Michael R Rickels | University of Pennsylvania (original) (raw)

Papers by Michael R Rickels

Frontiers in endocrinology, Feb 20, 2024

Insulin secretion within 30 minutes of nutrient ingestion is reduced in people with cystic fibros... more Insulin secretion within 30 minutes of nutrient ingestion is reduced in people with cystic fibrosis (PwCF) and pancreatic insufficiency and declines with worsening glucose tolerance. The glucose potentiated arginine (GPA) test is validated for quantifying b-cell secretory capacity as an estimate of functional b-cell mass but requires technical expertise and is burdensome. This study sought to compare insulin secretion during mixed-meal tolerance testing (MMTT) to GPA-derived parameters in PwCF. Methods: Secondary data analysis of CF-focused prospective studies was performed in PwCF categorized as 1) pancreatic insufficient [PI-CF] or 2) pancreatic sufficient [PS-CF] and in 3) non-CF controls. MMTT: insulin secretory rates (ISR) were derived by parametric deconvolution using 2compartment model of C-peptide kinetics, and incremental area under the curve (AUC) was calculated for 30, 60 and 180-minutes. GPA: acute insulin (AIR) and C-peptide responses (ACR) were calculated as average post-arginine insulin or C-peptide response minus pre-arginine insulin or C-peptide under fasting (AIR arg and ACR arg),~230 mg/dL (AIR pot and ACR pot), and~340 mg/dL (AIR max and ACR max) hyperglycemic clamp conditions. Relationships of MMTT to GPA parameters were derived using Pearson's correlation coefficient. Predicted values were generated for MMTT ISR and compared to GPA parameters using Bland Altman analysis to assess degree of concordance. Results: 85 PwCF (45 female; 75 PI-CF and 10 PS-CF) median (range) age 23 (6-56) years with BMI 23 (13-34) kg/m 2 , HbA 1c 5.5 (3.8-10.2)%, and FEV1%-predicted 88 (26-125) and 4 non-CF controls of similar age and BMI were included. ISR AUC 30min positively correlated with AIR arg (r=0.55), AIR pot (r=0.62), and AIR max (r=0.46) and with ACR arg (r=0.59), ACR pot (r=0.60), and ACR max (r=0.51) (all Frontiers in Endocrinology frontiersin.org 01

The Lancet, Oct 1, 2019

The primary goal of treatment for type diabetes is to control glycemia with insulin therapy in or... more The primary goal of treatment for type diabetes is to control glycemia with insulin therapy in order to reduce disease complications. For some patients, technological approaches to insulin delivery are inadequate, and allogeneic islet transplantation is a safe alternative for those who have experienced severe hypoglycemia complicated by hypoglycemia unawareness or glycemic lability, or who already receive immunosuppression for a kidney transplant. Since 2000, intrahepatic islet transplantation has proven long-term efficacy in alleviating the burden of labile diabetes and preventing long-term diabetes-related complications, whether or not a prior kidney graft is present. Age, body mass index, renal and cardiopulmonary status help to choose between pancreas or islet transplantation. Access is presently limited by the number of deceased donors and the necessity of immunosuppression. Future approaches may include alternative sources of islets (xenogeneic tissue, human stem cells), extra-hepatic sites of implantation (omental, sucutaneous, intramuscular), and immune tolerance or encapsulation. Search strategy and selection criteria Data for this review were identified by searching MEDLINE, PubMed, Pubmed clinical trials, and references from relevant articles using the search terms "islet transplantation", "clinical" and "type 1 diabetes", as well as "β-cell", "stem cell", "xenotransplantation", "immune tolerance". Articles published between 1990 and 2019 were included. We mostly selected publications from the past five years but did not exclude commonly referenced and highly regarded older publications. We also searched the reference lists of articles identified by this search and selected those we judged relevant. Review articles are cited to provide readers with more details. Pancreas transplantation and islet auto-transplantation were excluded from this review.

Diabetes Technology & Therapeutics, Jun 20, 2023

Diabetes, Jun 20, 2023

Prior exposure to hypoglycemia and exercise may each dampen the sympathoadrenal response to subse... more Prior exposure to hypoglycemia and exercise may each dampen the sympathoadrenal response to subsequent hypoglycemia, leading to impaired awareness of hypoglycemia (IAH) and increased risk for experiencing clinically significant hypoglycemia. Whether glucose changes during exercise differ in those with IAH vs. intact awareness of hypoglycemia (Aware) has not been assessed in a large sample of ambulatory adults with type 1 diabetes, nor is the risk for hypoglycemia events in the next 24 hours known in such individuals. Using a case-control design, we compared participants with IAH (Clarke score ≥4 or ≥1 severe hypoglycemic event [SHE] within the past year) to Aware participants (Clarke score of ≤2 and no SHE within the past year), matching on sex, insulin modality, baseline HbA1c, and age. The analysis cohort included 95 adults with IAH matched to 95 Aware adults (in both groups, 74% female, mean ± SD age of 43 ± 14 yr, and HbA1c of 6.5 ± 0.7%) with a total of 4,236 exercise sessions and 1,794 post-exercise and 839 sedentary days available for analysis. IAH had a trend toward a greater but not clinically significant decline in glucose during exercise compared to Aware (−21 ± 44 vs. −19 ± 43 mg/dL, adjusted group difference of −4.2 [95% CI: −8.7 to 0.3] mg/dL, p=0.06). IAH had a higher proportion of hypoglycemic events (≥15 minutes <70 mg/dL) vs. Aware on both post-exercise days (51% vs. 43%, p=0.008) and sedentary days (48% vs. 30%, p=0.002). There was no evidence that the increased odds of hypoglycemia for IAH compared with Aware differed between post-exercise and sedentary days (interaction p=0.36). In summary, participants with IAH have an overall higher baseline risk of hypoglycemia than Aware participants. However, for those with IAH exercise itself does not appear to differentially increase the risk for hypoglycemia during the activity, or in the subsequent 24 hours compared to Aware individuals with type 1 diabetes. Disclosure J.L. Jo Kamimoto: None. Z. Li: None. R.L. Gal: None. J.R. Castle: Research Support; Dexcom, Inc. Advisory Panel; Novo Nordisk. Stock/Shareholder; Pacific Diabetes Technologies. Advisory Panel; Zealand Pharma A/S. F.J. Doyle: Stock/Shareholder; Mode AGC. Other Relationship; Insulet Corporation, Roche Diabetes Care, Dexcom, Inc. P.G. Jacobs: Other Relationship; Pacific Diabetes Technologies. Board Member; Pacific Diabetes Technologies. Research Support; Dexcom, Inc. C.K. Martin: Research Support; Pack Health, Evidation Health, Lilly. Board Member; EHE Health, Wondr Health. Other Relationship; ABGIL. Research Support; WW International, Inc. R. Beck: Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company. Consultant; Eli Lilly and Company. Research Support; Novo Nordisk. Consultant; Novo Nordisk, Diasome, Insulet Corporation. P. Calhoun: None. M. Riddell: Stock/Shareholder; Supersapiens. Advisory Panel; Zealand Pharma A/S. Speaker's Bureau; Dexcom, Inc. Consultant; Lilly Diabetes. Speaker's Bureau; Novo Nordisk, Sanofi. Stock/Shareholder; Zucara Therapeutics. Advisory Panel; Zucara Therapeutics, Indigo Diabetes. Consultant; Eli Lilly and Company, Jaeb Center for Health Research. M.R. Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S. Research Support; Dompé. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Verily Life Sciences; Dexcom, Inc.

