Literature DB >> 26268857

Lack of correlation between the optimal glycaemic control and coronary micro vascular dysfunction in patients with diabetes mellitus: a cross sectional study.

Luis Felipe Valenzuela-Garcia1, Yasushi Matsuzawa2, Jaskanwal D S Sara3, Taek-Geun Kwon4, Ryan J Lennon5, Lilach O Lerman6, Rafael J Ruiz-Salmeron7, Amir Lerman8.   

Abstract

BACKGROUND: Coronary microvascular dysfunction (CMD) is associated with cardiovascular events in type 2 diabetes mellitus (T2DM). Optimal glycaemic control does not always preclude future events. We sought to assess the effect of the current target of HBA1c level on the coronary microcirculatory function and identify predictive factors for CMD in T2DM patients.
METHODS: We studied 100 patients with T2DM and 214 patients without T2DM. All of them with a history of chest pain, non-obstructive angiograms and a direct assessment of coronary blood flow increase in response to adenosine and acetylcholine coronary infusion, for evaluation of endothelial independent and dependent CMD. Patients with T2DM were categorized as having optimal (HbA1c < 7%) vs. suboptimal (HbA1c ≥ 7%) glycaemic control at the time of catheterization.
RESULTS: Baseline characteristics and coronary endothelial function parameters differed significantly between T2DM patients and control group. The prevalence of endothelial independent CMD (29.8 vs. 39.6%, p = 0.40) and dependent CMD (61.7 vs. 62.2%, p = 1.00) were similar in patients with optimal vs. suboptimal glycaemic control. Age (OR 1.10; CI 95% 1.04-1.18; p < 0.001) and female gender (OR 3.87; CI 95% 1.45-11.4; p < 0.01) were significantly associated with endothelial independent CMD whereas glomerular filtrate (OR 0.97; CI 95% 0.95-0.99; p < 0.05) was significantly associated with endothelial dependent CMD. The optimal glycaemic control was not associated with endothelial independent (OR 0.60, CI 95% 0.23-1.46; p 0.26) or dependent CMD (OR 0.99, CI 95% 0.43-2.24; p = 0.98).
CONCLUSIONS: The current target of HBA1c level does not predict a better coronary microcirculatory function in T2DM patients. The appropriate strategy for prevention of CMD in T2DM patients remains to be addressed.

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Year:  2015        PMID: 26268857      PMCID: PMC4535762          DOI: 10.1186/s12933-015-0269-1

Source DB:  PubMed          Journal:  Cardiovasc Diabetol        ISSN: 1475-2840            Impact factor:   9.951


Background

Cardiovascular disease is a major cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM) [1]. No clinical trial has provided conclusive evidence that improved glycaemic control reduces the risk of adverse events [2] and recent studies have even shown potential risks associated with intensive glycaemic control [3]. Coronary micro vascular dysfunction (CMD) is associated with cardiovascular related morbidity and mortality in T2DM patients [4]. Endothelial dysfunction (ED) plays an important role in the progression of atherosclerosis in DM patients [5]. Several trials have demonstrated that intensive glycaemic control reduces the progression of micro vascular disease including manifestation and progression of nephropathy, end stage renal disease and retinopathy [6]. However, the benefit of achieving an optimal haemoglobin A1c (HbA1c) level to minimize or reverse the manifestation and progression of CMD in T2DM patients has not been reported. Previous evidence on the subject is scarce and limited [7-9]. In the present study we aimed to evaluate the effect of achieving the current target of HbA1c < 7 % on the prevalence of CMD in a population of T2DM patients with chest pain and non-obstructive CAD. We also analysed other clinical factors in addition to lowering HbA1c potentially associated with CMD in these patients.

