Modeling the acute effects of exercise on glucose dynamics in healthy nondiabetic subjects.

To shed light on how acute exercise affects blood glucose (BG) concentrations in nondiabetic subjects, we develop a physiological pharmacokinetic/pharmacodynamic model of postprandial glucose dynamics during exercise. We unify several concepts of exercise physiology to derive a multiscale model that includes three important effects of exercise on glucose dynamics: increased endogenous glucose production (EGP), increased glucose uptake in skeletal muscle (SM), and increased glucose delivery to SM by capillary recruitment (i.e. an increase in surface area and blood flow in capillary beds). We compare simulations to experimental observations taken in two cohorts of healthy nondiabetic subjects (resting subjects (n = 12) and exercising subjects (n = 12)) who were each given a mixed-meal tolerance test. Metabolic tracers were used to quantify the glucose flux. Simulations reasonably agree with postprandial measurements of BG concentration and EGP during exercise. Exercise-induced capillary recruitment is predicted to increase glucose transport to SM by 100%, causing hypoglycemia. When recruitment is blunted, as in those with capillary dysfunction, the opposite occurs and higher than expected BG levels are predicted. Model simulations show how three important exercise-induced phenomena interact, impacting BG concentrations. This model describes nondiabetic subjects, but it is a first step to a model that describes glucose dynamics during exercise in those with type 1 diabetes (T1D). Clinicians and engineers can use the insights gained from the model simulations to better understand the connection between exercise and glucose dynamics and ultimately help patients with T1D make more informed insulin dosing decisions around exercise.

A novel natural tracer method to measure complex carbohydrate metabolism.

While the triple tracer isotope dilution method has enabled accurate estimation of carbohydrate turnover after a mixed meal, use of the simple carbohydrate glucose as the carbohydrate source limits its translational applicability to everyday meals that typically contain complex carbohydrates. Hence, utilizing the natural enrichment of [13C]polysaccharide in commercially available grains, we devised a novel tracer method to measure postprandial complex carbohydrate turnover and indices of insulin action and ß-cell function and compared the parameters to those obtained after a simple carbohydrate containing mixed meal. We studied healthy volunteers after either rice (n = 8) or sorghum (n = 8) and glucose (n = 16) containing mixed meals and modified the triple tracer technique to calculate carbohydrate turnover. All meals were matched for calories and macronutrient composition. Rates of meal glucose appearance (2,658 ± 736 vs. 4,487 ± 909 µM·kg-1·2 h-1), endogenous glucose production (-835 ± 283 vs. -1,123 ± 323 µM·kg-1·2 h-1) and glucose disappearance (1,829 ± 807 vs. 3,606 ± 839 µM·kg-1·2 h-1) differed (P < 0.01) between complex and simple carbohydrate containing meals, respectively. Interestingly, there were significant increase in indices of insulin sensitivity (32.5 ± 3.5 vs. 25.6 ± 3.2 10-5 (dl·kg-1·min-2)/pM, P = 0.006) and ß-cell responsivity (disposition index: 1,817 ± 234 vs. 1,236 ± 159 10-14 (dl·kg-1·min-2)/pM, P < 0.005) with complex than simple carbohydrate meals. We present a novel triple tracer approach to estimate postprandial turnover of complex carbohydrate containing mixed meals. We also report higher insulin sensitivity and ß-cell responsivity with complex than with simple carbohydrates in mixed meals of identical calorie and macronutrient compositions in healthy adults.

Modeling the acute effects of exercise on insulin kinetics in type 1 diabetes.

Our objective is to develop a physiology-based model of insulin kinetics to understand how exercise alters insulin concentrations in those with type 1 diabetes (T1D). We reveal the relationship between the insulin absorption rate ([Formula: see text]) from subcutaneous tissue, the insulin delivery rate ([Formula: see text]) to skeletal muscle, and two physiological parameters that characterize the tissue: the perfusion rate (Q) and the capillary permeability surface area (PS), both of which increase during exercise because of capillary recruitment. We compare model predictions to experimental observations from two pump-wearing T1D cohorts [resting subjects ([Formula: see text]) and exercising subjects ([Formula: see text])] who were each given a mixed-meal tolerance test and a bolus of insulin. Using independently measured values of Q and PS from literature, the model predicts that during exercise insulin concentration increases by 30% in plasma and by 60% in skeletal muscle. Predictions reasonably agree with experimental observations from the two cohorts, without the need for parameter estimation by curve fitting. The insulin kinetics model suggests that the increase in surface area associated with exercise-induced capillary recruitment significantly increases [Formula: see text] and [Formula: see text], which explains why insulin concentrations in plasma and skeletal muscle increase during exercise, ultimately enhancing insulin-dependent glucose uptake. Preventing hypoglycemia is of paramount importance in determining the proper insulin dose during exercise. The presented model provides mechanistic insight into how exercise affects insulin kinetics, which could be useful in guiding the design of decision support systems and artificial pancreas control algorithms.

