Validity of urine glucose measurements for estimating plasma glucose concentration

Utilizing machine learning algorithms for precise discrimination of glycosuria in fluorescence spectroscopic data

Fluorescence spectroscopy coupled with a random forest machine learning algorithm offers a promising non-invasive approach for diagnosing glycosuria, a condition characterized by excess sugar in the urine of diabetic patients. This study investigated the ability of this method to differentiate between diabetic and healthy control urine samples. Fluorescent spectra were captured from urine samples using a Xenon arc lamp emitting light within the 200 to 950 nm wavelength range, with consistent fluorescence emission observed at 450 nm under an excitation wavelength of 370 nm. Healthy control samples were also analyzed within the same spectral range for comparison. To distinguish spectral differences between healthy and infected samples, the random forest (RF) and K-Nearest Neighbors (KNN) machine learning algorithms have been employed. These algorithms automatically recognize spectral patterns associated with diabetes, enabling the prediction of unknown classifications based on established samples. Principal component analysis (PCA) was utilized for dimensionality reduction before feeding the data to RF and KNN for classification. The model's classification performance was evaluated using 10-fold cross-validation, resulting in the proposed RF-based model achieving accuracy of 96 %, specificity of 100 %, sensitivity of 93 %, and precision of 100 %. These results suggest that the proposed method holds promise for a more convenient and potentially more accurate method for diagnosing glycosuria in diabetic patients.

Self-Sustaining Triboelectric Nanosensors for Real-Time Urine Analysis in Smart Toilets

Healthcare has undergone a revolutionary shift with the advent of smart technologies, and smart toilets (STs) are among the innovative inventions offering non-invasive continuous health monitoring. The present technical challenges toward this development include limited sensitivity of integrated sensors, poor stability, slow response and the requirement external energy supply alongside manual sample collection. In this article, triboelectric nanosensor array (TENSA) is introduced featuring electrodes crafted from laser-induced 3D graphene with functional polymers like polystyrene, polyimide, and polycaprolactone for real-time urine analysis while generating 50 volts output via urine droplet-based triboelectrification. Though modulating interfacial double-layer capacitance, these sensors exhibit exceptional sensitivity and selectivity in detecting a broad spectrum of urinary biomarkers, including ions, glucose, and urea with a classification precision of 95% and concentration identification accuracy of up to 0.97 (R2), supported by artificial neural networks. Upon exposure to urine samples containing elevated levels of Na+, K+, and NH4 +, a notable decrease (ranging from 32% to 68%) is observed in output voltages. Conversely, urea induces an increase up to 13%. Experimental validation confirms the stability, robustness, reliability, and reproducibility of TENSA, representing a significant advancement in healthcare technology, offering the potential for improved disease management and prevention strategies.

A Narrative Review on Strategies for the Reversion of Prediabetes to Normoglycemia: Food Pyramid, Physical Activity, and Self-Monitoring Innovative Glucose Devices

In 2019, "Nutrition Therapy for Adults with Diabetes or Prediabetes: A Consensus Report" was published. This consensus report, however, did not provide an easy way to illustrate to subjects with prediabetes (SwPs) how to follow a correct dietary approach. The purpose of this review is to evaluate current evidence on optimum dietary treatment of SwPs and to provide a food pyramid for this population. The pyramid built shows that everyday consumption should consist of: whole-grain bread or potatoes eaten with their skins (for fiber and magnesium) and low glycemic index carbohydrates (GI < 55%) (three portions); fruit and vegetables (5 portions), in particular, green leafy vegetables (for fiber, magnesium, and polyphenols); EVO oil (almost 8 g); nuts (30 g, in particular, pistachios and almonds); three portions of dairy products (milk/yogurt: 300-400 g/day); mineral water (almost 1, 5 L/day for calcium intake); one glass of wine (125 mL); and three cups of coffee. Weekly portions should include fish (four portions), white meat (two portions), protein plant-based food (four portions), eggs (egg portions), and red/processed meats (once/week). At the top of the pyramid, there are two pennants: a green one means that SwPs need some personalized supplementation (if daily requirements cannot be satisfied through diet, vitamin D, omega-3, and vitamin B supplements), and a red one means there are some foods and factors that are banned (simple sugar, refined carbohydrates, and a sedentary lifestyle). Three to four times a week of aerobic and resistance exercises must be performed for 30-40 min. Finally, self-monitoring innovative salivary glucose devices could contribute to the reversion of prediabetes to normoglycemia.

