Is 'time in range' the preferred glycemic metric to evaluate cognitive fuction in diabetics?

In a recent study posted to the preprint server Research Square while under review for publication in BMC Diabetology & Metabolic Syndrome, researchers examine the association between time in range (TIR), a glycemic metric, and cognitive impairment (CI) in patients with type 2 diabetes (T2D). The aim of this study was to determine whether a TIR goal of over 70%, which is currently recommended by Advanced Technologies & Treatments for Diabetes (ATTD), preserves cognitive function in diabetics.

Study: Association of Time in Range with Cognitive Impairment in Type 2 Diabetic Patients. Image Credit: Proxima Studio / Shutterstock.com

*Important notice: Research Square publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Background

The decline of cognitive abilities like memory and executive function, leads to CI, which is one of the main complications of diabetes among middle-aged people. The most common indicator of blood glucose levels is hemoglobin A1c (HbA1c), with several studies reporting higher HbA1c levels with an increased risk of dementia in diabetics.

Importantly, HbA1c values do not provide any data on hypoglycemia. In fact, recent studies evaluating the relationship between HbA1c and cognitive function have led to inconsistent results. 

TIR, which reflects the time an individual spends within the 3.9-10.0 mmol/L glucose range, can be used to evaluate whether hypo- or hyperglycemia are improving over time. There is also a correlation between TIR and HbA1c, with a TIR of 70% aligned with an HbA1c of about 7%.

HbA1c is considered the gold standard for assessing glycemic management. Nevertheless, many studies have found TIR useful for predicting varying degrees of diabetes retinopathy in T2DM patients and their risk of developing other complications, such as diabetic foot and carotid intima-thicness. 

About the study

In the present cross-sectional study, researchers recruited 40-64-year-old T2DM patients between July 2018 and September 2021. Each study participant underwent seven-point blood glucose monitoring (BGM) during a 24-hour period within 72 hours of admission and independently completed neuropsychological tests.

Clinical and biochemical data were acquired from all the participants. Based on the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) results, the study participants were classified into Normal Cognitive Function (NCF) and CI groups. CI group participants had MMSE and MOCA scores over 24 and less than 26, respectively.

The researchers calculated TIR, Time above Target Glucose Range (TAR), and Glycemic Variability (GV) metrics for all study participants. Importantly, all participants maintained their original therapy regimen and diet during the BGM period.

Binary logistic regression analysis was used to identify the association of TIR with CI in T2D patients, in which CI was a dependent variable. Age at DM onset was considered a confounding factor in the multivariate regression analysis, whereas the univariate analysis had four variables including age, educational status, marital status, and the presence of cardiovascular disease (CVD).

Study findings

Of the 274 patients included in the current study, the prevalence of CI was 41.6%. The proportion of participants with CVD was higher in the CI group as compared to the NCF group at 31% and 11.9%, respectively. TAR was also higher in the CI group, whereas TIR was lower in the CI group as compared to the NCF group.

There was a higher proportion of patients with TIR exceeding 70% in the NCF than CI groups at 20.6% and 9.6%, respectively. Spearman correlation analysis revealed a negative correlation between TIR and HbA1c.

In recent studies, GV metrics such as standard deviation (SD) and coefficient of variation (CV) have emerged as independent predictors of diabetes-related complications. Likewise, a GV-independent effect of TIR on CI was observed in the current study.

Logistic regression analysis revealed a significant correlation between TIR greater than 70% and CI, even after adjusting for age, education level, marital status, CVD, and age at DM onset. Thus, a TIR goal of over 70% appears to be protective against cognitive decline in T2D patients.

Among other glycemic metrics, no linear association of HbA1c was observed with the risk of CI; however, a significant correlation of higher TAR was associated with an increased risk of CI.

Conclusions

In 2019, the ATTD congress recommended a glycemic cut-off of 3.9 to 10mmol/L  for people with both type 1 and type 2 diabetes. Given the growing evidence that TIR is an important metric for blood glucose management and prognosis in T2DM, this measure may become the preferred metric for predicting diabetes-related complications over HbA1c. TIR is a more accurate representation of daily glycemic fluctuation patterns, which may be relevant for assessing cognitive function in DM patients. 

Higher TIR indicates that a patient spends more time in the target glucose range and experienced fewer glycemic fluctuations or instances of hypo- or hyperglycemia. Thus, a higher TIR appears to have protective effect on cognitive function in T2DM. 

*Important notice: Research Square publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
  • Preliminary scientific report. Liu, Y., Liu, Y., Qiu, H., et al. (2023). Association of Time in Range with Cognitive Impairment in Type 2 Diabetic Patients. Research Square. doi:10.21203/rs.3.rs-3227918/v1
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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