Glucometer Research Articles

Target recycle initiated entropy driven assembly strategy for sensitive, enzyme-free, and portable miRNA detection

MicroRNA (miRNA) is a pivotal biomarker in the diagnosis of various cancers, including bladder cancer (BCa). Despite their significance, the low abundance of miRNA presents a substantial challenge for sensitive and reliable detection. We introduce an innovative, highly sensitive assay for miRNA expression quantification that is both enzyme-free and portable. This method leverages the synergy of target recycling and entropy-driven assembly (EDA) for enhanced sensitivity and specificity. The proposed method possesses several advantages, including i) dual signal amplification through target recycling and EDA, which significantly boosts sensitivity with a lower limit of detection of 2.54 fM; ii) elimination of enzyme requirements, resulting in a cost-effective and stable signal amplification process; and iii) utilization of a personal glucose meter (PGM) for signal recording, rendering the method portable and adaptable to diverse settings. In summary, this PGM-based approach holds promising potential for clinical molecular diagnostics, offering a practical and efficient solution for miRNA analysis in cancer detection.

Sucrose-Powered Liposome Nanosensors for Urinary Glucometer-Based Monitoring of Cancer.

Timely detection of early-stage cancer holds immense potential in enhancing prognostic outcomes. There is an increasing desire for versatile tools to enable simple, sensitive, and cost-effective cancer detection. By exploiting the extraintestinal metabolic inertness and efficiency renal clearance of sucrose, we designed a liposome nanosensor using sucrose as a messenger to convert tumor-specific esterase activity into glucose meter readout, enabling economical and sensitive urinalysis for cancer detection in point-of-care testing (POCT). Our results demonstrate that the nanosensors exhibited significant signal differences between tumor-bearing and healthy mice in both orthotopic and metastatic tumor models. Additionally, efficient elimination of the nanosensors through the hepatobiliary pathway was observed with no significant toxicity. Such a non-invasive diagnostic modality significantly assists in personalized pharmacological treatment and follow-up efficacy assessment. We envision that this modular liposome nanosensor platform might be applied for economically detecting diverse diseases via a simple urinary test.

Sucrose‐Powered Liposome Nanosensors for Urinary Glucometer‐Based Monitoring of Cancer

AbstractTimely detection of early‐stage cancer holds immense potential in enhancing prognostic outcomes. There is an increasing desire for versatile tools to enable simple, sensitive, and cost‐effective cancer detection. By exploiting the extraintestinal metabolic inertness and efficiency renal clearance of sucrose, we designed a liposome nanosensor using sucrose as a messenger to convert tumor‐specific esterase activity into glucose meter readout, enabling economical and sensitive urinalysis for cancer detection in point‐of‐care testing (POCT). Our results demonstrate that the nanosensors exhibited significant signal differences between tumor‐bearing and healthy mice in both orthotopic and metastatic tumor models. Additionally, efficient elimination of the nanosensors through the hepatobiliary pathway was observed with no significant toxicity. Such a non‐invasive diagnostic modality significantly assists in personalized pharmacological treatment and follow‐up efficacy assessment. We envision that this modular liposome nanosensor platform might be applied for economically detecting diverse diseases via a simple urinary test.

Functionalized primer initiated signal cycles and personal glucose meter for sensitive and portable miRNA analysis.

MicroRNA (miRNA) has garnered considerable attention due to its diagnostic capabilities, such as in hypoxic cognitive impairment and cancers. However, the existing miRNA detection methods are commonly criticized for the drawbacks of low sensitivity and false-positive detection derived from interfering molecules. Here, we provide a novel, sensitive and portable method for miRNA detection by combining target identification based cyclization of padlocks, immobilized primer-based signal amplification and a personal glucose meter. The proposed method exhibits several advantages, including precise identification of specific sites, exceptional sensitivity and instrument-free feature. These attributes hold great promise for the diagnosis and clinical investigation of various diseases, such as cancer and hypoxic cognitive impairment, enabling a deeper understanding of their pathological and physiological aspects.

