Relationship between Short- and Mid-Term Glucose Variability and Blood Pressure Profile Parameters: A Scoping Review.
Elena VakaliDimitrios RigopoulosPetros C DinasIoannis-Alexandros DrosatosAikaterini G TheodosiadiAndriani VazeouGeorge StergiouAnastasios KolliasPublished in: Journal of clinical medicine (2023)
Background. Increased variability of glucose (GV) and blood pressure (BPV) is linked to a higher risk of macro- and microvascular complications and other hard endpoints. This scoping review aims to summarize the existing evidence regarding the association between the parameters of the blood pressure (BP) profile, especially BPV, with indices of short- and mid-term GV. Methods . A literature search was conducted in the MEDLINE/PubMed, Cochrane, Embase, Web of Science, and Wiley Online Library databases. Results . The main findings of this review are as follows: (i) 13 studies were included, mainly with small sample sizes; (ii) there was a considerable degree of heterogeneity in the characteristics of the study participants (age range, individuals with normoglycemia, type 1 or 2 diabetes, normal BP, or hypertension), as well as in the methodologies (mainly in terms of the duration of the data collection period) and variability indices examined (mean amplitude of glycemic excursions and coefficient of glucose variation most frequently reported); and (iii) the results were heterogeneous regarding the association between GV and the parameters of the BP profile. Conclusions . There is a significant lack of evidence on the association between GV and BPV. Future research implementing a standardized methodology should focus on the determinants, association, and clinical relevance of GV and BPV.
Keyphrases
- blood pressure
- blood glucose
- hypertensive patients
- type diabetes
- heart rate
- glycemic control
- cardiovascular disease
- systematic review
- metabolic syndrome
- quality improvement
- single cell
- magnetic resonance
- adipose tissue
- computed tomography
- diffusion weighted imaging
- insulin resistance
- artificial intelligence
- electronic health record
- skeletal muscle