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Continuous glucose monitor

A continuous glucose monitor (CGM) is a wearable designed to automatically measure and display blood glucose levels in by detecting glucose concentrations in the beneath the skin, offering frequent updates—typically every 1 to —to support effective throughout the day and night. CGMs consist of three main components: a small filament inserted subcutaneously, usually in the or , which measures glucose; a transmitter attached to the that wirelessly sends ; and a , dedicated , or application that shows current glucose values, trends, and alerts for highs or lows. Unlike traditional fingerstick blood glucose meters, which provide only intermittent snapshots, CGMs generate approximately 288 readings per day, enabling users to identify patterns in glucose fluctuations and adjust insulin, diet, or activity accordingly. Approved for use in people with type 1 and , as well as during including , and for other insulin-dependent individuals, CGMs have demonstrated significant clinical benefits, including improved A1c levels, reduced incidence of severe , and better time in target glucose range. Popular systems include the G6 and G7, which require no fingerstick calibrations and are suitable for ages 2 and older; the FreeStyle Libre series, featuring factory-calibrated sensors lasting up to 15 days; and integrated pump-CGM hybrids like the Medtronic MiniMed and t:slim, which enable automated insulin delivery. As of 2025, advancements in CGM technology, including 15-day sensor options, enhanced accuracy during , and integration with for predictive analytics, continue to expand access and efficacy across diverse patient populations. Despite these advantages, CGMs are not without limitations; sensors must be replaced every 7 to 15 days for most models, potential skin irritation or adhesion issues can occur, and while costs have decreased with coverage expansions, equitable remains a challenge for underserved communities. Ongoing and efforts focus on broadening policies and developing longer-wear implantable options to further democratize this transformative tool in care.

Definition and principles

Overview of CGM

A (CGM) is a wearable designed to measure glucose concentrations in the fluid surrounding cells, providing automated readings typically every 1 to 15 minutes for real-time or retrospective analysis of glucose levels. This technology allows for frequent, minimally invasive monitoring of glycemia without the need for repeated manual interventions. The primary purpose of CGM is to support by monitoring trends in glucose levels, enabling users to identify patterns and take proactive steps to avoid episodes of (low blood sugar) or (high blood sugar). Studies have shown that CGM use can reduce time spent in hypoglycemic and hyperglycemic ranges, thereby improving overall glycemic control and reducing associated health risks. In contrast to traditional fingerstick , which involves discrete blood samples obtained via pricks, CGM derives measurements from interstitial fluid rather than blood, offering a continuous stream of data that captures fluctuations throughout the day and night. The basic workflow of a CGM system begins with the subcutaneous insertion of a , followed by ongoing ; this information is then wirelessly transmitted to a dedicated , , or other , where users access current readings, customizable alerts for out-of-range values, and graphical trend analyses.

Glucose measurement mechanisms

Continuous glucose monitors (CGMs) primarily measure glucose levels in fluid rather than , as the is typically implanted subcutaneously. Glucose diffuses from the bloodstream into the interstitial space through walls, a process governed by concentration gradients and . This diffusion introduces a physiological lag time of approximately 5-10 minutes between glucose changes and corresponding interstitial glucose levels, which can affect the timeliness of readings during rapid glucose fluctuations. The core detection mechanism in most CGMs is enzymatic electrochemical sensing, relying on the (GOx) enzyme immobilized on a . Glucose in the interstitial fluid reacts with GOx in the presence of oxygen to produce gluconolactone and (H₂O₂), as described by the reaction:
\ce{glucose + O2 + H2O ->[GOx] gluconolactone + H2O2}.
The H₂O₂ is then electrochemically oxidized at the electrode surface (typically at +0.6 V vs. Ag/AgCl), generating that produce a measurable proportional to the glucose concentration. In some designs, electron mediators facilitate direct from GOx to the , reducing from oxygen limitations.
This current output follows the steady-state diffusion-limited equation for amperometric sensors: I = n F A \frac{D C}{\delta}, where I is the measured current, n is the number of electrons transferred per glucose molecule (typically 2 for H₂O₂ oxidation), F is the (96,485 C/mol), A is the surface area, D is the coefficient of glucose or H₂O₂, C is the glucose concentration, and \delta is the thickness of the diffusion layer near the . This relationship ensures the sensor signal scales linearly with glucose levels under controlled conditions. Alternative measurement methods, though less common in commercial CGMs, include optical approaches such as fluorescence-based sensing, where glucose-binding dyes change emission properties, or spectroscopic techniques like near-infrared to detect glucose-specific shifts noninvasively. Amperometric methods without s, using direct electrocatalytic oxidation of glucose on nanostructured electrodes, are also under investigation to improve stability and eliminate enzyme degradation.