Sensitive, Semiquantitative, and Portable Nucleic Acid Detection of Rabies Virus Using a Personal Glucose Meter.

Rabies is a zoonotic infection with the potential to infect all mammals and poses a significant threat to mortality. Although enzyme-linked immunosorbent tests and real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) have been established for rabies virus (RABV) detection, they require skilled staff. Here, we introduce a personal glucose meter (PGM)-based nucleic acid (NA-PGM) detection method to diagnose RABV. This method ensures sensitive and convenient RABV diagnosis through hybridization of reverse transcription-recombinase aided amplification (RT-RAA) amplicons with probes labeled with sucrose-converting enzymes, reaching a detection level as low as 6.3 copies/μL equivalent to 12.26 copies. NA-PGM allows for the differentiation of RABV from other closely related viruses. In addition, NA-PGM showed excellent performance on 65 clinical samples with a 100% accuracy rate compared with the widely adopted RT-qPCR method. Thus, our developed NA-PGM method stands out as sensitive, semiquantitative, and portable for RABV detection, showcasing promise as a versatile platform for a wide range of pathogens.

Современные тенденции самоконтроля гликемии

Objective. To consider modern means of monitoring glycemia using a mobile application that allows remote control of diabetes mellitus (DM). The main provisions. The problem of self-control of DM in the modern world does not lose relevance. Recommendations on the management of patients with DM are updated annually. New approaches to self-monitoring of glycemia are being developed, innovative glucose meters are being introduced, which are a system with a mobile application.

Glucose sensing performance of bimetallic MOFs CoFe-ZIF/CC for enzyme-free saliva sensor applications

Co-ZIF is widely believed as a promising material which shows potential in MOFs based enzyme-free sensors. However, the research of Co-ZIF in glucose sensor filed has been hampered, due to its poor electronic conductivity and slow ion diffusion caused by closed rhombohedral dodecahedron structure. In this work, the obtained Co0.95Fe0.05-ZIF presents highly opened nanosheet structure on CC, resulting in rich open active sites and ions moving channels. Compared with other reported ZIFs, the Co0.95Fe0.05-ZIF/CC exhibits excellent sensing performance with a high sensitivity of 3232.30 μA mM−1 cm−2 in the range of 0.20–1.00 mM and a low detection limit of less than 5 μM, due to its highly opened nanosheet structure. The Co0.95Fe0.05-ZIF/CC also shows excellent selectivity, repeatability and reproducibility for glucose detection. Furthermore, the variation trend of test results measured by this saliva sensor without any sample pre-treatment, is consistent with that of commercial blood glucose meter, indicating its potential in real applications. This synthesis strategy also provides a new direction of structure construction for high performance MOFs in enzyme-free glucose sensor field.

Design and Development of a Non-invasive Opto-Electronic Sensor for Blood Glucose Monitoring Using a Visible Light Source.

Background The management of diabetes is critically dependent on the continuous monitoring of blood glucose levels. Contemporary approaches primarily utilize invasive methods, which often prove to be uncomfortable and can deter patient adherence. There is a pressing need for the development of novel strategies that improve patient compliance and simplify the process of glucose monitoring. Aim and objectives The primary objective of this research is to develop a non-invasive blood glucose monitoring system (NIBGMS) that offers a convenient alternative to conventional invasive methods. This study aims to demonstrate the feasibility and accuracy of using visible laser light at a wavelength of 650 nm for glucose monitoring and to address physiological and technical challenges associated with in vivo measurements. Methods Our approach involved the design of a device that exploits the quantitative relationship between glucose concentration and the refraction phenomena of laser light. The system was initially calibrated and tested using glucose solutions across a range of concentrations (25-500 mg/dL). To get around the problems that come up when people's skin and bodies are different, we combined an infrared (IR) transmitter (800 nm) and receiver that checks for changes in voltage, which are indicative of glucose levels. Results The prototype device was compared with a commercially available blood glucose monitor (Accu-Chek active machine; Roche Diabetes Care, Inc., Mumbai, India). The results demonstrated an average linearity of 95.7% relative to the Accu-Chek machine, indicating a high level of accuracy in the non-invasive measurement of glucose levels. Conclusions The findings suggest that our NIBGMS holds significant promise for clinical application. It reduces the discomfort associated with blood sampling and provides reliable measurements that are comparable to those of existing invasive methods. The successful development of this device paves the way for further commercial translation and could significantly improve the quality of life for individuals with diabetes, by facilitating easier and more frequent monitoring.

