How to Read Your Glucose Data Like a Doctor

👨‍⚕️ Why Doctors See What You Miss

When you look at your CGM app, you see numbers. When your doctor looks at the same data, they see:

• Patterns across time: "Your glucose always spikes at 3 PM on weekdays but not weekends"
• Statistical significance: "Your CV is 42%—that's clinically high variability"
• Medical context: "This dawn phenomenon pattern suggests we should adjust your basal insulin"
• Risk indicators: "You're spending 8% of time below 70 mg/dL—hypoglycemia risk"

The difference isn't intelligence—it's systematic training. Doctors use structured frameworks to analyze glucose data quickly and accurately.

📊 The 5 Core Glucose Metrics

Doctors prioritize these 5 metrics over everything else. Master these and you'll understand 80% of what matters.

1. Time in Range (TIR)

TIR %	Interpretation	Estimated HbA1c
>70%	Excellent control	<7%
50-70%	Good control	7-8%
<50%	Poor control	>8%

Why it matters: Each 5% increase in TIR reduces complication risk. Going from 60% to 70% TIR is clinically significant. Read more: What is Time in Range?

2. Average Glucose (Mean Glucose)

Target: <154 mg/dL (correlates to HbA1c <7%)

Important caveat: Average glucose alone is misleading. You can have a "good" average (150 mg/dL) with terrible variability (swinging from 60 to 250 mg/dL). That's why CV is critical.

3. Coefficient of Variation (CV)

Formula: CV = (Standard Deviation ÷ Average Glucose) × 100

CV %	Interpretation
<36%	Stable glucose (GOOD)
>36%	High variability (NEEDS IMPROVEMENT)

Why it matters: High CV means your glucose swings wildly even if average is normal. This increases hypoglycemia risk and long-term complications. Reducing CV is often more important than lowering average glucose.

4. Glucose Management Indicator (GMI)

Formula: GMI = 3.31 + (0.02392 × Average Glucose in mg/dL)

Target: <7% for most adults (equivalent to average glucose <154 mg/dL)

Note: GMI estimates what your HbA1c lab test would show. It's useful for tracking progress between quarterly lab tests but may differ from actual HbA1c due to individual factors.

5. Time Below Range (TBR)

Target: <4% (less than 1 hour per day below 70 mg/dL)

Critical threshold: <1% time below 54 mg/dL (severe hypoglycemia)

Why it matters: Hypoglycemia is dangerous and can be life-threatening. Even if your TIR and average glucose are good, high TBR means you're at risk. This gets priority attention from doctors.

📈 How to Read an AGP Chart

The Ambulatory Glucose Profile (AGP) is the single most useful visualization in glucose data analysis. It shows your typical daily pattern by overlaying multiple days of data.

What is an AGP Chart?

An AGP chart displays:

• Median line: Your typical glucose at each time of day
• 25th-75th percentile band: Where 50% of your readings fall
• 10th-90th percentile band: Where 80% of your readings fall
• Target range shading: 70-180 mg/dL highlighted

How to Read an AGP Chart (Step-by-Step)

Step 1: Check if the median line stays in target range (70-180 mg/dL)

• If yes: Good overall control
• If no: Identify when it goes out of range

Step 2: Look at the band width

• Narrow bands = stable, predictable glucose
• Wide bands = high variability (high CV)

Step 3: Identify specific time periods with problems

• Morning rise (4-8 AM): Dawn phenomenon?
• Post-meal spikes: Which meals cause the biggest jumps?
• Overnight dips: Nocturnal hypoglycemia risk?

Step 4: Note the patterns that repeat daily

Consistent patterns = addressable with routine changes (meal timing, medication adjustments)

🔍 7 Critical Patterns to Identify

These are the patterns doctors look for when reviewing your CGM data. Once you learn to spot them, you'll understand what's driving your glucose levels.