Types of CGM systems

Real-time CGM

Real-time continuous glucose monitoring (rtCGM) systems are advanced wearable devices designed to automatically measure glucose concentrations in fluid and transmit readings every 5 minutes to a compatible , application, or , delivering continuous data without requiring user-initiated actions. These systems enable proactive by providing immediate access to current glucose levels, historical trends, and directional arrows indicating the rate of change, along with customizable threshold alerts for (typically above 250 mg/dL) and (below 70 mg/dL). Unlike traditional of glucose, rtCGM reduces the frequency of fingerstick tests and supports round-the-clock surveillance, particularly during or exercise. A hallmark of rtCGM is its predictive alerting capability, which employs algorithms to forecast potential glucose excursions based on the rate of change, notifying users 20 to 60 minutes in advance of crossing predefined thresholds to prevent severe hypo- or . For instance, if glucose is rising rapidly toward a high , the can issue an early even if the current value remains within range. Furthermore, rtCGM integrates with bolus calculators in many setups, where the device uses glucose data, trend direction, and user-entered meal estimates to compute personalized insulin bolus recommendations, thereby minimizing dosing errors and improving postprandial control. These features collectively enhance user empowerment and glycemic outcomes, with studies showing reduced time spent in compared to intermittent methods. Prominent examples of rtCGM systems include the G7, a factory-calibrated worn for up to 15 days (as of 2025) on the or upper arm, which transmits data every 5 minutes via to paired devices and offers customizable high/low alerts, urgent low soon warnings based on predictive algorithms, and no requirement for routine fingerstick calibrations or scans. Similarly, the Medtronic Guardian 4 , integrated into systems like the MiniMed 780G , supports a 7-day wear duration, delivers real-time readings every 5 minutes, and features predictive alerts for lows up to 30 minutes ahead, with no routine fingerstick calibrations required. Both systems emphasize seamless, automatic data flow to facilitate immediate decision-making without manual intervention. rtCGM differs fundamentally from flash glucose monitoring, a related passive variant that stores data for user-initiated scans rather than providing automatic, always-on transmission and alerts. This continuous, proactive nature of rtCGM allows for uninterrupted monitoring and timely notifications, contrasting with the on-demand retrieval in scanning-based approaches. Examples of rtCGM include later Libre iterations like the Libre 3 and Libre 3 Plus (as of 2025), which provide real-time transmission every minute with optional alarms and up to 15-day wear.

Flash glucose monitoring

Flash glucose monitoring is a variant of continuous glucose monitoring (CGM) in which a wearable continuously measures glucose levels but transmits and displays data only when actively scanned by the user using (NFC) technology via a dedicated or compatible . This on-demand access distinguishes it from other CGM types, allowing users to retrieve current glucose values, directional trend arrows indicating the rate and direction of change, and historical data without automatic transmission. Key features of flash systems include the absence of proactive alarms or alerts, a typical sensor wear period of up to 14 days, and factory calibration that eliminates the need for user-initiated blood glucose calibrations. Upon scanning, users receive up to 8 hours of retrospective glucose trend data, enabling for , while the device stores up to 90 days of history for later review via software or apps. These systems are generally more affordable than traditional CGM options, with sensors priced lower due to simplified and no requirement for constant data transmission. As of , flash systems like the FreeStyle Libre 2 have been discontinued and replaced by variants. The primary example of a flash glucose monitoring system was the Libre 14 Day Flash Glucose Monitoring System, which featured a compact, disposable approximately the size of two stacked U.S. quarters, applied to the upper arm with an adhesive patch and a short subcutaneous for sampling. This operated without user calibration and provided enzyme-based electrochemical glucose detection, displaying results within seconds of an NFC scan from up to 4 cm away, even through clothing. Compared to traditional of glucose (SMBG), flash glucose monitoring significantly reduces the frequency of painful fingerstick tests by serving as a non-adjunctive replacement for routine checks, while providing richer trend insights that support proactive adjustments in insulin or diet. However, it relies on user initiative to perform scans—ideally multiple times daily—to capture timely data, potentially limiting its utility during sleep or low-awareness periods without external reminders.

Over-the-counter CGM

Over-the-counter (OTC) continuous glucose monitors represent a category of CGM devices approved by regulatory authorities for direct purchase by consumers without a prescription, primarily targeting individuals not using insulin for or those interested in general and metabolic tracking. These systems enable users to monitor glucose trends through wearable sensors and companion apps, focusing on lifestyle insights rather than therapeutic decision-making. The U.S. (FDA) marked a significant regulatory shift with the clearance of the first OTC CGM in March 2024, expanding access beyond traditional prescription-based systems for adults with , managed without insulin, or non-diabetic individuals seeking to understand dietary impacts on blood glucose. This approval, under the integrated CGM (iCGM) classification, allows for broader consumer availability through retail channels like pharmacies and online platforms, promoting proactive health monitoring without clinician oversight. A key example is the Stelo Glucose Biosensor System, the inaugural OTC CGM cleared by the FDA, designed for adults aged 18 and older not on insulin therapy. The system features a small, disposable worn on the upper arm for up to 15 days, which wirelessly transmits glucose data to a app every 15 minutes, displaying trends, averages, and time-in-range metrics without requiring fingerstick calibration. Subsequent FDA clearances in 2024 included Abbott's Lingo for non-diabetic wellness users and Libre Rio for patients managed via diet or oral medications, further diversifying OTC options with similar 14-day wear and . As of 2025, extended wear options up to 15 days are available for some systems. These OTC CGMs emphasize trend visualization over real-time alerts, with many models, including Stelo, lacking or notifications to avoid misuse in insulin-dependent scenarios. Users are advised to consult healthcare providers for interpreting data, as the devices are not intended for diagnosing or treating medical conditions but rather for informational purposes in daily health routines. This design prioritizes safety by limiting functionality, ensuring suitability for wellness-focused applications while highlighting the need for professional guidance in clinical contexts.