Methods

This retrospective study was approved by the Mayo Foundation Institutional Review Board. In keeping with Minnesota statute, only patients who granted use of their records for research purposes were included. Between January 1st 1993 and June 30st 2013, a total of 1,579 patients referred for assessment of chest pain suspected of cardiac ischemia underwent coronary angiography and invasive endothelial function testing at Mayo Clinic. Most patients underwent a non-invasive test for detection of ischemia, however a positive result was not an inclusion criteria in our study since a negative non-invasive stress test does not rule out coronary vasomotor dysfunction in symptomatic patients with nonobstructive coronary artery disease [10]. Patients with the following were excluded: greater than 40 % diameter stenosis of any coronary artery; acute coronary syndrome; uncontrolled hypertension; left ventricular ejection fraction of 50 % or less; left ventricular hypertrophy and severe endocrine, hepatic, renal or inflammatory disease. For the purpose of this study we excluded 476 patients because of missing values of HbA1c at the time of cardiac catheterization, and 36 patients who had not measurements available for both coronary blood flow (CBF) and coronary flow reserve (CFR). From the remaining 1,067 patients, we analyzed those with diagnosis of T2DM (n = 100) who were categorized according to HbA1c level in those having an optimal (HbA1c < 7 %) vs. suboptimal (HbA1c ≥ 7 %) glycaemic control as evaluated with a single measurement of this parameter at the time of catheterization. As a comparison group (n = 214) we considered those not matching diagnostic criteria for type 1 diabetes mellitus [11], Metabolic Syndrome, [12] or Pre-Diabetes, [13]. The duration of Diabetes was specifically addressed through a detailed revision of previous clinical records [14]. Patients presented to the cardiac catheterization laboratory in the fasting state and all cardiovascular medications, including nitrates and calcium channel blockers, were discontinued for at least 48 h. At the time of catheterization, blood samples were drawn to measure the biochemical profile and biomarkers including Lipoprotein A, high sensitivity C Reactive Protein and Homocysteine. Informed consent was obtained from each patient and the study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the institution’s human research committee. Routine diagnostic coronary angiography was performed in all patients using standard clinical protocols and reviewed prior to the infusion of any pharmacological agents. In cases where the severity of stenosis was uncertain, quantitative coronary angiography was used. All patients underwent evaluation of endothelial-dependent CBF and endothelial-independent CFR as previously described [15]. Following intravenous infusion of 5,000–7,000 U of heparin, a Doppler guidewire (Flo-wire, Volcano) 0.014 inches in diameter within a 3-F. Slip-Cath Infusion Catheter (Cook Medical) was positioned into the mid-portion of the left anterior descending coronary artery, 2–3 mm distal to the tip of the infusion catheter. Heart rate and mean arterial blood pressure were continuously monitored throughout each procedure. Baseline peak velocity was recorded using intravascular Doppler assessment after which intracoronary bolus injections of increasing doses (18–72 µg) of adenosine was administered through the guide catheter until maximal hyperemia was achieved. The maximal mean peak velocity was then recorded and CFR ratio calculated by dividing the mean peak velocity following the administration of adenosine by the baseline mean peak velocity. After a 5-min equilibration period, acetylcholine was infused at concentrations of 10−6, 10−5 and 10−4 M (to achieve estimated coronary bed concentrations of 10−8, 10−7 and 10−6 M respectively) for 3 min at each concentration to assess endothelium-dependent increase in CBF. Infusions were performed using a Medfusion® 3500 pump to maintain infusion rates of less than 1 % of the estimated CBF. Doppler measurements of mean peak velocity were performed after each infusion followed by repeat coronary angiography. Coronary artery diameter was measured by an independent investigator blinded to Doppler velocity data and CBF was then calculated using the following, as previously described: CBF = (mean peak velocity/2)(coronary artery diameter/2)2. Maximal CBF following the infusion of acetylcholine was then divided by the CBF at baseline to give the change in CBF as a ratio. Impaired endothelial-independent micro vascular function was defined as a CFR ratio in response to adenosine of 2.5 or less Impaired endothelial-dependent micro vascular function was defined as the maximal increase in CBF following infusion of any dose of acetylcholine compared to baseline of 50 % or less, giving a ratio of 1.5 or less. For quality control, all angles, skew rotation and table height were kept constant during each procedure. Furthermore, the distance between the image intensifier and x-ray tube relative to the patient was kept constant. Measurements were performed in the segment 5 mm distal to the tip of the Doppler wire and following each infusion, the diameter was measured in the same segment of the vessel [15].

Statistical analysis

Continuous variables are presented as a mean ± standard deviation where data is normally distributed and as a median (interquartile range) for skewed data. Categorical variables are presented as frequencies and percentages. Spearman correlation was used to evaluate possible associations between HbA1c and CFR, change in CBF, or change in CAD. Differences between groups were analyzed using the one-way ANOVA for continuous variables and Chi squared test for proportions. After univariate and age–sex adjustment, we consider variables significant at p 0.10 with clinical plausibility to perform a logistic regression model for the prediction of CMD. For that purpose patients were categorized according to the presence/absence of independent CMD (CFR after intracoronary adenosine <2.5) and presence/absence of dependent CMD (% of CBF increase after intracoronary acetylcholine <50 %). We considered shrinkage estimates to assess and avoid over fitting of the model. p-values of less than 0.05 were accepted as significant. All statistical analyses were carried out using JMP 9.0 (SAS Institute, Cary, North Carolina, USA).

