Continuous Glucose Monitoring: Complete Data Interpretation Guide

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Medical Disclaimer: This content is for educational purposes only and does not constitute medical advice, diagnosis, or treatment. Information is based on current medical literature and clinical guidelines but may not apply to your specific situation. Individual responses vary based on personal medical history and concurrent conditions. Always consult qualified healthcare providers for medical decisions. Never delay seeking medical care based on content you’ve read. If experiencing a medical emergency, seek immediate medical attention.

These articles provide education to enhance your healthcare partnership. All treatment decisions should involve your healthcare team. Use this knowledge to have informed discussions, not replace medical care.

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Clinical Overview: Continuous Glucose Monitoring in Brief

Modern glucose monitoring — particularly Continuous Glucose Monitoring — does not just measure a value. It reveals patterns periodic testing cannot. Two people with the same A1C can have very different days. This article provides a comprehensive ambulatory glucose profile interpretation, explaining how these systems work, who genuinely benefits, what time in range diabetes metrics really mean, and the specific patterns worth recognizing, and how to use the technology without letting it become a second job.

Blood vessels experience the metabolic environment continuously, even when symptoms are absent.

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Why Continuous Glycemic Metrics Matter to Your Heart

Diabetes is fundamentally a cardiovascular disease — and what happens to glucose between lab visits is what blood vessels actually experience. Traditional fingerstick testing captures isolated moments. A reading of 120 mg/dL before dinner means very little if glucose spent three hours above 250 mg/dL earlier in the day. The vessels were exposed to that elevation; the lab test did not record it.

In real life, this means glucose readings that look similar on paper can behave very differently inside the body. Once diabetes is established, the vessels continue responding to the day-to-day glucose pattern — the spikes, the swings, the lows — not just to the three-month average that A1C captures.

The DIAMOND trial in adults with Type 1 diabetes on multiple daily insulin injections found a between-group A1C reduction of 0.6% (CGM group dropped 1.0%; the self-monitoring control group dropped 0.4%) and less time spent in hypoglycemia.¹ The UKPDS observational analyses linked each 1% reduction in A1C to roughly 14% lower risk of myocardial infarction, among other complications.²

Two clear biological observations explain why day-to-day patterns impact vascular architecture:

• Endothelial Dysfunction: Acute glucose spikes and rapid oscillations impair endothelial function and elevate systemic oxidative stress markers far more aggressively than sustained elevation at a stable baseline.³,⁴
• Sympathetic Surge: Severe hypoglycemia triggers an intense counter-regulatory hormone response and sympathetic nervous system activation. This cascade raises heart rate and blood pressure, establishing a clear link to cardiovascular events within both observational and mechanistic literature.⁵

One conceptual distinction is worth knowing because it underlies why monitoring matters at all: normal glucose regulation and metabolic health are not the same thing. A person can have a normal fasting glucose because rising insulin levels are temporarily keeping it normal — a compensation pattern that masks underlying metabolic disease. This is one reason fasting glucose alone misses cases that CGM and OGTT detect, a point developed in Article 4.

Monitoring matters not because the numbers are interesting, but because patterns reveal what single tests miss.

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Clinical Criteria: Who Needs a Continuous Glucose Monitoring System?

The honest answer depends on the type of diabetes a person has and what their treatment regimen looks like. The evidence base supports CGM strongly in some populations, moderately in others, and minimally in some.

Type 1 diabetes — strong evidence. Multiple randomized trials in adults and children consistently demonstrate meaningful benefit: less hypoglycemia, A1C improvement (typically 0.3–0.6% between-group differences), more time in target range, and reduced diabetes distress.¹,¹⁶,¹⁷,²² Every major diabetes organization recommends CGM for all people with Type 1 diabetes.¹⁸

Type 2 diabetes on intensive insulin therapy — strong evidence. A randomized trial in adults with Type 2 diabetes on multiple daily injections (Beck and colleagues, 2017) demonstrated benefits similar to those seen in Type 1 diabetes — meaningful A1C reduction, less hypoglycemia, improved time in range.¹⁹

Type 2 diabetes on basal insulin alone — moderate evidence. The MOBILE trial in primary-care patients on basal insulin without prandial insulin showed Time in Range of 59% with CGM versus 43% with a blood glucose meter at 8 months, along with A1C improvement and reduced time below 70 mg/dL.²⁰

Pregnancy with Type 1 diabetes — moderate evidence. The CONCEPTT trial showed CGM use produced better neonatal outcomes — fewer large-for-gestational-age infants, fewer NICU admissions over 24 hours, and less neonatal hypoglycemia.²¹

Frequent severe hypoglycemia or hypoglycemia unawareness — strong evidence. CGM reduces time spent in hypoglycemia and identifies the patterns that predispose to severe episodes. Trials in impaired-awareness populations confirm benefit.¹,¹⁴,¹⁸

Type 2 diabetes on oral medications alone — limited evidence. Published trials show modest glucose improvement in some studied populations but not others. CGM may still be reasonable if frequent hypoglycemia occurs despite medication adjustment, or if a clinician and patient agree on specific pattern-analysis goals and how they will judge whether it helped.