Device components and functionality

Sensor design and implantation

The core component of a continuous glucose monitor (CGM) is a thin subcutaneous , typically 5-8 mm in length, that penetrates to reach the interstitial where glucose levels are measured. This is coated with an enzyme membrane containing , which reacts with glucose to produce a measurable electrical signal via electrochemical detection. The connects to a compact transmitter housing, often integrated into a single unit, and is deployed using a small auto-applicator that facilitates precise placement. Implantation of the is designed for user , typically on the back of the upper arm or , using the auto-applicator to insert the subcutaneously with minimal discomfort. Once inserted, the applicator is removed, leaving the adhered to via a strong, waterproof patch that secures it during daily activities, including and showering. The 's operational lifespan generally ranges from 7 to 15 days, after which it must be replaced due to —accumulation of proteins and cells on the that degrades performance; as of 2025, some systems like the Dexcom G7 offer up to 15 days of wear. To ensure biocompatibility, CGM sensors incorporate materials such as electrodes for stable and hydrogels, including or polyethylene glycol-based coatings, which reduce tissue inflammation, response, and infection risk at the implantation site. These materials help maintain sensor accuracy by limiting fibrous encapsulation and promoting a stable local environment around the . Modern CGM sensors have undergone significant size reductions to improve user comfort and discretion; for instance, the FreeStyle Libre 3 features a coin-sized approximately 21 mm in diameter and 2.9 mm in height, making it one of the smallest available.

Data transmission and display

Continuous glucose monitors (CGMs) primarily transmit glucose data from the to a receiver or compatible using (BLE), a wireless protocol designed for low-power, intermittent data exchange that supports monitoring without frequent battery drain. In CGM systems, the 's transmitter sends glucose readings every few minutes over BLE connections, typically maintaining a reliable range of up to 20-33 feet depending on the device model and environmental factors. This technology enables seamless connectivity to personal devices, reducing the need for physical docking while preserving energy efficiency for extended sensor wear. Flash glucose monitoring systems, in contrast, rely on Near Field Communication (NFC) for data access, where users initiate a scan by holding a compatible reader or within 1-4 cm of the to retrieve stored glucose values. NFC provides a secure, short-range method for on-demand data transfer without continuous broadcasting, which helps conserve battery life and limits unintended data exposure. Some hybrid systems combine NFC for initial reads with BLE for subsequent alarms or continuous updates. Data display occurs through dedicated receivers or mobile applications, which present glucose levels in numeric form alongside graphical trends, such as line charts showing patterns over hours or days, and directional arrows indicating the rate and direction of glucose change. These interfaces allow users to visualize time in range, hypoglycemic or hyperglycemic excursions, and overall variability, often with customizable views for short- or long-term insights. Sharing features in apps enable transmission of this data to up to multiple caregivers via secure links, facilitating remote oversight without direct device access. Advanced functionalities include cloud syncing, where glucose data is uploaded from the app to remote servers for and , supporting cross-device access and generating shareable reports. Integration with broader health ecosystems, such as Apple Health, permits automatic export of CGM metrics to aggregate with other wellness data like activity or sleep tracking. To safeguard this connectivity, CGM transmissions employ encryption protocols, including standards, to protect data integrity and confidentiality during wireless transfer and , mitigating risks of or unauthorized access.