Results

The comparative baseline characteristics of the T2DM study group are presented in Table 1. There were significant differences in most of the variables as well as a higher degree of endothelial dependent CMD and epicardial ED in T2DM patients as compared to controls, Fig. 1. The prevalence and endothelial dependence of CMD found in T2DM patients were as follow: 27 % of patients had not any type of CMD, 24 % patients had both independent and dependent CMD, 11 % had only independent CMD and 38 % patients had only dependent CMD.
Table 1

T2DM patients basal characteristics

Controln 214T2DMn 100 p value
Age (year)49 (41–58)54 (48–61)<0.001
BSA (m2)1.82 ± 0.212.06 ± 0.25<0.001
BMI (kg/m2)26.19 ± 5.3734.32 ± 7.48<0.001
Female sex (%)76.961.0<0.01
Creatinine (mg/dl)0.9 (0.8–1.0)0.9 (0.8–1.1)0.34
GFR c–c (ml/min)86.7 (69.5–107.1)112.5 (85.8–144.2)<0.001
GFR MRDR (ml/min)73.3 (65.4–86.6)74.1 (62.1–88.9)0.96
Risk factors and CAD history (%)
 Current smoker11.29.00.69
 Hypertension34.269.7<0.001
 Hyperlipidemia46.978.9<0.001
 Postmenopausal35.244.40.11
 CAD family history60.557.00.43
Inflammatory markers
 Lpa (mg/dl)11.0 (7.0–25.0)13.5 (7–35.7)0.16
 hsCrP (mg/l)0.4 (0.2–1.1)1.0 (0.4–3.8)<0.001
 Homocysteine (µmol/l)7.0 (6.0–9.0)8.0 (6.0–10.0)0.15
Coronary epicardial and microvascular function
 CFR2.9 (2.5–3.3)2.8 (2.3–3.5)0.71
 CRF < 2.5 (%)27.2 %35.0 %0.18
 CBF%Ach63.3 (9.4–131.4)25.2 (−20.5 to 68.8)<0.001
 CBFAch < 50 % (%)41.3 %62.0 %<0.001
 CLD%Ach–7.7 (−18.7 to 0.0)−11.4 (−27.1 to 3.1)<0.05
 CLDAch < 20 % (%)21.6 %32.0 %0.051
 CBFbasal50.2 (34.0–73.5)52.6 (37.8–72.6)0.42
 LVEDP (mmHG)13.5 (11.0–23.0)17.0 (13.0–26.0)<0.001
Medication (%)
 BBlockers24.441.0<0.01
 CC blockers36.032.00.52
 Nitrates32.245.0<0.05
 ASA50.764.0<0.05
 ACE/ARB inhibitor17.834.0<0.01
 Lipid lowering33.859.0<0.001

BMI body mass index, BSA body surface area, GFR c–c Cockroft–Gault glomerular filtrate rate, CAD coronary artery disease, Lpa lipoprotein A, hsCrP high sensitive C reactive protein, CFR coronary flow reserve, CMD coronary microvascular dysfunction, CFR < 2.5 independent CMD, CBF%Ach percentage of increase in CBF after intracoronary acetylcholine infusion, CBFAch < 50 % dependent CMD, CLD%Ach percentage of increase in coronary lumen diameter after intracoronary acetylcholine infusion, CLDAch < 20 % epicardial endothelial dysfunction, LVEDP left ventricular end-diastolic pressure, CC blockers calcium channel blocker, ASA acetylsalicylic acid, ACE/ARB inhibitor angiotensin-converting enzyme/angiotensin inhibitor.

Fig. 1

Coronary microvascular and epicardial endothelial function according to HbA1c level. a Values of CFR (endothelial independent CMD) according to glycaemic control. b Values (in percentages) of increase in CBF after Ach intracoronary infusion (endothelial dependent CMD). c Values (in percentages) of increase in CLD after Ach intracoronary infusion (epicardial endothelial dysfunction). CFR coronary flow reserve; CMD coronary micro vascular dysfunction; CFR < 2.5 endothelial independent CMD; CBF%Ach percentage of increase in CBF after intracoronary acetylcholine infusion; CBFAch < 50 % endothelial dependent CMD; CLD%Ach percentage of increase in coronary lumen diameter after intracoronary acetylcholine infusion; CLDAch < 20 % epicardial endothelial dysfunction. *p < 0.05; **p < 0.001.