Twelve-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A1c and Hypoglycemia.

OBJECTIVE: Artificial pancreas (AP) systems are best positioned for optimal treatment of type 1 diabetes (T1D) and are currently being tested in outpatient clinical trials. Our consortium developed and tested a novel adaptive AP in an outpatient, single-arm, uncontrolled multicenter clinical trial lasting 12 weeks. RESEARCH DESIGN AND METHODS: Thirty adults with T1D completed a continuous glucose monitor (CGM)-augmented 1-week sensor-augmented pump (SAP) period. After the AP was started, basal insulin delivery settings used by the AP for initialization were adapted weekly, and carbohydrate ratios were adapted every 4 weeks by an algorithm running on a cloud-based server, with automatic data upload from devices. Adaptations were reviewed by expert study clinicians and patients. The primary end point was change in hemoglobin A1c (HbA1c). Outcomes are reported adhering to consensus recommendations on reporting of AP trials. RESULTS: Twenty-nine patients completed the trial. HbA1c, 7.0 ± 0.8% at the start of AP use, improved to 6.7 ± 0.6% after 12 weeks (-0.3, 95% CI -0.5 to -0.2, P < 0.001). Compared with the SAP run-in, CGM time spent in the hypoglycemic range improved during the day from 5.0 to 1.9% (-3.1, 95% CI -4.1 to -2.1, P < 0.001) and overnight from 4.1 to 1.1% (-3.1, 95% CI -4.2 to -1.9, P < 0.001). Whereas carbohydrate ratios were adapted to a larger extent initially with minimal changes thereafter, basal insulin was adapted throughout. Approximately 10% of adaptation recommendations were manually overridden. There were no protocol-related serious adverse events. CONCLUSIONS: Use of our novel adaptive AP yielded significant reductions in HbA1c and hypoglycemia.

Overnight Closed-Loop Control Improves Glycemic Control in a Multicenter Study of Adults With Type 1 Diabetes.

Context: Closed-loop control (CLC) for the management of type 1 diabetes (T1D) is a novel method for optimizing glucose control, and strategies for individualized implementation are being developed. Objective: To analyze glycemic control in an overnight CLC system designed to "reset" the patient to near-normal glycemic targets every morning. Design: Randomized, crossover, multicenter clinical trial. Participants: Forty-four subjects with T1D requiring insulin pump therapy. Intervention: Sensor-augmented pump therapy (SAP) at home vs 5 nights of CLC (active from 23:00 to 07:00) in a supervised outpatient setting (research house or hotel), with a substudy of 5 nights of CLC subsequently at home. Main Outcome Measure: The percentage of time spent in the target range (70 to 180 mg/dL measured using a continuous glucose monitor). Results: Forty subjects (age, 45.5 ± 9.5 years; hemoglobin A1c, 7.4% ± 0.8%) completed the study. The time in the target range (70 to 180 mg/dL) significantly improved in CLC vs SAP over 24 hours (78.3% vs 71.4%; P = 0.003) and overnight (85.7% vs 67.6%; P < 0.001). The time spent in a hypoglycemic range (<70 mg/dL) decreased significantly in the CLC vs SAP group over 24 hours (2.5% vs 4.3%; P = 0.002) and overnight (0.9% vs 3.2%; P < 0.001). The mean glucose level at 07:00 was lower with CLC than with SAP (123.7 vs 145.3 mg/dL; P < 0.001). The substudy at home, involving 10 T1D subjects, showed similar trends with an increased time in target (70 to 180 mg/dL) overnight (75.2% vs 62.2%; P = 0.07) and decreased time spent in the hypoglycemic range (<70 mg/dL) overnight in CLC vs SAP (0.6% vs 3.7%; P = 0.03). Conclusion: Overnight-only CLC increased the time in the target range over 24 hours and decreased the time in hypoglycemic range over 24 hours in a supervised outpatient setting. A pilot extension study at home showed a similar nonsignificant trend.