Sleep, May 25, 2022

Lincoln medical center 1 Introduction: Obstructive sleep apnea (OSA) is a sleep disorder that has... more Lincoln medical center 1 Introduction: Obstructive sleep apnea (OSA) is a sleep disorder that has been linked to increase the risk for hypertension, ischemic heart failure, arrhythmia and heart failure. There are multiple similarities between OSA and Chronic Obstructive Pulmonary Disease (COPD); both are associated with hypoxia and hypercapnia, with different mechanisms of hypoxia; in COPD its chronic and slow progression, whereas it is suddenly intermittent hypoxia in OSA. Intermittent hypoxia was hypothesized to enhance the protective effect on subsequent hypoxia resulting in cardioprotective effect [1]. There is little data on rates of in-hospital mortality on patients with OSA and COPD using a nationwide study. In this study, we aim to analyze the impact on mortality and length of hospital stay of obstructive sleep apnea in patients with COPD. Methods: Adults with principal diagnosis of COPD were selected from the 2019 US National Inpatient Sample, using ICD 10 code primary diagnosis on discharge. We queried the 2019 National Inpatient Sample for OSA, and other secondary diagnoses (hyperlipidemia, hypertension, heart failure, smoking, CKD, electrolytes disturbances). Confounders were adjusted for using multivariable linear regression analysis for other secondary diagnoses. Results: In a total of 520,624 adult hospitalizations with COPD primary diagnosis on discharge were included from the 2019 national inpatient sample. 73,705 patients had concomitant secondary diagnosis with OSA. On weighted analysis, hospitalizations with primary diagnosis of COPD and secondary diagnosis of OSA had lower in-hospital mortality rates compared to hospitalizations with COPD alone (0.6% vs 1.08%, p= 0.000), .COPD hospitalizations with OSA had statistically significant lower odds for mortality compared to COPD patients without OSA (adjusted OR 0.73, 95% CI 0.57-0.93; p= 0.009).However, COPD hospitalizations with OSA showed increased in the mean length of stay by 0.21 days (95% CI 0.12-0.30, p=0.000) compared to patients without OSA. Conclusion: Our analysis showed better mortality outcomes for COPD patients with OSA , supporting the protective effect hypothesis of intermittent hypoxia. COPD patients with concomitant secondary OSA diagnosis have increased in-hospital length of stay.

Journal of the Endocrine Society, Apr 1, 2020

enzymes normalized when her glucose levels normalized and DKA resolved. Further work-up ruled out... more enzymes normalized when her glucose levels normalized and DKA resolved. Further work-up ruled out more common etiologies of liver injury. Multiple abdominal ultrasounds and CT scans showed a normal sized liver without obvious structural abnormalities. Labs were significant for negative hepatitis B and hepatitis C; several negative anti-smooth muscle, anti-nuclear antibody, centromere antibody, and liver kidney microsomal type 1 antibody; normal levels of ceruloplasmin and alpha 1 anti-trypsin; low iron levels 23 ug/dL (60-180 ug/dL); borderline low IgG 627 mg/dL (700-1600 mg/dL). We hypothesized that the patient likely had GH by exclusion of other liver pathologies and given the context of transient transaminitis during DKA. Conclusion: GH is a benign and favorable diagnosis in diabetic patients with elevated transaminases. 1 Given the small number of cases of GH reported, there is a need to record and analyze more patients with likely GH in order to better understand the condition. Appropriate clinician awareness of GH can also eliminate the need for time consuming and costly workup.

Arteriosclerosis, Thrombosis, and Vascular Biology, May 1, 2013

Introduction Cardiovascular disease rates are higher in type II diabetes mellitus, but often it r... more Introduction Cardiovascular disease rates are higher in type II diabetes mellitus, but often it remains silent until too late. It is unknown if baseline EKG changes are associated with the degree of impaired insulin sensitivity or with other markers of diabetes control. We sought to investigate these relationships in the Penn Diabetes Heart Study (PDHS), a cross-sectional study of diabetic patients without overt coronary artery disease. Methods EKG intervals were measured in a subset of PDHS participants (n=732; mean age 59.4 ± 8.4 years, 66.5% males, 60.1% Caucasians). At the same visit, subjects underwent 75 g oral glucose tolerance testing after overnight fast with measurement of glucose and insulin at 0, 30, 60, and 120 minutes. The Matsuda Insulin Sensitivity Index (MISI) was calculated to estimate insulin sensitivity and the Insulinogenic Index (IGI) to estimate pancreatic beta-cell function. We used spearman correlations, chi-squared tests, and logistic regression to test associations of EKG changes with clinical factors, log-transformed MISI, and inverse normal-transformed IGI. Results In unadjusted analysis, there was a higher prevalence of left ventricular hypertrophy (LVH) (3.6% vs. 0.9%, p = 0.005) and ST changes (24.5% vs. 14.6%, p = 0.004) in African Americans compared to Caucasians. In fully adjusted models controlling for age, race, sex, history of hypertension and Framingham risk score, a higher MISI was associated with lower incidence of Q waves (OR 0.50, CI 0.33-0.76, p = 0.001). In addition, higher IGI scores were associated with a lower incidence of nonspecific ST changes (OR 0.82, CI 0.65-0.96, p= 0.035). There was also a trend for higher HbA1c values associated with LVH; however, this association was not statistically significant in fully adjusted models (OR 1.29, CI 0.90-1.86, p = 0.163). Conclusion Q wave abnormalities on routine EKGs were associated with reduced insulin sensitivity at baseline, while nonspecific ST changes were associated with lower pancreatic beta-cell function in patients with diabetes. Specific baseline EKG changes are indicators of the degree of metabolic disturbance in type 2 diabetes and may provide insight into the extent and risk of macrovascular and microvascular complications in diabetic patients.

Transplantation, Jul 22, 2022

Background. The long-term outcomes of both pancreas and islet allotransplantation have been compr... more Background. The long-term outcomes of both pancreas and islet allotransplantation have been compromised by difficulties in the detection of early graft dysfunction at a time when a clinical intervention can prevent further deterioration and preserve allograft function. The lack of standardized strategies for monitoring pancreas and islet allograft function prompted an international survey established by an International Pancreas and Islet Transplant Association/European Pancreas and Islet Transplant Association working group. Methods. A global survey was administered to 24 pancreas and 18 islet programs using Redcap. The survey addressed protocolized and for-cause immunologic and metabolic monitoring strategies following pancreas and islet allotransplantation. All invited programs completed the survey. Results. The survey identified that in both pancreas and islet allograft programs, protocolized clinical monitoring practices included assessing body weight, fasting glucose/C-peptide, hemoglobin A1c, and donor-specific antibody. Protocolized monitoring in islet transplant programs relied on the addition of mixed meal tolerance test, continuous glucose monitoring, and autoantibody titers. In the setting of either suspicion for rejection or serially increasing hemoglobin A1c/fasting glucose levels postpancreas transplant, Doppler ultrasound, computed tomography, autoantibody titers, and pancreas graft biopsy were identified as adjunctive strategies to protocolized monitoring studies. No additional assays were identified in the setting of serially increasing hemoglobin A1c levels postislet transplantation. Conclusions. This international survey identifies common immunologic and metabolic monitoring strategies utilized for protocol and for cause following pancreas and islet transplantation. In the absence of any formal studies to assess the efficacy of immunologic and metabolic testing to detect early allograft dysfunction, it can serve as a guidance document for developing monitoring algorithms following beta-cell replacement.

JBMR plus, Aug 3, 2020

Type 1 diabetes (T1D) increases fracture risk across the lifespan. The low bone turnover associat... more Type 1 diabetes (T1D) increases fracture risk across the lifespan. The low bone turnover associated with T1D is thought to be related to glycemic control, but it is unclear whether peripheral hyperinsulinemia due to dependence on exogenous insulin has an independent effect on suppressing bone turnover. The purpose of this study was to test the bone turnover marker (BTM) response to acute hyperinsulinemia. Fifty-eight adults aged 18 to 65 years with T1D over 2 years were enrolled at seven T1D Exchange Clinic Network sites. Participants had T1D diagnosis between age 6 months to 45 years. Participants were stratified based on their residual endogenous insulin secretion measured as peak C-peptide response to a mixed meal tolerance test. BTMs (CTX, P1NP, sclerostin [SCL], osteonectin [ON], alkaline phosphatase [ALP], osteocalcin [OCN], osteoprotegerin [OPG], osteopontin [OPN], and IGF-1) were assessed before and at the end of a 2-hour hyperinsulinemic-euglycemic clamp (HEC). Baseline ON (r = −0.30, p = .022) and OCN (r = −0.41, p = .002) were negatively correlated with age at T1D diagnosis, but baseline BTMs were not associated with HbA1c. During the HEC, P1NP decreased significantly (−14.5 AE 44.3%; p = .020) from baseline. OCN, ON, and IGF-1 all significantly increased (16.0 AE 13.1%, 29.7 AE 31.7%, 34.1 AE 71.2%, respectively; all p < .001) during the clamp. The increase in SCL was not significant (7.3 AE 32.9%, p = .098), but the decrease in CTX (−12.4 AE 48.9, p = .058) neared significance. ALP and OPG were not changed from baseline (p = .23 and p = .77, respectively). Baseline ON and SCL were higher in men, but OPG was higher in women (all p ≤ .029). SCL was the only BTM that changed differently in women than men. There were no differences in baseline BTMs or change in BTMs between C-peptide groups. Exogenous hyperinsulinemia acutely alters bone turnover, suggesting a need to determine whether strategies to promote healthy remodeling may protect bone quality in T1D.

