The open-source multi-wavelength non-invasive blood glucose sensing system.

Diabetes prevalence is increasing globally especially in the Asian subcontinent. It is expected that by the year 2030 there may be close to 400 million people with diabetes. All of the research in the past 25 years has clearly documented the effectiveness of improving glucose control in reducing long-term complications of diabetes, both microvascular and macrovascular. The improvement in glucose control usually requires continuous intensive diabetes management, particularly in insulin-requiring patients, which must include home self-monitoring of blood glucose (SMBG). Despite the convincing evidence, the role of SMBG in diabetes management is still being debated even though its availability in the past 35 years has revolutionised diabetes care, especially at home. The International Diabetes Federation (IDF) recently published guidelines for SMBG use in non-insulin-treated diabetic patients, recommending that SMBG should be used only when patients and/or their clinicians possess the ability, willingness and knowledge to incorporate SMBG and therapy adjustment into their diabetes care plan. The IDF also recommends that structured SMBG be performed with the choice of applying different defined blood glucose testing algorithms to patients' individual diabetes care plans. These defined blood glucose testing algorithms give SMBG a medically meaningful structure to collect high quality glucose information and are called structured SMBG. Former SMBG studies have demonstrated SMBG to be beneficial when patients receive feedback regarding the impact of their behaviours on SMBG results. Other studies which did not link SMBG results to these principal behaviours have shown no SMBG benefit. A new wave of clinical studies performed after the release of the IDF guideline have recently been published and have proved the success of the new application of SMBG. The reasons for this ongoing debate may in part be due to rising healthcare costs globally, lack of convincing data in non-insulin-requiring patients with type 2 diabetes in randomised controlled clinical trials and multiple controversial meta-analyses performed on several studies. Sometimes the decisions are extended to insulin-requiring patients, even those with type 1 diabetes. For example, last year in the state of Washington in the USA, legislators were going to stop reimbursing glucose test strips for children with type 1 diabetes. After much debate with committee members (who were not diabetologists and or endocrinologists) and law makers, not only SMBG but even in some cases continuous glucose monitoring (CGM) is now reimbursed. The issue was simply educating non-understanding but well-meaning people whose main concern is saving money. In the end, no one, even those not familiar with paediatric type 1 diabetes, can disagree about the need for SMBG in this age group. It seems to us that we should instead be spending our time and effort in advancing the field and improving diabetes management for patients through newer technologies like CGM and closed-loop systems. As discussed in the section on CGM (Chapter 2) there is ample data from both non-randomised and randomised clinical trials showing the efficacy in reducing time spent in hypoglycaemia and hyperglycaemia along with improvement in glucose control without introducing any additional medication. We hope that the future will be spent in advancing the care rather than useless meta-analyses or going back in time. It is worthwhile to review existing evidence about SMBG to learn, transfer and apply knowledge about the core requirement for good diabetes management, glucose information. Fendler W, Hogendorf A, Szadkowska A, Młynarski W Department of Pediatrics, Oncology, Hematology and Diabetology, Medical University of Lodz, Poland Pediatr Endocrinol Diabetes Metab 2011; 17 : 57–63 Background: SMBG is one of the major components of diabetes management. Aims: To evaluate the potential for miscoding of a personal glucometer, to define a target population among paediatric patients with diabetes for a non-coding glucometer and to assess the accuracy of the Contour TS non-coding system. Methods: Potential for miscoding during SMBG was evaluated by means of an anonymous questionnaire, with worst and best case scenarios evaluated depending on the response pattern. Testing of the Contour TS system was performed according to the national committee for clinical laboratory standards guidelines. Results: The estimated frequency of individuals prone to non-coding ranged from 68.21% [95% confidence interval (CI) 60.70%–75.72%] to 7.95% (95% CI 3.86%–12.31%) for the worse and best case scenarios, respectively. Factors associated with increased likelihood of non-coding were a smaller number of tests per day, a greater number of individuals involved in testing and self-testing by the patient. The Contour TS device showed intra- and inter-assay accuracy of –95%, a linear association with laboratory measurements (R2 = 0.99, p < 0.0001) and small bias of –1.12% (95% CI –3.27% to 1.02%). Clarke error grid analysis showed 4% of values within the benign error zone (B) with the other measurements yielding an acceptably accurate result (zone A). Conclusions: The Contour TS system showed sufficient accuracy to be safely used in the monitoring of paediatric patients with diabetes. Patients from families with a high throughput of test-strips or multiple individuals involved in SMBG using the same meter are candidates for clinical use of such devices due to an increased risk of calibration errors. Comment: This study further highlights the role of making SMBG simpler and easier so that patients can monitor the glucose more effectively. The current study used the Contour TS system which does not require coding by the patient and thus removes the barrier of mis-coding of SMBG. We personally think that all meters going forward must be non-coding meters. Nerhus K 1 , Rustad P 2 , Sandberg S 1,3 1 Norwegian Centre for Quality Improvement of Primary Care Laboratories, Department of Public Health and Primary Health Care, University of Bergen, Bergen, Norway, 2 Norwegian Clinical Chemistry EQA-Program, Fürst Medical Laboratory, Oslo, Norway, 3 Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway Diabetes Technol Ther 2011; 13: 883–92 Background: Analytical quality of SMBG can be affected by environmental conditions. Aims: To determine the influence of a shift in the ambient temperature immediately