Clinical and functional characterization of a novel KCNJ11 (c.101G > A, p.R34H) mutation associated with maturity-onset diabetes mellitus of the young type 13.

This study aimed to describe the clinical features, diagnostic and therapeutic course of a patient with MODY13 caused by KCNJ11 (c.101G > A, p.R34H) and how it contributes to the pathogenesis of MODY13, and to explore new therapeutic targets. Whole-exome sequencing was used to screen prediagnosed individuals and family members with clinically suspected KCNJ11 mutations. Real-time fluorescence quantitative PCR, western blotting, thallium flux of potassium channels, glucose-stimulated insulin secretion (GSIS), and immunofluorescence assays were used to analyze the regulation of insulin secretion by the KCNJ11 mutant in MIN6 cells. Daily blood glucose levels were continuously monitored for 14 days in the proband using the ambulatory blood glucose meter (SIBIONICS). Mutation screening of the entire exon of the gene identified a heterozygous KCNJ11 (c.101G > A, p.R34H) mutation in the proband and his mother. Cell-based GSIS assays after transfection of MIN6 using wild-type and mutant plasmids revealed that this mutation impaired insulin secretory function. Furthermore, we found that this impaired secretory function is associated with reduced functional activity of the mutant KCNJ11 protein and reduced expression of the insulin secretion-associated exocytosis proteins STXBP1 and SNAP25. For the first time, we revealed the pathogenic mechanism of KCNJ11 (c.101G > A, p.R34H) associated with MODY13. This mutant can cause alterations in KATP channel activity, reduce sensitivity to glucose stimulation, and impair pancreatic β-cell secretory function by downregulating insulin secretion-associated exocytosis proteins. Therefore, oral sulfonylurea drugs can lower blood glucose levels through pro-insulinotropic effects and are more favorable for patients with this mutation.

The effect of caffeine on running performance in performance triathletes

Background and purpose In an endurance sport such as triathlon, coaches at the elite level strive to select an appropriate nutritional strategy prior to performance in addition to optimizing the training process. Based on this, the research in question was designed with the aim to verify the effect of caffeine on the running performance of performance triathletes during the preparation period. Purpose is to determine the effect of caffeine on running performance in triathletes. Material and methods The study sample consisted of 8 performance triathletes from the TRIAN club of ŠK UMB Banská Bystrica, whose age was 16.7 ± 0.67 years. Diagnostics were run on InSPORTline Condi T6000i treadmill with the aim of detecting lactate and blood sugar levels (mmol/l) before the performance and within 10 seconds after the performance. The blood lactate level was detected with the portable device Lactate Scout+ and the blood glucose level was measured with the Wellion CALLA light glucose meter. The running pace at which the participants performed the test was at anaerobic threshold and they attempted to cover a distance of 1,500 m at a constant incline of 3%. The testing took place 1 time per week in the morning hours (08:00-08:30). On the second day after the initial testing from 01.03.2023 to 14.03.2023, the participants started taking placebo (magnesii lactas) on a daily basis in form of capsules. The participants took 2 capsules (200 mg magnesium) which they consumed with 200 mL of water 45 to 60 minutes before each morning workout/test. This was followed by the administration of caffeine capsules, which they consumed for an additional 2 weeks from 03.15.2023 to 03.28.2023. The participants consumed caffeine capsules at 5 mg/kg body weight 45 to 60 minutes before each morning workout/test. The intervention programme lasted 5 weeks. Results When administering caffeine capsules at a dose of 5 mg/kg body weight, there was a significant reduction of approximately 26% in the average blood lactate level of the participants after the 1,500 m run. The participants' mean blood glucose levels increased by approximately 4.9% after the 1500 m run. Conclusions Based on the results we can claim that for ergogenic effects on performance we recommend supplementing with 5mg/kg body weight of caffeine approximately 45 to 60 minutes before training.

