Glycemic variability in nondiabetic morbidly obese persons: results of an observational study and review of the literature

Glycemic variability (GV) is correlated with oxidative stress which may lead to increased cardiovascular risk and poor clinical outcomes in people with prediabetes and diabetes. We sought to understand whether morbidly obese persons without diabetes by standard criteria have dysglycemia as measured by GV. We performed an observational study of GV metrics and carotid intima media thickness (CIMT) in 21 morbidly obese normoglycemic and 15 morbidly obese prediabetic applicants to The Biggest Loser television show. The results were compared to previously published studies in normoglycemic nonobese and obese individuals. Glucose was measured with a masked continuous glucose monitor (CGM) over 3 to 8 days and carotid intima media thickness (CIMT) was determined by ultrasound. CGM-derived GV metrics for GV were coefficient of variation (CV), standard deviation (SD), mean amplitude of glycemic excursions (MAGE), continuous overall net glycemic action-1 hour (CONGA1), and mean of daily differences (MODD). We found that morbidly obese subjects (n = 21) who were normoglycemic by standard criteria had higher GV (CV = 22%, SD = 24.2 mg/dl and MAGE = 48.6 mg/dl) than previous reports of normoglycemic, nonobese individuals (CV = 12-18%, SD = 11.5-15.0 mg/dl, and MAGE = 26.3-28.3 mg/dl). Morbidly obese prediabetic subjects (n = 15) had GV metrics indistinguishable from those morbidly obese subjects who were normoglycemic. CIMT was higher in both morbidly obese groups compared with historical age- and sex-matched controls. Normoglycemic and prediabetic morbidly obese individuals have higher GV compared with normal weight, nondiabetic individuals. We speculate that this may increase the risk for macrovascular disease through excessive oxidative stress.

Continuous glucose control in the ICU: report of a 2013 round table meeting

Achieving adequate glucose control in critically ill patients is a complex but important part of optimal patient management. Until relatively recently, intermittent measurements of blood glucose have been the only means of monitoring blood glucose levels. With growing interest in the possible beneficial effects of continuous over intermittent monitoring and the development of several continuous glucose monitoring (CGM) systems, a round table conference was convened to discuss and, where possible, reach consensus on the various aspects related to glucose monitoring and management using these systems. In this report, we discuss the advantages and limitations of the different types of devices available, the potential advantages of continuous over intermittent testing, the relative importance of trend and point accuracy, the standards necessary for reporting results in clinical trials and for recognition by official bodies, and the changes that may be needed in current glucose management protocols as a result of a move towards increased use of CGM. We close with a list of the research priorities in this field, which will be necessary if CGM is to become a routine part of daily practice in the management of critically ill patients.

Barriers and potential solutions to providing optimal guideline-driven care to patients with diabetes in the U.S

The cost of diabetes, driven primarily by the cost of preventable diabetes complications, will continue to increase with the epidemic rise in its prevalence in the U.S. The Diabetes Working Group (DWG), a consortium of professional organizations and individuals, was created to examine the barriers to better diabetes care and to recommend mitigating solutions. We consolidated three sets of guidelines promulgated by national professional organizations into 29 standards of optimal care and empanelled independent groups of diabetes care professionals to estimate the minimum and maximum time needed to achieve those standards of care for each of six clinical vignettes representing typical patients seen by diabetes care providers. We used a standards-of-care economic model to compare provider costs with reimbursement and calculated "reimbursement gaps." The reimbursement gap was calculated using the maximum and minimum provider cost estimate (reflecting the baseline- and best-case provider time estimates from the panels). The cost of guideline-driven care greatly exceeded reimbursement in almost all vignettes, resulting in estimated provider "losses" of 470,000-750,000 USD/year depending on the case mix. Such "losses" dissuade providers of diabetes care from using best practices as recommended by national diabetes organizations. The DWG recommendations include enhancements in care management, workforce supply, and payment reform.