Effect of Pramlintide on Postprandial Glucose Fluxes in Type 1 Diabetes.

CONTEXT: Early postprandial hyperglycemia and delayed hypoglycemia remain major problems in current management of type 1 diabetes (T1D). OBJECTIVE: Our objective was to investigate the effects of pramlintide, known to suppress glucagon and delay gastric emptying, on postprandial glucose fluxes in T1D. DESIGN: This was a single-center, inpatient, randomized, crossover study. PATIENTS: Twelve patients with T1D who completed the study were analyzed. INTERVENTIONS: Subjects were studied on two occasions with or without pramlintide. Triple tracer mixed-meal method and oral minimal model were used to estimate postprandial glucose turnover and insulin sensitivity (SI). Integrated liver insulin sensitivity was calculated based on glucose turnover. Plasma glucagon and insulin were measured. MAIN OUTCOME MEASURE: Glucose turnover and SI were the main outcome measures. RESULTS: With pramlintide, 2-hour postprandial glucose, insulin, glucagon, glucose turnover, and SI indices showed: plasma glucose excursions were reduced (difference in incremental area under the curve [iAUC], 444.0 mMmin, P = .0003); plasma insulin concentrations were lower (difference in iAUC, 7642.0 pMmin; P = .0099); plasma glucagon excursions were lower (difference in iAUC, 1730.6 pg/mlmin; P = .0147); meal rate of glucose appearance was lower (difference in iAUC: 1196.2 µM/kg fat free mass [FFM]; P = .0316), endogenous glucose production was not different (difference in iAUC: -105.5 µM/kg FFM; P = .5842), rate of glucose disappearance was lower (difference in iAUC: 1494.2 µM/kg FFM; P = .0083). SI and liver insulin sensitivity were not different between study visits (P > .05). CONCLUSIONS: Inhibition of glucagon and gastric emptying delaying reduced 2-hour prandial glucose excursions in T1D by delaying meal rate of glucose appearance.

Reliability of a 3D Body Scanner for Anthropometric Measurements of Central Obesity.

BACKGROUND: Central obesity poses a significant risk for cardiovascular diseases, but the reproducibility of manual measurements of waist and hip circumferences has been questioned. An automated 3D body scanner that uses white light rays could potentially increase the reliability of these anthropometric measurements. METHODS: We assessed the reproducibility of anthropometric measurements performed manually and using a 3D-scanner in 83 adult volunteers. Manual measures of WC and HC were obtained using unmarked, non-elastic ribbons in order to avoid observer and confirmation bias. The 3D-scanner was used to create body images and to obtain WC and HC measurements in an automated fashion. RESULTS: The inter-observer mean differences were 3.9 ± 2.4 cm for WC; 2.7 ± 2.4 cm, for HC, and 0.006 ± 0.02 cm for WHR. Intra-observer mean differences for manual measurements were 3.1 ± 1.9 cm for WC, 1.8 ± 2.2 cm for HC and 0.11 ± 0.1 cm for WHR. The 3D-scanner variability for WC was 1.3 ± 0.9 cm, for HC was 0.8 ± 0.1 and 0.005 ± 0.01 cm for WHR. All means were significantly different (p<0.05) between manual and automated methods. CONCLUSION: The 3D-scanner is a more reliable and reproducible method for measuring WC, HC and WHR to detect central obesity.

Glucagon sensitivity and clearance in type 1 diabetes: insights from in vivo and in silico experiments.

Glucagon use in artificial pancreas for type 1 diabetes (T1D) is being explored for prevention and rescue from hypoglycemia. However, the relationship between glucagon stimulation of endogenous glucose production (EGP) viz., hepatic glucagon sensitivity, and prevailing glucose concentrations has not been examined. To test the hypothesis that glucagon sensitivity is increased at hypoglycemia vs. euglycemia, we studied 29 subjects with T1D randomized to a hypoglycemia or euglycemia clamp. Each subject was studied at three glucagon doses at euglycemia or hypoglycemia, with EGP measured by isotope dilution technique. The peak EGP increments and the integrated EGP response increased with increasing glucagon dose during euglycemia and hypoglycemia. However, the difference in dose response based on glycemia was not significant despite higher catecholamine concentrations in the hypoglycemia group. Knowledge of glucagon's effects on EGP was used to develop an in silico glucagon action model. The model-derived output fitted the obtained data at both euglycemia and hypoglycemia for all glucagon doses tested. Glucagon clearance did not differ between glucagon doses studied in both groups. Therefore, the glucagon controller of a dual hormone control system may not need to adjust glucagon sensitivity, and hence glucagon dosing, based on glucose concentrations during euglycemia and hypoglycemia.