Prediabetes — no demonstrated benefit. No randomized trials demonstrate that tracking Time in Range as a target for Type 2 diabetes or prediabetes prevention improves long-term glucose outcomes in this specific cohort. Structured lifestyle intervention, by contrast, prevents 58% of progression to Type 2 diabetes.²⁹ That is where effort has proven payoff.

People without diabetes — no established medical indication. Normal glucose regulation does not require technological monitoring. Healthy glucose regulation does not mean glucose never rises after meals; it means the rise is proportionate, temporary, and appropriately regulated by insulin and tissue responsiveness. Continuous monitoring in healthy people may create unnecessary anxiety about normal physiology.¹⁸ Detecting physiologic glucose fluctuations is not the same thing as identifying disease, and consumer marketing of CGM to non-diabetic populations is currently ahead of the evidence.

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The Mechanics: Interstitial Fluid vs. Whole Blood Tracking

CGM sensors measure glucose in interstitial fluid — the fluid between cells — using enzyme-based electrochemical reactions. A small sensor sits just under the skin and generates a signal proportional to glucose concentration. A transmitter sends this data to a receiver, smartphone, or insulin pump.

The Interstitial Lag

The CGM measures a related compartment, not the same fluid as a fingerstick. Accuracy research documents a physiological lag of interstitial fluid relative to capillary blood glucose, typically lasting a few minutes.⁹ That biological delay matters most when glucose is changing quickly — after meals, during exercise, or during developing hypoglycemia.⁹ During rapid glucose movement, CGM readings may temporarily trail behind blood glucose enough to alter treatment interpretation in real time.

Trust symptoms first, then confirm with a fingerstick when needed.

This is the most important practical point in this section. Symptomatic hypoglycemia requires immediate treatment regardless of what the CGM displays. The lag biology, not skepticism of the device, is the reason.

Current CGM Systems

System	Wear time	Calibration	Key feature
Dexcom G7	10 days	None required	Factory calibrated, smartphone integration
Medtronic Guardian 4	7 days	Per system protocol	Insulin pump integration
FreeStyle Libre 3	14 days	None required	Factory calibrated, small sensor
FreeStyle Libre 2 (flash)	14 days	None required	Scan-to-read, less alert protection

Evaluating accuracy, engineering, and clinical data highlights several key operational variables:

• Accuracy Fluctuations: Modern factory-calibrated devices achieve clinically acceptable accuracy in validation trials, though real-time variance occurs based on hardware generation, anatomical placement site, personal physiology, and glycemic velocity.⁹–¹²
• Rapid Device Evolution: Engineering specifications alter rapidly; wear intervals, physical dimensions, and exact mean absolute relative difference (MARD) values change with each iteration. Always confirm labeling for your explicit model.
• Alert Architecture: Flash systems mandate an active manual scan to retrieve information. While the landmark IMPACT trial proved flash systems mitigate total hypoglycemia exposure,¹³ paradigms lacking proactive, automated alarms are significantly less protective against unrecognized nocturnal drops or within populations experiencing impaired hypoglycemia awareness.¹⁴,¹⁸

Automated Insulin Delivery

For people using insulin pumps, CGM can connect seamlessly to advanced automated insulin delivery aid systems (often called hybrid closed-loop systems). The built-in algorithm uses real-time data to increase, decrease, or suspend basal insulin, and some systems also deliver automated correction doses.

A large randomized trial of closed-loop control in Type 1 diabetes demonstrated improved time in range and reduced hypoglycemia exposure compared with standard sensor-augmented therapy.³³ The cardiovascular relevance, stated carefully: AID systems reduce both hyperglycemia and hypoglycemia by improving time in range and smoothing variability — changes directionally consistent with reducing the metabolic stressors discussed earlier, even though long-term cardiovascular outcomes trials specifically powered for AID-driven endpoints are not yet the standard evidence base.