before measurement and taking measurements in the lower and upper part of the operating temperature range. Methods: Different SMBG systems (n = 9) available on the Norwegian market were tested with heparinised venous blood (4.8 and 19.0 mmol/l). To test the effect of a shift in ambient temperature, the glucometer and strips were equilibrated for 1 h at 5 °C or 30 °C before the meter and strips were moved to room temperature, and measurements were performed after 0, 5, 10, 15 and 30 min. To test the lower and upper temperature range, measurements were performed at 10 °C and at 39 °C after 1 h for temperature equilibration of the glucometer and strips. All the measurements were compared with measurements performed simultaneously on a meter and strips kept the whole time at room temperature. Results: Six of nine SMBG systems overestimated and/or underestimated results by more than 5% after moving meters and strips from 5 °C or 30 °C to room temperature immediately before the measurements. Two systems underestimated the results at 10 °C. One system overestimated and another underestimated the results by more than 5% at 39 °C. Conclusions: A rapid shift in the ambient temperature affects analytical performance. Therefore patients need to wait at least 15 min for temperature equilibration of affected meters and strips before measuring blood glucose. Comment: This study highlights the importance of ambient temperature on analytical performance of SMBG. The study shows that rapid shift in ambient temperature may affect the accuracy and bias in SMBG measurement and highlights the need for 15 min temperature equilibration. In addition to what has been highlighted in the study, future studies also need to assess the accuracy of existing meters (especially the one using glucose oxidase) at higher altitudes (10,000 feet or higher). It is known that many of these meters do not perform well at high altitudes. McAndrew LM 1,2 , Horowitz CR 3 , Lancaster KJ 4 , Quigley KS 2,5,6 , Pogach LM 1,2 , Mora PA 7 , Leventhal H 8 1 War Related Illness and Injury Study Center and REAP Center for Healthcare Knowledge Management, Department of Veterans Affairs, New Jersey Health Care System, East Orange, NJ, USA, 2 University of Medicine and Dentistry of New Jersey, Newark, NJ, USA, 3 Department of Health Evidence and Policy, Mount Sinai School of Medicine,New York, NY, USA, 4 Department of Nutrition, Food Studies and Public Health, New York University, New York, NY, USA, 5 Department of Veterans Affairs, Edith Nourse Rogers Memorial VA Hospital, Bedford, MA, USA, 6 Department of Psychology, Northeastern University, Boston, MA, USA, 7 Psychology Department, University of Texas at Arlington, Arlington, TX, USA, and 8 Institute for Health, Health Care Policy and Research, Rutgers University, New Brunswick, NJ, USA J Diabetes 2011; 3 : 147–52; Comment in J Diabetes 2011; 3 : 93–4 Background: It is unknown whether SMBG can motivate adherence to dietary recommendations. Aims: To evaluate if patients who used more SMBG would also report lower fat and greater fruit and vegetable consumption. Methods: This was a cross-sectional study of primarily minority individuals living with diabetes in East Harlem, New York (n = 401). Fat intake and fruit and vegetable consumption were measured with the Block Fruit/Vegetable/Fiber and Fat Screeners. Results: Greater frequency of SMBG was associated with lower fat intake [r(s) = –0.15; p < 0.01], but not fruit and vegetable consumption. The effects of SMBG were not moderated by insulin use. A significant interaction was found between frequency of SMBG and changing one's diet in response to SMBG on total fat intake. Conclusions: The frequency of SMBG was associated with lower fat intake. The data suggest that participants who use SMBG to guide their diet do not have to monitor multiple times a day to benefit. Comment: This study further highlights the importance of SMBG in daily lifestyle changes. Subjects with higher frequency of SMBG consumed less fat, in part related to overall education and seeing the impact from making dietary changes on SMBG levels. Kuo CY 1,2 , Hsu CT 3 , Ho CS 3 , Su TE 3 , Wu MH 4 , Wang CJ 2,5 1 Department of Clinical Laboratory, Tai-An Hospital, Taichung, Taiwan, 2 Institute of Biochemistry and Biotechnology, Chung Shan Medical University, Taichung, Taiwan, 3 Department of Core Technical Research, Bionime Corporation, Taichung, Taiwan, 4 Department of Laboratory Medicine, Min-Sheng General Hospital, Taoyuan, Taiwan, 5 Department of Medical Research, Chung Shan Medical University Hospital, Taichung, Taiwan Diabetes Technol Ther 2011; 13 : 596–600 Background: SMBG systems should at least meet the minimal requirement of the World Health Organization's ISO 15197:2003. For tight glycaemic control, a tighter accuracy requirement is needed. Methods: Seven SMBG systems were evaluated for accuracy and precision: Bionime Rightest™ GM550 (Bionime Corp., Dali City, Taiwan), Accu-Chek® Performa (Roche Diagnostics, Indianapolis, IN, USA), OneTouch® Ultra®2 (LifeScan Inc., Milpitas, CA, USA), MediSense® Optium™ Xceed (Abbott Diabetes Care Inc., Alameda, CA, USA), Medisafe (TERUMO Corp., Tokyo, Japan), Fora® TD4227 (Taidac Technology Corp., Wugu Township, Taiwan) and Ascensia Contour® (Bayer HealthCare LLC, Mishawaka, IN, USA). The 107 participants were 23–91 years old. The analytical results of seven SMBG systems were compared with those of plasma analysed with the hexokinase method (Olympus AU640, Olympus America Inc., Center Valley, PA, USA). Results: The imprecision of the seven blood glucose meters ranged from 1.1% to 4.7%. Three of the seven blood glucose meters (42.9%) fulfilled the minimum accuracy criterion of ISO 15197:2003. The mean absolute relative error value for each blood glucose meter was calculated and ranged from 6.5% to 12.0%. Conclusions: More than 40% of evaluated SMBG systems meet the minimal accuracy criterion requirement of ISO 15197:2003. However, considering a tighter criterion for accuracy of ±15%, only the Bionime Rightest GM550 meets this requirement. Manufacturers have to try to improve accuracy and precision and to ensure the good quality of blood glucose meters and test strips. Comment: This study further highlights the need for more accurate SMBG systems. Their data concluded that more than 40% of the evaluated SMBG systems meet the minimum ISO criteria. Since patients use blood glucose information for adjusting their insulin dose and/or treating hypoglycaemia, the accuracy of the