About 30%-40% of Type 1 Diabetes (T1D) patients in the United States use insulin pumps. Current i... more About 30%-40% of Type 1 Diabetes (T1D) patients in the United States use insulin pumps. Current insulin infusion systems require users to manually input meal carb count and approve or modify the system-suggested meal insulin dose. Users can give correction insulin boluses at any time. Since meal carbohydrates and insulin are the two main driving forces of the glucose physiology, the user-specific eating and pump-using behavior has a great impact on the quality of glycemic control. In this paper, we propose an "Eat, Trust, and Correct" (ETC) framework to model the T1D insulin pump users' behavior. We use machine learning techniques to analyze the user behavior from a clinical dataset that we collected on 55 T1D patients who use insulin pumps. We demonstrate the usefulness of the ETC behavior modeling framework by performing in silico experiments. To this end, we integrate the user behavior model with an individually parameterized glucose physiological model, and perform probabilistic model checking on the user-in-the-loop system. The experimental results show that switching behavior types can significantly improve a patient's glycemic control outcomes. These analysis results can boost the effectiveness of T1D patient education and peer support.

Diabetes Technology & Therapeutics, Feb 1, 2021

Background: People with type 1 diabetes estimate meal carbohydrate content to accurately dose ins... more Background: People with type 1 diabetes estimate meal carbohydrate content to accurately dose insulin, yet, protein and fat content of meals also influences postprandial glycemia. We examined accuracy of macronutrient content estimation via a novel phone app. Participant estimates were compared with expert nutrition analyses performed via the Remote Food Photography Method© (RFPM©).Methods: Data were collected through a novel phone app. Participants were asked to take photos of meals/snacks on the day of and day after scheduled exercise, enter carbohydrate estimates, and categorize meals as low, typical, or high protein and fat. Glycemia was measured via continuous glucose monitoring.Results: Participants (n = 48) were 15–68 years (34 ± 14 years); 40% were female. The phone app plus RFPM© analysis captured 88% ± 29% of participants' estimated total energy expenditure. The majority (70%) of both low-protein and low-fat meals were accurately classified. Only 22% of high-protein meals and 17% of high-fat meals were accurately classified. Forty-nine percent of meals with <30 g of carbohydrates were overestimated by an average of 25.7 ± 17.2 g. The majority (64%) of large carbohydrate meals (≥60 g) were underestimated by an average of 53.6 ± 33.8 g. Glycemic response to large carbohydrate meals was similar between participants who underestimated or overestimated carbohydrate content, suggesting that factors beyond carbohydrate counting may impact postprandial glycemic response.Conclusions: Accurate estimation of total macronutrients in meals could be leveraged to improve insulin decision support tools and closed loop insulin delivery systems; development of tools to improve macronutrient estimation skills should be considered.

Diabetes, Jun 20, 2023

Social determinants of health (SDH), or the conditions in which people live, learn, work, play, a... more Social determinants of health (SDH), or the conditions in which people live, learn, work, play, and age strongly influence health inequities among adults with type 1 diabetes (T1D). Diabetes self-care, or daily behaviors performed to maintain health (maintenance), monitor for changes (monitoring), and manage illness (management), is essential for T1D management, but may also be impacted by SDH. We aimed to determine if SDH predicted self-care maintenance, monitoring and management, and if so, identify which SDH items were the most salient predictors. A diverse sample of adults with T1D (n=200, 27% Black, 61% female, median age: 35 years, disease duration: 19 years) completed an SDH risk assessment (PRAPARE tool; Risk Tally Scoring Method applied to 14 items to yield a composite risk score) and self-care assessment (Self-Care of Diabetes Inventory [SCODI]; 3 self-care [maintenance, monitoring, and management] and 1 confidence scale). A multivariable linear regression model of each self-care scale was built with SDH risk and confidence as predictors of self-care. For each self-care scale exhibiting a significant association with SDH risk, an exploratory multivariable model was built to determine which of the 14 SDH items were the most salient predictors. SDH risk was a significant predictor of self-care maintenance. For every 1 unit increase in SDH risk, maintenance was estimated to decrease by 1.14 units (p&lt; .01). Exploratory multivariable analysis revealed employment insecurity and material insecurity to be the most salient SDH risk predictors of maintenance. Participants who were not employed full-time were estimated to have maintenance scores 5.15 ± 2.27 units (p&lt;.05) less. For every 1 unit increase in material insecurity (score range:0 - 7), estimated maintenance decreased by 2.6 ± .89 units (p &lt; .01). Those with higher SDH risks are less likely to perform behaviors to maintain health. Providers may facilitate self-care of patients by assessing SDH risks and offering self-care guidance considerate of SDH risks. Disclosure A. M. Matus: None. B. Riegel: None. M. R. Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Research Support; Dompé. Funding National Institutes of Health (31NR020137, R01DK091331)

Diabetes, Jun 20, 2023

Achieving 7-10K steps per day is recommended to maintain health; however, the influence of step c... more Achieving 7-10K steps per day is recommended to maintain health; however, the influence of step count on time in range (70-180mg/dL: TIR), time above range (&gt;180mg/dL: TAR), and time below range (&lt;70mg/dL: TBR) in adults with T1D on different insulin delivery modalities (multiple daily injections [MDI], standard pump [SP], closed loop system [CLS]) is unclear. Using data from the Type 1 Diabetes Exercise Initiative, we examined the impact of failing to meet (&lt;7k), meeting (7k-10k) and exceeding (&gt;10k) step count goal on glycemic outcomes by insulin modality. Adults with T1D (37±14 yrs, 73% F, A1C 6.6±0.7%) wore a Verily Study Watch and CGM (Dexcom G6) for 4 weeks. Participants had at least two days where they failed to meet, met, and exceeded step count goal. For all users, mean TIR was 2% lower and TAR was 2% higher on days when participants failed to meet step count goal compared to meeting or exceeding step goal. TBR was 0.3% higher on days exceeding step count goal compared to failing to meet or meeting goal. Trends were similar across insulin delivery modalities, but variation differed, which affected significance levels. Meeting or exceeding 7-10K steps per day is associated with marginal improvements in TIR in adults with T1D. Disclosure L.Turner: None. F.J.Doyle: Other Relationship; Insulet Corporation, Roche Diabetes Care, Dexcom, Inc., Stock/Shareholder; Mode AGC. J.R.Castle: Advisory Panel; Novo Nordisk, Zealand Pharma A/S, Research Support; Dexcom, Inc., Stock/Shareholder; Pacific Diabetes Technologies. M.B.Gillingham: None. M.R.Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Research Support; Dompé. R.Beck: Consultant; Eli Lilly and Company, Novo Nordisk, Diasome, Insulet Corporation, Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company, Novo Nordisk. P.G.Jacobs: Board Member; Pacific Diabetes Technologies, Other Relationship; Pacific Diabetes Technologies, Research Support; Dexcom, Inc. M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Indigo Diabetes, Consultant; Lilly Diabetes, Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Novo Nordisk, Sanofi, Stock/Shareholder; Supersapiens, Zucara Therapeutics. T1dexi study group: n/a. C.Marak: None. P.Calhoun: None. R.L.Gal: None. Z.Li: None. G.Young: None. S.R.Patton: None. M.A.Clements: Consultant; Glooko, Inc., Research Support; Dexcom, Inc., Abbott Diabetes. C.K.Martin: Board Member; EHE Health, Wondr Health, Other Relationship; ABGIL, Research Support; Pack Health, Evidation Health, Lilly, WW International, Inc. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Verily Life Sciences; Dexcom, Inc.