Pathways to quality inpatient management of hyperglycemia and diabetes: a call to action

Currently patients with diabetes comprise up to 25-30% of the census of adult wards and critical care units in our hospitals. Although evidence suggests that avoidance of hyperglycemia (>180 mg/dL) and hypoglycemia (<70 mg/dL) is beneficial for positive outcomes in the hospitalized patient, much of this evidence remains controversial and at times somewhat contradictory. We have recently formed a consortium for Planning Research in Inpatient Diabetes (PRIDE) with the goal of promoting clinical research in the area of management of hyperglycemia and diabetes in the hospital. In this article, we outline eight aspects of inpatient glucose management in which randomized clinical trials are needed. We refer to four as system-based issues and four as patient-based issues. We urge further progress in the science of inpatient diabetes management. We hope this call to action is supported by the American Diabetes Association, The Endocrine Society, the American Association of Clinical Endocrinologists, the American Heart Association, the European Association for the Study of Diabetes, the International Diabetes Federation, and the Society of Hospital Medicine. Appropriate federal research funding in this area will help ensure high-quality investigations, the results of which will advance the field. Future clinical trials will allow practitioners to develop optimal approaches for the management of hyperglycemia in the hospitalized patient and lessen the economic and human burden of poor glycemic control and its associated complications and comorbidities in the inpatient setting.

Heterogeneity of responses to real-time continuous glucose monitoring (RT-CGM) in patients with type 2 diabetes and its implications for application

OBJECTIVE

To characterize glucose response patterns of people who wore a real-time continuous glucose monitor (RT-CGM) as an intervention to improve glycemic control. Participants had type 2 diabetes, were not taking prandial insulin, and interpreted the RT-CGM data independently.

RESEARCH DESIGN AND METHODS

Data were from the first 12 weeks of a 52-week, prospective, randomized trial comparing RT-CGM (n = 50) with self-monitoring of blood glucose (n = 50). RT-CGM was used in 8 of the first 12 weeks. A1C was collected at baseline and quarterly. This analysis included 45 participants who wore the RT-CGM ≥4 weeks. Analyses examined the RT-CGM data for common response patterns-a novel approach in this area of research. It then used multilevel models for longitudinal data, regression, and nonparametric methods to compare the patterns of A1C, mean glucose, glycemic variability, and views per day of the RT-CGM device.

RESULTS

There were five patterns. For four patterns, mean glucose was lower than expected as of the first RT-CGM cycle of use given participants' baseline A1C. We named them favorable response but with high and variable glucose (n = 7); tight control (n = 14); worsening glycemia (n = 6); and incremental improvement (n = 11). The fifth was no response (n = 7). A1C, mean glucose, glycemic variability, and views per day differed across patterns at baseline and longitudinally.

CONCLUSIONS

The patterns identified suggest that targeting people with higher starting A1Cs, using it short-term (e.g., 2 weeks), and monitoring for worsening glycemia that might be the result of burnout may be the best approach to using RT-CGM in people with type 2 diabetes not taking prandial insulin.

Minding the gaps in continuous glucose monitoring: a method to repair gaps to achieve more accurate glucometrics

Estimation of glycemic variability requires frequent measures of glucose and is greatly aided by continuous glucose monitoring (CGM); however, under real-world conditions, missing data or "gaps" of ≥ 10 minutes can occur in CGM data, affecting the reliability of certain estimates. Thus, we determined the magnitude of the gap problem as observed in a cohort of patients with type 2 diabetes and demonstrated an approach to fill the gaps. The approach takes the difference between readings before and after a gap and distributes the difference equally across the number of missing readings, as determined by the sensor's setting for reading frequency. The approach is easy to implement, conservative, and improves estimation of variability measures that reference time, namely, mean of daily differences and continuous overlapping net glycemic action.

A review and critical analysis of professional societies' guidelines for pharmacologic management of type 2 diabetes mellitus

The development of clinical practice guidelines (CPGs), which are promulgated by various sponsoring organizations to provide direction to clinicians for management of complex problems, generally adhere to a set of key principles. To reassure the users of their scientific and ethical validity, these include the use of a system to rate the quality of evidence on which the guideline is based and the divulgence of any conflicts of interest (COI) among members of the panel developing the guidelines. I analyzed the CPGs for pharmacologic management of patients with type 2 diabetes written by the two US professional societies that developed such guidelines (American Association of Clinical Endocrinologists [AACE] and the American Diabetes Association/European Association for the Study of Diabetes [ADA/EASD]) to assess their adherence to these principles of guideline development and to compare them with regard to simplicity, consideration of costs, and peer review status. To put the existence of COIs in these guidelines into context, I also reviewed the COIs from government-sponsored panels that developed diabetes CPGs. The results of this analysis suggest that both the AACE and ADA/EASD guidelines should be regarded as consensus documents rather than true CPGs, since neither guideline employed evidence grading. COI was extremely common among the members of both CPG panels from professional organizations, as well in the CPG panels with government sponsorship. In addition, the nature and extent of external peer review of these guidelines is unclear. Given these limitations, the AACE and ADA/EASD CPGs for diabetes management should be regarded as advisory at best, rather than prescriptive or authoritative, especially in view of their noncompliance with key principles of guideline development.