Analytical Challenges in Diabetes Management: Towards Glycated Albumin Point-of-Care Detection

Diabetes mellitus is a worldwide-spread chronic metabolic disease that occurs when the pancreas fails to produce enough insulin levels or when the body fails to effectively use the secreted pancreatic insulin, eventually resulting in hyperglycemia. Systematic glycemic control is the only procedure at our disposal to prevent diabetes long-term complications such as cardiovascular disorders, kidney diseases, nephropathy, neuropathy, and retinopathy. Glycated albumin (GA) has recently gained more and more attention as a control biomarker thanks to its shorter lifespan and wider reliability compared to glycated hemoglobin (HbA1c), currently the “gold standard” for diabetes screening and monitoring in clinics. Various techniques such as ion exchange, liquid or affinity-based chromatography and immunoassay can be employed to accurately measure GA levels in serum samples; nevertheless, due to the cost of the lab equipment and complexity of the procedures, these methods are not commonly available at clinical sites and are not suitable to home monitoring. The present review describes the most up-to-date advances in the field of glycemic control biomarkers, exploring in particular the GA with a special focus on the recent experimental analysis techniques, using enzymatic and affinity methods. Finally, analysis steps and fundamental reading technologies are integrated into a processing pipeline, paving the way for future point-of-care testing (POCT). In this view, we highlight how this setup might be employed outside a laboratory environment to reduce the time from measurement to clinical decision, and to provide diabetic patients with a brand-new set of tools for glycemic self-monitoring.

Telehealth Technologies and Their Benefits to People With Diabetes

This article reviews the current diabetes technology landscape and how recent advancements are being used to help overcome barriers in the management of diabetes. The authors offer case examples of how digital tools and platforms can facilitate diabetes care via telehealth and remote patient monitoring for individuals in special populations. They also provide tips to ensure success in implementing diabetes technology to provide the best possible care for people with diabetes in outpatient settings.

Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices

The demand of glucose monitoring devices and even of updated guidelines for the management of diabetic patients is dramatically increasing due to the progressive rise in the prevalence of diabetes mellitus and the need to prevent its complications. Even though the introduction of the first glucose sensor occurred decades ago, important advances both from the technological and clinical point of view have contributed to a substantial improvement in quality healthcare. This review aims to bring together purely technological and clinical aspects of interest in the field of glucose devices by proposing a roadmap in glucose monitoring and management of patients with diabetes. Also, it prospects other biological fluids to be examined as further options in diabetes care, and suggests, throughout the technology innovation process, future directions to improve the follow-up, treatment, and clinical outcomes of patients.

In-Vivo Microsystems: A Review

In-vivo sensors yield valuable medical information by measuring directly on the living tissue of a patient. These devices can be surface or implant devices. Electrical activity in the body, from organs or muscles can be measured using surface electrodes. For short term internal devices, catheters are used. These include cardiac catheter (in blood vessels) and bladder catheters. Due to the size and shape of the catheters, silicon devices provided an excellent solution for sensors. Since many cardiac catheters are disposable, the high volume has led to lower prices of the silicon sensors. Many catheters use a single sensor, but silicon offers the opportunity to have multi sensors in a single catheter, while maintaining small size. The cardiac catheter is usually inserted for a maximum of 72 h. Some devices may be used for a short-to-medium period to monitor parameters after an operation or injury (1-4 weeks). Increasingly, sensing, and actuating, devices are being applied to longer term implants for monitoring a range of parameters for chronic conditions. Devices for longer term implantation presented additional challenges due to the harshness of the environment and the stricter regulations for biocompatibility and safety. This paper will examine the three main areas of application for in-vivo devices: surface devices and short/medium-term and long-term implants. The issues of biocompatibility and safety will be discussed.

Applying Nanomaterials to Modern Biomedical Electrochemical Detection of Metabolites, Electrolytes, and Pathogens

Personal biosensors and bioelectronics have been demonstrated for use in out-of-clinic biomedical devices. Such modern devices have the potential to transform traditional clinical analysis into a new approach, allowing patients or users to screen their own health or warning of diseases. Researchers aim to explore the opportunities of easy-to-wear and easy-to-carry sensors that would empower users to detect biomarkers, electrolytes, or pathogens at home in a rapid and easy way. This mobility would open the door for early diagnosis and personalized healthcare management to a wide audience. In this review, we focus on the recent progress made in modern electrochemical sensors, which holds promising potential to support point-of-care technologies. Key original research articles covered in this review are mainly experimental reports published from 2018 to 2020. Strategies for the detection of metabolites, ions, and viruses are updated in this article. The relevant challenges and opportunities of applying nanomaterials to support the fabrication of new electrochemical biosensors are also discussed. Finally, perspectives regarding potential benefits and current challenges of the technology are included. The growing area of personal biosensors is expected to push their application closer to a new phase of biomedical advancement.