T2DM patients basal characteristics BMI body mass index, BSA body surface area, GFR c–c Cockroft–Gault glomerular filtrate rate, CAD coronary artery disease, Lpa lipoprotein A, hsCrP high sensitive C reactive protein, CFR coronary flow reserve, CMD coronary microvascular dysfunction, CFR < 2.5 independent CMD, CBF%Ach percentage of increase in CBF after intracoronary acetylcholine infusion, CBFAch < 50 % dependent CMD, CLD%Ach percentage of increase in coronary lumen diameter after intracoronary acetylcholine infusion, CLDAch < 20 % epicardial endothelial dysfunction, LVEDP left ventricular end-diastolic pressure, CC blockers calcium channel blocker, ASA acetylsalicylic acid, ACE/ARB inhibitor angiotensin-converting enzyme/angiotensin inhibitor. Coronary microvascular and epicardial endothelial function according to HbA1c level. a Values of CFR (endothelial independent CMD) according to glycaemic control. b Values (in percentages) of increase in CBF after Ach intracoronary infusion (endothelial dependent CMD). c Values (in percentages) of increase in CLD after Ach intracoronary infusion (epicardial endothelial dysfunction). CFR coronary flow reserve; CMD coronary micro vascular dysfunction; CFR < 2.5 endothelial independent CMD; CBF%Ach percentage of increase in CBF after intracoronary acetylcholine infusion; CBFAch < 50 % endothelial dependent CMD; CLD%Ach percentage of increase in coronary lumen diameter after intracoronary acetylcholine infusion; CLDAch < 20 % epicardial endothelial dysfunction. *p < 0.05; **p < 0.001. The baseline characteristics of the T2DM according to their status of glycaemic control are presented in Table 2. Spearman correlation analyses showed the weak negative correlation between HbA1c and Ach induced CBF% change in total subjects including control and DM patients (Table 3). However, after divided subjects into the control and DM group, HbA1c was not significantly associated with any coronary function parameters, either in control group or in DM group. The prevalence of endothelial independent CMD (29.8 vs. 39.6 %, p = 0.40) and endothelial dependent CMD (61.7 vs. 62.2 %, p > 0.99) were similar in T2DM patients with optimal vs. suboptimal control respectively, Table 2 and Fig. 1. The mean difference between optimal and suboptimal glycaemic controls for CFR was −0.059 [95 % confidence interval (CI) −0.368, 0.250; p = 0.70]. The mean difference for CBF% change between the two groups was −3.91 (95 % CI −33.35, 25.52; p = 0.792).
Table 2

Basal characteristics according to level of HbA1c

HBA1c > 7 (n 53)HBA1c < 7 (n 47) p value
Age (year)55 (49–61)54 (47–61)0.45
BSA (m2)2.04 ± 0.252.09 ± 0.250.40
BMI (kg/m2)33.95 ± 6.5934.73 ± 8.420.63
Female sex (%)58.563,90.54
GFR c–c (ml/min)108.0 (81.4–144.2)117.7 (89.2–136.5)0.79
GFR MRDR (ml/min)75.9 (62.1–92.8)71.9 (64.3–83.7)0.23
Risk factors and CAD history (%)
 Current smoker (%)13.24.20.16
 Hypertension (%)57.782.9<0.01
 Hyperlipidemia (%)75.082.90.33
 HDL (mg/dl)45.0 (37.0–54.5)45.5 (39.0–54.0)0.83
 Triglycerides (mg/dl)160.0 (98.0–230.0)118.5 (86.7–159.5)<0.05
Inflammatory markers
 Lpa (mg/dl)14.0 (7.0–35.0)13.0 (7.0–40.0)0.74
 hsCrP (mg/l)1.0 (0.4–4.0)1.0 (0.4–3.7)0.31
 Homocysteine (µmol/l)8.0 (6.0–9.0)8.0 (6.0–10.0)0.30
Coronary epicardial and microvascular function
 CFR2.8 (2.3–3.6)2.8 (2.4–3.4)0.55
 CRF < 2.5 (%)39.629.80.53
 CBF%Ach27.4 (−16.6 to 67.4)15.2 (−28.2 to 69.1)0.79
 CBFAch < 50 % (%)62.261.71.00
 CLD%Ach−10.0 (−24.8 to −3.4)−12.5 (−31.8 to 0.0)0.93
 CLDAch < 20 % (%)28.336.10.52
 CBFbasal52.9 (33.5–70.4)51.2 (38.0–73.1)0.45
 LVEDP (mmHG)18.0 (12.2–24.7)17.0 (15.0–22.0)0.71
Diabetes status and treatment characterization
 DM duration (months)60.0 (24.0–100.0)41.0 (8.0–90.0)0.22
 Fasting glucose (mg/dl)148.0 (118.0–179.0)125.0 (103.7–141.0)<0.01
 Insulin (µIU/ml)14.0 (6.9–20.6)10.0 (5.1–18.0)0.47
 DM family history (%)60.447.70.29
 Insulin therapy (%)33.921.20.18
 Metformin (%)44.244.41.00
 Metformin only (%)28.835.50.66
 Insulin releasing (%)28.822.70.49
Medication (%)
 BBlockers35.846.80.31
 CC blockers28.336.10.29
 Nitrates33.957.4<0.05
 ACE/ARB inhibitor30.138.30.53
 Lipid lowering40.170.2<0.05

BMI body mass index, BSA body surface area, GFR c–c Cockroft–Gault glomerular filtrate rate, ACS acute coronary syndrome, CAD coronary artery disease, Lpa lipoprotein A, hsCrP high sensitive C reactive protein, CFR coronary flow reserve, CMD coronary microvascular dysfunction, CFR < 2.5 independent CMD, CBF%Ach percentage of increase in CBF after acetylcholine infusion, CBFAch < 50 % dependent CMD, CLD%Ach percentage of increase in coronary lumen diameter after acetylcholine infusion, CLDAch < 20 % epicardial endothelial dysfunction, LVEDP left ventricular end-diastolic pressure, CC blockers calcium channel blocker, ACE/ARB inhibitor angiotensin-converting enzyme/angiotensin inhibitor.