Predicting human subcutaneous glucose concentration in real time: a universal data-driven approach

Continuous glucose monitoring (CGM) devices measure and record a patient's subcutaneous glucose concentration as frequently as every minute for up to several days. When coupled with data-driven mathematical models, CGM data can be used for short-term prediction of glucose concentrations in diabetic patients. In this study, we present a real-time implementation of a previously developed offline data-driven algorithm. The implementation consists of a Kalman filter for real-time filtering of CGM data and a data-driven autoregressive model for prediction. Results based on CGM data from 3 different studies involving 34 type 1 and 2 diabetic patients suggest that the proposed real-time approach can yield ~10-min-ahead predictions with clinically acceptable accuracy and, hence, could be useful as a tool for warning against impending glucose deregulation episodes. The results further support the feasibility of "universal" glucose prediction models, where an offline-developed model based on one individual's data can be used to predict the glucose levels of any other individual in real time.

Mobile phone-based video messages for diabetes self-care support

BACKGROUND

This study examined whether mobile phone-based, one-way video messages about diabetes self-care improve hemoglobin A1c (A1C) and self-monitoring of blood glucose (SMBG).

METHODS

This was a 1-year prospective randomized trial with two groups. The active intervention lasted 6 months. The study enrolled 65 people with A1C >8.0% who were established (>6 months) patients in the endocrinology clinics of the Walter Reed Health Care System. Participants were randomized to receive "usual care" or self-care video messages from their diabetes nurse practitioner. Video messages were sent daily to cell phones of study participants. Hemoglobin A1c and SMBG data were collected at 0, 3, 6, 9, and 12 months.

RESULTS

Participants who received the messages had a larger rate of decline in A1C than people who received usual care (0.2% difference over 12 months, adjusting for covariates; p = .002 and p = .004 for the interaction between time and group and for the quadratic effect of time by group, respectively). Hemoglobin A1c decline was greatest among participants who received video messages and viewed >10 a month (0.6% difference over 12 months, adjusting for covariates; p < .001 for the interaction between time and group and the quadratic effect). Self-monitoring of blood glucose metrics were not related to the intervention.

CONCLUSIONS

A one-way intervention using mobile phone-based video messages about diabetes self-care can improve A1C. Engagement with the technology is an important predictor of its success. This intervention is simple to implement and sustain.

New Criteria for Assessing the Accuracy of Blood Glucose Monitors meeting, October 28, 2011

Glucose meters (GMs) are routinely used for self-monitoring of blood glucose by patients and for point-of-care glucose monitoring by health care providers in outpatient and inpatient settings. Although widely assumed to be accurate, numerous reports of inaccuracies with resulting morbidity and mortality have been noted. Insulin dosing errors based on inaccurate GMs are most critical. On October 28, 2011, the Diabetes Technology Society invited 45 diabetes technology clinicians who were attending the 2011 Diabetes Technology Meeting to participate in a closed-door meeting entitled New Criteria for Assessing the Accuracy of Blood Glucose Monitors. This report reflects the opinions of most of the attendees of that meeting. The Food and Drug Administration (FDA), the public, and several medical societies are currently in dialogue to establish a new standard for GM accuracy. This update to the FDA standard is driven by improved meter accuracy, technological advances (pumps, bolus calculators, continuous glucose monitors, and insulin pens), reports of hospital and outpatient deaths, consumer complaints about inaccuracy, and research studies showing that several approved GMs failed to meet FDA or International Organization for Standardization standards in postapproval testing. These circumstances mandate a set of new GM standards that appropriately match the GMs' analytical accuracy to the clinical accuracy required for their intended use, as well as ensuring their ongoing accuracy following approval. The attendees of the New Criteria for Assessing the Accuracy of Blood Glucose Monitors meeting proposed a graduated standard and other methods to improve GM performance, which are discussed in this meeting report.

Short- and long-term effects of real-time continuous glucose monitoring in patients with type 2 diabetes

OBJECTIVE

To determine whether short-time, real-time continuous glucose monitoring (RT-CGM) has long-term salutary glycemic effects in patients with type 2 diabetes who are not on prandial insulin.

RESEARCH DESIGN AND METHODS

This was a randomized controlled trial of 100 adults with type 2 diabetes who were not on prandial insulin. This study compared the effects of 12 weeks of intermittent RT-CGM with self-monitoring of blood glucose (SMBG) on glycemic control over a 40-week follow-up period. Subjects received diabetes care from their regular provider without therapeutic intervention from the study team.