Morning Spot Urine Glucose-to-Creatinine Ratios Predict Overnight Urinary Glucose Excretion in Patients With Type 2 Diabetes

BACKGROUND

With the advent of sodium glucose co-transporter 2 inhibitors to control glucose and treat diabetes, laboratory data aided by either timed or spot glucose levels in the urine could be used as an alternative marker of drug response. The aim of this study was to assess the agreement between overnight urinary glucose excretion (UGE) and morning spot urinary glucose-to-creatinine ratio (UGCR).

METHODS

In this prospective cross-sectional study, we enrolled a total of 215 participants with either normal glucose tolerance (NGT), pre-diabetes, or type 2 diabetes mellitus (T2DM). To exclude external factors such as food intake and physical activity, urine samples collected overnight at an 8-hr interval and the first-voided morning spot urine were collected and compared.

RESULTS

The median values of overnight 8-hr UGE in participants with NGT (N=14), pre-diabetes (N=41), and T2DM (N=160) were 35.0 mg, 35.6 mg, and 653.4 mg, respectively. In participants with T2DM, the median values of overnight 8-hr UGCR and first-voided morning spot UGCR (M-UGCR) were 1.37 mg/mg and 0.16 mg/mg, respectively. Quantitative analyses using an intraclass correlation coefficient (ICC) demonstrated a good reliability of measurement of the overnight 8-hr UGCR and M-UGCR (ICC=0.943, P<0.001). The M-UGCR was also significantly related to the overnight 8-hr UGE (r=0.828, P<0.001).

CONCLUSIONS

M-UGCR and overnight 8-hr UGCR showed good agreement, suggesting that M-UGCR be used as a simple index for estimating overnight amounts of UGE in patients with T2DM.

Developing a Screening Algorithm for Type II Diabetes Mellitus in the Resource-Limited Setting of Rural Tanzania

BACKGROUND

Noncommunicable diseases are on pace to outnumber infectious disease as the leading cause of death in sub-Saharan Africa, yet many questions remain unanswered with concern toward effective methods of screening for type II diabetes mellitus (DM) in this resource-limited setting. We aim to design a screening algorithm for type II DM that optimizes sensitivity and specificity of identifying individuals with undiagnosed DM, as well as affordability to health systems and individuals.

METHODS

Baseline demographic and clinical data, including hemoglobin A1c (HbA1c), were collected from 713 participants using probability sampling of the general population. We used these data, along with model parameters obtained from the literature, to mathematically model 8 purposed DM screening algorithms, while optimizing the sensitivity and specificity using Monte Carlo and Latin Hypercube simulation.

RESULTS

An algorithm that combines risk assessment and measurement of fasting blood glucose was found to be superior for the most resource-limited settings (sensitivity 68%, sensitivity 99% and cost per patient having DM identified as $2.94). Incorporating HbA1c testing improves the sensitivity to 75.62%, but raises the cost per DM case identified to $6.04. The preferred algorithms are heavily biased to diagnose those with more severe cases of DM.

CONCLUSIONS

Using basic risk assessment tools and fasting blood sugar testing in lieu of HbA1c testing in resource-limited settings could allow for significantly more feasible DM screening programs with reasonable sensitivity and specificity.

Salivary glucose concentration exhibits threshold kinetics in normal-weight, overweight, and obese children

BACKGROUND

Metabolic syndrome in childhood predicts the development of cardiovascular disease and type 2 diabetes (T2D) in adulthood. Testing for features of metabolic syndrome, such as fasting plasma glucose concentration, requires blood sampling which can be difficult in children. Here we evaluated salivary glucose concentration as a surrogate measurement for plasma glucose concentration in 11-year-old US children.

METHODS

Children from Portland, Maine, and Cambridge, Massachusetts, with a mean age of 10.6±0.2 years provided 6-hour fasting samples of both blood and whole saliva. Salivary glucose levels were measured with a high-sensitivity assay (sensitivity =0.002 mg/dL). Plasma glucose levels were determined by a commercial clinical laboratory. Blood pressure, salivary flow rate, height, and weight were also measured.