Diabetes, Jul 1, 2018

In this report, we examined and compared changes in diabetes technology use and HbA1c levels from... more In this report, we examined and compared changes in diabetes technology use and HbA1c levels from data collected in 22,470 participants in the T1DX clinic registry (mean age 26±18 years, duration 14±13 years) between 2016 and 2017 with registry data collected from 25,529 participants (mean age 22±17 years, duration 10±12 years) between 2010 and 2012. There was a moderate increase in insulin pump use across all age groups from 57% in the 2010-12 cohort to 63% in the 2016-17 cohort. In contrast, continuous glucose monitoring (CGM) use rose sharply from 7% to 28%, with the most dramatic increase in the preadolescent and young child groups (4% to 35% for participants &lt;13 years old) (Table). Despite adjustments for differences in age and diabetes duration, mean HbA1c levels increased over time (from 8.2% in 2010-12 to 8.6% in 2016-17), with the greatest rise in participants 13-25 years old (Table). In both cohorts CGM users had lower HbA1c levels than non-users (7.6% in CGM users vs. 8.3% in non-users in 2010-12 and 7.9% in CGM users vs. 8.8% in non-users in 2016-17). Conclusion: In the T1D Exchange registry, HbA1c levels have increased although HbA1c remains lower in CGM users than non-users. Disclosure N.C. Foster: None. K. Miller: None. L. DiMeglio: Advisory Panel; Self; Eli Lilly and Company. Research Support; Self; Dexcom, Inc., Medtronic, Sanofi, Caladrius Biosciences, Inc., Janssen Research &amp; Development, Xeris Pharmaceuticals, Inc., Sanofi. D.M. Maahs: Advisory Panel; Self; Insulet Corporation. Consultant; Self; Abbott. Research Support; Self; Medtronic, Bigfoot Biomedical, Dexcom, Inc., Insulet Corporation, Roche Diabetes Care Health and Digital Solutions. W.V. Tamborlane: Consultant; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company, Medtronic MiniMed, Inc., Novo Nordisk Inc., Sanofi, Takeda Pharmaceuticals U.S.A., Inc. R.M. Bergenstal: Research Support; Self; Johnson &amp; Johnson Services, Inc.. Consultant; Self; Johnson &amp; Johnson Services, Inc.. Research Support; Self; Abbott. Advisory Panel; Self; Abbott. Research Support; Self; Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., AstraZeneca, Takeda Pharmaceuticals U.S.A., Inc., Dexcom, Inc.. Stock/Shareholder; Self; Merck &amp; Co., Inc.. Research Support; Self; Eli Lilly and Company, Sanofi. Advisory Panel; Self; Sanofi, Roche Pharma. Research Support; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc.. Research Support; Self; Medtronic. Consultant; Self; Medtronic. Research Support; Self; Hygieia. Advisory Panel; Self; Hygieia, Glooko, Inc.. Research Support; Self; JAEB Center For Health Research, JDRF, National Institute of Diabetes and Digestive and Kidney Diseases. M.A. Clements: Speaker's Bureau; Self; Medtronic. Advisory Panel; Self; Glooko, Inc. M.R. Rickels: Consultant; Self; Hua Medicine, Xeris Pharmaceuticals, Inc.. E. Smith: None. B.A. Olson: None. R. Beck: Consultant; Self; Eli Lilly and Company. Research Support; Self; Abbott. Consultant; Self; Bigfoot Biomedical. Research Support; Self; Dexcom, Inc.. Consultant; Self; Insulet Corporation. Research Support; Self; Roche Diabetes Care Health and Digital Solutions. Consultant; Self; Merck &amp; Co., Inc., Xeris Pharmaceuticals, Inc..

Diabetes Care, Dec 22, 2022

American Journal of Kidney Diseases, Sep 1, 2021

Optimal glycemic control in kidney transplant recipients with diabetes is associated with improve... more Optimal glycemic control in kidney transplant recipients with diabetes is associated with improved morbidity, mortality and allograft survival. Transplant options for patients with diabetes requiring insulin therapy and chronic kidney disease who are suitable candidates for kidney transplantation should include consideration of β-cell replacement therapy: pancreas or islet transplantation. International variation, related to national regulatory policies, exists in offering one or both of these options to suitable candidates, and is further affected by pancreas/islet allocation policies and waiting list dynamics. Selection of appropriate candidates depends on patient age, co-existent morbidities, timing of referral to the transplant center (pre-vs. on dialysis) and availability of living kidney donors. Early referral is therefore of the utmost importance (ideally when eGFR is <30 ml/min/1.73 m2), to ensure adequate time for informed decision making and thorough pre-transplant evaluation. Obesity, CVD, peripheral vascular disease, smoking, and frailty are some of the conditions that need to be considered prior to acceptance on the transplant list, and ideally prior to dialysis becoming imminent. This review offers insights into selection of pancreas/islet transplant candidates by transplant centers and an update on post-transplant outcomes, which may have practice implications for referring nephrologists.

Journal of diabetes science and technology, Jul 14, 2023

Background: This study assessed changes in actigraphy-estimated sleep and glycemic outcomes after... more Background: This study assessed changes in actigraphy-estimated sleep and glycemic outcomes after initiating automated insulin delivery (AID). Methods: Ten adults with long-standing type 1 diabetes and impaired awareness of hypoglycemia (IAH) participated in an 18-month clinical trial assessing an AID intervention on hypoglycemia and counter-regulatory mechanisms. Data from eight participants (median age = 58 years) with concurrent wrist actigraph and continuous glucose monitoring (CGM) data were used in the present analyses. Actigraphs and CGM measured sleep and glycemic control at baseline (one week) and months 3, 6, 9, 12, 15, and 18 (three weeks) following AID initiation. HypoCount software integrated actigraphy with CGM data to separate wake and sleep-associated glycemic measures. Paired sample t-tests and Cohen’s d effect sizes modeled changes and their magnitude in sleep, glycemic control, IAH (Clarke score), hypoglycemia severity (HYPO score), hypoglycemia exposure (CGM), and glycemic variability (lability index [LI]; CGM coefficient-of-variation [CV]) from baseline to 18 months. Results: Sleep improved from baseline to 18 months (shorter sleep latency [ P &lt; .05, d = 1.74], later sleep offset [ P &lt; .05, d = 0.90], less wake after sleep onset [ P &lt; .01, d = 1.43]). Later sleep onset ( d = 0.74) and sleep midpoint ( d = 0.77) showed medium effect sizes. Sleep improvements were evident from 12 to 15 months after AID initiation and were preceded by improved hypoglycemia awareness (Clarke score [ d = 1.18]), reduced hypoglycemia severity (HYPO score [ d = 2.13]), reduced sleep-associated hypoglycemia (percent time glucose was &lt; 54 mg/dL, &lt; 60 mg/dL,&lt; 70 mg/dL; d = 0.66-0.81), and reduced glucose variability (LI, d = 0.86; CV, d = 0.62). Conclusion: AID improved sleep initiation and maintenance. Improved awareness of hypoglycemia, reduced hypoglycemia severity, hypoglycemia exposure, and glucose variability preceded sleep improvements. This trial is registered with ClinicalTrials.gov NCT03215914 https://clinicaltrials.gov/ct2/show/NCT03215914 .

Diabetes, Jun 20, 2023

PI-CF is characterized by impaired insulin secretion with disruption of the enteroinsular axis an... more PI-CF is characterized by impaired insulin secretion with disruption of the enteroinsular axis and alterations in incretin secretion and action. We have reported augmented glucose-dependent insulin secretion to glucose-potentiated arginine (GPA) testing with GLP-1 infusion but not GIP, with these effects independent of glucose tolerance in PI-CF. We aimed to assess the effect of incretin infusion on insulin clearance during GPA testing and explore its relationship to second-phase insulin response in individuals with PI-CF in a retrospective analysis. Thirty-two individuals with PI-CF and abnormal glucose tolerance underwent GPA testing of islet function following intravenous infusion of incretin or placebo in a randomized cross-over study design. Sixteen individuals were randomized to incretin infusion with GLP-1 and sixteen with GIP. Insulin clearance was assessed by the molar ratio of acute C-peptide to insulin response over the 5-minutes following glucose-potentiation of arginine-induced insulin and C-peptide secretion (target glucose ~230 mg/dL). Insulin clearance was related to second-phase insulin secretion by hyperbolic function (y=P1/(P2 + x) with a reduction in insulin clearance for increasing second-phase insulin secretion (R2=0.20; p&lt;0.001). A reduction in insulin clearance was observed with both GLP-1 vs. placebo (mean±SD 2.7±2.1 vs. 15.5±5.7; p&lt;0.001) and GIP vs. placebo (2.4±0.8 vs. 18.0±10.8; p&lt;0.001). GLP-1 and GIP appear to reduce insulin clearance in individuals with PI-CF presumably through effects at the liver. Reduced insulin clearance is most apparent following GIP infusion where there is no augmentation of second-phase insulin secretion, supporting that the effect of GIP occurs independently of an increase in pre-hepatic insulin secretion. Further work should explore underlying mechanisms of incretin-induced reduction in insulin clearance in PI-CF that could support therapeutic approaches to improve glucose homeostasis. Disclosure A.Flatt: None. A.Doliba: None. A.J.Peleckis: None. R.C.Rubenstein: None. A.Kelly: None. M.R.Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Research Support; Dompé. Funding National Institutes of Health (R01DK97830, UL1TR001878, P30DK19525, T32DK007314); Cystic Fibrosis Foundation (to M.R.R.)