RESULTS

There was a significant difference in A1C at the end of the 3-month active intervention that was sustained during the follow-up period. The mean, unadjusted A1C decreased by 1.0, 1.2, 0.8, and 0.8% in the RT-CGM group vs. 0.5, 0.5, 0.5, and 0.2% in the SMBG group at 12, 24, 38, and 52 weeks, respectively (P = 0.04). There was a significantly greater decline in A1C over the course of the study for the RT-CGM group than for the SMBG group, after adjusting for covariates (P < 0.0001). The subjects who used RT-CGM per protocol (≥48 days) improved the most (P < 0.0001). The improvement in the RT-CGM group occurred without a greater intensification of medication compared with those in the SMBG group.

CONCLUSIONS

Subjects with type 2 diabetes not on prandial insulin who used RT-CGM intermittently for 12 weeks significantly improved glycemic control at 12 weeks and sustained the improvement without RT-CGM during the 40-week follow-up period, compared with those who used only SMBG.

Continuous glucose monitoring: an Endocrine Society Clinical Practice Guideline

OBJECTIVE

The aim was to formulate practice guidelines for determining settings where patients are most likely to benefit from the use of continuous glucose monitoring (CGM).

PARTICIPANTS

The Endocrine Society appointed a Task Force of experts, a methodologist, and a medical writer.

EVIDENCE

This evidence-based guideline was developed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system to describe both the strength of recommendations and the quality of evidence.

CONSENSUS PROCESS

One group meeting, several conference calls, and e-mail communications enabled consensus. Committees and members of The Endocrine Society, the Diabetes Technology Society, and the European Society of Endocrinology reviewed and commented on preliminary drafts of these guidelines.

CONCLUSIONS

The Task Force evaluated three potential uses of CGM: 1) real-time CGM in adult hospital settings; 2) real-time CGM in children and adolescent outpatients; and 3) real-time CGM in adult outpatients. The Task Force used the best available data to develop evidence-based recommendations about where CGM can be beneficial in maintaining target levels of glycemia and limiting the risk of hypoglycemia. Both strength of recommendations and quality of evidence were accounted for in the guidelines.

The use of optical coherence tomography to determine the effect of thiazolidinediones on retinal thickness in patients with type 2 diabetes

OBJECTIVE

Thiazolidinediones (TZDs) are insulin-sensitizing agents that are associated with peripheral edema and have been reported to be associated with diabetic macular edema (DME). We hypothesized that TZDs produce subclinical increases in retinal thickness that may be detected by optical coherence tomography (OCT) but are not seen on routine dilated funduscopic examination.

RESEARCH DESIGN AND METHODS

We used OCT to screen for subclinical DME in a cross-sectional study of patients with type 2 diabetes; 29 patients were taking TZDs and 58 were not taking TZDs. We analyzed data using multiple linear regression analysis to investigate associations of retinal thickness with clinical characteristics.

RESULTS

There was no significant difference between the central subfield retinal thickness in the non-TZD group (206.4 ± 28.0 microns; n = 59) and TZD group (204.1 ± 26.1 microns; n = 29) (p = .72) nor were there significant differences in any other retinal subfield. There was no significant correlation of retinal thickness with laboratory results studies--peripheral edema, gender, age, duration of diabetes, individual, or combinations of medications. Retinal thickness differences between regions displayed normal anatomical variation. However, ethnic differences were found in which African-Americans had thinner retinas in all regions than Caucasians regardless of whether or not they used TZDs.

CONCLUSIONS

These data suggest that TZDs do not cause subclinical DME in a demographically diverse patient population with diabetes. The established normal ranges for macular thickness may require adjustment based on ethnicity.

The effect of real-time continuous glucose monitoring on glycemic control in patients with type 2 diabetes mellitus

BACKGROUND

Real-time continuous glucose monitoring (RT-CGM) improves hemoglobin A1c (A1C) and hypoglycemia in people with type 1 diabetes mellitus and those with type 2 diabetes mellitus (T2DM) on prandial insulin; however, it has not been tested in people with T2DM not taking prandial insulin. We evaluated the utility of RT-CGM in people with T2DM on a variety of treatment modalities except prandial insulin.