glucose meters has to be consistent and improved. Hortensius J 1 , Slingerland RJ 2 , Kleefstra N 1,3,4 , Logtenberg SJ 1 , Groenier KH 5 , Houweling ST 3,6 , Bilo HJ 1,4 1 Diabetes Centre, Isala Clinics, Zwolle, The Netherlands, 2 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 3 Medical Research Group, Langerhans, The Netherlands, 4 Department of Internal Medicine, University Medical Center, Groningen, The Netherlands, 5 Department of General Practice, University of Groningen, Groningen, The Netherlands, and 6 General Practice Sleeuwijk, Sleeuwijk, The Netherlands Diabetes Care 2011; 34 : 556–60 Background: There is no agreement regarding the use of the first or second drop of blood for glucose monitoring. Aims: To investigate whether capillary glucose concentrations, as measured in the first and second drops of blood, differed ≥10% compared with a control glucose concentration in different situations. Methods: Capillary glucose concentrations were measured in two consecutive drops of blood in 123 patients with diabetes in the following circumstances: without washing hands, after exposing the hands to fruit, after washing the fruit-exposed hands, and during application of different amounts of external pressure around the finger. The results were compared with control measurements. Results: Not washing hands led to a difference of ≥10% in glucose concentration in the first and in the second drops of blood in 11% and 4% of the participants, respectively. In fruit exposed fingers, these differences were found in 88% and 11% of the participants, respectively. Different external pressures led to ≥10% differences in glucose concentrations in 5%–13% of the participants. Conclusions: Washing hands with soap and water, drying them, and using the first drop of blood for SMBG is recommended. If washing hands is not possible, it is acceptable to use the second drop of blood after wiping away the first drop. External pressure may lead to unreliable readings. Comment: Over the years we have probably under-emphasised the importance of technique with SMBG. One has to wonder how much iatrogenic hypoglycaemia has occurred due to unintended exposure to glucose on the hands, and how often CGM devices are due to technique with SMBG use. 1,2 , 3 , 4 , 5 , 6 , 7 , 8 , 8 , 8 1 University of CA, USA, 2 Diabetes CA, USA, 3 University of CA, USA, 4 University Health System, USA, 5 America Diabetes USA, 6 Health IN, USA, 7 USA, and 8 Diagnostics, Indianapolis, IN, USA Diabetes Care 2011; 34 : To assess the effectiveness of structured blood glucose testing in controlled patients with type 2 diabetes without insulin Methods: A study patients with type 2 diabetes (n = and glycaemic control from 34 care in the were randomised to an control with care or a structured testing with care and at least use of structured SMBG. patients and were to use a to glucose consecutive The was measured at Results: The analysis = = showed greater in mean in the compared with the = p = analysis = = showed even greater mean in the compared with the p < more patients a at the first compared with patients, of the p < and patients significant < 0.0001) in Conclusions: use of structured SMBG glycaemic control and more changes in patients with type 2 diabetes without Comment: It is with an healthcare using a structured glucose testing can improve glucose control in non-insulin-treated Potential are of this can be in a with the more time in a care to be , 5 , 6 , 1,4 1 Department of and Laboratory Medicine, University of 2 Department of and University of 3 Department of Pediatrics, University of 4 Laboratory 5 Corporation, MA, USA, and 6 Department of Health University of J Diabetes Technol 4 : Aims: To analytical error in and glucose meters by in and Methods: The of and were tested and in with each glucose meter and with a plasma glucose method at glucose was by consecutive analysis (n = at glucose levels. analysis was used to the bias associated with the and in Results: Three meters demonstrated bias that was glucose bias on the and the of bias was on small significant on meters. of and of increased the bias and was by of total analytical the glucose meter devices of total analytical error in glucose measurement ranged from to the Conclusions: The of glucose meters to significant analytical is the analytical Comment: with to for SMBG and the research is it does not that many people the This has impact on as new guidelines for greater of are the impact on SMBG accuracy be particularly by the device should be a 1 , 1 , 2 , 3 1 Health and 2 Health, and 3 of and Department of Internal Medicine, : Aims: To evaluate the of SMBG in patients with type 2 diabetes with in Methods: In a study a of diabetes was used to from a published study of SMBG in patients with type 2 diabetes, with and with no of a time was from the of a healthcare and clinical were at Results: or times daily SMBG was associated with in which led to increased and and of diabetes complications compared with no SMBG in type 2 diabetes patients on costs increased by and in patients SMBG or times daily compared with those not using SMBG. were well at and per year respectively. Conclusions: SMBG is to be by standards in patients on in the Comment: This analysis is on a showing of and The concern of is that this analysis is not a randomised controlled and at best the data are about the efficacy of this population using this analysis is probably on controversial 1,2 , 3 , S 3 , 1 Health Research, University School of Medicine, Indianapolis, IN, USA, 2 Institute for Health Care, Indianapolis, IN, USA, 3 of University School of Medicine, Indianapolis, IN, USA, and 4 Diabetes and Center, University School of Medicine, Indianapolis, IN, USA Diabetes 2011; : To assess the and of a glucose monitoring system for with type 1 diabetes and their Methods: Patients with type 1 diabetes who been for at least 1 year in the used the system for 6 3 to and with the glucose monitoring as well as how use of the system affect quality of and diabetes management. Results: about the a number of significant that affected use of the all that the in monitoring testing was The use of the did not the quality of their of with their their of diabetes, or their glycaemic control within the time of the Conclusions: This that glucose monitoring can be used in an population to and in self-monitoring Comment: for both SMBG and CGM is clearly the future for with type 1 diabetes. The will be to how to best use this to improve in this To the is new to how best to use