Frontiers in endocrinology, Feb 20, 2024

Insulin secretion within 30 minutes of nutrient ingestion is reduced in people with cystic fibros... more Insulin secretion within 30 minutes of nutrient ingestion is reduced in people with cystic fibrosis (PwCF) and pancreatic insufficiency and declines with worsening glucose tolerance. The glucose potentiated arginine (GPA) test is validated for quantifying b-cell secretory capacity as an estimate of functional b-cell mass but requires technical expertise and is burdensome. This study sought to compare insulin secretion during mixed-meal tolerance testing (MMTT) to GPA-derived parameters in PwCF. Methods: Secondary data analysis of CF-focused prospective studies was performed in PwCF categorized as 1) pancreatic insufficient [PI-CF] or 2) pancreatic sufficient [PS-CF] and in 3) non-CF controls. MMTT: insulin secretory rates (ISR) were derived by parametric deconvolution using 2compartment model of C-peptide kinetics, and incremental area under the curve (AUC) was calculated for 30, 60 and 180-minutes. GPA: acute insulin (AIR) and C-peptide responses (ACR) were calculated as average post-arginine insulin or C-peptide response minus pre-arginine insulin or C-peptide under fasting (AIR arg and ACR arg),~230 mg/dL (AIR pot and ACR pot), and~340 mg/dL (AIR max and ACR max) hyperglycemic clamp conditions. Relationships of MMTT to GPA parameters were derived using Pearson's correlation coefficient. Predicted values were generated for MMTT ISR and compared to GPA parameters using Bland Altman analysis to assess degree of concordance. Results: 85 PwCF (45 female; 75 PI-CF and 10 PS-CF) median (range) age 23 (6-56) years with BMI 23 (13-34) kg/m 2 , HbA 1c 5.5 (3.8-10.2)%, and FEV1%-predicted 88 (26-125) and 4 non-CF controls of similar age and BMI were included. ISR AUC 30min positively correlated with AIR arg (r=0.55), AIR pot (r=0.62), and AIR max (r=0.46) and with ACR arg (r=0.59), ACR pot (r=0.60), and ACR max (r=0.51) (all Frontiers in Endocrinology frontiersin.org 01

The Lancet, Oct 1, 2019

The primary goal of treatment for type diabetes is to control glycemia with insulin therapy in or... more The primary goal of treatment for type diabetes is to control glycemia with insulin therapy in order to reduce disease complications. For some patients, technological approaches to insulin delivery are inadequate, and allogeneic islet transplantation is a safe alternative for those who have experienced severe hypoglycemia complicated by hypoglycemia unawareness or glycemic lability, or who already receive immunosuppression for a kidney transplant. Since 2000, intrahepatic islet transplantation has proven long-term efficacy in alleviating the burden of labile diabetes and preventing long-term diabetes-related complications, whether or not a prior kidney graft is present. Age, body mass index, renal and cardiopulmonary status help to choose between pancreas or islet transplantation. Access is presently limited by the number of deceased donors and the necessity of immunosuppression. Future approaches may include alternative sources of islets (xenogeneic tissue, human stem cells), extra-hepatic sites of implantation (omental, sucutaneous, intramuscular), and immune tolerance or encapsulation. Search strategy and selection criteria Data for this review were identified by searching MEDLINE, PubMed, Pubmed clinical trials, and references from relevant articles using the search terms "islet transplantation", "clinical" and "type 1 diabetes", as well as "β-cell", "stem cell", "xenotransplantation", "immune tolerance". Articles published between 1990 and 2019 were included. We mostly selected publications from the past five years but did not exclude commonly referenced and highly regarded older publications. We also searched the reference lists of articles identified by this search and selected those we judged relevant. Review articles are cited to provide readers with more details. Pancreas transplantation and islet auto-transplantation were excluded from this review.

Diabetes Technology & Therapeutics, Jun 20, 2023

Diabetes, Jun 20, 2023

Prior exposure to hypoglycemia and exercise may each dampen the sympathoadrenal response to subse... more Prior exposure to hypoglycemia and exercise may each dampen the sympathoadrenal response to subsequent hypoglycemia, leading to impaired awareness of hypoglycemia (IAH) and increased risk for experiencing clinically significant hypoglycemia. Whether glucose changes during exercise differ in those with IAH vs. intact awareness of hypoglycemia (Aware) has not been assessed in a large sample of ambulatory adults with type 1 diabetes, nor is the risk for hypoglycemia events in the next 24 hours known in such individuals. Using a case-control design, we compared participants with IAH (Clarke score ≥4 or ≥1 severe hypoglycemic event [SHE] within the past year) to Aware participants (Clarke score of ≤2 and no SHE within the past year), matching on sex, insulin modality, baseline HbA1c, and age. The analysis cohort included 95 adults with IAH matched to 95 Aware adults (in both groups, 74% female, mean ± SD age of 43 ± 14 yr, and HbA1c of 6.5 ± 0.7%) with a total of 4,236 exercise sessions and 1,794 post-exercise and 839 sedentary days available for analysis. IAH had a trend toward a greater but not clinically significant decline in glucose during exercise compared to Aware (−21 ± 44 vs. −19 ± 43 mg/dL, adjusted group difference of −4.2 [95% CI: −8.7 to 0.3] mg/dL, p=0.06). IAH had a higher proportion of hypoglycemic events (≥15 minutes &lt;70 mg/dL) vs. Aware on both post-exercise days (51% vs. 43%, p=0.008) and sedentary days (48% vs. 30%, p=0.002). There was no evidence that the increased odds of hypoglycemia for IAH compared with Aware differed between post-exercise and sedentary days (interaction p=0.36). In summary, participants with IAH have an overall higher baseline risk of hypoglycemia than Aware participants. However, for those with IAH exercise itself does not appear to differentially increase the risk for hypoglycemia during the activity, or in the subsequent 24 hours compared to Aware individuals with type 1 diabetes. Disclosure J.L. Jo Kamimoto: None. Z. Li: None. R.L. Gal: None. J.R. Castle: Research Support; Dexcom, Inc. Advisory Panel; Novo Nordisk. Stock/Shareholder; Pacific Diabetes Technologies. Advisory Panel; Zealand Pharma A/S. F.J. Doyle: Stock/Shareholder; Mode AGC. Other Relationship; Insulet Corporation, Roche Diabetes Care, Dexcom, Inc. P.G. Jacobs: Other Relationship; Pacific Diabetes Technologies. Board Member; Pacific Diabetes Technologies. Research Support; Dexcom, Inc. C.K. Martin: Research Support; Pack Health, Evidation Health, Lilly. Board Member; EHE Health, Wondr Health. Other Relationship; ABGIL. Research Support; WW International, Inc. R. Beck: Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company. Consultant; Eli Lilly and Company. Research Support; Novo Nordisk. Consultant; Novo Nordisk, Diasome, Insulet Corporation. P. Calhoun: None. M. Riddell: Stock/Shareholder; Supersapiens. Advisory Panel; Zealand Pharma A/S. Speaker's Bureau; Dexcom, Inc. Consultant; Lilly Diabetes. Speaker's Bureau; Novo Nordisk, Sanofi. Stock/Shareholder; Zucara Therapeutics. Advisory Panel; Zucara Therapeutics, Indigo Diabetes. Consultant; Eli Lilly and Company, Jaeb Center for Health Research. M.R. Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S. Research Support; Dompé. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Verily Life Sciences; Dexcom, Inc.