Pattern 1: Dawn Phenomenon

What it looks like: Glucose rises between 4-8 AM without food intake, often peaking around 6-9 AM

Cause: Hormonal changes (cortisol, growth hormone) increase insulin resistance in early morning

How to spot it on AGP: Upward slope from 4-8 AM on the median line

Action: Adjust basal insulin, change dinner timing, try morning exercise

Pattern 2: Post-Meal Spikes

What it looks like: Glucose rises >50 mg/dL within 2 hours after eating, often exceeding 180 mg/dL

Cause: High glycemic index foods, large portions, insufficient insulin

How to spot it on AGP: Sharp spikes after typical meal times (8-9 AM, 12-1 PM, 6-8 PM)

Action: Adjust meal carb content, increase protein/fiber, adjust mealtime insulin. See: 10 Foods That Stabilize Blood Sugar

Pattern 3: Nocturnal Hypoglycemia

What it looks like: Glucose drops below 70 mg/dL during sleep (10 PM - 6 AM)

Cause: Too much basal insulin, late-day exercise without carb adjustment, alcohol

How to spot it on AGP: Median line or lower percentile band dips below 70 mg/dL overnight

Action: PRIORITY—address immediately with doctor. Reduce basal insulin, add bedtime snack

Pattern 4: Meal-Specific Spikes

What it looks like: One meal consistently causes bigger spikes than others (e.g., breakfast always spikes more than lunch)

Cause: Time-of-day insulin sensitivity differences, specific food triggers

How to spot it: Compare AGP patterns at different meal times (breakfast spike vs dinner spike)

Action: Adjust that specific meal (different foods, different timing, adjusted insulin ratio)

Pattern 5: Exercise-Induced Drops

What it looks like: Glucose drops 30-50+ mg/dL during or after physical activity

Cause: Muscles use glucose for energy, increasing insulin sensitivity

How to spot it: Consistent drops at times you typically exercise (e.g., 5-7 PM)

Action: Reduce pre-exercise insulin, consume 15-30g carbs before activity. Read: Best Exercises for Blood Sugar Control

Pattern 6: Stress Spikes

What it looks like: Unexplained glucose elevation without food, often during workday or stressful events

Cause: Stress hormones (cortisol, adrenaline) trigger glucose release from liver

How to spot it: Spikes during known stress times (work meetings, exams, deadlines) without corresponding meals

Action: Stress management techniques, consider adjusting insulin for high-stress days

Pattern 7: Rebound Hyperglycemia (Somogyi Effect)

What it looks like: Low glucose overnight followed by very high morning glucose

Cause: Your body overcompensates for nocturnal hypoglycemia by releasing glucose from liver

How to spot it: AGP shows overnight drop below 70 mg/dL followed by morning spike above 180 mg/dL

Action: Reduce basal insulin to prevent the initial overnight drop (counterintuitive but effective)

🧠 The SOAP Analysis Framework

SOAP is a systematic method used in medical training. It ensures you don't miss anything important.

S - Statistics (5 minutes)

Review your summary statistics:

• Time in Range: ____%
• Average Glucose: ____ mg/dL
• Coefficient of Variation: ____%
• GMI: ____%
• Time Below Range (<70 mg/dL): ____%
• Time Above Range (>180 mg/dL): ____%

Ask yourself: Which metrics are out of target? Which needs the most improvement?

O - Overview (5 minutes)

Look at your AGP chart:

• Does the median line stay in range throughout the day?
• Are the bands narrow (stable) or wide (variable)?
• What time periods have the biggest problems?

A - Analyze Patterns (10 minutes)

Go through the 7 critical patterns:

• Dawn phenomenon present? (4-8 AM rise)
• Post-meal spikes? (which meals?)
• Nocturnal lows? (any time below 70 mg/dL overnight?)
• Exercise drops? (consistent post-activity patterns?)
• Meal-specific issues? (breakfast worse than dinner?)
• Stress spikes? (weekday vs weekend differences?)
• Rebound patterns? (overnight low → morning high?)

P - Plan Actions (5 minutes)

Prioritize interventions:

1. First priority: Address hypoglycemia (TBR >4%)
2. Second priority: Reduce variability (CV >36%)
3. Third priority: Improve TIR and lower average glucose

Choose 1-2 specific changes to make this week. Track results for 7-14 days before making additional changes.

💡 Example: Analyzing 14 Days of Real Data

Let's walk through a real example using the SOAP framework.

S - Statistics

• Time in Range: 58%
• Average Glucose: 165 mg/dL
• Coefficient of Variation: 42%
• GMI: 7.2%
• Time Below Range: 3%
• Time Above Range: 39%

Initial assessment: TIR is below target (need >70%). High CV (42%) indicates unstable glucose. GMI slightly elevated.

