to 8% no significant CV disease or severe renal insufficiency | Metformin | ΔFMD% ΔFMD% in patients with HBA1C > 7% |
NS P < .05 |
| Zainordin, 2020[21] | 72 | Dapagliflozin | High risk T2DM 30–75 yo with HBA1c 7% to 10.5%, and an established ischemic heart disease significant renal insufficiency | Placebo | ΔFMD ICAM-1 eNOS |
NS NS NS |
| Sakai, 2019[7] | 184 | 3 study arms Empagliflozin (10–25 mg), luseogliflozin (2.5–5 mg), tofogliflozin (20 mg) 3 mo |
HFpEF and T2DM | – | Δ FMD% | P < .05 |
| Correale, 2022[8] | 55 | Empagliflozin (14), Dapagliflozin (4) canagliflozin (3) 3 mo |
HF and T2DM without moderate or severe renal insufficiency | Observational study. Other antidiabetic drugs in patients who did not switch to SGLT2i despite HF | Δ FMD% | <0.001 |
| Our study | 113 | Dapagliflozin 3 mo |
ACS patients either diabetic or non-diabetic patients, without restriction for renal function unless contraindicating SGLT2i use | Observational study. Patients who did not use SGLT2i for diabetes or HF | Δ FMD% | P < .001 |
Δ = change from baseline, ACS = acute coronary syndrome, CV = cardiovascular, FMD = flow-mediated dilation, HBA1c = Glycated hemoglobin, HFpEF = heart failure with preserved ejection fraction, ICAM-1 = intercellular adhesion molecule 1, eNOS = endothelial nitric oxide synthase, T2DM =type2 diabetes mellitus.
Concerning non-diabetic patients, our study is to our knowledge, the first trial encompassing this patients’ category. In non-diabetics FMD% was enhanced by SGLT2i intake while it deteriorated in the non-SGLT2i non-D group with a significant difference (P = .008). Also notably, among patients who received SGLT2i, FMD improvement was more pronounced in the SGLT2i non-D group. This suggests an impact of Dapagliflozin on the endothelium, independent of glycemic control. This finding is supported by non-human studies. Alshnbari et al[23] led a meta-analysis that collected 24 studies using animals, vascular tissue, or vascular endothelial cells in both diabetic and non-diabetic models. They found direct underlying mechanisms of action of SGLT2i on endothelial function independent of glucose-lowering effect such as vasodilation via K + channels activation, increased NO production, delayed vascular fibrosis, and reduced macrophage infiltration.[23]
Clinical implications: Endothelial dysfunction was considered a critical early step in atherosclerosis. It was further found to be a major prognostic factor. A meta-analysis indicated that each 1% rise in FMD% leads to a 13% reduction in cardiovascular risk.[21] Other extensive studies showed that FMD independently predicted cardiac events in moderate to high CV-risk patients.[24] Finally, FMD predicted restenosis in patients who underwent coronary angioplasty.[25]
4.2. Effect of Dapagliflozin on CIMT
CIMT was reduced in our SGLT2i patients but without statistical difference in comparison with the Non-SGLT2i group. In this regard, studies were led in diabetic populations. Even if positive results were found in small samples or nonspecific cohorts,[26] in UTOPIA; a prospective randomized study led in 340 T2DM patients, followed for 104 weeks, tofogliflozin reduced CIMT compared to baseline (−0.132 ± 0.007, P < .001), but there was not a significant difference between the tofogliflozin and the control groups[27] thereby corroborating our results.
CIMT is a noninvasive measure of subclinical atherosclerosis with an established association with coronary artery disease.[28] CIMT reduction is beneficial and was observed similarly in SGLT2i non-SGLT2i groups, it could be induced by agents used in our ACS patients like statins. The duration of the study might impede the emergence of a significant difference between the SGLT2i and the control groups.
Finally, the recent EMAPACT-myocardial infarction study[29] included ACS patients at risk of HF, the primary endpoint: time to hospitalization for heart failure or death from any cause, was negative. One of the key secondary endpoints was any cause of death or hospitalization for myocardial infarction which was negative as well.
The main study limitations were its monocentric, small size, limited duration, and observational characteristics. The use of a probe holder could improve the accuracy of our measurements.
5. Conclusion
This pilot study was led in a specific high-risk population consisting of ACS patients. Its main particularity was the inclusion of both diabetic and non-diabetic patients. It showed a significant improvement in endothelial function assessed by FMD associated with Dapagliflozin use. Our major practical fallout was that the use of SGLT2i in all ACS patients improved endothelial function in both diabetic and non-diabetic subgroups and thus reduced atherosclerosis burden. However, large clinical trials are needed before the transfer of these results to clinical practice randomized, large clinical trials are needed.
Author contributions
Conceptualization: Fathia Mghaieth Zghal.
Data curation: Fathia Mghaieth Zghal, Manel Abbassi, Ahlem Silini, Sana Ouali, Abdeljelil Farhati.
Formal analysis: Manel Abbassi, Ahlem Silini, Nadia Ben Mansour.
Investigation: Manel Abbassi, Zeynab Jebberi.
Methodology: Fathia Mghaieth Zghal, Manel Abbassi.
Project administration: Fathia Mghaieth Zghal.
Resources: Foued Daly.
Supervision: Fathia Mghaieth Zghal, Mohamed Sami Mourali.
Validation: Fathia Mghaieth Zghal, Manel Ben Halima, Nadia Ben Mansour.
Writing – original draft: Fathia Mghaieth Zghal, Manel Abbassi, Zeynab Jebberi.
Writing – review & editing: Manel Ben Halima, Foued Daly, Selim Boudiche, Mohamed Sami Mourali.
Abbreviations:
- ACS
- acute coronary syndrome
- ASCVD
- atherosclerotic cardiovascular disease
- CIMT
- carotid intima-media thickness
- CV
- cardiovascular
- FMD
- flow mediated dilation
- HbA1C
- glycated hemoglobin
- HF
- heart failure
- LVEF
- left ventricular ejection fraction
- SBP
- systolic blood pressure
- SGLT2i
- sodium-glucose co-transporter 2 inhibitors
- STEMI
- myocardial infarction with ST-segment elevation
- T2DM
- type 2 diabetes mellitus.
The authors have no funding and conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Mghaieth Zghal F, Abbassi M, Silini A, Ben Halima M, Jebberi Z, Daly F, Ouali S, Farhati A, Ben Mansour N, Boudiche S, Mourali MS. Impact of sodium-glucose cotransporter inhibitors in acute coronary syndrome patients on endothelial function and atherosclerosis related-biomarkers: ATH-SGLT2i pilot study. Medicine 2024;103:47(e40536).
Contributor Information
Manel Abbassi, Email: abbassimanel2018@gmail.com.
Ahlem Silini, Email: ahlemsilini7@gmail.com.
Manel Ben Halima, Email: manel.benhalima@fmt.utm.tn.
Zeynab Jebberi, Email: zeynab.jebberi@fmt.utm.tn.
Foued Daly, Email: foued.daly@fmt.utm.tn.
Sana Ouali, Email: sana.ouali@fmt.utm.tn.
Abdeljelil Farhati, Email: abdeljelil_farhati@yahoo.fr.
Nadia Ben Mansour, Email: nadia.benmansour@fmt.utm.tn.
Selim Boudiche, Email: selim.boudiche@fmt.utm.tn.
Mohamed Sami Mourali, Email: mouralimsm@yahoo.fr.
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