Accuracy metrics and calibration

The accuracy of continuous glucose monitors (CGMs) is primarily evaluated using the Mean Absolute Relative Difference (MARD), which quantifies the average deviation between CGM readings and reference blood glucose measurements. MARD is calculated as the mean of the absolute relative differences, expressed as: \text{MARD} = \frac{1}{N} \sum_{i=1}^{N} \left| \frac{\text{CGM}_i - \text{Reference}_i}{\text{Reference}_i} \right| \times 100\% where N is the number of paired measurements, \text{CGM}_i is the CGM glucose value, and \text{Reference}_i is the corresponding reference value. Lower MARD values indicate higher accuracy, with modern CGM systems typically achieving 8-10%. For instance, the Dexcom G7 system reports an overall MARD of 8.2% in adults. CGM calibration ensures alignment between sensor readings and actual glucose levels, with two main approaches: factory-calibrated systems, which require no user input and rely on pre-set algorithms, and those necessitating periodic user-entered fingerstick blood glucose values for adjustment. Factory-calibrated devices, such as the Dexcom G7 and FreeStyle Libre, eliminate routine fingersticks, improving user convenience while maintaining accuracy through advanced manufacturing processes. In contrast, older systems like early Dexcom models required twice-daily fingerstick calibrations to correct for potential sensor variability. Several factors can influence CGM accuracy beyond calibration. Physiological lag time, arising from the delay in glucose diffusion from blood to interstitial fluid, typically ranges from 5-20 minutes and can lead to discrepancies during rapid glucose changes. Compression lows occur when external pressure on the sensor site, such as during sleep, temporarily reduces local blood flow and causes falsely low readings. Sensor drift, a gradual shift in sensitivity over the device's lifespan due to biofouling or enzyme degradation, may increase error rates toward the end of wear, often prompting replacement after 7-14 days. Clinical validation of CGM accuracy often employs the Clarke Error Grid analysis, which categorizes paired CGM-reference readings into zones based on potential clinical impact. Zone A represents clinically accurate readings (no error in treatment), while Zone B indicates benign errors (benign treatment deviations); modern CGMs typically place over 95% of points in these zones, confirming reliability for therapeutic decisions. This method, originally developed for blood glucose meters, has been adapted for CGMs to assess overall performance in diverse glycemic ranges.

Clinical applications and integration

Benefits in diabetes management

Continuous glucose monitoring (CGM) has demonstrated substantial benefits in enhancing glycemic control for individuals with diabetes, particularly through improvements in time in range (TIR), defined as the percentage of time glucose levels remain between 70 and 180 mg/dL. Clinical studies indicate that CGM use can increase TIR by 10-20% compared to traditional self-monitoring of blood glucose, with one randomized trial showing a baseline-adjusted mean TIR improvement of 15% in adults with type 1 diabetes using real-time CGM over six months. This enhanced TIR correlates with reductions in HbA1c levels, typically by 0.5-1%, as evidenced by meta-analyses and cohort studies across type 1 and type 2 diabetes populations, where CGM initiation led to sustained HbA1c decreases without compromising overall glucose stability. These outcomes underscore CGM's role in minimizing exposure to both hyperglycemia and hypoglycemia, thereby reducing long-term complications such as cardiovascular disease and neuropathy. A key advantage of CGM lies in its capacity to prevent , especially in , where predictive alerts enable proactive interventions. Research shows that real-time CGM can reduce severe hypoglycemic events by up to 50% in high-risk patients, including those with impaired awareness of , as demonstrated in randomized trials where event rates dropped significantly over 6-24 months of use. For instance, in adults with recurrent severe , CGM implementation led to a near-elimination of episodes in many cases, improving safety during daily activities and . This reduction is particularly vital for vulnerable groups, such as older adults, where even modest decreases in hypoglycemic time translate to fewer emergency interventions and better . CGM empowers users by providing real-time trend analysis, allowing for informed lifestyle adjustments and improved treatment adherence, especially in management. Patients can visualize how diet, exercise, and medication timing affect glucose patterns, fostering behavioral changes that enhance and long-term compliance; studies report higher satisfaction and sustained adherence rates among CGM users compared to standard monitoring. In , this trend visibility supports personalized strategies, such as optimizing carbohydrate intake or , leading to better glycemic variability and weight control without intensive oversight. Beyond established diabetes, CGM offers broader applications in and for early intervention. In , CGM improves maternal glycemic control, reducing HbA1c by approximately 0.2-0.5% and lowering risks of macrosomia and , as shown in meta-analyses of randomized controlled trials. For , CGM facilitates detection of dysglycemic patterns, enabling timely lifestyle modifications to prevent progression to , with emerging evidence from cohort studies highlighting its utility in guiding individualized preventive measures.

Closed-loop insulin systems

Closed-loop insulin systems, also known as artificial pancreas systems, integrate (CGM) data with automated insulin delivery to mimic the glucose-regulating function of a healthy . These systems use real-time glucose readings from the CGM to drive algorithmic adjustments in insulin dosing via an , aiming to maintain blood glucose levels within a target range without constant user intervention. The core components include a CGM for continuous glucose sensing, an for subcutaneous delivery, and a control algorithm that processes glucose data to compute insulin rates. Common algorithms include proportional-integral-derivative () controllers, which adjust insulin based on the difference between current and target glucose levels, and (MPC), which forecasts future glucose trends using mathematical models to optimize dosing while anticipating constraints like meal effects or exercise. Most commercially available systems are hybrid closed-loop, requiring users to announce meals for boluses while automating basal insulin and corrections. Prominent examples include the MiniMed 780G system, which employs SmartGuard technology with an MPC-based algorithm to automatically adjust basal insulin and deliver correction boluses every five minutes, suspending delivery to prevent lows. Similarly, the Tandem t:slim X2 pump with Control-IQ technology uses predictive algorithms to forecast glucose 30 minutes ahead based on CGM data, automatically increasing, decreasing, or suspending basal insulin to target a range of 112.5-160 mg/dL, while also providing automatic correction boluses. These systems automate responses to highs and lows, reducing the need for manual interventions. Clinical outcomes demonstrate significant improvements in time in range (TIR, 70-180 mg/dL), with users achieving 70-80% TIR on average, alongside reductions in and HbA1c levels, thereby decreasing the daily burden of . For instance, real-world use of the MiniMed 780G has shown TIR increases to about 79% after six months, while Control-IQ systems have reported similar gains in glycemic control across diverse populations. These advancements enhance by minimizing user oversight while maintaining safety.

