Impact of Continuous Glucose Monitors on Diabetes Complications

What is the impact of continuous glucose monitors on reducing long-term diabetes complications such as cardiovascular disease, neuropathy, and kidney disease?

Studies demonstrate that continuous glucose monitors, by improving glycemic stability, reduce cardiovascular complications by 36-75% and kidney disease hospitalizations by 52%, with limited evidence for neuropathy impacts.

Abstract

Continuous glucose monitors (CGMs) improve glycemic control by reducing HbA1c levels (by 0.2%–0.76%), increasing time in range, and lowering hypoglycemia exposure. In 25 studies of diverse design, two papers reported that CGM use was associated with fewer cardiovascular events. One reported relative risk reductions of:

• 52% for stroke (RR 0.48)
• 36% for myocardial infarction (RR 0.64)
• 41% for atrial fibrillation (RR 0.59)
• 75% for heart failure (RR 0.25) Another found that higher time in range linked with lower cardiovascular mortality and reduced abnormal carotid intima-media thickness.

Similarly, two studies addressed renal outcomes. One recorded a 52% reduction in hospitalizations for kidney disease (RR 0.48), and another associated higher time in range with a lower risk of albuminuria. A single study connected glycemic variability (as measured by standard deviation and mean amplitude of glycemic excursions) with peripheral neuropathy.

Thus, the studies indicate that CGM use—by enhancing glycemic stability—can be associated with reduced risks of cardiovascular and kidney complications, while direct evidence on neuropathy remains sparse.

Methods

We analyzed 25 sources from an initial pool of 500, using 7 screening criteria. Each paper was reviewed for 5 key aspects that mattered most to the research question. More on methods

Papers identified with Elicit search

• n = 500

Papers screened using:

• Population Age

• Intervention Type

• Control Group

• Study Duration

• Outcomes Measured

• Study Design

• Evidence Quality

• n = 500 Papers screened out

• n = 475 Papers included for extraction

Data extraction

We asked a large language model to extract each data column below from each paper:

• Study Design: Identify the specific type of study design used:

  • Randomized controlled trial (RCT)
  • Systematic review
  • Meta-analysis
  • Other

• Participant Characteristics: Extract the following participant details:

  • Diabetes type (Type 1 or Type 2)
  • Age range or mean age
  • Total number of participants
  • Gender distribution
  • Baseline HbA1c levels
  • Duration of diabetes

• Continuous Glucose Monitor (CGM) Intervention Details: Specify:

  • Type of CGM used (real-time, flash, intermittently scanned)
  • Duration of CGM intervention
  • Frequency of CGM usage per week
  • Any specific instructions for CGM use

• Primary Outcomes Measured: List all primary outcomes:

  • HbA1c changes
  • Time in glycemic range
  • Hypoglycemia exposure
  • Long-term diabetes complications (cardiovascular disease, neuropathy, kidney disease)

• Study Limitations: Extract:

  • Acknowledged study limitations
  • Sample size constraints
  • Potential biases
  • Generalizability concerns

Results

Characteristics of Included Studies

Among the included studies, we found a mix of study designs and characteristics:

• Study Design:

  • Retrospective cohort studies appeared to be the most common (7 studies)
  • Meta-analyses and systematic reviews (5 studies)
  • Randomized Controlled Trials (RCTs) (7 studies total, with 4 parallel and 3 crossover designs)

• Population Size:

  • 11 studies had between 100-1000 participants
  • 7 large-scale studies with over 10,000 participants
  • 4 studies with 1000-10000 participants
  • 3 studies with fewer than 100 participants

• Duration: Study durations varied widely in the information available to us:

  • 6 studies lasting 1 year
  • 5 studies lasting more than 1 year
  • 3 studies lasting 6 months
  • 4 studies with mixed durations
  • We didn’t find duration information for 5 studies in their abstracts or available full texts

• Primary Outcomes:

  • HbA1c changes and hypoglycemia exposure were the most commonly measured outcomes
  • Time in glycemic range was reported in 8 studies
  • Other less frequently measured outcomes included hyperglycemia exposure, complications, hospitalization, and healthcare utilization

Effects of Continuous Glucose Monitoring (CGM) on Diabetes Complications

Cardiovascular Outcomes

• We found specific cardiovascular outcomes reported in only 2 out of the 25 studies we examined, based on the available abstracts and full texts.

Neurological Complications

• We found that only 1 out of 25 studies specifically mentioned a neurological outcome.

Renal Outcomes

• We found specific renal outcomes reported in only 2 out of 25 studies.

Implementation Factors

Duration of Continuous Glucose Monitoring (CGM) Use

The duration of CGM use varied widely across studies:

• Short-term vs. Long-term Use:

  • Anderson et al. (2011) found that long-term use was associated with greater improvements in glycemic control.

• Sustained Benefits:

  • Several studies with longer follow-up periods (1 year or more) demonstrated sustained benefits of CGM use.

• Dose-Response Relationship:

  • Karter et al. (2021) reported a dose-response association between CGM adherence and changes in HbA1c level and hypoglycemia-related healthcare utilization.

Technology Type Impact

The studies included various types of CGM technologies:

• Real-time CGM (rt-CGM):

  • Several studies reported significant benefits with rt-CGM use.

• Flash CGM (FGM):

  • Some studies included FGM systems, with reported benefits in glycemic control.

• Intermittently Scanned CGM (isCGM):

  • Eeg-Olofsson et al. (2024) specifically studied isCGM.

While different CGM technologies showed benefits in glycemic control, the impact of specific technology types on long-term complications was not directly compared in most studies we examined.