Anyone using an insulin pump or considering one should ask their clinician whether an AID-capable system fits their medical situation, safety needs, and ability to engage with training and follow-up.¹⁸

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The Core Metrics: Ambulatory Glucose Profile Interpretation

CGM generates thousands of data points every week. The Ambulatory Glucose Profile compresses this massive volume of information into a standardized one-page report that has become the working reference framework for clinical device interpretation.²⁵

An AGP is closer to a weather map than to a thermometer. It does not show you a single reading; it shows you where glucose is usually stable and where it tends to behave unpredictably across the typical day.

What the AGP Shows

The dark line (median). Where glucose typically falls at each time of day — the usual pattern.

The shaded bands. A narrow band means glucose is predictable at that time of day. A wide band means glucose is behaving inconsistently — sometimes high, sometimes low — at that hour. Wider bands mean less predictability.

Time blocks. Midnight to 6 AM (overnight), 6 AM to noon (morning), noon to 6 PM (afternoon), 6 PM to midnight (evening).

What to Look For

Wide bands at specific times point to higher variability at those times. That is where to investigate. Wide overnight bands often reflect late meals, alcohol effects, or basal insulin mismatch. Wide post-lunch bands often reflect meal composition, timing, or medication timing.

A median line trending up overnight may reflect a dawn phenomenon pattern — the early morning glucose rise driven by counter-regulatory hormones, which is normal in physiology but exaggerated in diabetes.³⁰

Dips below 70 mg/dL show hypoglycemia patterns. The time of day matters. Dips before lunch may implicate morning medication timing; overnight dips may implicate basal insulin or evening behaviors. Spikes above 180 mg/dL after meals show post-prandial hyperglycemia, and identifying which meals create the largest excursions helps prioritize where lifestyle and medication discussions focus.

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Optimizing Time in Range Diabetes Targets

Time in Range (TIR) measures the percentage of time glucose stays between 70 and 180 mg/dL.³¹ Seventy percent TIR is roughly 17 hours per day in that range.

Commonly used international consensus targets for non-pregnant adults with Type 1 or Type 2 diabetes:³¹

• Target range (70–180 mg/dL): greater than 70% of the time
• Time below 70 mg/dL: less than 4%
• Time below 54 mg/dL: less than 1%
• Glucose Coefficient of Variation (a statistical measure of glucose stability): less than 36%

Targets differ for specific populations. Older adults and those at high hypoglycemia risk typically have a lower TIR target (greater than 50%), and pregnancy with Type 1 diabetes uses both a tighter target range (63–140 mg/dL) and different time thresholds.³¹ These targets are designed to balance microvascular protection against the higher risk and consequences of hypoglycemia in vulnerable groups.

Evaluating GMI and Time in Range vs A1C Outcomes

Analyses linking TIR to complications come largely from clinical trial datasets and re-analyses.⁶,⁷,³² These analyses support that TIR correlates with microvascular outcomes.⁶,⁷ A more recent DCCT/EDIC analysis emphasized that the association between estimated TIR and microvascular progression is strongly intertwined with mean glycemia (A1C), raising the question of how much independent prognostic information TIR adds beyond A1C alone.³²

Analyzing time in range vs a1c demonstrates that TIR is a complementary evaluation metric, not a replacement. It captures daily physiological exposure — especially overnight drops and erratic variability — that A1C testing alone cannot capture.

A1C reflects average exposure, not the shape of the glucose curve. Frequent highs and lows can mathematically average into a reasonable-looking A1C while producing substantial day-to-day instability — which is part of why two people with the same A1C can have meaningfully different patterns of metabolic stress.

Understanding Glycemic Fluctuations and the Glucose Coefficient of Variation

CGM becomes clinically valuable when it reveals actionable patterns. Two practical principles before the patterns themselves:

First, monitoring is not management. Monitoring itself does not improve outcomes unless the information changes behavior, treatment, or safety decisions. The value lives in what is done with the data, not in the data itself.

Second, treat the trend, not the single number. Individual readings matter less than the direction, velocity, and reproducibility of the overall pattern. CGM creates enormous amounts of data, but more data does not automatically create better decisions. Small fluctuations are often normal physiology rather than problems requiring action. Reacting aggressively to every fluctuation can sometimes worsen glucose stability rather than improve it.

With those framings in place, six patterns are worth recognizing.