O - Overview (AGP)

(Hypothetical AGP description)

• Median line mostly 140-180 mg/dL during the day
• Wide bands (high variability)
• Noticeable morning rise 5-9 AM
• Post-lunch spike consistently above 200 mg/dL
• Overnight mostly stable around 120-140 mg/dL

A - Analyze Patterns

1. Dawn phenomenon: YES—glucose rises from 110 mg/dL at 5 AM to 155 mg/dL by 8 AM
2. Post-meal spikes: YES—lunch causes consistent spike to 220+ mg/dL
3. Nocturnal lows: NO—overnight is stable
4. High CV: Wide variability, likely due to lunch spikes and morning rise

P - Plan Actions

1. Week 1-2: Address lunch spikes
   • Reduce carbs at lunch from 60g to 40g
   • Add protein and fiber (see low GI foods)
   • Test different lunch options for 7 days
2. Week 3-4: Address dawn phenomenon
   • Try 10-minute morning walk immediately upon waking
   • If ineffective, consult doctor about adjusting basal insulin

Expected outcome: Reducing lunch spikes should improve TIR by 5-10% and lower CV. Addressing dawn phenomenon adds another 3-5% TIR improvement. Target: 70% TIR, CV <36% within 8 weeks.

🤖 How AI Automates This (My Health Gheware™)

Everything we've covered takes 30-45 minutes to do manually. My Health Gheware™ does it in 10 minutes using Claude Sonnet 4.5 AI.

What the AI Does Automatically

1. Calculates All 5 Core Metrics

TIR, Average Glucose, CV, GMI, TBR—all calculated instantly across any time period (7, 14, or 30 days)

2. Identifies All 7 Patterns

The AI scans your data for dawn phenomenon, post-meal spikes, nocturnal lows, exercise drops, stress spikes, meal-specific issues, and rebound patterns. It reports which ones are present with specific timestamps.

3. Multi-Data Correlation

This is where AI surpasses manual analysis. My Health Gheware™ correlates your glucose data with:

• Sleep data (Google Fit): "Your average glucose is 35 mg/dL higher on days with <6 hours sleep"
• Activity data (Strava): "5km+ morning runs reduce your post-breakfast spike by 28%"
• Nutrition logs: "Dinners with >50g carbs consistently spike you above 200 mg/dL"

4. Generates Comprehensive Insights Report

You get a structured report with:

• Executive summary (2-3 paragraphs)
• All 5 core metrics with trend analysis
• Specific patterns identified with data references ("On Day 3 at 14:30...")
• 5-7 prioritized, actionable insights
• Expected impact of each action

5. Tracks Progress Over Time

Run analyses weekly or bi-weekly. The AI shows whether your changes are working by comparing current vs previous periods.

✅ Your Weekly Analysis Routine

Use this simple weekly routine to stay on top of your glucose data:

Weekly Review (Every Sunday, 15 minutes)

Option 1: Manual SOAP Analysis

1. Export 7-14 days of CGM data
2. Calculate 5 core metrics (or use CGM app summary)
3. Review AGP chart
4. Identify patterns using the 7-pattern checklist
5. Plan 1-2 actions for the upcoming week

Option 2: AI Analysis (Recommended)

1. Upload CGM data to My Health Gheware™
2. Click "Generate Comprehensive Insight" (10 minute AI analysis)
3. Review the generated report
4. Implement top 1-2 recommended actions
5. Track results the following week

Before Doctor Appointments (Every 3 months)

• Run a 30-day comprehensive analysis
• Print or email the report to your doctor
• Come prepared with specific questions about patterns you've identified

When Making Changes

• Change ONE thing at a time (meal timing, exercise, medication)
• Track for 7-14 days before evaluating
• Run a new analysis to objectively measure impact
• Keep what works, adjust what doesn't

Final Thoughts: Data is Power—If You Know How to Use It

CGM data is the most powerful tool available for diabetes management. But raw data alone isn't useful—it's the analysis that creates insights, and insights that drive action.

You now know exactly what doctors look for when analyzing glucose data:

• The 5 core metrics that define success
• How to read an AGP chart like a medical professional
• The 7 critical patterns that explain your glucose behavior
• A systematic SOAP framework for weekly analysis

You have two paths forward:

Path 1: Spend 30-45 minutes weekly doing manual SOAP analysis. This works, and many people prefer hands-on understanding of their data.

Path 2: Let AI do the heavy lifting in 10 minutes. My Health Gheware™ performs the same analysis doctors use, plus multi-data correlations you couldn't do manually. You get the insights without the time investment.

Either way, the key is systematic, regular analysis—not random data checking. That's how you go from drowning in numbers to mastering your health.