SDAGS: SMOTE+FOREST DIFFUSION-BASED DATA AUGMENTATION AND GBT-BASED STACKING ENSEMBLE LEARNING FOR HOLISTIC AI-POWERED DIABETES MELLITUS PREDICTION

It's critical to track and anticipate diabetes in emerging nations like Vietnam, particularly for those with type 1 diabetes. This article proposes SDAPS, an AI-powered diabetes prediction technique. Our method is based on two ideas: (i) using the SFDM method to make the training data better by combining the oversampling of the Forest Diffusion Model with the SMOTE data balancing method; and (ii) making the GSDP model by stacking different boosting machine learning models together. We also suggest an AI-powered blood glucose monitoring and recommendation system based on SDAPS to provide diabetic patients with all-encompassing assistance with blood glucose monitoring, dietary counseling, physical activity, and the proper use of medications. Our thorough experiments using the Pima Indians diabetes dataset and the 5-fold cross-validation evaluation method demonstrate that SDAPS outperforms the state-of-the-art methods, with the following results: sensitivity, specificity, F1, accuracy, and precision: 98.03\%, 99.49%, 98.74%, 98.75%, and 98.00%, respectivelyOrder

Impact of Telemedicine on Blood Glucose Control and Ophthalmic Screenings for Patients with Diabetes in Remote Areas During the COVID-19 Pandemic: A Real-World Study in Northern Taiwan.

Introduction: The purpose of this study was to assess the impact of telemedicine on ophthalmic screening and blood glucose control for patients with diabetes in remote areas of Northern Taiwan during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Telemedicine was implemented in Shiding and Wanli Districts using a 5G platform from April 2021 to December 2022. Patients with poorly controlled diabetes received real-time consultations from endocrinologists at Far Eastern Memorial Hospital, 50 km away, for medication adjustment, diet control, and lifestyle recommendations. The study also provided cloud-upload blood glucose meters for self-monitoring and regular medical advice from hospital nurses. Ophthalmic screenings included fundus imaging, external eye image, and intraocular pressure measurement, with instant communication and diagnosis by ophthalmologists through telemedicine. A satisfaction questionnaire survey was conducted. Results: The study enrolled 196 patients with diabetes. Blood glucose and glycosylated hemoglobin levels were significantly reduced after applying telemedicine (p = 0.01 and p = 0.005, respectively). Ophthalmic screenings led to hospital referrals for 16.0% with abnormal fundus images, 15.6% with severe cataract or anterior segment disorders, and 27.9% with ocular hypertension or glaucoma. Fundus screening rates remained high at 86.3% and 80.4% in 2022, mainly using telemedicine, comparable with the traditional screening rate in the past 5 years. The overall satisfaction rate was 98.5%. Conclusions: Telemedicine showed effectiveness and high satisfaction in managing diabetes and conducting ophthalmic screenings in remote areas during the COVID-19 pandemic. It facilitated early diagnosis and treatment of ocular conditions while maintaining good blood glucose control and fundus screening rates.