more studies will be to this P 1 , 2 , ST 3 , 2 , 2 , 4 , Bilo 5 , Bilo HJ 1 Department of Internal Medicine, Hospital, The Netherlands, 2 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 3 Department of Isala Clinics, Zwolle, The Netherlands, 4 Centre for The Netherlands, 5 Department of Internal Medicine, Isala Clinics, Zwolle, The Netherlands, and 6 Department of Internal Medicine, University Medical Centre, Groningen, The Netherlands One 5 : Background: Patients with diabetes part in and thus blood glucose meters are studies bias in blood glucose measurements using different at high To evaluate if glucose are more by the lower pressure at than glucose Methods: measurements at of nine glucose glucose were compared with glucose measurement on a at and with a laboratory glucose blood of different glucose were were at a bias from glucose and from glucose mmol/l). Results: significant difference was between measurements at and for glucose or glucose as a Two glucose did not meet performance criteria. Conclusions: high all tested glucose did not influence of All for two glucose performed within criteria. are glucose concentration at high high one glucose best precision and Comment: testing for SMBG meters may be In glucose test strips should be at high altitudes. not in this it should be that patients do not this into when or 1 , J 2 , 2 , 1 , 3 , 4 , J 3 , 5 , J 6 , 7 , 7 , 8 1 Department of Health University of Health Center, USA, 2 and Health Department of Medical and University of USA, 3 Department of and Health University of USA, 4 Diabetes Care Center, Medical USA, 5 Department of University of USA, 6 Medicine Technology Center USA, 7 Department of Medicine, University of USA, and 8 Health Research USA J Aims: To assess the and of using as part of an existing system for between patients with diabetes and a care Methods: In glucose meter and two to feedback on glycaemic control were Results: glucose meter with and data feedback were the system to an and feedback system for value in the system as an to the and Conclusions: diabetes management systems may one to improve the quality of diabetes Comment: best to in a care for type 2 diabetes is still It is that there will be different of that will for different patient the use of the as a means of that device like the of in diabetes management. the now seems to be how to is a It may be that will be the only for many the of time this population 1 , 2 1 Centre for Policy Research, of Health Health Policy and Research, University of and 2 Institute for Medicine, and Health University Medical Centre 2011; : Background: the of and in Patients with 2 Diabetes a in the risk of in patients with type 2 diabetes who performed SMBG. Aims: To evaluate if these are by a that time Methods: The bias in the study was and demonstrated that it is to the effect of SMBG on Results: In the study, patients were as exposed to SMBG for their whole time if performed SMBG for at least 1 year during the study the time between and the after 1 year of self-monitoring was performed is for patients with SMBG. Patients to at least 1 year to be as exposed to this and were from The total of in the SMBG is at least of at risk After of as the relative risk from to Conclusions: The effect of SMBG on in the study is by time Comment: The study is one of the trials in the of SMBG. Study is probably a major for between the studies. Kleefstra N 1,2 , Hortensius J 1 , Logtenberg SJ 1 , 3 , Groenier K 4 , Houweling ST 2,5 , 6 , 2 , Bilo HJ 1 Diabetes Centre, Isala Clinics, Zwolle, The Netherlands, 2 Medical Research Langerhans, Zwolle, The Netherlands, 3 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 4 Department of General Practice, University of Groningen, Groningen, The Netherlands, 5 General Practice Sleeuwijk, Sleeuwijk, The Netherlands, 6 Department of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands J : Background: It is not if SMBG glycaemic control in patients with type 2 diabetes. To investigate the effects of SMBG in patients with type 2 diabetes who were in glycaemic Methods: Patients years with an of using one to two blood glucose were in the Patients (n = were to receive SMBG to care or to with care for 1 A glucose value and glucose values were measured The efficacy was quality of and were using the Health the the Diabetes and the Results: in between was (95% CI to p = There were no significant changes between on the type or for the which was lower in the difference (95% CI to Conclusions: type 2 diabetes patients some of their the use of SMBG in these patients is and its use should be Comment: This is another SMBG study in non-insulin-treated type 2 the of not patients what to do with the information is one has to wonder if this at some to have some of the it is to that the in care is to more education and time than is in many of these studies. A 1 , 1 , 1 , S 2 , S 3 , A 1 , A 1 , 1 , 4 , 3 , 3 , 1 1 Department of and School of Medicine, 2 Department of School of Medicine, 3 Department of Biochemistry, School of Medicine, and 4 Department of School of Medicine, Diabetes Technol Ther : Background: glucose meters may not be accurate to Aims: of the accuracy and the capillary and venous of different Xceed (Abbott Diabetes Care, Alameda, CA, USA), Contour TS (Bayer Diabetes Care, (Roche Milpitas, CA, and Inc., in an Methods: The insulin hypoglycaemia test was performed for of mean age was measured from venous blood and capillary before and after of insulin were analysed in the laboratory by the hexokinase In tests for method and precision were also performed by the venous Results: All to hypoglycaemia to some was in error zone and was in the error zone Xceed and Contour TS and were than the other two according to error grid analysis or International for criteria. The in tests were consistent with the clinical The capillary and venous of and were than the other Not all are accurate in blood glucose levels. The patients and the should be of these of the and give more to the hypoglycaemia than the values with the These results that there is a need for the of accuracy standards of at blood glucose levels. Comment: We have the that meters are from especially at levels. patients can state a time when an The are not only for the of hypoglycaemia but also as we forward with CGM about how this about this the with the for use of the meters our clinical with patient error us that accuracy a for glucose meters at levels. has research from Inc., Corporation, Inc., and is a for Diagnostics, Diabetes Care and