METHODS

We conducted a prospective, 52-week, two-arm, randomized trial comparing RT-CGM (n = 50) versus self-monitoring of blood glucose (SMBG) (n = 50) in people with T2DM not taking prandial insulin. Real-time continuous glucose monitoring was used for four 2-week cycles (2 weeks on/1 week off). All patients were managed by their usual provider. This article reports on changes in A1C 0-12 weeks.

RESULTS

Mean (± standard deviation) decline in A1C at 12 weeks was 1.0% (± 1.1%) in the RT-CGM group and 0.5% (± 0.8%) in the SMBG group (p = .006). There were no group differences in the net change in number or dosage of hypoglycemic medications. Those who used the RT-CGM for ≥ 48 days (per protocol) reduced their A1C by 1.2% (± 1.1%) versus 0.6% (± 1.1%) in those who used it <48 days (p = .003). Multiple regression analyses statistically adjusting for baseline A1C, an indicator for usage, and known confounders confirmed the observed differences between treatment groups were robust (p = .009). There was no improvement in weight or blood pressure.

CONCLUSIONS

Real-time continuous glucose monitoring significantly improves A1C compared with SMBG in patients with T2DM not taking prandial insulin. This technology might benefit a wider population of people with diabetes than previously thought.

An overview of management issues in adult patients with type 2 diabetes mellitus

Despite some progress in reducing the rate of diabetic complications, the epidemic rise in incidence of diabetes mellitus ensures that there will be an increasing number of patients in the coming decades with complex health care management issues who will need efficient and effective care. The management of patients with diabetes is an ever-challenging endeavor attributable to several factors. These include, among others, (1) limited provider expertise, (2) decreasing time of a patient visit, (3) increasing complexity of drug management, (4) limited use of self-monitoring of blood glucose by patients and/or providers, (5) clinical inertia, and (6) nonadherence. Technology-driven innovative solutions, including those using virtual reality, are desperately needed to assist both patients and their providers in overcoming the exigencies of this protean disease.

Design of a decision support system to help clinicians manage glycemia in patients with type 2 diabetes mellitus

OBJECTIVE

We sought to develop a computerized clinical decision support for clinicians treating patients with type 2 diabetes mellitus (T2DM).

METHODS

We designed, developed, and tested a computer-assisted decision support (CADS) system using statistical analyses of self-monitoring of blood glucose data, laboratory data, medical and medication history, and individualized hemoglobin A1c goals. A rule-based expert system generated recommendations for changes in therapy and accompanying explanations.

RESULTS

A clinical decision support system (CADS) was developed that considers 9 classes of medications and 69 regimens with combinations of up to 4 therapeutic agents. The preferred sequences of regimens can be customized. The program is integrated with a "comprehensive diabetes management system," electronic medical record systems, and a method for uploading data from memory glucose meters via telephone without use of a computer or the Internet. The software provides a report to the clinician regarding the overall quality of glycemic control and identifies problems, e.g., hypoglycemia, hyperglycemia, glycemic variability, and insufficient data. The program can recommend continuation of current therapy, adjustment of dosages of current medications, or change of regimen and can provide explanations for its recommendations. If the user rejects the recommendations, the program will recommend alternative approaches. The CADS also provides access to Food and Drug Administration-approved prescribing information, guidelines from professional organizations, and selections from the general medical literature. The system has been extensively tested with real and synthetic data and is ready for evaluation in multicenter clinical trials.

CONCLUSION

A clinical decision support system to assist with the management of patients with T2DM was designed, developed, tested, and found to perform well.

Evolution of a web-based, prototype Personal Health Application for diabetes self-management

Behaviors carried out by the person with diabetes (e.g., healthy eating, physical activity, judicious use of medication, glucose monitoring, coping and problem-solving, regular clinic visits, etc.) are of central importance in diabetes management. To assist with these behaviors, we developed a prototype PHA for diabetes self-management that was based on User-Centered Design principles and congruent with the anticipatory vision of Project Health Design (PHD). This article presents aspects of the prototype PHA's functionality as conceived under PHD and describes modifications to the PHA now being undertaken under new sponsorship, in response to user feedback and timing tests we have performed. In brief, the prototype Personal Health Application (PHA) receives data on the major diabetes management domains from a Personal Health Record (PHR) and analyzes and provides feedback based on clinically vetted educational content. The information is presented within "gadgets" within a portal-based website. The PHR used for the first implementation was the Common Platform developed by PHD. Key changes include a re-conceptualization of the gadgets by topic areas originally defined by the American Association of Diabetes Educators, a refocusing on low-cost approaches to diabetes monitoring and data entry, and synchronization with a new PHR, Microsoft® HealthVault™.