Limitations and challenges

Technical and performance issues

Continuous glucose monitors (CGMs) encounter several technical challenges that can compromise their reliability and , including malfunctions and software limitations that lead to incomplete or erroneous data. These issues arise from the invasive nature of the sensors, which are inserted subcutaneously and must maintain stable contact with over extended periods, often 7 to 14 days. Despite advancements, real-world can deviate from ideal specifications, such as mean absolute relative difference (MARD) accuracy metrics, due to environmental and physiological factors. One prevalent hardware failure is sensor occlusion, where biological material such as blood clots or tissue debris blocks the sensor's glucose-sensing membrane, interfering with accurate readings. This phenomenon, observed in vitro studies, increases red blood cell density around the sensor and reduces signal integrity, potentially leading to abrupt data cessation. Complementing this, skin irritation at the insertion site affects approximately 25-30% of users, manifesting as redness, itching, or rash due to adhesive components or prolonged contact, and in severe cases prompts early sensor removal. Such irritations are more common in pediatric populations and can exacerbate occlusion by promoting inflammation around the device. Signal loss represents another critical issue, often resulting from Bluetooth connectivity disruptions or sensor dislodgement, which create data gaps in the glucose trace. Studies indicate that these gaps can constitute up to 10% of recording time in some user cohorts, though higher rates of up to 30% have been simulated with minimal overall impact on aggregated metrics; however, frequent interruptions hinder trend detection and increase reliance on confirmatory fingerstick tests. In active users, sweat or movement can contribute to partial detachment, amplifying signal instability. A inherent limitation of CGM technology is the physiological lag in interstitial fluid glucose measurements, typically ranging from 5 to behind blood glucose levels, with delays more pronounced during rapid changes such as postprandial spikes or exercise-induced drops. This lag stems from the time required for glucose from blood to and can lead to inaccuracies of 10-20% during dynamic conditions, potentially delaying user interventions for hypo- or . Fibrotic encapsulation of the sensor over time further contributes to this discrepancy by impeding glucose access to the sensing element. Alarm fatigue emerges as a software-related performance challenge, where frequent alerts for breaches or rate-of-change exceedances desensitize users and can reduce response rates to critical notifications over time. Over-alerting, often triggered by the lag-induced false positives during glucose transitions, can lead some users to deliberately deactivate alarms, compromising in automated systems. Customizable alert s mitigate this to some extent, but persistent high-frequency notifications remain a barrier to sustained adherence. Durability concerns, particularly adhesive failures under moisture , further undermine CGM performance, with sensors prone to edge lifting or complete detachment during , showering, or sweating. Clinical reports highlight that sweat can exacerbate poor , shortening wear duration and necessitating frequent replacements. While many devices are rated water-resistant to 2.4 meters for short durations, prolonged or high-intensity often results in ingress that corrodes components or disrupts electrical contacts.

Cost, accessibility, and user barriers

The cost of continuous glucose monitoring (CGM) systems represents a significant barrier to widespread adoption, particularly for individuals without coverage. Without insurance, users typically pay between $200 and $500 per month for sensors and related supplies, depending on the brand and quantity needed for continuous use. For example, a month's supply of sensors from popular systems like or FreeStyle Libre can range from $200 to $400, excluding additional costs for transmitters or readers. Insurance coverage for CGM varies widely by region and payer, often limiting access for certain patient groups. In the United States, Medicare has covered CGM for individuals with type 1 diabetes since 2017, provided they meet criteria such as insulin use and frequent self-monitoring. Coverage expanded in 2025 to include those with type 2 diabetes on basal insulin or with a history of problematic hypoglycemia, though gaps persist for non-insulin users without such complications. Private insurance and Medicaid coverage is inconsistent, with many plans requiring prior authorization or limiting reimbursement based on clinical need. Globally, reimbursement policies differ; for instance, public health systems in Europe and Canada often cover CGM for type 1 diabetes but restrict it for type 2, exacerbating inequities. Beyond financial hurdles, users face practical and demographic challenges that hinder CGM . Insertion of the can cause discomfort or skin irritation for some, leading to hesitation among those averse to wearable devices. The for interpreting data via companion apps and integrating it into daily routines poses another obstacle, particularly for older adults or those with limited , requiring substantial education to achieve effective use. issues further compound these barriers, as low-income, rural, and racial/ethnic minority populations experience lower prescription rates due to provider biases, inadequate access to training, and socioeconomic constraints. Global disparities in CGM availability are pronounced, with limited access in developing countries stemming from high import costs, regulatory delays, and weak healthcare infrastructure. In low- and middle-income nations, such as those in and parts of , CGM devices are often unavailable through public systems, forcing reliance on unaffordable out-of-pocket purchases or traditional fingerstick methods. For example, in , despite growing prevalence, CGM access remains restricted for most patients outside elite private care. These gaps contribute to poorer glycemic control and higher complication rates in resource-limited settings. Over-the-counter CGM options, where available, may help mitigate some cost barriers by bypassing prescriptions.