Special RCA based sensitive point‐of‐care detection of HPV mRNA for cervical cancer screening

AbstractDeveloping the sensitive point‐of‐care testing (POCT) of oncogenic nucleic acids from human papillomavirus (HPV) infection is essential in preventing cervical cancer, especially in resource‐limited settings. Rolling circle amplification (RCA) is attractive in achieving POCT via nucleic acid‐based aggregation under isothermal conditions. However, the influence of RCA product structure on the aggregation remains unexplored resulting in limited sensitivity. Here, a minimum secondary structured RCA technique (MSS‐RCA) is developed by designing a unique circular template, demonstrating significantly enhanced detection sensitivity with only one amplification step and one primer under isothermal conditions. The amplification efficiency of MSS‐RCA could be kinetically manipulated by controlling the secondary structure of the circular template. Introducing the invertase probe to MSS‐RCA, HPV16 E6/E7 nucleic acid target was detected with a personal glucose meter (PGM) with a sensitivity of 5 fm (50 zmol in 10 µL). This integrated MSS‐RCA‐PGM detection system was successfully applied to detect HPV16 E6/E7 mRNA extracted from 54 cervical swab samples reaching a positive predictive value of 100.00% and negative predictive values of 96.00% (77.77% to 99.40%, 95% CI). MSS‐RCA‐PGM provides a sensitive POCT platform for the detection of nucleic acid biomarkers for screening of cervical cancer or other diseases.

The progress of clinical research on the detection of 1,5-anhydroglucitol in diabetes and its complications.

1,5-Anhydroglucitol (1,5-AG) is sensitive to short-term glucose fluctuations and postprandial hyperglycemia, which has great potential in the clinical application of diabetes as a nontraditional blood glucose monitoring indicator. A large number of studies have found that 1,5-AG can be used to screen for diabetes, manage diabetes, and predict the perils of diabetes complications (diabetic nephropathy, diabetic cardiovascular disease, diabetic retinopathy, diabetic pregnancy complications, diabetic peripheral neuropathy, etc.). Additionally, 1,5-AG and β cells are also associated with each other. As a noninvasive blood glucose monitoring indicator, salivary 1,5-AG has much more benefit for clinical application; however, it cannot be ignored that its detection methods are not perfect. Thus, a considerable stack of research is still needed to establish an accurate and simple enzyme assay for the detection of salivary 1,5-AG. More clinical studies will also be required in the future to confirm the normal reference range of 1,5-AG and its role in diabetes complications to further enhance the blood glucose monitoring system for diabetes.

All-printed wearable biosensor based on MWCNT-iron oxide nanocomposite ink for physiological level detection of glucose in human sweat

Wearable sensors for sweat glucose monitoring are gaining massive interest as a patient-friendly and non-invasive way to manage diabetes. The present work offers an alternative on-body method employing an all-printed flexible electrochemical sensor to quantify the amount of glucose in human sweat. The working electrode of the glucose sensor was printed using a custom-formulated ink containing multi-walled carbon nanotube (MWCNT), poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOPT: PSS), and iron (II, III) oxide (Fe3O4) nanoparticles. This novel ink composition has good conductivity, enhanced catalytic activity, and excellent selectivity. The working electrode was modified using Prussian blue (PB) nanoparticles and glucose oxidase enzyme (GOx). The sensor displayed a linear chronoamperometric response to glucose from 1 μM to 400 μM, with a precise detection limit of ∼0.38 μM and an impressive sensitivity of ∼4.495 μAμM−1cm−2. The sensor stored at 4 °C exhibited excellent stability over 60 days, high selectivity, and greater reproducibility. The glucose detection via the standard addition method in human sweat samples acquired a high recovery rate of 96.0–98.6%. Examining human sweat during physical activity also attested to the biosensor's real-time viability. The results also show an impressive correlation between glucose levels obtained from a commercial blood glucose meter and sweat glucose concentrations. Remarkably, the present results outperform previously published printed glucose sensors in terms of detection range, low cost, ease of manufacturing, stability, selectivity, and wearability.