Blood Glucose Monitoring: Necessary and Sufficient?

Blood glucose monitoring is an important part and means in the process of diabetes treatment and management. There is a high correlation between glucose concentration in interstitial fluid and glucose concentration in blood. Real-time monitoring of glucose concentration in interstitial fluid has important clinical significance. Continuous glucose monitoring (CGM) is an emerging glucose monitoring technology, which indirectly reflects the blood glucose level of the body through the glucose level in the interstitial fluid, providing continuous and comprehensive information and rules of blood glucose variation over a period of time. There are three main categories of CGM: minimally invasive implantation, non-invasive microtransparency and non-invasive technology. Noninvasive blood glucose monitoring technology is the future development direction, but accuracy and delay of blood glucose will be the biggest challenge to be overcome in clinical application. Key words: Blood glucose monitoring; Continuous glucose monitoring; Noninvasive glucose monitoring

The objective of this feasibility study was to test an optical coherence tomography (OCT)-based system for noninvasive, accurate, and continuous monitoring of blood (as opposed to interstitial) glucose concentration in subjects with diabetes. OCT uses low coherence light with precise depth focusing ability to measure changes in the microvasculature structure for glucose detection. Thirty-three subjects with diabetes had blood glucose concentrations evaluated using simultaneous capillary and OCT-based device (Sentris-100, GlucoLight, Bethlehem, PA) measurements. Subjects received a 50-g carbohydrate load at the start of the study period. Two glucose values with 60 mg separation were used to calibrate the OCT system. Six subjects were excluded (two because of hardware and/or software failures at study initiation, two because of sensor connection problems, and two others because of problems with disposable device positioning on the skin). Of the 27 subjects who completed the study, 12 had type 1 diabetes, and 15 had type 2 diabetes. Statistical analysis included plotting of the Clarke error grid, comparison to International Organization for Standardization (ISO) standards for glucose monitoring systems, and calculation of the Pearson correlation coefficient. Based on a total of 236 matched points, Clarke error grid analysis indicated 83% in zone A, 16% in zone B, and <1% in zones C and D. ISO standards comparison showed 83% of OCT estimates were within 20% of the reference value for blood glucoses >75 mg/dL. No conclusions can be made about blood glucose estimates in the <75 mg/dL range since no low reference values occurred. The Pearson correlation coefficient comparing OCT versus capillary blood glucose was 0.85 (95% confidence interval 0.81-0.88, P < 0.0001). Mean relative absolute deviation was 11.5%, and median relative absolute deviation was 8.2%. This study demonstrated that the OCT system shows acceptable accuracy in the prediction of blood glucose levels in subjects with both type 1 and type 2 diabetes. Future efforts will evaluate the accuracy of the system in the hypoglycemic range.