History and development

Early innovations and prototypes

The development of continuous glucose monitors (CGMs) originated with foundational work on enzymatic biosensors in the . In 1962, Leland C. Clark Jr. and Champ Lyons introduced the first enzyme electrode, a device that utilized immobilized on an oxygen electrode to selectively measure glucose concentrations by detecting changes in oxygen consumption. This innovation, presented at the , laid the theoretical groundwork for electrochemical glucose sensing, enabling continuous monitoring without discrete blood sampling. During the , subsequent refinements focused on improving sensor stability and selectivity, though practical implementation remained limited by enzymatic degradation and signal drift. By the 1980s, researchers advanced toward implantable prototypes, primarily tested in animal models to assess performance. A pivotal example was the needle-type glucose sensor developed by Motoaki Shichiri and colleagues, first implanted in rats in to monitor subcutaneous glucose levels continuously. These early devices, often enzyme-based and needle-shaped for vascular or subcutaneous placement, faced significant challenges including to reduce , limited power sources reliant on batteries or external wiring, and that caused signal instability after days of implantation. , such as those in dogs and rats, demonstrated feasibility for short-term monitoring but highlighted the need for biocompatible coatings to extend functionality beyond hours or days. The 1990s marked the transition to human testing with wired subcutaneous systems. MiniMed, a key pioneer in diabetes technology, initiated clinical trials of its prototype sensor in 1993, inserting a thin-wire into to record interstitial glucose every 10 seconds over 72 hours. This wired system, which required calibration with fingerstick measurements, underwent first human trials leading to the 1999 launch of the MiniMed Continuous Glucose Monitoring System (CGMS), the earliest approved CGM for retrospective data analysis in clinical settings. MiniMed's focus on subcutaneous implantation addressed prior vascular risks, setting the stage for broader adoption despite ongoing issues with sensor longevity and accuracy.

Key regulatory approvals and commercialization

The first regulatory approval for a continuous glucose monitoring (CGM) system was granted by the (FDA) in 1999 to the MiniMed Continuous Glucose Monitoring System (CGMS), developed by , for professional, retrospective use where patients wore the device for up to three days without real-time access to data. This marked the initial commercialization of CGM technology, limited to clinician analysis of downloaded glucose trends to inform adjustments. In the 2000s, the FDA shifted toward CGM systems, approving Dexcom's Seven Short-Term Sensor (STS) Continuous Glucose Monitoring System in March 2006 as the first patient-accessible device, allowing continuous monitoring for up to seven days with periodic calibration. This was followed by Abbott's FreeStyle Navigator Continuous Glucose Monitoring System in March 2008, which provided readings every five minutes for up to five days and integrated with insulin pumps, expanding commercial availability through prescription channels. These approvals facilitated broader market entry, with devices priced in the range of several hundred dollars per sensor kit, though requiring frequent fingerstick calibrations limited user adoption initially. The 2010s and early 2020s saw advancements in accuracy, usability, and integration, with the FDA approving Dexcom's system in March 2018 as the first factory-calibrated CGM that eliminated routine fingerstick confirmations for treatment decisions, enabling seamless integration with . Similarly, 's Libre 2 flash glucose monitoring system received FDA clearance in June 2020, introducing optional real-time alarms for hypo- and while maintaining a 14-day wear time and no requirement, which accelerated commercialization for both type 1 and patients. In 2025, transitioned to the Libre 3 Plus sensor, discontinuing prior Libre 2 and 3 models to enhance real-time monitoring features. A pivotal milestone occurred in March 2024 when the FDA cleared Dexcom's Stelo Glucose System as the first over-the-counter (OTC) CGM, available without a prescription for adults not using insulin, priced at approximately $90 for a two-pack of 15-day sensors to promote wider accessibility. Internationally, regulatory pathways often preceded U.S. approvals, with the European Union's granted earlier for several systems under the Directive. For instance, Abbott's FreeStyle Libre received mark in 2014, enabling commercial launch in two years before FDA approval, and Dexcom's obtained certification in June 2018 shortly after its U.S. clearance. In , local manufacturers advanced CGM commercialization during the 2020s; Sinocare's iCan i3 system was approved by the in 2023 as a factory-calibrated, CGM for adults with , supporting domestic market growth with sensors offering 14-day wear. These international approvals, including Sinocare's CE-MDR certification in July 2025 for use in people with aged 2 and above and an additional Mark in September 2025 for upper arm placement from age 13, have diversified global options while aligning with standards for accuracy and safety comparable to FDA requirements. The adoption of continuous glucose monitors (CGMs) has expanded rapidly worldwide, driven by regulatory approvals, over-the-counter (OTC) availability of certain systems, and decreasing costs that have made the technology more accessible to people with . By , the global user base has surpassed 7 million, with major systems like Abbott's FreeStyle Libre alone accounting for 7 million users, reflecting a substantial increase from earlier years when adoption was limited to under 1 million in due to high prices and limited insurance coverage. This growth is supported by market expansion, with the global CGM market valued at approximately USD 13.66 billion in 2024 and projected to reach USD 15.81 billion in , fueled by innovations in sensor longevity and integration with mobile apps. In the United States, CGM adoption accelerated following key coverage expansions starting in 2016, including FDA approval of the G5 system—the first CGM without routine fingerstick calibration—and subsequent coverage in 2017 for beneficiaries with who self-monitor. As of 2021–2023, approximately 57% of adults with were using CGMs, up from low single-digit percentages a decade earlier, with rates projected to exceed 60% by 2025 following 2023 revisions that simplified eligibility for all insulin-using adults. This uptake has been particularly strong among privately insured individuals, contributing to the U.S. holding over 38% of the global CGM market share. Europe, particularly the , has seen high CGM adoption through public health subsidies, with the (NHS) offering real-time CGMs to all children and young people with since 2023, and flash glucose monitoring systems like FreeStyle Libre to adults using multiple daily insulin injections. Flash systems have gained popularity due to their scan-on-demand functionality and lower cost compared to traditional CGMs, leading to widespread use in NHS settings and contributing to the European market's projected growth to €2.04 billion in 2025. guidelines have further promoted access, emphasizing flash monitoring for those with frequent or testing burdens. In , particularly , CGM adoption is rising in tandem with the region's high prevalence, estimated at over 140 million adults, supported by local initiatives such as Sinocare's iCan CGM system launched in 2022 with regulatory clearance in . This system, along with others from domestic producers, has driven a 63% year-on-year sales surge for Sinocare's CGM products in late 2024, making devices more affordable and tailored to local needs through with apps for 24-hour monitoring. The Chinese CGM market, valued at USD 231.4 million in 2024, is growing at a compound annual rate of 19.4% into 2025, reflecting broader regional trends in urban areas where adoption is accelerating.