Adjustment of Open-Loop Settings to Improve Closed-Loop Results in Type 1 Diabetes: A Multicenter Randomized Trial.

CONTEXT: Closed-loop control (CLC) relies on an individual's open-loop insulin pump settings to initialize the system. Optimizing open-loop settings before using CLC usually requires significant time and effort. OBJECTIVE: The objective was to investigate the effects of a one-time algorithmic adjustment of basal rate and insulin to carbohydrate ratio open-loop settings on the performance of CLC. DESIGN: This study reports a multicenter, outpatient, randomized, crossover clinical trial. PATIENTS: Thirty-seven adults with type 1 diabetes were enrolled at three clinical sites. INTERVENTIONS: Each subject's insulin pump settings were subject to a one-time algorithmic adjustment based on 1 week of open-loop (i.e., home care) data collection. Subjects then underwent two 27-hour periods of CLC in random order with either unchanged (control) or algorithmic adjusted basal rate and carbohydrate ratio settings (adjusted) used to initialize the zone-model predictive control artificial pancreas controller. Subject's followed their usual meal-plan and had an unannounced exercise session. MAIN OUTCOMES AND MEASURES: Time in the glucose range was 80-140 mg/dL, compared between both arms. RESULTS: Thirty-two subjects completed the protocol. Median time in CLC was 25.3 hours. The median time in the 80-140 mg/dl range was similar in both groups (39.7% control, 44.2% adjusted). Subjects in both arms of CLC showed minimal time spent less than 70 mg/dl (median 1.34% and 1.37%, respectively). There were no significant differences more than 140 mg/dL. CONCLUSIONS: A one-time algorithmic adjustment of open-loop settings did not alter glucose control in a relatively short duration outpatient closed-loop study. The CLC system proved very robust and adaptable, with minimal (<2%) time spent in the hypoglycemic range in either arm.

Nocturnal Glucose Metabolism in Type 1 Diabetes: A Study Comparing Single Versus Dual Tracer Approaches.

BACKGROUND: Understanding the effect size, variability, and underlying physiology of the dawn phenomenon is important for next-generation closed-loop control algorithms for type 1 diabetes (T1D). SUBJECTS AND METHODS: We used an iterative protocol design to study 16 subjects with T1D on individualized insulin pump therapy for two successive nights. Endogenous glucose production (EGP) rates at 3 a.m. and 7 a.m. were measured with [6,6-(2)H(2)]glucose as a single tracer, infused from midnight to 7 a.m. in all subjects. To explore possibility of tracer recycling due to prolonged [6,6-(2)H(2)]glucose infusion, which was highly probable after preplanned interim data analyses, we infused a second tracer, [6-(3)H]glucose, from 4 a.m. to 7 a.m. in the last seven subjects to measure EGP at 7 a.m. RESULTS: Cortisol concentrations increased during both nights, but changes in glucagon and insulin concentration were inconsistent. Although the plasma glucose concentrations rose from midnight to 7 a.m. during both nights, EGP measured with [6,6-(2)H(2)]glucose between 3 a.m. and 7 a.m. did not differ during Night 1 but fell in Night 2. However, EGP measured with [6-(3)H]glucose at 7 a.m. was higher than that measured with [6,6-(2)H(2)]glucose during both nights, thereby suggesting tracer recycling probably underestimating EGP calculated at 7 a.m. with [6,6-(2)H(2)]glucose. Likewise, EGP was higher at 7 a.m. with [6-(3)H]glucose than at 3 a.m. with [6,6-(2)H(2)]glucose during both nights. CONCLUSIONS: The data demonstrate a consistent overnight rise in glucose concentrations through increased EGP, mediated likely by rising cortisol concentrations. The observations with the dual tracer approach imply significant tracer recycling leading to underestimation of EGP measured by longer-duration tracer infusion.

Exercise effects on postprandial glucose metabolism in type 1 diabetes: a triple-tracer approach.