Table 3

Correlation between HbA1c level and coronary vascular function

Correlation with HbA1cIn total subjectsIn control groupIn DM group
Spearman ρ p Spearman ρ p Spearman ρ p
CFR0.0230.680.0460.510.0060.96
CBF% change−0.1660.003*0.0150.83−0.0550.59
CLD% change−0.0280.620.1140.096−0.0240.82

CLD coronary lumen diameter, CBF coronary blood flow, CFR coronary flow reserve, HbA1c hemoglobin A1c.

* Statistically significant.

Basal characteristics according to level of HbA1c BMI body mass index, BSA body surface area, GFR c–c Cockroft–Gault glomerular filtrate rate, ACS acute coronary syndrome, CAD coronary artery disease, Lpa lipoprotein A, hsCrP high sensitive C reactive protein, CFR coronary flow reserve, CMD coronary microvascular dysfunction, CFR < 2.5 independent CMD, CBF%Ach percentage of increase in CBF after acetylcholine infusion, CBFAch < 50 % dependent CMD, CLD%Ach percentage of increase in coronary lumen diameter after acetylcholine infusion, CLDAch < 20 % epicardial endothelial dysfunction, LVEDP left ventricular end-diastolic pressure, CC blockers calcium channel blocker, ACE/ARB inhibitor angiotensin-converting enzyme/angiotensin inhibitor. Correlation between HbA1c level and coronary vascular function CLD coronary lumen diameter, CBF coronary blood flow, CFR coronary flow reserve, HbA1c hemoglobin A1c. * Statistically significant. Table 4 shows the age–sex adjusted analysis for the prediction of CMD with those variables significantly associated to CMD in Table 2. In the multivariate analysis (Table 5), age [odds ratio (OR) 1.10; CI 95 % 1.04–1.18; p < 0.001] and female gender (OR 3.87; CI 95 % 1.45–11.4; p < 0.01) were associated with endothelial independent CMD whereas glomerular filtration rate (OR 0.97; CI 95 % 0.95–0.99; p < 0.05) was found to be significantly associated to endothelial dependent CMD.
Table 4

Age–sex adjusted analysis for prediction of CMD in T2DM patients

Independent CMD OR (CI 95 %) p value Dependent CMD OR (CI 95 %) p value
Age (year)1.06 (1.01–1.12) p 0.01*0.98 (0.94–1.02) p 0.55
Female sex (%)3.24 (1.24–9.14) p 0.01*1.36 (0.90–1.02) p 0.23
BMI (kg/m2)1.06 (0.99–1.48) p 0.070.96 (0.52–1.24) p 0.25
GFR MDRD (ml/min)1.00 (0.98–1.02) p 0.490.97 (0.95–0.99) p 0.04*
Risk factors
 Hypertension (%)1.16 (0.43–3.27) p 0.751.27 (0.52–3.26) p 0.59
 Triglycerides (mg/dl)1.00 (0.99–1.00) p 0.870.99 (0.99–1.00) p 0.61
Diabetes control
 HBA1c (%)1.21 (0.94–1.59) p 0.130.88 (0.67–1.12) p 0.32
 HBA1c < 7%0.60 (0.23–1.46) p 0.260.99 (0.43–2.24) p 0.98
 Fasting glucose (mg/dl)1.00 (0.99–1.01) p 0.670.99 (0.98–1.00) p 0.20
Medication
 Nitrates1.50 (0.61–3.76) p 0.360.59 (0.26–1.36) p 0.22
 Lipid lowering1.21 (0.48–3.07) p 0.681.22 (0.53–2.80) p 0.63

CMD coronary microvascular dysfunction, BMI body mass index, GFR glomerular filtrate rate, CFR coronary flow reserve, CRF < 2.5 independent CMD, CBFAch<50 % endothelial dependent CMD.

* Statistically significant.

Table 5

Multivariate model for prediction of CMD in T2DM patients

Endothelial independent CMDEndothelial dependent CMD
Age (year)1.10 (1.04–1.18) p 0.000*0.98 (0.94–1.03) p 0.647
Female sex3.87 (1.45–11.4) p 0.006*0.71 (0.29–1.70) p 0.451
BMI (kg/m2)1.07 (0.99–1.15) p 0.054
GFR MDRD (ml/min)0.97 (0.95–0.99) p 0.038*
HbA1c%1.24 (0.96–1.64) p 0.1011.13 (0.362.22) p 0.366

BMI body mass index, CMD coronary microvascular dysfunction, CFR coronary flow reserve, CRF < 2.5 endothelial independent CMD, CBFAch < 50% endothelial dependent CMD, GFR glomerular filtrate rate, HTN hypertension, HbA1c < 7 % optimal glycaemic control.

* Statistically significant.