Self-powered biosensing sutures for real-time wound monitoring

Effective wound management has the potential to reduce both the duration and cost of wound healing. However, traditional methods often rely on direct observation or complex and expensive biological testing to monitor and evaluate the invasive damage caused by wound healing, which can be time-consuming. Biosensors offer the advantage of precise and real-time monitoring, but existing devices are not suitable for integration with sensitive wound tissue due to their external dimensions. Here, we have designed a self-powered biosensing suture (SPBS) based on biofuel cells to accurately monitor glucose concentration at the wound site and promote wound healing. The anode of the SPBS consists of carbon nanotubes-modified carbon fibers, tetrathiafulvalene (TTF), and glucose oxidase (GOx), while the cathode is composed of Ag2O and carbon nanotubes modified nanotubes modified carbon fibers. It was observed that SPBS exhibited excellent physical and chemical stability in vitro. Regardless of different bending degrees or pH values, the maximum power density of SPBS remained above 92%, which is conducive to long-term dynamic evaluation. Furthermore, the voltage generated by SPBS reflects blood glucose concentration, and measurements at wound sites are consistent with those obtained using a commercially available blood glucose meter. SPBS achieves the healing effect of traditional medical sutures after complete healing within 14 days. It offers valuable insights for intelligent devices dedicated to real-time wound monitoring.

Analysis of standardized use and accuracy of home self-monitoring portable blood glucose meters in South China

Analysis of standardized use and accuracy of home self-monitoring portable blood glucose meters in South China

Non-invasive Blood Glucose Monitoring System

The project presents a novel approach to blood glucose monitoring, offering a non-invasive and pain-free method for individuals with diabetes to track their glucose levels. The system utilizes advanced sensor technology coupled with signal processing techniques to detect glucose levels in the body without the need for traditional needle pricking. The key components of the system include a power supply, voltage regulator, ESP32 microcontroller, LCD display, photo sensor, amplifier circuit, and linearization circuit, all seamlessly integrated to provide accurate and real-time glucose readings. This breakthrough technology holds great promise in revolutionizing diabetes management, enhancing the quality of life for millions of affected individuals.By placing the sensor on the individual’s hand, the Glucometer system employs a combination of photonic and electronic principles to non-invasively measure glucose levels. The photo sensor captures specific wavelengths of light that interact with glucose molecules within the tissue, generating a signal proportional to the glucose concentration. This signal is then amplified and processed through the integrated circuits, ensuring accurate linearization and calibration. The ESP32 microcontroller orchestrates these operations, facilitating seamless communication with the LCD display to present the glucose reading in a clear and user-friendly format.The Glucometer’s innovative design eliminates the discomfort associated with traditional blood sampling methods, making it a highly accessible and convenient tool for diabetes management. The system’s efficiency in providing accurate glucose readings without the need for invasive procedures represents a significant advancement in healthcare technology. With further development and refinement, the Glucometer holds the potential to significantly enhance the daily lives of individuals living with diabetes, offering a reliable and painless means of monitoring blood glucose levels.

Insulin and glucose tolerance assessment in guanylyl cyclase/natriuretic peptide receptor-A gene-targeted mutant mice