Sleep, May 25, 2022

Lincoln medical center 1 Introduction: Obstructive sleep apnea (OSA) is a sleep disorder that has... more Lincoln medical center 1 Introduction: Obstructive sleep apnea (OSA) is a sleep disorder that has been linked to increase the risk for hypertension, ischemic heart failure, arrhythmia and heart failure. There are multiple similarities between OSA and Chronic Obstructive Pulmonary Disease (COPD); both are associated with hypoxia and hypercapnia, with different mechanisms of hypoxia; in COPD its chronic and slow progression, whereas it is suddenly intermittent hypoxia in OSA. Intermittent hypoxia was hypothesized to enhance the protective effect on subsequent hypoxia resulting in cardioprotective effect [1]. There is little data on rates of in-hospital mortality on patients with OSA and COPD using a nationwide study. In this study, we aim to analyze the impact on mortality and length of hospital stay of obstructive sleep apnea in patients with COPD. Methods: Adults with principal diagnosis of COPD were selected from the 2019 US National Inpatient Sample, using ICD 10 code primary diagnosis on discharge. We queried the 2019 National Inpatient Sample for OSA, and other secondary diagnoses (hyperlipidemia, hypertension, heart failure, smoking, CKD, electrolytes disturbances). Confounders were adjusted for using multivariable linear regression analysis for other secondary diagnoses. Results: In a total of 520,624 adult hospitalizations with COPD primary diagnosis on discharge were included from the 2019 national inpatient sample. 73,705 patients had concomitant secondary diagnosis with OSA. On weighted analysis, hospitalizations with primary diagnosis of COPD and secondary diagnosis of OSA had lower in-hospital mortality rates compared to hospitalizations with COPD alone (0.6% vs 1.08%, p= 0.000), .COPD hospitalizations with OSA had statistically significant lower odds for mortality compared to COPD patients without OSA (adjusted OR 0.73, 95% CI 0.57-0.93; p= 0.009).However, COPD hospitalizations with OSA showed increased in the mean length of stay by 0.21 days (95% CI 0.12-0.30, p=0.000) compared to patients without OSA. Conclusion: Our analysis showed better mortality outcomes for COPD patients with OSA , supporting the protective effect hypothesis of intermittent hypoxia. COPD patients with concomitant secondary OSA diagnosis have increased in-hospital length of stay.

Journal of the Endocrine Society, Apr 1, 2020

enzymes normalized when her glucose levels normalized and DKA resolved. Further work-up ruled out... more enzymes normalized when her glucose levels normalized and DKA resolved. Further work-up ruled out more common etiologies of liver injury. Multiple abdominal ultrasounds and CT scans showed a normal sized liver without obvious structural abnormalities. Labs were significant for negative hepatitis B and hepatitis C; several negative anti-smooth muscle, anti-nuclear antibody, centromere antibody, and liver kidney microsomal type 1 antibody; normal levels of ceruloplasmin and alpha 1 anti-trypsin; low iron levels 23 ug/dL (60-180 ug/dL); borderline low IgG 627 mg/dL (700-1600 mg/dL). We hypothesized that the patient likely had GH by exclusion of other liver pathologies and given the context of transient transaminitis during DKA. Conclusion: GH is a benign and favorable diagnosis in diabetic patients with elevated transaminases. 1 Given the small number of cases of GH reported, there is a need to record and analyze more patients with likely GH in order to better understand the condition. Appropriate clinician awareness of GH can also eliminate the need for time consuming and costly workup.

Arteriosclerosis, Thrombosis, and Vascular Biology, May 1, 2013

Introduction Cardiovascular disease rates are higher in type II diabetes mellitus, but often it r... more Introduction Cardiovascular disease rates are higher in type II diabetes mellitus, but often it remains silent until too late. It is unknown if baseline EKG changes are associated with the degree of impaired insulin sensitivity or with other markers of diabetes control. We sought to investigate these relationships in the Penn Diabetes Heart Study (PDHS), a cross-sectional study of diabetic patients without overt coronary artery disease. Methods EKG intervals were measured in a subset of PDHS participants (n=732; mean age 59.4 ± 8.4 years, 66.5% males, 60.1% Caucasians). At the same visit, subjects underwent 75 g oral glucose tolerance testing after overnight fast with measurement of glucose and insulin at 0, 30, 60, and 120 minutes. The Matsuda Insulin Sensitivity Index (MISI) was calculated to estimate insulin sensitivity and the Insulinogenic Index (IGI) to estimate pancreatic beta-cell function. We used spearman correlations, chi-squared tests, and logistic regression to test associations of EKG changes with clinical factors, log-transformed MISI, and inverse normal-transformed IGI. Results In unadjusted analysis, there was a higher prevalence of left ventricular hypertrophy (LVH) (3.6% vs. 0.9%, p = 0.005) and ST changes (24.5% vs. 14.6%, p = 0.004) in African Americans compared to Caucasians. In fully adjusted models controlling for age, race, sex, history of hypertension and Framingham risk score, a higher MISI was associated with lower incidence of Q waves (OR 0.50, CI 0.33-0.76, p = 0.001). In addition, higher IGI scores were associated with a lower incidence of nonspecific ST changes (OR 0.82, CI 0.65-0.96, p= 0.035). There was also a trend for higher HbA1c values associated with LVH; however, this association was not statistically significant in fully adjusted models (OR 1.29, CI 0.90-1.86, p = 0.163). Conclusion Q wave abnormalities on routine EKGs were associated with reduced insulin sensitivity at baseline, while nonspecific ST changes were associated with lower pancreatic beta-cell function in patients with diabetes. Specific baseline EKG changes are indicators of the degree of metabolic disturbance in type 2 diabetes and may provide insight into the extent and risk of macrovascular and microvascular complications in diabetic patients.

Transplantation, Jul 22, 2022

Background. The long-term outcomes of both pancreas and islet allotransplantation have been compr... more Background. The long-term outcomes of both pancreas and islet allotransplantation have been compromised by difficulties in the detection of early graft dysfunction at a time when a clinical intervention can prevent further deterioration and preserve allograft function. The lack of standardized strategies for monitoring pancreas and islet allograft function prompted an international survey established by an International Pancreas and Islet Transplant Association/European Pancreas and Islet Transplant Association working group. Methods. A global survey was administered to 24 pancreas and 18 islet programs using Redcap. The survey addressed protocolized and for-cause immunologic and metabolic monitoring strategies following pancreas and islet allotransplantation. All invited programs completed the survey. Results. The survey identified that in both pancreas and islet allograft programs, protocolized clinical monitoring practices included assessing body weight, fasting glucose/C-peptide, hemoglobin A1c, and donor-specific antibody. Protocolized monitoring in islet transplant programs relied on the addition of mixed meal tolerance test, continuous glucose monitoring, and autoantibody titers. In the setting of either suspicion for rejection or serially increasing hemoglobin A1c/fasting glucose levels postpancreas transplant, Doppler ultrasound, computed tomography, autoantibody titers, and pancreas graft biopsy were identified as adjunctive strategies to protocolized monitoring studies. No additional assays were identified in the setting of serially increasing hemoglobin A1c levels postislet transplantation. Conclusions. This international survey identifies common immunologic and metabolic monitoring strategies utilized for protocol and for cause following pancreas and islet transplantation. In the absence of any formal studies to assess the efficacy of immunologic and metabolic testing to detect early allograft dysfunction, it can serve as a guidance document for developing monitoring algorithms following beta-cell replacement.

JBMR plus, Aug 3, 2020

Type 1 diabetes (T1D) increases fracture risk across the lifespan. The low bone turnover associat... more Type 1 diabetes (T1D) increases fracture risk across the lifespan. The low bone turnover associated with T1D is thought to be related to glycemic control, but it is unclear whether peripheral hyperinsulinemia due to dependence on exogenous insulin has an independent effect on suppressing bone turnover. The purpose of this study was to test the bone turnover marker (BTM) response to acute hyperinsulinemia. Fifty-eight adults aged 18 to 65 years with T1D over 2 years were enrolled at seven T1D Exchange Clinic Network sites. Participants had T1D diagnosis between age 6 months to 45 years. Participants were stratified based on their residual endogenous insulin secretion measured as peak C-peptide response to a mixed meal tolerance test. BTMs (CTX, P1NP, sclerostin [SCL], osteonectin [ON], alkaline phosphatase [ALP], osteocalcin [OCN], osteoprotegerin [OPG], osteopontin [OPN], and IGF-1) were assessed before and at the end of a 2-hour hyperinsulinemic-euglycemic clamp (HEC). Baseline ON (r = −0.30, p = .022) and OCN (r = −0.41, p = .002) were negatively correlated with age at T1D diagnosis, but baseline BTMs were not associated with HbA1c. During the HEC, P1NP decreased significantly (−14.5 AE 44.3%; p = .020) from baseline. OCN, ON, and IGF-1 all significantly increased (16.0 AE 13.1%, 29.7 AE 31.7%, 34.1 AE 71.2%, respectively; all p < .001) during the clamp. The increase in SCL was not significant (7.3 AE 32.9%, p = .098), but the decrease in CTX (−12.4 AE 48.9, p = .058) neared significance. ALP and OPG were not changed from baseline (p = .23 and p = .77, respectively). Baseline ON and SCL were higher in men, but OPG was higher in women (all p ≤ .029). SCL was the only BTM that changed differently in women than men. There were no differences in baseline BTMs or change in BTMs between C-peptide groups. Exogenous hyperinsulinemia acutely alters bone turnover, suggesting a need to determine whether strategies to promote healthy remodeling may protect bone quality in T1D.