Emerging technologies

Improvements in invasive CGM

Recent advancements in invasive continuous glucose monitoring (CGM) technology have focused on enhancing and clinical utility through iterative refinements to subcutaneous designs. As of 2025, key improvements include extended longevity, reduced insertion discomfort via miniaturized components, expanded detection capabilities, and superior measurement , all while maintaining the core electrochemical sensing that involves a inserted into the . These developments address longstanding user feedback on wear duration, comfort, and comprehensive metabolic insights, enabling more seamless integration into daily . One prominent enhancement is the extension of sensor wear time to up to 15 days, significantly reducing the frequency of replacements and associated costs and inconveniences. For instance, the FDA-cleared G7 15-Day sensor, approved in April 2025, supports continuous monitoring for 15.5 days including a 12-hour , surpassing the previous 10-day limit of earlier models. Similarly, Medtronic's CGM, launched in September 2025 in partnership with , offers 15-day wear and integrates directly with the MiniMed 780G system for automated adjustments. These longer durations are achieved through optimized bio-compatible materials and stabilization, minimizing degradation over time without compromising reliability. Improvements in have prioritized user comfort by employing thinner, more flexible filaments and streamlined applicators. Modern invasive CGMs feature filaments as narrow as 0.4 mm in , which insert with minimal disruption and reduce reports of insertion-site pain or irritation compared to earlier rigid designs. Devices like the Libre 3, recognized for its compact profile, utilize all-in-one applicators that combine filament deployment and adhesion in a single step, further simplifying self-application and lowering the sensory burden for users, particularly children and those with needle . These design evolutions stem from advancements in techniques, allowing sensors to be 30% smaller in overall footprint while preserving . The integration of multi-analyte sensing represents a leap toward holistic metabolic tracking within invasive CGM platforms. In 2025, announced progress on its Biowearable sensor, a dual-analyte system capable of simultaneously monitoring glucose and via a single subcutaneous filament, aiding early detection of risks. Dexcom's forthcoming G8 sensor, in human trials as of mid-2025, similarly incorporates multi-analyte functionality for glucose and , leveraging shared electrochemical pathways to expand beyond glucose-only metrics. This capability enhances safety during high-risk scenarios like exercise or illness by providing alerts alongside glucose , without requiring separate devices. Accuracy has also seen notable gains, with mean absolute relative difference (MARD) values dipping below 8.5% in leading systems, driven by innovations in selective that mitigate interferents like acetaminophen or . The G7 15-Day achieves a MARD of 8.0%, an improvement over prior iterations, through refined enzyme layers and algorithms that correct for lag time between blood and interstitial fluid. Such precision reduces erroneous alerts and supports non-adjunctive use, where CGM readings guide insulin dosing without confirmatory fingersticks, as validated in clinical settings. These membrane advancements, including coatings for better selectivity, have been pivotal in meeting regulatory thresholds for expanded indications, including management.