Atrial natriuretic peptide (ANP), acting through guanylyl cyclase/natriuretic peptide receptor-A (GC-A/NPRA) regulates blood pressure and cardiac homeostasis. The disruption of Npr1 (encoding NPRA) in mice exhibits hypertension and provokes renal and cardiac disorder. However, the underlying mechanisms are not yet precisely determined. The objective of this study was to determine whether Npr1 plays a role in regulating glucose homeostasis in global Npr1 gene-disrupted mice. The adult male (14-18 wks) Npr1 haplotype gene-knockout ( Npr1+/-, 1-copy), wild-type ( Npr1+/+, 2-copy), and gene-duplicated ( Npr1+ +/+ +, 4-copy) mice were fasted overnight (16 h) and given free access to water. The mice were administered with glucose both orally and intraperitoneally (2 g/kg body weight) to determine the oral glucose tolerance test (OGTT) and intraperitoneal glucose tolerance test (IPGTT). For the insulin tolerance test (ITT), mice were also fasted for 16 h and then received an ip-injection of insulin (1.0 UI/kg body weight). Blood glucose levels were determined by performing tail bleeds at 0, 15, 30, 60, 90, and 120 min using the AlphaTRAK blood glucose monitoring system. The results showed that administration of glucose resulted in a greater increases in blood glucose levels at 120 mins in 1-copy mice (OGTT: 237 ± 5 mg/dL, IPGT: 246 ± 6 mg/dL, ITT; 239 ± 7 mg/dL) than 2-copy male (OGTT: 131 ± 3 mg/dL, IPGT: 126 ± 6 mg/dL, ITT; 127 ± 6 mg/dL), respectively. The blood glucose was also significantly lower in 4-copy mice (OGTT: 113 ± 5 mg/dL, IPGT: 108 ± 7 mg/dL, ITT; 107 ± 3 mg/dL) than in 2-copy mice. Systolic blood pressure (SBP) was determined by non-invasive tail-cuff method (Visitech 2000). SBP was significantly greater in 1-copy mice (130 ± 4 mmHg) than 2-copy mice (100 ± 3 mmHg). Similarly, SBP was also significantly lower in 4-copy mice (90 ± 2) than 2-copy mice. The increase in plasma glucose levels was significantly lower in OGTT than in IPGTT. The present results suggest that decreased Npr1 gene copy number predisposes to hyperglycemia, insulin resistance, and hypertension. These results indicate that the Npr1 gene might regulate blood glucose homeostasis. This work was supported by the NIH grant (DK133833). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Proactive Identification of Patients with Diabetes at Risk of Uncontrolled Outcomes during a Diabetes Management Program: Conceptualization and Development Study Using Machine Learning.

The growth in the capabilities of telehealth have made it possible to identify individuals with a higher risk of uncontrolled diabetes and provide them with targeted support and resources to help them manage their condition. Thus, predictive modeling has emerged as a valuable tool for the advancement of diabetes management. This study aimed to conceptualize and develop a novel machine learning (ML) approach to proactively identify participants enrolled in a remote diabetes monitoring program (RDMP) who were at risk of uncontrolled diabetes at 12 months in the program. Registry data from the Livongo for Diabetes RDMP were used to design separate dynamic predictive ML models to predict participant outcomes at each monthly checkpoint of the participants' program journey (month-n models) from the first day of onboarding (month-0 model) up to the 11th month (month-11 model). A participant's program journey began upon onboarding into the RDMP and monitoring their own blood glucose (BG) levels through the RDMP-provided BG meter. Each participant passed through 12 predicative models through their first year enrolled in the RDMP. Four categories of participant attributes (ie, survey data, BG data, medication fills, and health signals) were used for feature construction. The models were trained using the light gradient boosting machine and underwent hyperparameter tuning. The performance of the models was evaluated using standard metrics, including precision, recall, specificity, the area under the curve, the F1-score, and accuracy. The ML models exhibited strong performance, accurately identifying observable at-risk participants, with recall ranging from 70% to 94% and precision from 40% to 88% across the 12-month program journey. Unobservable at-risk participants also showed promising performance, with recall ranging from 61% to 82% and precision from 42% to 61%. Overall, model performance improved as participants progressed through their program journey, demonstrating the importance of engagement data in predicting long-term clinical outcomes. This study explored the Livongo for Diabetes RDMP participants' temporal and static attributes, identification of diabetes management patterns and characteristics, and their relationship to predict diabetes management outcomes. Proactive targeting ML models accurately identified participants at risk of uncontrolled diabetes with a high level of precision that was generalizable through future years within the RDMP. The ability to identify participants who are at risk at various time points throughout the program journey allows for personalized interventions to improve outcomes. This approach offers significant advancements in the feasibility of large-scale implementation in remote monitoring programs and can help prevent uncontrolled glycemic levels and diabetes-related complications. Future research should include the impact of significant changes that can affect a participant's diabetes management.