To determine the effects of exercise on postprandial glucose metabolism and insulin action in type 1 diabetes (T1D), we applied the triple tracer technique to study 16 T1D subjects on insulin pump therapy before, during, and after 75 min of moderate-intensity exercise (50% V̇o2max) that started 120 min after a mixed meal containing 75 g of labeled glucose. Prandial insulin bolus was administered as per each subject's customary insulin/carbohydrate ratio adjusted for meal time meter glucose and the level of physical activity. Basal insulin infusion rates were not altered. There were no episodes of hypoglycemia during the study. Plasma dopamine and norepinephrine concentrations rose during exercise. During exercise, rates of endogenous glucose production rose rapidly to baseline levels despite high circulating insulin and glucose concentrations. Interestingly, plasma insulin concentrations increased during exercise despite no changes in insulin pump infusion rates, implying increased mobilization of insulin from subcutaneous depots. Glucagon concentrations rose before and during exercise. Therapeutic approaches for T1D management during exercise will need to account for its effects on glucose turnover, insulin mobilization, glucagon, and sympathetic response and possibly other blood-borne feedback and afferent reflex mechanisms to improve both hypoglycemia and hyperglycemia.

Effects of delayed gastric emptying on postprandial glucose kinetics, insulin sensitivity, and ß-cell function.

Controlling meal-related glucose excursions continues to be a therapeutic challenge in diabetes mellitus. Mechanistic reasons for this need to be understood better to develop appropriate therapies. To investigate delayed gastric emptying effects on postprandial glucose turnover, insulin sensitivity, and ß-cell responsivity and function, as a feasibility study prior to studying patients with type 1 diabetes, we used the triple tracer technique C-peptide and oral minimal model approach in healthy subjects. A single dose of 30 µg of pramlintide administered at the start of a mixed meal was used to delay gastric emptying rates. With delayed gastric emptying rates, peak rate of meal glucose appearance was delayed, and rate of endogenous glucose production (EGP) was lower. C-peptide and oral minimal models enabled the assessments of ß-cell function, insulin sensitivity, and ß-cell responsivity simultaneously. Delayed gastric emptying induced by pramlintide improved total insulin sensitivity and decreased total ß-cell responsivity. However, ß-cell function as measured by total disposition index did not change. The improved whole body insulin sensitivity coupled with lower rate of appearance of EGP with delayed gastric emptying provides experimental proof of the importance of evaluating pramlintide in artificial endocrine pancreas approaches to reduce postprandial blood glucose variability in patients with type 1 diabetes.

Comparison of physical activity sensors and heart rate monitoring for real-time activity detection in type 1 diabetes and control subjects.

BACKGROUND: Currently, patients with type 1 diabetes decide on the amount of insulin to administer based on several factors, including current plasma glucose value, expected meal input, and physical activity (PA). One future therapeutic modality for patients with type 1 diabetes is the artificial endocrine pancreas (AEP). Incorporation of PA could enhance the efficacy of AEP significantly. We compared the main technologies used for PA quantitation. SUBJECTS AND METHODS: Data were collected during inpatient studies involving healthy control subjects and type 1 diabetes. We report PA quantified from accelerometers (acceleration units [AU]) and heart rate (HR) monitors during a standardized activity protocol performed after a dinner meal at 7 p.m. from nine control subjects (four were males, 37.4±12.7 years old, body mass index of 24.8±3.8 kg/m(2), and fasting plasma glucose of 4.71±0.63 mmol/L) and eight with type 1 diabetes (six were males, 45.2±13.4 years old, body mass index of 25.1±2.9 kg/m(2), and fasting plasma glucose of 8.44±2.31 mmol/L). RESULTS: The patient-to-patient variability was considerably less when examining AU compared with HR monitors. Furthermore, the exercise bouts and rest periods were more evident from the data streams when AUs were used to quantify activity. Unlike the AU, the HR measurements provided little insight for active and rest stages, and HR data required patient-specific standardizations to discern any meaningful pattern in the data. CONCLUSIONS: Our results indicated that AU provides a reliable signal in response to PA, including low-intensity activity. Correlation of this signal with continuous glucose monitoring data would be the next step before exploring inclusion as input for AEP control.

Postprandial glucose fluxes and insulin sensitivity during exercise: a study in healthy individuals.

