A Continuous Glucose Monitor (CGM) is a wearable device that tracks glucose levels 24 hours a day, offering data far beyond the single-point snapshot of a traditional finger-stick test. The CGM provides direction, speed, and long-term context for your glucose control. Learning to interpret this information is essential for making informed health adjustments that significantly impact daily well-being and long-term outcomes.
Understanding Real-Time Glucose Readings and Trend Arrows
The current glucose reading displayed on a CGM screen measures sugar concentration in the interstitial fluid, the fluid surrounding your cells, not directly in the blood. This distinction creates a physiological “lag time” between the CGM reading and a traditional blood glucose meter reading. When glucose levels are stable, this lag is minimal. However, when levels are changing rapidly—such as after a meal or during intense exercise—the CGM reading can trail the actual blood glucose level by several minutes.
The power of the CGM lies in the trend arrow, which indicates the rate and direction of glucose change, allowing for proactive decisions. A horizontal arrow signifies stable glucose levels, meaning the rate of change is less than 1 mg/dL per minute. A single diagonal arrow up or down suggests a moderate rate of change, typically between 1 and 2 mg/dL per minute.
Two arrows pointing straight up or straight down indicate a rapid rate of change, exceeding 2 mg/dL per minute or a change of 90 mg/dL or more within 30 minutes. Knowing this speed is important; for example, a reading of 180 mg/dL with a double-down arrow suggests a rapid fall, requiring immediate action to prevent a low reading. Conversely, a reading of 120 mg/dL with a double-up arrow suggests a steep climb that may require intervention to prevent a significant spike.
Interpreting Key Summary Metrics
CGM reports provide aggregated metrics that offer a comprehensive view of glucose control over weeks or months. The primary metric is Time in Range (TIR), the percentage of time glucose levels remain within a predetermined target zone. For most adults, this range is 70 to 180 mg/dL, and the consensus recommendation is to aim for a TIR of 70% or greater.
Achieving a high TIR is associated with a lower risk of long-term diabetes complications, as it minimizes exposure to excessively high and low glucose levels. Reports also detail time spent below range (typically below 70 mg/dL) and time spent above range (usually above 180 mg/dL). Targets aim for less than 4% time below range.
The Glucose Management Indicator (GMI) provides an estimate of the laboratory A1c value based on the average glucose level from at least 14 days of CGM data. GMI offers a more dynamic view of recent control than the traditional A1c, which reflects an average over the past two to three months. While GMI and A1c are closely related, they may not match exactly due to individual biological factors.
The Coefficient of Variation (CV) measures glucose stability and variability by calculating the ratio of the glucose standard deviation to the mean glucose. A lower CV indicates less fluctuation and tighter control. A consensus threshold suggests aiming for a CV of 36% or less to minimize the risk of hypoglycemia and achieve stable glucose levels. High variability, indicated by a high CV, can be damaging even if the average glucose is acceptable.
Analyzing Glucose Patterns and Variability
Interpreting the summary metrics requires diving into the daily glucose graphs to identify recurring patterns, which helps determine the underlying cause of high variability or low TIR. One common pattern is the post-meal spike, identified by consistently high glucose readings 90 to 120 minutes after eating. Analyzing the timing and magnitude of these spikes reveals which foods or meal compositions cause the largest glucose excursions.
Nocturnal patterns are highly revealing, particularly the “dawn phenomenon,” a natural rise in glucose levels occurring between 3 a.m. and 8 a.m. as the body releases hormones like cortisol. This rise is often distinguished from other causes of high morning glucose by checking the glucose level between 2 a.m. and 3 a.m. A different pattern, the Somogyi effect, involves a sharp drop in glucose overnight followed by a rebound high, triggered by the body releasing counter-regulatory hormones.
Exercise creates varied patterns; high-intensity workouts may cause a temporary glucose rise, while moderate, sustained activity often leads to a drop. Understanding your personal glucose response to different types of physical activity is necessary for making proactive adjustments to food or medication. By stacking or overlaying the daily glucose graphs, you can confirm if a pattern is a one-time event or a consistent challenge. Recognizing these consistent trends is key to implementing targeted changes for better control.
Applying CGM Data for Health Management Adjustments
The final step in CGM interpretation involves translating identified patterns into practical adjustments in the daily health management routine. If the data consistently shows a post-dinner glucose spike, adjustments may involve modifying meal composition to include more fiber and protein, or adjusting medication timing relative to the meal. Similarly, a pattern of pre-lunch lows might suggest reducing the morning medication dose or increasing the size of a morning snack.
The CGM data provides the evidence base for “testing a hypothesis” about your body’s response. If you observe consistent high morning glucose, you can try avoiding carbohydrates close to bedtime or moving an evening medication dose closer to sleep to see if the pattern resolves. The resulting data immediately reveals the effectiveness of the change, allowing for precise, personalized adjustments that improve time in range without causing excessive lows.
Significant changes to medication dosages or timing should always be discussed with a healthcare provider. The detailed, objective data from the CGM report facilitates a more informed conversation with your medical team, allowing for collaborative decisions on treatment adjustments. Using the data to make small, informed changes to diet, exercise timing, and medication is the most effective way to leverage continuous glucose monitoring.