Noninvasive CGM developments

Noninvasive continuous glucose monitors (CGMs) aim to measure blood glucose levels without , leveraging alternative detection modalities to improve user comfort and reduce risks. Optical methods represent a primary focus in prototype developments, utilizing light-based to detect glucose transdermally. , for instance, exploits glucose's bands in the 700-2500 nm range to estimate concentrations through and , with devices like the Wizmi™ achieving a mean absolute relative difference (MARD) of 7.23% in clinical evaluations. complements this by analyzing molecular vibrations via laser excitation, often enhanced with surface-enhanced techniques (SERS) for sensitivity; an system using 830 nm excitation demonstrated transcutaneous glucose detection with reduced interference. However, both approaches face significant challenges from signal noise, as low-intensity glucose signatures are obscured by dominant absorbers like , , and in , compounded by variations in thickness, , and motion artifacts. Wearable integrations are advancing noninvasive CGM toward consumer devices, particularly smartwatches incorporating optical or radiofrequency (RF) sensors. Companies like Apple and are developing silicon photonics-based systems that combine absorption spectroscopy with photoplethysmography for wrist-based monitoring, aiming to embed glucose tracking alongside and oxygen metrics. Prototypes from PKVitality's K'Watch demonstrate feasibility with noninvasive optical glucose estimation, though full remains in R&D phases without FDA clearance yet. These efforts prioritize seamless form factors but must address calibration needs and environmental interferences to match invasive CGM accuracies around 8-12% MARD. Alternative biofluid-based approaches explore fluids accessible without penetration. Sweat analysis employs enzymatic sensors in wearable patches to detect glucose correlations with levels, with early prototypes showing 10-hour and MARD values of approximately 10-15% in pilot studies under induced . Tear glucose monitoring, via smart contact lenses or devices like NovioSense's fiber-optic probe, offers continuous sampling with phase II trials reporting MARDs of 12.8%, leveraging ' proximity to ocular vessels. Reverse extracts fluid nonthermally using low electric currents, as in the EU-approved SugarBEAT™ system, which achieved 8-17% MARD in clinical use by reversing natural flow across . These methods correlate biofluid glucose (lagging by 5-15 minutes) via algorithms, but lag times and hydration dependencies limit . Development timelines indicate accelerating progress, with pilot clinical trials for sweat- and iontophoresis-based systems underway in , including Persperion's touch-based sweat advancing toward FDA submissions. First commercial noninvasive CGMs are projected for 2026-2028, driven by regulatory approvals in and preceding U.S. launches, potentially transforming accessibility for the 500 million global population.

AI-enhanced and multi-analyte monitoring

Artificial intelligence (AI) has been integrated into continuous glucose monitoring (CGM) systems to enable predictive analytics, allowing for glucose level forecasting 30 to 60 minutes in advance through machine learning models such as long short-term memory (LSTM) networks and deep neural networks. These models analyze real-time CGM data alongside factors like insulin dosing and nutritional intake to anticipate postprandial glucose excursions, improving proactive diabetes management. Additionally, AI facilitates anomaly detection by identifying irregular glucose patterns, such as impending hypoglycemia or hyperglycemia, using supervised machine learning algorithms trained on historical CGM datasets for early intervention. Multi-analyte CGM systems expand beyond glucose to monitor additional biomarkers like , ketones, and stress markers such as , providing holistic insights into metabolic health. Microneedle-based platforms, for instance, enable simultaneous electrochemical detection of these analytes in interstitial fluid via enzyme-specific sensors, revealing correlations between glucose fluctuations and conditions like or exercise-induced . In 2025, companies like Biolinq received FDA de novo clearance for intradermal glucose sensors and are advancing clinical trials for multi-analyte versions incorporating and ketones, while Abbott's Biowearable technology is in development for dual glucose-ketone monitoring to support comprehensive detection. The evolution of closed-loop insulin delivery systems incorporates to create fully automated platforms that adapt to individual user patterns, minimizing manual overrides. algorithms process CGM data to personalize insulin dosing in real time, adjusting for variations and reducing time spent outside the target glucose range by up to 10-15% compared to systems. These -enhanced systems build on basic closed-loop mechanisms by incorporating predictive elements for seamless operation. Ethical considerations in AI-driven CGM applications center on data privacy, as continuous monitoring generates sensitive vulnerable to breaches and unauthorized access. Patients with often express concerns over inadequate and constant , with studies highlighting risks like data exposure in apps and the need for robust compliance with regulations such as HIPAA and GDPR. Solutions include blockchain-based frameworks to ensure secure data sharing and algorithmic transparency, addressing potential loss of autonomy from over-reliance on insights.

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