Quantifying the effect size of acute exercise on insulin sensitivity (SI(exercise)) and simultaneous measurement of glucose disappearance (R(d)), endogenous glucose production (EGP), and meal glucose appearance in the postprandial state has not been developed in humans. To do so, we studied 12 healthy subjects [5 men, age 37.1 ± 3.1 yr, body mass index 24.1 ± 1.1 kg/m², fat-free mass (FFM) 50.9 ± 3.9 kg] during moderate exercise at 50% V(O2max) for 75 min, 120-195 min after a triple-tracer mixed meal consumed at time 0. Tracer infusion rates were adjusted to achieve constant tracer-to-tracee ratio and minimize non-steady-state errors. Glucose turnover was estimated by accounting for the nonstationary kinetics introduced by exercise. Insulin sensitivity index was calculated in each subject both in the absence [time (t) = 0-120 min, SI(rest)] and presence (t = 0-360 min, SI(exercise)) of physical activity. EGP at t = 0 min (13.4 ± 1.1 µM·kg FFM⁻¹·min⁻¹) fell at t = 120 min (2.4 ± 0.4 µM·kg FFM⁻¹·min⁻¹) and then rapidly rose almost eightfold at t = 180 min (18.2 ± 2.6 µM·kg FFM⁻¹·min⁻¹) before gradually falling at t = 360 min (10.6 ± 0.9 µM·kg FFM⁻¹·min⁻¹). R(d) rapidly peaked at t = 120 min at the start of exercise (89.5 ± 11.6 µM·kg FFM⁻¹·min⁻¹) and then gradually declined at t = 195 min (26.4 ± 3.3 µM·kg FFM⁻¹·min⁻¹) before returning to baseline at t = 360 min. SI(exercise) was significantly higher than SI(rest) (21.6 ± 3.7 vs. 12.5 ± 2.0 10⁻4 dl·kg⁻¹·min⁻¹ per µU/ml, P < 0.0005). Glucose turnover was estimated for the first time during exercise with the triple-tracer technique. Our results, applying state-of-the-art techniques, show that moderate exercise almost doubles postprandial insulin sensitivity index in healthy subjects.

Diurnal pattern of insulin action in type 1 diabetes: implications for a closed-loop system.

We recently demonstrated a diurnal pattern to insulin action (i.e., insulin sensitivity [SI]) in healthy individuals with higher SI at breakfast than at dinner. To determine whether such a pattern exists in type 1 diabetes, we studied 19 subjects with C-peptide-negative diabetes (HbA1c 7.1 ± 0.6%) on insulin pump therapy with normal gastric emptying. Identical mixed meals were ingested during breakfast, lunch, and dinner at 0700, 1300, and 1900 h in randomized Latin square of order on 3 consecutive days when measured daily physical activity was equal. The triple tracer technique enabled measurement of glucose fluxes. Insulin was administered according to the customary insulin:carbohydrate ratio for each participant. Although postprandial glucose excursions did not differ among meals, insulin concentration was higher (P < 0.01) and endogenous glucose production less suppressed (P < 0.049) at breakfast than at lunch. There were no differences in meal glucose appearance or in glucose disappearance between meals. Although there was no statistical difference (P = 0.34) in SI between meals in type 1 diabetic subjects, the diurnal pattern of SI taken across the three meals in its entirety differed (P = 0.016) from that of healthy subjects. Although the pattern in healthy subjects showed decreasing SI between breakfast and lunch, the reverse SI pattern was observed in type 1 diabetic subjects. The results suggest that in contrast to healthy subjects, SI diurnal pattern in type 1 diabetes is specific to the individual and cannot be extrapolated to the type 1 diabetic population as a whole, implying that artificial pancreas algorithms may need to be personalized.

Recommendations for managing patients with diabetes mellitus in cardiopulmonary rehabilitation: an American Association of Cardiovascular and Pulmonary Rehabilitation statement.

Diabetes mellitus is a highly prevalent condition in patients participating in cardiopulmonary rehabilitation. However, research and subsequent guidelines specifically applicable to patients with diabetes, participating in cardiopulmonary rehabilitation, are limited. Recognizing this limitation, the American Association of Cardiovascular and Pulmonary Rehabilitation (AACVPR) initiated this statement, with the goal of developing a template that incorporated recommendations provided in the AACVPR Core Components and the American Association of Diabetes Educators 7 Self-Care Behaviors. This statement describes key processes regarding evaluation, interventions, and expected outcomes in each of the core components for the management of patients with diabetes in a cardiopulmonary rehabilitation program.