Age–sex adjusted analysis for prediction of CMD in T2DM patients CMD coronary microvascular dysfunction, BMI body mass index, GFR glomerular filtrate rate, CFR coronary flow reserve, CRF < 2.5 independent CMD, CBFAch<50 % endothelial dependent CMD. * Statistically significant. Multivariate model for prediction of CMD in T2DM patients BMI body mass index, CMD coronary microvascular dysfunction, CFR coronary flow reserve, CRF < 2.5 endothelial independent CMD, CBFAch < 50% endothelial dependent CMD, GFR glomerular filtrate rate, HTN hypertension, HbA1c < 7 % optimal glycaemic control. * Statistically significant.

Discussion

The current study demonstrates for the first time that glycaemic control is not an independent predictor of a better coronary microvascular function in T2DM patients with chest pain and non-obstructive coronary angiogram. The finding is in line with the reported discrepancy between the optimal control of DM and cardiovascular events [3] and extend some previous reports performed with remarkable differences in study population and methodology. Two small randomized trials evaluating different therapeutic strategies over peripheral ED did not find any relationship between glycaemic control and ED [16, 17]. However CMD was not evaluated in these studies and the current glycaemic target of Hb1C < 7 % was not necessarily achieved [11]. Two studies that addressed the association between HbA1c levels and CFR as evaluated with Doppler echocardiography [7, 18] found no differences between T2DM patients with a good vs. poor glycaemic control, but one reported an improvement of CFR after 6 months in those patients who achieved HbA1c < 7 %. These authors did not evaluate the endothelial dependent CMD and moreover reported differences in study population and methodology may account for the discrepancy. An optimal blood sugar control does not reduce the incidence of epicardial coronary artery spasm in DM patients with chest pain and normal coronary angiogram [8]. Our study extends this previous report to a different population [19] and more importantly, to the coronary microcirculation. The endothelium independent CFR in response to adenosine did not differ significantly between our subgroup of T2DM patients and the control group (Table 1) as well as between those T2DM patients with optimal vs. suboptimal control (Table 2). The mean values are essentially above the conventional cut-off of normality in a population study of patients with chest pain and non-obstructive coronary angiogram. Since there is significant differences in the CBF increase in response to intracoronary acetylcholine infusion between our subgroup of T2DM patients and the control group, this finding underscore the importance of endothelial function and supports that in similar T2DM patients, endothelial dependent CMD may be the primary mechanism for ischemia. Moreover, according to previous reports, there is conflicting evidence of the predictive value of CFR for cardiovascular events, however the predictive value of epicardial and micro vascular ED in predicting major cardiovascular events is well established [20, 21]. Patients with T2DM and optimal glycaemic control showed a higher prevalence of hypertension. Our study specifically excluded patients with uncontrolled hypertension, left ventricular hypertrophy or renal disease. This fact may possibly explain the lack of association between hypertension and CMD in our study, since the blunting of endothelium-independent CFR and dependent CBF in hypertension is associated with left ventricular hypertrophy [22-25]. Also, those patients were more frequently treated with drugs that have shown to improve endothelial function [26-28]. Our data argue against different prevalence of CMD between T2DM patients with an optimal vs. poor glycaemic control based on the current guidelines recommendations of HbA1c < 7 %. The present study evaluated only the effect of chronic sustained hyperglycemia through a single measurement of HbA1c at the time of catheterization, an accepted reliable marker of the overall exposure integrating fasting, postprandial glycaemic state [29] and mean plasma glucose level [30]. Previous studies have addressed the limited value of the assessment of HbA1c variability [31] while others have emphasized the role of acute glycaemic fluctuations from peaks to nadir as a cause of excessive protein glycation, activations of oxidative stress [32] and ED in DM patients [33]. Our study would be in accordance with this reported evidence supporting that in order to reduce coronary micro vascular complications the target for an optimal glycaemic control should be improved and new ones should be identified [3, 29, 34]. Measures could possibly include reduction of glycaemic variability through self-monitored blood glucose, real time continuous glucose monitoring or the use of new drugs like incretins, with proposed but yet unproven glucose-independent beneficial effects on the endothelium and CV outcomes [35-37]. However, an individualized approach with careful consideration not only to glycaemic control but also to a comprehensive vascular [16] and endothelial health as the final pathway of any possible injury may be necessary to perform successful intervention strategies in T2DM patients. The assessment of ED through peripheral and/or direct coronary measurement in T2DM patients would be therefore a unique tool to obtain that important information about individual patient risk and vulnerability.

Limitations

The study population comprises T2DM patients with chest pain suspected of cardiac ischemia who were referred for coronary angiography to a tertiary referral center by an independent cardiologist. Therefore the prevalence, severity and reversibility of CMD may be different to other T2DM patients without chest pain. Specifically, our results could not be generalized to diabetes patients with significant CAD, and those with depressed LV function and/or LVH who were excluded in our study. Second, the study was a cross sectional design and does not allow longitudinal study of the effect of glycaemic control on endothelial function. Third, our negative findings may be related to statistical power. However, the confidence intervals for the mean differences in CFR and CBF%Ach between the two groups seem to rule out large differences. Fourth, despite the retrospective nature of our analysis, the collection at the time of catheterization of clinical, laboratory and the direct measurement of CMD was prospectively recorded with a carefully planned protocol that minimized missing and/or error values. The role of new drugs for glycaemic control as well as the effect of a sustained optimal HbA1c level along with glycaemic fluctuations in the long-term is out of the scope of any retrospective analysis and should be clarified in future prospective studies.