About 30%-40% of Type 1 Diabetes (T1D) patients in the United States use insulin pumps. Current i... more About 30%-40% of Type 1 Diabetes (T1D) patients in the United States use insulin pumps. Current insulin infusion systems require users to manually input meal carb count and approve or modify the system-suggested meal insulin dose. Users can give correction insulin boluses at any time. Since meal carbohydrates and insulin are the two main driving forces of the glucose physiology, the user-specific eating and pump-using behavior has a great impact on the quality of glycemic control. In this paper, we propose an "Eat, Trust, and Correct" (ETC) framework to model the T1D insulin pump users' behavior. We use machine learning techniques to analyze the user behavior from a clinical dataset that we collected on 55 T1D patients who use insulin pumps. We demonstrate the usefulness of the ETC behavior modeling framework by performing in silico experiments. To this end, we integrate the user behavior model with an individually parameterized glucose physiological model, and perform probabilistic model checking on the user-in-the-loop system. The experimental results show that switching behavior types can significantly improve a patient's glycemic control outcomes. These analysis results can boost the effectiveness of T1D patient education and peer support.

Diabetes Technology & Therapeutics, Feb 1, 2021

Background: People with type 1 diabetes estimate meal carbohydrate content to accurately dose ins... more Background: People with type 1 diabetes estimate meal carbohydrate content to accurately dose insulin, yet, protein and fat content of meals also influences postprandial glycemia. We examined accuracy of macronutrient content estimation via a novel phone app. Participant estimates were compared with expert nutrition analyses performed via the Remote Food Photography Method© (RFPM©).Methods: Data were collected through a novel phone app. Participants were asked to take photos of meals/snacks on the day of and day after scheduled exercise, enter carbohydrate estimates, and categorize meals as low, typical, or high protein and fat. Glycemia was measured via continuous glucose monitoring.Results: Participants (n = 48) were 15–68 years (34 ± 14 years); 40% were female. The phone app plus RFPM© analysis captured 88% ± 29% of participants' estimated total energy expenditure. The majority (70%) of both low-protein and low-fat meals were accurately classified. Only 22% of high-protein meals and 17% of high-fat meals were accurately classified. Forty-nine percent of meals with <30 g of carbohydrates were overestimated by an average of 25.7 ± 17.2 g. The majority (64%) of large carbohydrate meals (≥60 g) were underestimated by an average of 53.6 ± 33.8 g. Glycemic response to large carbohydrate meals was similar between participants who underestimated or overestimated carbohydrate content, suggesting that factors beyond carbohydrate counting may impact postprandial glycemic response.Conclusions: Accurate estimation of total macronutrients in meals could be leveraged to improve insulin decision support tools and closed loop insulin delivery systems; development of tools to improve macronutrient estimation skills should be considered.

Diabetes, Jun 20, 2023

Social determinants of health (SDH), or the conditions in which people live, learn, work, play, a... more Social determinants of health (SDH), or the conditions in which people live, learn, work, play, and age strongly influence health inequities among adults with type 1 diabetes (T1D). Diabetes self-care, or daily behaviors performed to maintain health (maintenance), monitor for changes (monitoring), and manage illness (management), is essential for T1D management, but may also be impacted by SDH. We aimed to determine if SDH predicted self-care maintenance, monitoring and management, and if so, identify which SDH items were the most salient predictors. A diverse sample of adults with T1D (n=200, 27% Black, 61% female, median age: 35 years, disease duration: 19 years) completed an SDH risk assessment (PRAPARE tool; Risk Tally Scoring Method applied to 14 items to yield a composite risk score) and self-care assessment (Self-Care of Diabetes Inventory [SCODI]; 3 self-care [maintenance, monitoring, and management] and 1 confidence scale). A multivariable linear regression model of each self-care scale was built with SDH risk and confidence as predictors of self-care. For each self-care scale exhibiting a significant association with SDH risk, an exploratory multivariable model was built to determine which of the 14 SDH items were the most salient predictors. SDH risk was a significant predictor of self-care maintenance. For every 1 unit increase in SDH risk, maintenance was estimated to decrease by 1.14 units (p&lt; .01). Exploratory multivariable analysis revealed employment insecurity and material insecurity to be the most salient SDH risk predictors of maintenance. Participants who were not employed full-time were estimated to have maintenance scores 5.15 ± 2.27 units (p&lt;.05) less. For every 1 unit increase in material insecurity (score range:0 - 7), estimated maintenance decreased by 2.6 ± .89 units (p &lt; .01). Those with higher SDH risks are less likely to perform behaviors to maintain health. Providers may facilitate self-care of patients by assessing SDH risks and offering self-care guidance considerate of SDH risks. Disclosure A. M. Matus: None. B. Riegel: None. M. R. Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Research Support; Dompé. Funding National Institutes of Health (31NR020137, R01DK091331)

Diabetes, Jun 20, 2023

Achieving 7-10K steps per day is recommended to maintain health; however, the influence of step c... more Achieving 7-10K steps per day is recommended to maintain health; however, the influence of step count on time in range (70-180mg/dL: TIR), time above range (&gt;180mg/dL: TAR), and time below range (&lt;70mg/dL: TBR) in adults with T1D on different insulin delivery modalities (multiple daily injections [MDI], standard pump [SP], closed loop system [CLS]) is unclear. Using data from the Type 1 Diabetes Exercise Initiative, we examined the impact of failing to meet (&lt;7k), meeting (7k-10k) and exceeding (&gt;10k) step count goal on glycemic outcomes by insulin modality. Adults with T1D (37±14 yrs, 73% F, A1C 6.6±0.7%) wore a Verily Study Watch and CGM (Dexcom G6) for 4 weeks. Participants had at least two days where they failed to meet, met, and exceeded step count goal. For all users, mean TIR was 2% lower and TAR was 2% higher on days when participants failed to meet step count goal compared to meeting or exceeding step goal. TBR was 0.3% higher on days exceeding step count goal compared to failing to meet or meeting goal. Trends were similar across insulin delivery modalities, but variation differed, which affected significance levels. Meeting or exceeding 7-10K steps per day is associated with marginal improvements in TIR in adults with T1D. Disclosure L.Turner: None. F.J.Doyle: Other Relationship; Insulet Corporation, Roche Diabetes Care, Dexcom, Inc., Stock/Shareholder; Mode AGC. J.R.Castle: Advisory Panel; Novo Nordisk, Zealand Pharma A/S, Research Support; Dexcom, Inc., Stock/Shareholder; Pacific Diabetes Technologies. M.B.Gillingham: None. M.R.Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Research Support; Dompé. R.Beck: Consultant; Eli Lilly and Company, Novo Nordisk, Diasome, Insulet Corporation, Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company, Novo Nordisk. P.G.Jacobs: Board Member; Pacific Diabetes Technologies, Other Relationship; Pacific Diabetes Technologies, Research Support; Dexcom, Inc. M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Indigo Diabetes, Consultant; Lilly Diabetes, Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Novo Nordisk, Sanofi, Stock/Shareholder; Supersapiens, Zucara Therapeutics. T1dexi study group: n/a. C.Marak: None. P.Calhoun: None. R.L.Gal: None. Z.Li: None. G.Young: None. S.R.Patton: None. M.A.Clements: Consultant; Glooko, Inc., Research Support; Dexcom, Inc., Abbott Diabetes. C.K.Martin: Board Member; EHE Health, Wondr Health, Other Relationship; ABGIL, Research Support; Pack Health, Evidation Health, Lilly, WW International, Inc. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Verily Life Sciences; Dexcom, Inc.

