Affiliation:
1. Division of Cardiology, Department of Internal Medicine Fu Jen Catholic University Hospital New Taipei City Taiwan
2. Division of Cardiology, Department of Internal Medicine National Taiwan University College of Medicine and Hospital Taipei Taiwan
3. Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health National Taiwan University Taipei Taiwan
4. Department of Medical Research National Taiwan University Hospital Taipei Taiwan
5. Division of Cardiology, Department of Internal Medicine National Taiwan University Hospital Hsinchu Taiwan
6. Department of Laboratory Medicine National Taiwan University College of Medicine Taipei Taiwan
7. Cardiovascular Center National Taiwan University Hospital Taipei Taiwan
8. Telehealth Center National Taiwan University Hospital Taipei Taiwan
Abstract
Background
Peripheral arterial disease (PAD) is a severe complication in patients with type 2 diabetes. Glycemic variability (GV) is associated with increased risks of developing microvascular and macrovascular diseases. However, few studies have focused on the association between GV and PAD.
Methods and Results
This cohort study used a database maintained by the National Taiwan University Hospital, a tertiary medical center in Taiwan. For each individual, GV parameters were calculated, including fasting glucose coefficient of variability (FGCV) and hemoglobin A1c variability score (HVS). Multivariate Cox regression models were constructed to estimate the relationships between GV parameters and composite scores for major adverse limb events (MALEs) and major adverse cardiovascular events (MACEs). Between 2014 and 2019, a total of 45 436 adult patients with prevalent type 2 diabetes were enrolled for analysis, and GV was assessed during a median follow‐up of 64.4 months. The average number of visits and time periods were 13.38 and 157.87 days for the HVS group and 14.27 and 146.59 days for the FGCV group, respectively. The incidence rates for cardiac mortality, PAD, and critical limb ischemia (CLI) were 5.38, 20.11, and 2.41 per 1000 person‐years in the FGCV group and 5.35, 20.32, and 2.50 per 1000 person‐years in HVS group, respectively. In the Cox regression model with full adjustment, the highest FGCV quartile was associated with significantly increased risks of MALEs (hazard ratio [HR], 1.57 [95% CI, 1.40–1.76];
P
<0.001) and MACEs (HR, 1.40 [95% CI, 1.25–1.56];
P
<0.001). Similarly, the highest HVS quartile was associated with significantly increased risks of MALEs (HR, 1.44 [95% CI, 1.28–1.62];
P
<0.001) and MACEs (HR, 1.28 [95% CI, 1.14–1.43];
P
<0.001). The highest FGCV and HVS quartiles were both associated with the development of PAD and CLI (FGCV: PAD [HR, 1.57;
P
<0.001], CLI [HR, 2.19;
P
<0.001]; HVS: PAD [HR, 1.44;
P
<0.001], CLI [HR, 1.67;
P
=0.003]). The Kaplan‐Meier analysis showed significantly higher risks of MALEs and MACEs with increasing GV magnitude (log‐rank
P
<0.001).
Conclusions
Among individuals with diabetes, increased GV is independently associated with the development of MALEs, including PAD and CLI, and MACEs. The benefit of maintaining stable glycemic levels for improving clinical outcomes warrants further studies.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Cardiology and Cardiovascular Medicine