Post-Prandial Hyperglycemia (post-meal spikes). Glucose rises after eating, typically peaking within 1 to 2 hours. Acute spikes during Post-Prandial Hyperglycemia impair endothelial function and raise oxidative stress markers in mechanistic studies.³,⁴ Identifying which meals cause the largest spikes is where lifestyle work (covered in Article 6) becomes visible. Carbohydrate quantity and type matter, but so do meal timing, food combinations, and eating speed.

The dawn diabetes phenomenon. Glucose rises in the early morning hours without eating, driven by a surge of overnight counter-regulatory hormones.³⁰ The pattern is rooted in normal human physiology but becomes highly exaggerated in diabetes. Documenting the pattern clearly before a clinic visit makes medication-timing decisions more accurate. The decision itself is clinician-guided.

Nocturnal hypoglycemia (overnight hypoglycemia). Glucose drops during sleep, sometimes without symptoms. This nocturnal hypoglycemia pattern is particularly dangerous because standard warning symptoms may fail to wake the person before glucose falls into a dangerous range. Severe hypoglycemia creates a surge of physiologic stress at the exact moment the brain and cardiovascular system are receiving inadequate glucose supply. This physiologic stress response is what links severe hypoglycemia to cardiovascular events in observational and mechanistic literature.⁵ Preventing episodes through clinician-guided adjustment is the goal; CGM alerts are an important safety feature, not the full solution.

Glucose variability. Wide swings throughout the day appear as broader AGP bands and elevated coefficient of variation.³¹ The mechanistic evidence suggests oscillating glucose may be more injurious than stable hyperglycemia in endothelial-function models.³,⁴ Translating that into long-term outcomes remains an area of active research. Some variability reflects lifestyle patterns, but some reflects the underlying biology of diabetes itself — insulin deficiency, insulin resistance, counter-regulatory hormones, stress physiology, and medication pharmacology all contribute. Looking for causes that can be named (meals, activity, stress, sleep, medication timing, missed doses) is the practical first step. Predictable variability is more fixable than “random” variability, and many “random” patterns become predictable once enough data accumulate.

Exercise effects. During intense activity, glucose may rise due to stress hormones and hepatic glucose release; during moderate aerobic activity, glucose often falls. Delayed hypoglycemia can occur hours later, especially in insulin-treated individuals. Exercise is among the most cardioprotective interventions available, and understanding the typical glucose response helps make exercise safer and more sustainable rather than something to avoid.

Illness and stress. Glucose rises during infection and physiologic stress, sometimes into ranges rarely seen otherwise. Illness increases dehydration risk and destabilizes insulin needs; DKA risk rises in insulin-deficient states, especially in Type 1 diabetes. Follow your clinician-provided sick-day plan. Professional standards emphasize proactive planning and early escalation when vomiting, ketones, or persistent hyperglycemia occur.¹⁸

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Practical Implementation: Making Your Continuous Glucose Monitor Work in Real Life

Best Practices for Sensor Placement and Site Rotation

Skin issues are a common reason people discontinue CGM in qualitative research.²⁴ The general principle, consistent with insulin delivery recommendations,²⁶ is to rotate within approved sites and minimize local trauma over time.

A systematic strategy optimizes device integration and preserves skin barrier integrity (always cross-reference labeling for your explicit device):

• Aseptic Preparation: Cleanse the selected cutaneous zone thoroughly with isopropyl alcohol and allow the epidermis to dry completely before applying the sensor.
• Anatomical Rotation: Regularly shift the insertion point across different approved structural zones, strictly adhering to manufacturer minimum-distance parameters relative to prior insertion points.
• Mechanical Protection: Purposefully avoid body surfaces subjected to sustained mechanical compression during nocturnal sleep or high-friction zones (such as waistbands).
• Enhanced Adhesion: Utilize medical-grade over-patches to ensure device durability during heavy diaphoresis, swimming, or repeated friction from thick clothing fabrics.

Managing Accuracy Challenges During the First 24 Hours

Accuracy during initial wear can be lower as the sensor environment stabilizes.⁹,²⁵ On day one, be more willing to confirm with a fingerstick if decisions feel high-stakes or if symptoms do not match readings.

Troubleshooting Discrepancies When Sensor Readings and Symptoms Disagree

This will happen. The CGM reads 95 mg/dL but the person feels shaky and sweaty. Or it reads 65 mg/dL and the person feels completely fine.