Diabetes, Jul 1, 2018

In this report, we examined and compared changes in diabetes technology use and HbA1c levels from... more In this report, we examined and compared changes in diabetes technology use and HbA1c levels from data collected in 22,470 participants in the T1DX clinic registry (mean age 26±18 years, duration 14±13 years) between 2016 and 2017 with registry data collected from 25,529 participants (mean age 22±17 years, duration 10±12 years) between 2010 and 2012. There was a moderate increase in insulin pump use across all age groups from 57% in the 2010-12 cohort to 63% in the 2016-17 cohort. In contrast, continuous glucose monitoring (CGM) use rose sharply from 7% to 28%, with the most dramatic increase in the preadolescent and young child groups (4% to 35% for participants &lt;13 years old) (Table). Despite adjustments for differences in age and diabetes duration, mean HbA1c levels increased over time (from 8.2% in 2010-12 to 8.6% in 2016-17), with the greatest rise in participants 13-25 years old (Table). In both cohorts CGM users had lower HbA1c levels than non-users (7.6% in CGM users vs. 8.3% in non-users in 2010-12 and 7.9% in CGM users vs. 8.8% in non-users in 2016-17). Conclusion: In the T1D Exchange registry, HbA1c levels have increased although HbA1c remains lower in CGM users than non-users. Disclosure N.C. Foster: None. K. Miller: None. L. DiMeglio: Advisory Panel; Self; Eli Lilly and Company. Research Support; Self; Dexcom, Inc., Medtronic, Sanofi, Caladrius Biosciences, Inc., Janssen Research &amp; Development, Xeris Pharmaceuticals, Inc., Sanofi. D.M. Maahs: Advisory Panel; Self; Insulet Corporation. Consultant; Self; Abbott. Research Support; Self; Medtronic, Bigfoot Biomedical, Dexcom, Inc., Insulet Corporation, Roche Diabetes Care Health and Digital Solutions. W.V. Tamborlane: Consultant; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company, Medtronic MiniMed, Inc., Novo Nordisk Inc., Sanofi, Takeda Pharmaceuticals U.S.A., Inc. R.M. Bergenstal: Research Support; Self; Johnson &amp; Johnson Services, Inc.. Consultant; Self; Johnson &amp; Johnson Services, Inc.. Research Support; Self; Abbott. Advisory Panel; Self; Abbott. Research Support; Self; Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., AstraZeneca, Takeda Pharmaceuticals U.S.A., Inc., Dexcom, Inc.. Stock/Shareholder; Self; Merck &amp; Co., Inc.. Research Support; Self; Eli Lilly and Company, Sanofi. Advisory Panel; Self; Sanofi, Roche Pharma. Research Support; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc.. Research Support; Self; Medtronic. Consultant; Self; Medtronic. Research Support; Self; Hygieia. Advisory Panel; Self; Hygieia, Glooko, Inc.. Research Support; Self; JAEB Center For Health Research, JDRF, National Institute of Diabetes and Digestive and Kidney Diseases. M.A. Clements: Speaker's Bureau; Self; Medtronic. Advisory Panel; Self; Glooko, Inc. M.R. Rickels: Consultant; Self; Hua Medicine, Xeris Pharmaceuticals, Inc.. E. Smith: None. B.A. Olson: None. R. Beck: Consultant; Self; Eli Lilly and Company. Research Support; Self; Abbott. Consultant; Self; Bigfoot Biomedical. Research Support; Self; Dexcom, Inc.. Consultant; Self; Insulet Corporation. Research Support; Self; Roche Diabetes Care Health and Digital Solutions. Consultant; Self; Merck &amp; Co., Inc., Xeris Pharmaceuticals, Inc..

Diabetes Care, Dec 22, 2022

American Journal of Kidney Diseases, Sep 1, 2021

Optimal glycemic control in kidney transplant recipients with diabetes is associated with improve... more Optimal glycemic control in kidney transplant recipients with diabetes is associated with improved morbidity, mortality and allograft survival. Transplant options for patients with diabetes requiring insulin therapy and chronic kidney disease who are suitable candidates for kidney transplantation should include consideration of β-cell replacement therapy: pancreas or islet transplantation. International variation, related to national regulatory policies, exists in offering one or both of these options to suitable candidates, and is further affected by pancreas/islet allocation policies and waiting list dynamics. Selection of appropriate candidates depends on patient age, co-existent morbidities, timing of referral to the transplant center (pre-vs. on dialysis) and availability of living kidney donors. Early referral is therefore of the utmost importance (ideally when eGFR is <30 ml/min/1.73 m2), to ensure adequate time for informed decision making and thorough pre-transplant evaluation. Obesity, CVD, peripheral vascular disease, smoking, and frailty are some of the conditions that need to be considered prior to acceptance on the transplant list, and ideally prior to dialysis becoming imminent. This review offers insights into selection of pancreas/islet transplant candidates by transplant centers and an update on post-transplant outcomes, which may have practice implications for referring nephrologists.

Journal of diabetes science and technology, Jul 14, 2023

Background: This study assessed changes in actigraphy-estimated sleep and glycemic outcomes after... more Background: This study assessed changes in actigraphy-estimated sleep and glycemic outcomes after initiating automated insulin delivery (AID). Methods: Ten adults with long-standing type 1 diabetes and impaired awareness of hypoglycemia (IAH) participated in an 18-month clinical trial assessing an AID intervention on hypoglycemia and counter-regulatory mechanisms. Data from eight participants (median age = 58 years) with concurrent wrist actigraph and continuous glucose monitoring (CGM) data were used in the present analyses. Actigraphs and CGM measured sleep and glycemic control at baseline (one week) and months 3, 6, 9, 12, 15, and 18 (three weeks) following AID initiation. HypoCount software integrated actigraphy with CGM data to separate wake and sleep-associated glycemic measures. Paired sample t-tests and Cohen’s d effect sizes modeled changes and their magnitude in sleep, glycemic control, IAH (Clarke score), hypoglycemia severity (HYPO score), hypoglycemia exposure (CGM), and glycemic variability (lability index [LI]; CGM coefficient-of-variation [CV]) from baseline to 18 months. Results: Sleep improved from baseline to 18 months (shorter sleep latency [ P &lt; .05, d = 1.74], later sleep offset [ P &lt; .05, d = 0.90], less wake after sleep onset [ P &lt; .01, d = 1.43]). Later sleep onset ( d = 0.74) and sleep midpoint ( d = 0.77) showed medium effect sizes. Sleep improvements were evident from 12 to 15 months after AID initiation and were preceded by improved hypoglycemia awareness (Clarke score [ d = 1.18]), reduced hypoglycemia severity (HYPO score [ d = 2.13]), reduced sleep-associated hypoglycemia (percent time glucose was &lt; 54 mg/dL, &lt; 60 mg/dL,&lt; 70 mg/dL; d = 0.66-0.81), and reduced glucose variability (LI, d = 0.86; CV, d = 0.62). Conclusion: AID improved sleep initiation and maintenance. Improved awareness of hypoglycemia, reduced hypoglycemia severity, hypoglycemia exposure, and glucose variability preceded sleep improvements. This trial is registered with ClinicalTrials.gov NCT03215914 https://clinicaltrials.gov/ct2/show/NCT03215914 .

Diabetes, Jun 20, 2023

PI-CF is characterized by impaired insulin secretion with disruption of the enteroinsular axis an... more PI-CF is characterized by impaired insulin secretion with disruption of the enteroinsular axis and alterations in incretin secretion and action. We have reported augmented glucose-dependent insulin secretion to glucose-potentiated arginine (GPA) testing with GLP-1 infusion but not GIP, with these effects independent of glucose tolerance in PI-CF. We aimed to assess the effect of incretin infusion on insulin clearance during GPA testing and explore its relationship to second-phase insulin response in individuals with PI-CF in a retrospective analysis. Thirty-two individuals with PI-CF and abnormal glucose tolerance underwent GPA testing of islet function following intravenous infusion of incretin or placebo in a randomized cross-over study design. Sixteen individuals were randomized to incretin infusion with GLP-1 and sixteen with GIP. Insulin clearance was assessed by the molar ratio of acute C-peptide to insulin response over the 5-minutes following glucose-potentiation of arginine-induced insulin and C-peptide secretion (target glucose ~230 mg/dL). Insulin clearance was related to second-phase insulin secretion by hyperbolic function (y=P1/(P2 + x) with a reduction in insulin clearance for increasing second-phase insulin secretion (R2=0.20; p&lt;0.001). A reduction in insulin clearance was observed with both GLP-1 vs. placebo (mean±SD 2.7±2.1 vs. 15.5±5.7; p&lt;0.001) and GIP vs. placebo (2.4±0.8 vs. 18.0±10.8; p&lt;0.001). GLP-1 and GIP appear to reduce insulin clearance in individuals with PI-CF presumably through effects at the liver. Reduced insulin clearance is most apparent following GIP infusion where there is no augmentation of second-phase insulin secretion, supporting that the effect of GIP occurs independently of an increase in pre-hepatic insulin secretion. Further work should explore underlying mechanisms of incretin-induced reduction in insulin clearance in PI-CF that could support therapeutic approaches to improve glucose homeostasis. Disclosure A.Flatt: None. A.Doliba: None. A.J.Peleckis: None. R.C.Rubenstein: None. A.Kelly: None. M.R.Rickels: Consultant; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Research Support; Dompé. Funding National Institutes of Health (R01DK97830, UL1TR001878, P30DK19525, T32DK007314); Cystic Fibrosis Foundation (to M.R.R.)