The accuracy of glucose test strip in critically care has been questioned. We investigated the accuracy of glucose test strip in critically ill children. Patients, aged from 1 month to 18 years admitted in pediatric intensive care unit. Demographic data, hemodynamic parameters, and perfusion index (PI) were recorded. Glucose test strips were performed from finger stick blood [capillary blood glucose (CBG)] and from whole blood [whole blood glucose (WBG)] along with laboratory plasma blood glucose (PBG) from either arterial or venous blood samples. The accuracy of glucose test strips was defined according to ISO 15197 and Clarke error grid (CEG). One hundred and eighty one blood samplings including 117 arterial blood (CBG, WBGa, PBGa) and 64 venous blood (CBG, WBGv, PBGv) were obtained. The accuracy of WBGa was 98.3 and 95.2% when compared to the accuracy of CBG (88.7 and 83.3%. The accuracy of WBGv was 92.2% and 87.0 when compared to the accuracy of CBG which was 79.7 and 72.9% (ISO 15197: 2003 and 2013, respectively). Bland-Altman plot demonstrated bias and precision of 7.4±17.7 mg/dL in acceptable PI group compared to 30.2±23.4 mg/dL in low PI group (PI≤0.3). The CBG test strip must be interpreted carefully in critically ill children. A low PI was associated with poor CBG strip accuracy. WBG test strip from arterial blood was more appropriate for glucose monitoring in children with peripheral hypoperfusion.

