We enrolled 25 patients who were admitted to the University of Fukui Hospital with ACS between September 2017 and March 2018. Patients with hemodynamic instability, such as those with complications of infection, catecholamine or sedative use, ventilator management, or ventricular arrhythmia, were excluded because of concerns about the effects of infection, drugs, and severe stress on blood glucose levels. Patients on insulin were also excluded because of the possible effect on blood glucose variability.

Smoking is defined as any smoking in the past year. Diabetes was defined based on one or more of the following: self-reported, use of diabetes medications, fasting plasma glucose ≥ 126 mg/dl, or hemoglobin A1c (National Glycohemoglobin Standardization Program) ≥ 6.5%. Clinical histories of the patients were obtained from interviews with patients.

After the purpose and methods of the study were explained to patients, they provided written informed consent for participation in the study. In this study, continuous glucose levels were monitored using a flash glucose monitoring (FGM) system (Free-Style Libre™ or Free-Style Libre Pro, Abbott™, UK). All patients were implanted with sensors of Free-Style Libre™ or Free-Style Libre Pro™ in their left upper arm within 3–5 days after hospitalization. Glucose levels were recorded using the FGM system for up to 14 days, excluding the first 2 days after sensor implantation because of the risk of errors due to inflammatory reactions, which could produce unstable glucose data. After analysis of the CGM data, MAGE, MODD, ADRR (average daily risk range, mg/dl), J-index, M-value (mg/dl), LBGI (low blood glucose index), and HBGI (high blood glucose index) were calculated using EasyGV^© software. The formulas for each parameter are based on Nathan et al. [11] Chen et al. reported the MODD of non-diabetic patients is 16.0 ± 5.4 mg/dl [12]. Therefore, a MODD value of 16.0 or higher was chosen as the abnormal value. MODD was calculated by \(\frac{\sum_{t={t}_{1}}^{{t}_{k}}|{G}_{t}-{G}_{t-1440}|}{k}\) (k = number of observations with an observation 24 h ago, G = glucose measured, t = time). To assess cardiac function, patients underwent echocardiography at 3–5 days after admission and at 10–12 months after the disease onset. The patients' diet consisted of a cardiac diet of 30 kcal/kg in ideal body weight in three portions. They did not receive any intravenous catecholamines or antibiotics. This investigation conformed to the principles outlined in the 1975 Declaration of Helsinki and later amendments. This study was approved by the Research Ethics Committee of University of Fukui and informed consent from all patients were obtained, and the follow-up results were registered in the Universal Hospital Medical Information Network Clinical Trials Registry (UMIN 000023837, 30/08/2016).

Within 4 days after hospitalization, following overnight fasting, blood samples were collected from the peripheral vein of each patient and kept on ice. Plasma was collected with EDTA-2Na as an anti-coagulant, and serum samples were separated by centrifugation within 30 min. Blood parameters were determined using standard methods.

All statistical analyses were performed using Statcel2 software (OMS Publishing Inc., Saitama, Japan) and Excel2019 (Microsoft Corporation). Data are presented as frequencies and percentages for categorical variables and mean ± SD for continuously distributed variables. Differences between categorical variables were assessed using the χ² test. Correlations between continuous variables were determined using Pearson’s correlation coefficient test. A p value of < 0.05 was considered statistically significant.

The characteristics of all patients are listed in Table 1. The mean age was 69.7 years, and 84% of patients were male. The study included 25 patients (14 patients with ST-elevated acute myocardial infarction, 6 patients with non-ST-elevated acute myocardial infarction, and 5 patients with unstable angina). In the study, 72% had a medical history of hypertension, and 24% had hypercholesterolemia. DM was observed in 8 patients (32%), and 7 patients (28%) were taking one or more antidiabetes medications. The mean value of peak CK was 1310.1 ± 1293.0 U/l, and NT-pro BNP was 2032.0 ± 2063.3 pg/ml (Table 1).

On admission, only 8 patients (32%) were diagnosed with diabetes. On the other hand, as many as 17 of 25 patients (68%) had abnormally high MODD values. The rate of abnormal MODD was significantly higher than the diagnosed rate of DM (32% vs. 68%, p = 0.011) (Fig. 1).

MODD was correlated with MAGE, J-index, and M-value (mg/dl), which are indicators of GV. MODD was also correlated with LBGI, HBGI, and ADRR, which is another indicator of day-to-day GV. There was no correlation between MODD and lipid-related coronary risk factors such as LDL, apoB, and EPA/AA (Table 2). There was no correlation between clinical parameters such as age, renal function, and echocardiography measurements and markers of blood glucose variability, including MODD.

A positive correlation was found between MODD and NT-pro BNP (r = 0.409, p = 0.042), although MODD did not correlate with max CK (Table 2, Fig. 2). HBGI was correlated with NT-pro BNP (r = 0.46, p = 0.019) as well as MODD.

Using the cut off value of 400 pg/ml, the reference value for heart failure in NT-proBNP, 19 of 25 patients were abnormal. The mean MODD of the group with high NT-proBNP (≥ 400 pg/ml) was 22.2 and the percentage of abnormalities was 73.7%, while the mean MODD of the group with low NT-proBNP was 17.6 and the percentage of abnormalities was 60%, which was not a significant difference. The high MODD group (≥ 16 mg/dl) had a mean NT-proBNP of 2323 pg/ml, 82.4% of abnormalities, while the MODD normal group had a mean NT-proBNP of 1324 pg/ml, 71.4% of abnormalities, also not significantly different.

There have been no studies comparing MODD with traditional BNP or myocardial infarction. The significance of measuring MODD in patients with ACS is that the measurement can predict poor cardiac prognosis beyond those expected based on infarct volume and may serve as a marker for more-intensive anti-cardiac therapy. In addition, CGM in DM routine practice may help in risk stratification of vulnerable patients with ACS.