The rules: if a person feels hypoglycemic, treat first and verify later. A fingerstick blood glucose is more accurate than CGM at a single moment in time.⁹ Rapid glucose change is the setting most likely to produce sensor-symptom disagreement. Similarly, sustained physical pressure on the device while sleeping can produce false, dangerous-looking drops—widely known as Compression Lows. These Compression Lows reflect mechanical artifact rather than a true systemic drop in blood sugar. Device-specific factors, including medication interferences in some sensor generations, are addressed in device labeling; when in doubt, confirm with a fingerstick.⁹

Metabolic Realities: Alcohol Consumption and Delayed Hypoglycemia Risks

Alcohol creates delayed hypoglycemia risk in insulin-treated people, because ethanol metabolism impairs the liver’s ability to produce glucose through gluconeogenesis, especially when glycogen stores are limited.³⁴,³⁵ CGM can help detect overnight drops after evening drinking — if alerts are enabled and the delayed-risk pattern is understood. The right approach for anyone with diabetes who drinks is an individualized conversation with their diabetes care team, especially if there is any history of severe hypoglycemia.

Collaborative Care: Sharing Your Ambulatory Glucose Profile Data with Your Provider

Registry analyses show an association between more frequent monitoring and lower A1C, supporting the idea that actionable monitoring — not passive data collection — is what matters.²⁸ Pre-appointment preparation also matters: reviewing two to three weeks of AGP data and arriving with specific observations shifts visits from data download to pattern-based decisions. Common platforms include Dexcom Clarity, LibreView, and CareLink.

The Psychological Dimension: How to Prevent Continuous Glucose Monitor (CGM) Alert Fatigue

Feeling overwhelmed by constant glucose information is common.²³ For some people, CGM reduces anxiety by replacing uncertainty with clarity; for others, it increases anxiety by turning every fluctuation into a perceived failure. For some, seeing physiologic responses in real time makes lifestyle patterns more concrete and actionable than delayed laboratory feedback. If device alerts cause stress rather than benefit, focusing on summary metrics can help. Mastering How to prevent Continuous Glucose Monitor (CGM) alert fatigue is crucial; streamlining your settings to silence non-critical noise while keeping life-saving alarms safeguards both your mental peace and physical health. The principle is to keep the alerts that prevent harm and silence the noise. Clinically emphasized priority alerts are typically very low glucose (below 54 mg/dL), low glucose alerts when hypoglycemia risk is relevant, and very high glucose alerts in insulin-deficient states.³¹,¹⁸ A clinician can help set thresholds that match individual risk.

CGM should serve a person’s health and life. It should not become a second job. And it is worth holding onto this: CGM is a measurement tool, not a judgment about personal success or failure.

Navigating Cost, Insurance Coverage, and Prior Authorization Requirements

Economic modeling suggests CGM can be cost-effective for adults with Type 1 diabetes over time,²⁷ but coverage and out-of-pocket cost depend on device pricing, payer structures, and individual baseline risk — none of which predicts what any one person will pay.

Securing financial clearance requires a methodical approach to clinical documentation and coverage policy review:

• Establish Clinical Necessity: Thoroughly document persistent hypoglycemia events, wide glycemic swings, and complex intensive therapy regimens within the primary medical record.
• Incorporate Relevant Trial Data: Reference landmark randomized trials that mirror your diagnostic status (e.g., the DIAMOND trial for Type 1 diabetes; the Beck 2017 or MOBILE trial parameters for insulin-requiring Type 2 diabetes).¹,¹⁹,²⁰
• Execute Structured Appeals: Promptly contest coverage denials utilizing formal clinical justifications, and request an explicit list of formulary-approved alternative systems if your primary device choice is rejected.
• Direct Benefit Verification: Because commercial and Medicare guidelines undergo frequent revisions, confirm your exact current plan allowances with your provider prior to finalizing hardware procurement.

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Ketone Monitoring, SGLT2 Inhibitors of Euglycemic DKA Symptoms, and Diabetic Ketoacidosis ICD 10 Safety Metrics

Most of this article has been about pattern recognition over weeks and months. Ketone monitoring is different. It is a tool for detecting an acute metabolic emergency in real time.

Ketones are acids the body produces when it burns fat for energy instead of glucose. This happens when insulin is insufficient to let glucose into cells. High ketones combined with high glucose can signal acute metabolic distress. Standard diabetic ketoacidosis icd 10 diagnostic pathways classify this as a profound medical emergency that can develop rapidly, requiring immediate clinical intervention.