Objective: Since the introduction of continuous glucose monitoring (CGM) technology, developers have rigorously researched the feasibility of creating a noninvasive glucose monitoring device. In a recent pilot study, investigators reported a strong correlation between glucose values obtained from novel noninvasive monitoring device (GWave) values to venous and capillary glucose measurements. Research Design and Methods: We investigated whether the level of accuracy observed in the pilot study could be reproduced in a larger cohort, using a smaller third-generation manufacturable device (Gen III GWave) containing a standardized sensor chip that can be mass produced for commercial use. The evaluation assessed concordance with capillary blood glucose, reproducibility between two Gen III devices, and accuracy during insulin-induced hypoglycemia. Results: Assessment of samples from 75 subjects (type 2 diabetes, n = 6; type 1 diabetes, n = 28; nondiabetic pregnant subjects, n = 10; and nondiabetic, n = 31) showed that 97% of values were in Zone A with 3% in Zone B of the Clarke Error Grid, with a mean absolute relative difference of 6.7% from reference blood glucose. Comparison between two independent Gen III GWave devices demonstrated reproducibility between the sensors (R2 = 0.95), with 100% of values within Zone A. In the hypoglycemia assessment, measurements from the Gen III sensor tightly followed the capillary glucose measurements down to 42 mg/dL (2.3 mmol/L), whereas the CGM measurements from two different CGM only converged with the GWave and capillary glucose readings after 90 min of decreasing glucose levels. Conclusion: Our results show promise as potentially the first noninvasive technology. Future studies will focus on larger number of people in all glucose ranges. Real-time noninvasive blood glucose monitoring is possible using GWave technology.

Non-communicable diseases, such as diabetes, are the leading cause of mortality worldwide. Effective diabetes management is crucial for ensuring the well-being of diabetics. Existing glucose monitoring technologies are often invasive and uncomfortable, eliciting anxiety among patients. Non-invasive procedures offer a promising solution for these issues, but their widespread adoption is restricted by cost and accuracy constraints. This study investigates the use of green light Photoplethysmography (PPG) signals for non-invasive blood glucose monitoring. A custom-designed PPG acquisition setup was developed to collect PPG data from 80 subjects under controlled conditions. Simultaneously, reference capillary blood glucose readings were obtained using a lancing device to serve as the gold standard. Signals were enhanced by applying different processing techniques and 32 features were extracted, which were scaled and subjected to correlation analysis to retain the highly correlated features. Feature engineering further optimized the feature set, which was then used to train and validate regression models. Model performance was evaluated using R2 (coefficient of determination), mean absolute error (MAE), and bias analysis across glucose ranges. Among the tested models, the Random Forest Regression (RFR) showed the best performance with an R2 value of 0.92 and MAE of 4.8 mg/dL. Predicted glucose levels demonstrated minimal bias across glucose ranges, with mean differences of -5.11 ± 0.80 mg/dL (<90 mg/dL), -3.68 ± 1.24 mg/dL (90-120 mg/dL), and -5.61 ± 0.75 mg/dL (≥120 mg/dL). The findings demonstrate that PPG signals in the green light spectrum effectively reflect blood glucose levels, supporting their potential for non-invasive glucose monitoring.

Frequent blood glucose level (BGL) monitoring is essential for effective diabetes management. Poor compliance is common due to the painful finger pricking or subcutaneous lancet implantation required from existing technologies. There are currently no commercially available non-invasive devices that can effectively measure BGL. In this real-world study, a prototype non-invasive continuous glucose monitoring system (NI-CGM) developed as a wearable ring was used to collect bioimpedance data. The aim was to develop a mathematical model that could use these bioimpedance data to estimate BGL in real time. The prototype NI-CGM was worn by 14 adult participants with type 2 diabetes for 14 days in an observational clinical study. Bioimpedance data were collected alongside paired BGL measurements taken with a Food and Drug Administration (FDA)-approved self-monitoring blood glucose (SMBG) meter and an FDA-approved CGM. The SMBG meter data were used to improve CGM accuracy, and CGM data to develop the mathematical model. A gradient boosted model was developed using a randomized 80-20 training-test split of data. The estimated BGL from the model had a Mean Absolute Relative Difference (MARD) of 17.9%, with the Parkes error grid (PEG) analysis showing 99% of values in clinically acceptable zones A and B. This study demonstrated the reliability of the prototype NI-CGM at collecting bioimpedance data in a real-world scenario. These data were used to train a model that could successfully estimate BGL with a promising MARD and clinically relevant PEG result. These results will enable continued development of the prototype NI-CGM as a wearable ring.

The influence of glucose self-monitoring on glycaemic control in patients with diabetes mellitus in Sudan

Approaches for measuring blood glucose levels using noninvasive techniques also known as non-invasive glucose monitoring and minimally-invasive glucose monitoring techniques can help support easier and more frequent measurement of blood glucose levels and also lend themselves to support continuous glucose monitoring. This paper focuses on reviewing the emerging technologies for such monitoring, and their interrelationship with data analytics. The paper describes how these two areas of development together are contributing to the field of diabetes informatics, a more data-rich approach to understanding and managing diabetes.