Conclusion

The current study demonstrates that in patients with T2DM with preserved left ventricular function but not coronary artery disease or left ventricular hypertrophy, appropriate glycaemic control does not predict a better microvascular endothelial function. The results may explain the discrepancy between glycaemic control and cardiac events and suggest that vascular function may serve as a therapeutic target in patients with DM.
  37 in total

1.  ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: the Task Force on diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and developed in collaboration with the European Association for the Study of Diabetes (EASD).

Authors:  Lars Rydén; Peter J Grant; Stefan D Anker; Christian Berne; Francesco Cosentino; Nicolas Danchin; Christi Deaton; Javier Escaned; Hans-Peter Hammes; Heikki Huikuri; Michel Marre; Nikolaus Marx; Linda Mellbin; Jan Ostergren; Carlo Patrono; Petar Seferovic; Miguel Sousa Uva; Marja-Riita Taskinen; Michal Tendera; Jaakko Tuomilehto; Paul Valensi; Jose Luis Zamorano; Jose Luis Zamorano; Stephan Achenbach; Helmut Baumgartner; Jeroen J Bax; Héctor Bueno; Veronica Dean; Christi Deaton; Cetin Erol; Robert Fagard; Roberto Ferrari; David Hasdai; Arno W Hoes; Paulus Kirchhof; Juhani Knuuti; Philippe Kolh; Patrizio Lancellotti; Ales Linhart; Petros Nihoyannopoulos; Massimo F Piepoli; Piotr Ponikowski; Per Anton Sirnes; Juan Luis Tamargo; Michal Tendera; Adam Torbicki; William Wijns; Stephan Windecker; Guy De Backer; Per Anton Sirnes; Eduardo Alegria Ezquerra; Angelo Avogaro; Lina Badimon; Elena Baranova; Helmut Baumgartner; John Betteridge; Antonio Ceriello; Robert Fagard; Christian Funck-Brentano; Dietrich C Gulba; David Hasdai; Arno W Hoes; John K Kjekshus; Juhani Knuuti; Philippe Kolh; Eli Lev; Christian Mueller; Ludwig Neyses; Peter M Nilsson; Joep Perk; Piotr Ponikowski; Zeljko Reiner; Naveed Sattar; Volker Schächinger; André Scheen; Henrik Schirmer; Anna Strömberg; Svetlana Sudzhaeva; Juan Luis Tamargo; Margus Viigimaa; Charalambos Vlachopoulos; Robert G Xuereb
Journal:  Eur Heart J       Date:  2013-08-30       Impact factor: 29.983

2.  Attenuated coronary flow reserve and vascular remodeling in patients with hypertension and left ventricular hypertrophy.

Authors:  S Hamasaki; J Al Suwaidi; S T Higano; K Miyauchi; D R Holmes; A Lerman
Journal:  J Am Coll Cardiol       Date:  2000-05       Impact factor: 24.094

Review 3.  Endothelial dysfunction in diabetes: pathogenesis, significance, and treatment.

Authors:  Sandra J Hamilton; Gerald F Watts
Journal:  Rev Diabet Stud       Date:  2013-08-10

4.  Comparison of coronary artery flow impairment in diabetic and hypertensive patients with stable microvascular angina.

Authors:  V Sucato; S Evola; A Quagliana; G Novo; G Andolina; P Assennato; S Novo
Journal:  Eur Rev Med Pharmacol Sci       Date:  2014       Impact factor: 3.507

5.  The resting status of the coronary microcirculation is a predictor of microcirculatory function following elective PCI for stable angina.

Authors:  Jamie Layland; Chris Judkins; Sonny Palmer; Rob Whitbourn; Amy Wilson-O'Brien; Andrew MacIsaac; Andrew Wilson
Journal:  Int J Cardiol       Date:  2013-09-13       Impact factor: 4.164

6.  Coronary endothelial dysfunction is associated with an increased risk of cerebrovascular events.

Authors:  Paul V Targonski; Piero O Bonetti; Geralyn M Pumper; Stuart T Higano; David R Holmes; Amir Lerman
Journal:  Circulation       Date:  2003-05-27       Impact factor: 29.690

7.  Additional prognostic value of coronary flow reserve in diabetic and nondiabetic patients with negative dipyridamole stress echocardiography by wall motion criteria.