RESULTS

Of the 65 children enrolled, there were two underweight children (3.1%), 30 normal-weight children (46.2%), 12 overweight children (18.4%), and 21 obese children (32.3%). The mean overall glucose concentrations were 0.11±0.02 mg/dL in saliva and 86.3±0.8 mg/dL in plasma, and these did not differ significantly by body-weight groups. By regression analysis, the plasma concentration equaled 13.5 times the saliva concentration, with a threshold level of 84.8 mg/dL. Salivary glucose values less than threshold plasma concentration were essentially zero. Diagnostic analysis indicated a positive predictive value of 50%, a negative predictive value of 90%, and a sensitivity and specificity both of approximately 75%. The salivary glucose concentration did not vary with saliva flow rate.

CONCLUSION

Taking into account the threshold response characteristics of the salivary glucose concentration response, these results suggest that testing salivary glucose levels may be useful as a screening assay for high fasting plasma glucose levels. The low false positive value is important to assure a low fraction of missed diagnoses.

Recommendations for self-monitoring in pediatric diabetes: a consensus statement by the ISPED

A panel of experts of the Italian Society of Pediatric Endocrinology and Diabetology comprehensively discussed and approved the Italian recommendations regarding self-monitoring of blood glucose, continuous glucose monitoring and other measures of glycemic control in children and adolescents with type 1 diabetes. After an extensive review of the literature, we took these issues into account: self-monitoring blood glucose, continuous glucose monitoring, glycemic variability, glycosuria, ketonuria, ketonemia, glycated hemoglobin, fructosamine and glycated albumin, logbook, data downloading, lancing devices, carbohydrate counting, and glycemic measurements at school. We concluded that clinical guidelines on self-management should be developed in every country with faithful adaptation to local languages and taking into account specific contexts and local peculiarities, without any substantial modifications to the international recommendations. We believe that the National Health Service should provide all necessary resources to ensure self-monitoring of blood glucose and possibly continuous glucose monitoring of all children and adolescents with type 1 diabetes, according to the standards of care provided by these recommendations and internationally.

A mathematical model of the oral glucose tolerance test illustrating the effects of the incretins

Despite important empirical findings, current models of the oral glucose tolerance test (OGTT) do not incorporate the essential contributions of the incretin hormones, glucagon-like peptide-1 and glucose-dependent insulinotropic peptide, to glucose-stimulated insulin secretion. In order to address this deficiency, a model was, therefore, developed in which the incretins, as well as a term reflecting net hepatic glucose balance, were included. Equations modeling the changes in incretins, hepatic glucose balance, insulin and glucose were used to simulate the responses to 50 and 100 g oral glucose loads under normal conditions. The model successfully captures main trends in mean data from the literature using a simple 'lumped-parameter,' single-compartment approach in which the majority of the parameters were matched to known clinical data. The accuracy of the model and its applicability to understanding fundamental mechanisms was further assessed using a variety of glycemic and insulinemic challenges beyond those which the model was originally created to encompass, including hyper- and hypoinsulinemia, changes in insulin sensitivity, and the insulin infusion-modified intravenous glucose tolerance test.

Assessing glycemic control in patients with diabetes and end-stage renal failure

Blood glucose monitoring is important in optimizing long-term outcomes in diabetic patients. Reliance on near-patient testing and the use of longer term measures of glycation are the current cornerstones. However, as this review details, there are significant problems using blood tests as measures of metabolic control in uremic diabetic patients.

Monitoring glycemia in diabetes. Short-term assessment

The monitoring of glycemic status is considered a cornerstone of diabetes care. This article reviews current recommendations for routine glycemia monitoring, with emphasis on practical applications. A description of the newly developed National Glycohemoglobin Standardization Program also is provided.

Medical diagnostic technology in the home

This article studies the issues surrounding the assessment of several home diagnostic tests. First, the authors review the current data and proper use of fecal occult blood and pregnancy tests. Second, they evaluate the roles of blood and urine glucose monitoring in the management of diabetes mellitus and home pressure monitoring in the management of hypertension. The authors conclude that while home measurement of blood pressure or blood sugar can be recommended to improve compliance with medical programs, home fecal occult blood testing, while helpful, has not been fully investigated.