Enteral nutrition (EN) support therapy increases the risk of abnormal blood glucose (BG). The aim of this study is to evaluate the clinical value of a real-time continuous glucose monitoring (rt-CGM) system in BG monitoring during postoperative EN support therapy in patients with esophageal cancer. Patients without diabetes mellitus (DM) with esophageal cancer who planned to receive postoperative EN were enrolled. With the self-monitoring of BG value as the reference BG, the accuracy of rt-CGM was evaluated by the mean absolute relative difference (MARD) value, correlation efficient, agreement analysis, and Parkes and Clarke error grid plot. Finally, paired t tests were used to compare the differences in glucose fluctuations between EN and non-EN days and slow and fast days. The total MARD value of the rt-CGM system was 13.53%. There was a high correlation between interstitial glucose and fingertip capillary BG (consistency correlation efficient = 0.884 [95% confidence interval, 0.874-0.894]). Results of 15/15%, 20/20%, 30/30% agreement analysis were 58.51%, 84.71%, and 99.65%, respectively. The Parkes and Clarke error grid showed that the proportion of the A and B regions were 100% and 99.94%, respectively. The glucose fluctuations on EN days vs non-EN days and on fast days vs slow days were large, and the difference was statistically significant (P < 0.001). The rt-CGM system achieved clinical accuracy and can be used as a new option for glucose monitoring during postoperative EN therapy. The magnitude of glucose fluctuation during EN therapy remains large, even in the postoperative population without DM.

This study investigates a noninvasive continuous glucose monitoring (NI-CGM) system optimized for earlobe application, leveraging the site's anatomical advantages-absence of bone, muscle, and thick skin-for enhanced optical transmission. The system integrates multimodal sensing, combining near-infrared (NIR) diffuse transmission with temperature and pressure sensors. A novel Multi-Wavelength Slope Efficiency Near-Infrared Spectroscopy (MW-SE-NIRS) method is introduced, enhancing noise robustness through the slope efficiency-based parameterization of NIR signal dynamics. By employing three NIR wavelengths with distinct scattering and absorption properties, the method improves glucose detection reliability, addressing tissue heterogeneity and physiological noise in noninvasive monitoring. To validate the feasibility, a pilot clinical trial enrolled five participants with normal or pre-diabetic glucose profiles. Continuous glucose data capturing pre- and postprandial variations were analyzed using a 1D convolutional neural network (Conv1D). For three subjects under stable physiological conditions, the model achieved 97.0% Clarke error grid (CEG) A-Zone accuracy and a mean absolute relative difference (MARD) of 5.2%. Across all participants, results showed 90.9% CEG A-Zone accuracy and a MARD of 8.4%, with performance variations linked to individual factors such as earlobe thickness variability and physical activity. These outcomes demonstrate the potential of the MW-SE-NIRS system for noninvasive glucose monitoring and highlight the importance of future work on personalized modeling, sensor optimization, and larger-scale clinical validation.

A review of non-invasive blood glucose monitoring through breath acetone and body surface

Diagnostic performance of 2 h postprandial capillary and venous glucose as a screening test for abnormal glucose tolerance

Aims/IntroductionA flash glucose monitoring (FGM) system has become available. To clarify the relationship between FGM and self‐monitoring blood glucose (SMBG) values, we compared the two values after simultaneous measurement in Japanese patients with type 1 diabetes, under daily life settings.Materials and MethodsA total of 20 outpatients with type 1 diabetes were analyzed. When FGM and SMBG were carried out simultaneously (within ±3 min), the values were adopted and each FGM value was matched and compared with the corresponding SMBG value. In addition, we analyzed other cases of simultaneity defined as “within ±2 min,” “within ±1 min” and “at the exact same time.”ResultsThe percentage of SMBG and FGM values in the clinically acceptable zone A + B in Clarke and consensus error grid analyses were 97.9 and 99.2%, respectively. Deming regression (x‐axis: FGM values, y‐axis: SMBG values) determined a slope of 0.9128 (95% confidence interval 0.9008–0.9247) and an intercept of +15.94 mg/dL (95% confidence interval 14.05–17.84). FGM values were lower than SMBG values in the lower glucose range, and higher in the higher glucose range. The shorter the time lag between measurements, the higher the rate of concordance between FGM and SMBG values.ConclusionsThe results of this study provided evidence on the reliability of FGM in Japanese patients with type 1 diabetes in home conditions. Based on the results, if an abnormal glucose value is detected by FGM, SBMG should then be used to confirm the result.