Authors:  Lauro Cortigiani; Fausto Rigo; Sonia Gherardi; Rosa Sicari; Maurizio Galderisi; Francesco Bovenzi; Eugenio Picano
Journal:  J Am Coll Cardiol       Date:  2007-09-17       Impact factor: 24.094

8.  Hemoglobin A1c variability as an independent correlate of cardiovascular disease in patients with type 2 diabetes: a cross-sectional analysis of the renal insufficiency and cardiovascular events (RIACE) Italian multicenter study.

Authors:  Giuseppe Penno; Anna Solini; Giacomo Zoppini; Emanuela Orsi; Cecilia Fondelli; Gianpaolo Zerbini; Susanna Morano; Franco Cavalot; Olga Lamacchia; Roberto Trevisan; Monica Vedovato; Giuseppe Pugliese
Journal:  Cardiovasc Diabetol       Date:  2013-07-05       Impact factor: 9.951

9.  Preserved endothelium-dependent dilatation of the coronary microvasculature at the early phase of diabetes mellitus despite the increased oxidative stress and depressed cardiac mechanical function ex vivo.

Authors:  Evangelia Mourmoura; Guillaume Vial; Brigitte Laillet; Jean-Paul Rigaudière; Isabelle Hininger-Favier; Hervé Dubouchaud; Beatrice Morio; Luc Demaison
Journal:  Cardiovasc Diabetol       Date:  2013-03-25       Impact factor: 9.951

Review 10.  Cardiovascular disease and glycemic control in type 2 diabetes: now that the dust is settling from large clinical trials.

Authors:  Francesco Giorgino; Anna Leonardini; Luigi Laviola
Journal:  Ann N Y Acad Sci       Date:  2013-02-06       Impact factor: 5.691

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  8 in total

Review 1.  Coronary microvascular dysfunction in diabetes mellitus.

Authors:  Aleksandar Kibel; Kristina Selthofer-Relatic; Ines Drenjancevic; Tatjana Bacun; Ivica Bosnjak; Dijana Kibel; Mario Gros
Journal:  J Int Med Res       Date:  2017-01-12       Impact factor: 1.671

2.  The prevalence of diabetes, hypertension and obesity among immigrants from East Africa and the former Soviet Union: a retrospective comparative 30-year cohort study.

Authors:  Yonatan Reuven; Jacob Dreiher; Pesach Shvartzman
Journal:  Cardiovasc Diabetol       Date:  2016-05-05       Impact factor: 9.951

3.  PRotective Effect on the coronary microcirculation of patients with DIabetes by Clopidogrel or Ticagrelor (PREDICT): study rationale and design. A randomized multicenter clinical trial using intracoronary multimodal physiology.

Authors:  Enrico Cerrato; Alicia Quirós; Mauro Echavarría-Pinto; Hernan Mejia-Renteria; Andres Aldazabal; Nicola Ryan; Nieves Gonzalo; Pilar Jimenez-Quevedo; Luis Nombela-Franco; Pablo Salinas; Iván J Núñez-Gil; José Ramón Rumoroso; Antonio Fernández-Ortiz; Carlos Macaya; Javier Escaned
Journal:  Cardiovasc Diabetol       Date:  2017-05-19       Impact factor: 9.951

Review 4.  Diabetes, cardiovascular disease and the microcirculation.

Authors:  W David Strain; P M Paldánius
Journal:  Cardiovasc Diabetol       Date:  2018-04-18       Impact factor: 9.951

5.  The impact of cardiovascular co-morbidities and duration of diabetes on the association between microvascular function and glycaemic control.

Authors:  F Casanova; D D Adingupu; F Adams; K M Gooding; H C Looker; K Aizawa; F Dove; S Elyas; J J F Belch; P E Gates; R C Littleford; M Gilchrist; H M Colhoun; A C Shore; F Khan; W D Strain
Journal:  Cardiovasc Diabetol       Date:  2017-09-15       Impact factor: 9.951

Review 6.  Cardiologist and Diabetologist crosstalk in the era of cardiovascular outcome trials of novel glucose-lowering drugs.

Authors:  Francesco Maranta; Lorenzo Cianfanelli; Maria Regoni; Domenico Cianflone
Journal:  Int J Cardiol Heart Vasc       Date:  2018-10-24

7.  Cardiovascular Determinants of Aerobic Exercise Capacity in Adults With Type 2 Diabetes.

Authors:  Gaurav S Gulsin; Joseph Henson; Emer M Brady; Jack A Sargeant; Emma G Wilmot; Lavanya Athithan; Zin Z Htike; Anna-Marie Marsh; John D Biglands; Peter Kellman; Kamlesh Khunti; David Webb; Melanie J Davies; Thomas Yates; Gerry P McCann
Journal:  Diabetes Care       Date:  2020-07-17       Impact factor: 19.112

Review 8.  Continued efforts to translate diabetes cardiovascular outcome trials into clinical practice.

Authors:  Angelo Avogaro; Gian Paolo Fadini; Giorgio Sesti; Enzo Bonora; Stefano Del Prato
Journal:  Cardiovasc Diabetol       Date:  2016-08-11       Impact factor: 9.951

  8 in total

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