One critical clinical exception occurs in patients using SGLT2 inhibitors of euglycemic dka symptoms. In this demographic, ketone bodies can accumulate to life-threatening levels while blood glucose measurements remain entirely normal or only mildly elevated. The clinical lesson: do not rely on glucose alone as the signal to check ketones if you are on an SGLT2 inhibitor. Symptoms like nausea, abdominal pain, unusual fatigue, or rapid breathing warrant a ketone check even with normal-looking glucose.

When to check ketones. During illness with fever, vomiting, or diarrhea; when glucose remains above approximately 250 mg/dL despite correction (especially in Type 1 diabetes);¹⁸ or with symptoms suggesting DKA — nausea, abdominal pain, fruity breath odor, unusual fatigue, or rapid breathing.

How to check. Urine ketone strips are widely available. Blood ketone meters are often more precise but access varies. Clinical teams use specific ketone thresholds to triage urgency, and the right action plan is the one your diabetes care team has provided in advance.¹⁸

Emergency warning signs that warrant calling 911 or going to the emergency room: high ketones with high glucose; ketones with normal glucose in someone on an SGLT2 inhibitor; persistent vomiting or inability to keep fluids down; difficulty breathing or rapid breathing; severe abdominal pain; extreme fatigue or confusion. Do not wait or try to treat these at home.

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The Clinical Bottom Line: Prioritizing Time in Range as a Target for Type 2 Diabetes

For people using insulin, the evidence supporting CGM is strong. Randomized trials in Type 1 diabetes (DIAMOND, GOLD) and in insulin-treated Type 2 diabetes (Beck 2017 in multiple daily injection users; MOBILE in basal insulin users) demonstrate meaningful A1C improvement, reduced hypoglycemia, and improved time in range.¹,¹⁶,¹⁹,²⁰ Automated insulin delivery extends those benefits in Type 1 diabetes when appropriate training and follow-up exist.³³,¹⁸

Time in Range is a useful complement to A1C, not a replacement. International consensus targets are well-defined,³¹ and TIR captures hypoglycemia burden and variability that A1C alone misses. The independent prognostic information TIR adds beyond A1C is still being clarified.³²

For people with Type 2 diabetes on oral medications alone, evidence for CGM benefit is limited but evolving. For people without diabetes, there is no established medical indication for continuous monitoring despite consumer marketing.¹⁸

Getting value from CGM takes time. Early overwhelm and alert fatigue are common, and fixable with better settings, better interpretation frameworks, and realistic expectations.²³,²⁴ The goal is not constant numerical vigilance. It is recognizing patterns that reduce avoidable metabolic instability over decades.

The cardiovascular system remembers metabolic exposure long after individual glucose readings are forgotten.

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What Comes Next: Integrating Technology with Lifestyle Medicine

Article 6 examines lifestyle medicine — the evidence-based interventions that work synergistically with monitoring technology, translating the patterns CGM reveals into actions that protect the vascular system.

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Glossary of Key Continuous Glucose Monitoring Terms

A1C (Hemoglobin A1C): Blood test measuring average glucose over approximately three months; the standard metric for overall glycemic control.

Ambulatory Glucose Profile (AGP): A standardized one-page report format summarizing CGM data, showing typical glucose patterns and variability across the day.

Automated Insulin Delivery (AID): Systems combining CGM with an insulin pump and algorithm to automatically adjust insulin delivery; also called hybrid closed-loop systems.

Coefficient of Variation (CV): A measure of glucose variability; standard deviation divided by mean glucose, expressed as a percentage. Lower CV reflects more stable glucose.

Compression low: A falsely low CGM reading caused by pressure on the sensor, typically while sleeping on it.

Continuous Glucose Monitoring (CGM): Technology that measures glucose in interstitial fluid continuously, typically providing readings every 1–5 minutes.

Dawn phenomenon: Early morning glucose rise driven by overnight secretion of counter-regulatory hormones; normal physiology but exaggerated in diabetes.

Diabetic Ketoacidosis (DKA): A dangerous condition in which insulin deficiency leads to high glucose, ketone buildup, and blood acidification; a medical emergency, particularly in Type 1 diabetes.

Flash glucose monitoring: A CGM variant in which the user scans the sensor to obtain a reading rather than receiving automatic alerts.

Hypoglycemia unawareness: Reduced ability to perceive symptoms of low blood sugar; increases risk of severe hypoglycemia.

Interstitial fluid: The fluid between cells where CGM sensors measure glucose; glucose levels lag slightly behind blood glucose, especially when glucose is changing rapidly.

Time in Range (TIR): The percentage of time glucose stays within a target range (typically 70–180 mg/dL); a key CGM metric.

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References

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