Management of diabetics with the use of a microprocessor: comparison of insulin treatments based on blood and urine glucose levels

The insulin treatment of 8 insulin-dependent diabetics was controlled with a microprocessor (Better Control Medical Computer, BCMC, Inc., Toronto, Canada) with information derived from blood or first voided urine glucose concentrations assessed by reagent strips four times a day, before the three main meals and bedtime snack. The microprocessor recommends modification of the insulin doses so as to reach a pre-prandial blood glucose value of 110 mg/dl or a urine glucose concentration of 0.1 g/dl. During the first two weeks self-management was uniformly applied by the patients, based on their blood glucose concentration. Subsequently, it was continued by the patients who were divided into two groups, one using the blood, the other the urine glucose concentrations, each for three weeks, alternately. During microprocessor treatment the patients' mean blood glucose profiles decreased from 152 +/- 37 mg/dl to 126 +/- 28 mg/dl. No difference was found between treatments based on blood or urine glucose concentrations concerning either the mean blood glucose profiles or the number of hypoglycemic episodes in the presence of an average glucose threshold and good renal function. The first voided urine glucose concentration and mean and maximal blood glucose values obtained at the time of urine filtration were closely correlated (r = 0.82 and 0.86, p less than 0.001).

Evaluation of two reagent strips and three reflectance meters for rapid determination of blood glucose concentrations

We evaluated three reflectance meters (Accu-Chek II, Glucometer II, and Glucoscan 2000) and two reagent strips (Chemstrip bG and Glucostix) for accuracy and precision in determining blood glucose concentrations in the dog. To evaluate accuracy, we compared results of blood glucose determinations performed on 95 samples using the various strips and meters vs. the glucose concentrations obtained using the glucose-oxidase method on a Beckman Glucose Analyzer. Accuracy was evaluated statistically using least squares regression analysis. To evaluate precision, samples in various ranges of blood glucose concentration were tested repeatedly (20 times within a 1-hour period) on the same reflectance meter. Coefficient of variation (CV) was determined to evaluate reproducibility of results. Overall, there were significant correlations (P less than 0.001) between the laboratory glucose values and the blood glucose concentrations obtained with Chemstrip bG (r = 0.976), Glucostix (r = 0.904), Accu-Chek II (r = 0.986), Glucometer II (r = 0.911) and Glucoscan 2000 (r = 0.944). In the precision study, all three meters had excellent CVs in the normal range (3.6% to 4.9%). However, Accu-Chek II was found to be more precise in the hypoglycemic and hyperglycemic ranges (3.6% and 2.6%, respectively) than either Glucometer II (8.8% and 5.4%) or Glucoscan 2000 (7.8% and 8.2%). The results of this study indicate that all of the meters and reagent strips tested are highly accurate in determining blood glucose concentrations in the dog. However, both in terms of accuracy and reproducibility of results, Accu-Chek II and Chemstrip bG, gave the highest correlation coefficients and, as such, are probably of the greatest clinical value.

The limited clinical value of home urine testing by diabetic patients

To investigate the value of home urine glucose testing in assessing chronic diabetic glucose control, the authors compared patients' glycosuria patterns with their mean blood glucose (MBG) levels calculated from glycosylated hemoglobin (Hb Alc). One hundred and twenty-one patients who regularly checked their urines reported on the frequencies of glycosuria over the preceding ten weeks. There was substantial overlap in the glycosuria patterns of patients at different levels of MBG. Glycosuria was not detectable in only 44% of patients with good control (MBG less than or equal to 150 mg/dl). The probability of such good control given no glycosuria was only 26%. Similarly, frequent glycosuria was reported by only 27% of patients with poor control (MGB greater than 250 mg/dl). The probability of such poor control given frequent glycosuria was only 34%. Because home urine testing cannot reliably identify good or poor control, it has a very limited role in assessing patients' chronic glucose control.

Computerized assessment of self-monitored blood glucose results using a Glucometer reflectance photometer with memory and microcomputer

A microcomputer software package to receive, analyse, and present blood glucose/time information has been developed. Data input is accomplished automatically via interface to Glucometer reflectance photometer instruments which have been specially modified to retain glucose/time results by addition of a clock and electronic memory. This new development in self-monitoring of blood glucose (SMBG) has a number of advantages. It allows the rapid and meaningful analysis of large quantities of patient generated data to assess short- and long-term trends in BG patterns, and eliminates the tedium and possible errors of manual graphing. Patients were most interested in the positive feedback provided. The system has considerable potential in patient diabetes education and management.