Combining iGoogle and personal health records to create a prototype personal health application for diabetes self-management

OBJECTIVE

The aim of this project is to create a prototype for a personal health application (PHA) for patients (i.e., consumers) with diabetes by employing a user-centered design process. This article describes the design process for and resulting architecture, workflow, and functionality of such a PHA.

MATERIALS AND METHODS

For the design process, we conducted focus groups with people who have diabetes (n = 21) to ascertain their needs for a PHA. We then developed a prototype in response to these needs, and through additional focus groups and step-by-step demonstrations for people with diabetes as well as healthcare providers, we obtained feedback about the prototype. The feedback led to changes in the PHA's presentation and function.

RESULTS

Focus group participants said they wanted a tool that could give them timely, readily available information on how diabetes-related domains interact, how their behaviors affect them, and what to do next. Thus, the prototype PHA is Internet-based, retrieves data for diabetes self-management from a personal health record, displays those data using gadgets in the consumer's iGoogle page, and makes the data available to a decision-support component that provides lifestyle-oriented advice. Manipulation of the data enables consumers to anticipate the results of future actions and to see interrelationships.

CONCLUSIONS

A user-centered design process resulted in a PHA that uses technology that is publicly available, employs a personal health record, and is Internet based. This PHA can provide the backbone for a decision support system that can bring together the cornerstones of diabetes self-management and integrate them into the life of the person with diabetes.

A Head-to-Head Comparison of the Postprandial Effects of 3 Meal Replacement Beverages Among People With Type 2 Diabetes

Purpose

The purpose of this study was to compare the effects of 3 meal replacement beverages on glycemic response among people with type 2 diabetes.

Methods

The study examined Glucerna® Weight Loss Shake, Slim-Fast® Shake, and Ensure® with Fiber Shake, using a prospective, 3-way, cross-over design. Eighteen subjects with type 2 diabetes drank the beverages in random order on different weeks. The volume of each beverage was adjusted to include 50 grams of carbohydrates. Glucose was measured 0 to 180 minutes postprandial. Analyses included 2-factor analysis of variance (ANOVA) for repeated measures on both factors, calculation of area under the curve (AUC), and 1-way repeated measures ANOVA of AUC.

Results

The postprandial glucose profiles of the shakes differed. Glucerna® had the best profile as indicated by the graph of mean postprandial glucose levels and its lower incremental AUC. Despite the superiority of Glucerna®, 2-hour postprandial blood glucose values exceeded the ADA’s recommended upper limit for 22% of the subjects.

Conclusions

Meal replacement beverages are a popular and potentially effective option for people trying to lose or maintain weight; however, it is unknown to what degrees they affect postprandial blood glucose in people with type 2 diabetes. Because postprandial glycemic excursion is linked to cardiovascular disease, identifying a meal replacement beverage with the lowest glycemic response may mitigate some of the risks in patients with diabetes. Of the meal replacements observed in this study, Glucerna® had the smallest effect on postprandial glucose. Glycemic response to meal replacements should be monitored given product and individual variability.

Universal glucose models for predicting subcutaneous glucose concentration in humans

This paper tests the hypothesis that a "universal," data-driven model can be developed based on glucose data from one diabetic subject, and subsequently applied to predict subcutaneous glucose concentrations of other subjects, even of those with different types of diabetes. We employed three separate studies, each utilizing a different continuous glucose monitoring (CGM) device, to verify the model's universality. Two out of the three studies involved subjects with type 1 diabetes and the other one with type 2 diabetes. We first filtered the subcutaneous glucose concentration data by imposing constraints on their rate of change. Then, using the filtered data, we developed data-driven autoregressive models of order 30, and used them to make short-term, 30-min-ahead glucose-concentration predictions. We used same-subject model predictions as a reference for comparisons against cross-subject and cross-study model predictions, which were evaluated using the root-mean-squared error (RMSE) and Clarke error grid analysis (EGA). We found that, for each studied subject, the average cross-subject and cross-study RMSEs of the predictions were small and indistinguishable from those obtained with the same-subject models. These observations were corroborated by EGA, where better than 99.0% of the paired sensor-predicted glucose concentrations lay in the clinically acceptable zone A. In addition, the predictive capability of the models was found not to be affected by diabetes type, subject age, CGM device, and interindividual differences. We conclude that it is feasible to develop universal glucose models that allow for clinical use of predictive algorithms and CGM devices for proactive therapy of diabetic patients.