Kudva, Yogish C.

OBJECTIVE Limited information is available about glycemic outcomes with a closed-loop control (CLC) system compared with a predictive low-glucose suspend (PLGS) system. RESEARCH DESIGN AND METHODS After 6 months of use of a CLC system in a randomized trial, 109 participants with type 1 diabetes (age range, 14–72 years; mean HbA1c, 7.1% [54 mmol/mol]) were randomly assigned to CLC (N = 54, Control-IQ) or PLGS (N = 55, Basal-IQ) groups for 3 months. The primary outcome was continuous glucose monitor (CGM)-measured time in range (TIR) for 70–180 mg/dL. Baseline CGM metrics were computed from the last 3 months of the preceding study. RESULTS All 109 participants completed the study. Mean ± SD TIR was 71.1 ± 11.2% at baseline and 67.6 ± 12.6% using intention-to-treat analysis (69.1 ± 12.2% using per-protocol analysis excluding periods of study-wide suspension of device use) over 13 weeks on CLC vs. 70.0 ± 13.6% and 60.4 ± 17.1% on PLGS (difference = 5.9%; 95% CI 3.6%, 8.3%; P < 0.001). Time >180 mg/dL was lower in the CLC group than PLGS group (difference = −6.0%; 95% CI −8.4%, −3.7%; P < 0.001) while time <54 mg/dL was similar (0.04%; 95% CI −0.05%, 0.13%; P = 0.41). HbA1c after 13 weeks was lower on CLC than PLGS (7.2% [55 mmol/mol] vs. 7.5% [56 mmol/mol], difference −0.34% [−3.7 mmol/mol]; 95% CI −0.57% [−6.2 mmol/mol], −0.11% [1.2 mmol/mol]; P = 0.0035). CONCLUSIONS Following 6 months of CLC, switching to PLGS reduced TIR and increased HbA1c toward their pre-CLC values, while hypoglycemia remained similarly reduced with both CLC and PLGS.

Abstract Introduction: Patients and their families and medical providers have assumed that psychologic stress impacts glucose control in T1D (Type 1 Diabetes) though studies providing confirmatory evidence in real world settings are, to our knowledge, lacking. We hypothesized that self-reported psychologic stress worsens glucose control in T1D. Method: We studied 20 adults with T1D on continuous glucose monitor (CGM), sensor augmented insulin pump (SAP) prospectively at 2 clinical research centers. Patients reported psychological stress through stress diaries for 5 weeks on a severity scale of 1-7 using hard copy logs including time of onset and offset of stress and severity. For analytic purpose, grades 1-4 are classified as mild and grades 5-7 as severe. Results: Baseline characteristics were age 44.9±15.0 years, F/M 12/8, HbA1c 6.8 ± 0.7%, and diabetes duration of 22.9±15.9 years. We analyzed glucose variability during days of stress versus days without stress. During a 24 hour period, patients experienced less hypoglycemia during days with stress versus days without stress (p value 0.03). During the 5 week period, patients reported 23 ± 19.5 events. We analyzed the impact of self-reported stress on CGM data streams after excluding stress events associated with missing CGM data, nocturnal events (from 12 MN to 6 AM, too few events) and events for which subjects did not provide duration of stress. Thus, we analyzed 19.5 ± 17 events per patient from 6AM to 12MN. From 6 AM to 12 MN, the episodes lasted 179 ± 255 minutes with 83 % episodes being mild/moderate and 17% moderate/ severe. Number of CGM readings during daytime stress episodes were 717± 1120 compared to 8768± 1238 during non-stress periods. Impact of stress from 6 AM to 12 MN (Mid-Night) on CGM glucose was analyzed using matched paired t test. Mean glucose (160.6±41.9 vs 148.3± 28.6) and SD (53.2 ±17.7 vs 56.1±14.6) did not show a difference; however % of time spent below 70 mg/dl was less (4 ± 5) in patients during stressful periods compared to times without stress (6.3± 5.5, P value 0.02). Conclusions: To our knowledge, this is the first study attempting to analyze the impact of self-reported stress using daily stress diaries on CGM data streams in T1D patients on SAP. The study revealed significant challenges experienced by patients in reporting adequate data. Self-reported stress was not associated with hyperglycemia. However, days of self-reported stress and periods during patients reported stress were characterized by less hypoglycemia on CGM data streams.

Abstract INTRODUCTION: Type 1 Diabetes (T1D) patients have an increased risk for major adverse cardiovascular events (MACE). Pancreas Transplantation Alone (PTA) in patients with T1D achieves near normal glucose control for a prolonged period but limited data are available to date regarding MACE during a 10 year follow up period after the procedure. OBJECTIVE: We studied incidence of MACE after PTA in T1D patients over a 10 year follow-up period. METHODS: Retrospectively, we studied 113 T1D recipients of PTA at Mayo Clinic, Rochester with the procedure performed between January 1998 and August 2018 and follow up of at least 1 year. Data were collected before transplantation and up to 10 year follow up after the first PTA. MACE data were gathered until primary non function, re-transplantation, or complete loss of c-peptide (<0.01ng/ml). We report vascular risk factors including hypertension, hyperlipidemia, smoking and BMI along with MACE (defined as cardiac events as unstable angina, Myocardial Infarction (MI), need for re-vascularization, cardiac death, cerebral events as Transient ischemic attack (TIA), stroke, need for re-vascularization and peripheral arterial disease as need for re-vascularization, gangrene and amputation). RESULTS: Eighteen subjects had pre-transplant MACE. A total of 14 subjects had graft failure within 24 to 36 hours due to thrombosis, with 3 in pre-transplant MACE cohort and 11 in no MACE cohort. Thus, we followed 99 subjects for the development of post-transplant MACE for a period of 6.3 ± 3.6 years. T1D subjects with MACE (n=15) had baseline characteristics: Age 48± 7.8 years, gender F/M 9/6,, duration of diabetes 33 ± 12 years, BMI 26± 3.1(Kg/m2), HbA1c 9.3 ± 1.5% and C-peptide 0.09 ng/ml. 84 T1D patients without MACE were age 42 ± 10.6 years, gender F/M 55/29, duration of diabetes 26.5 ± 10.7 years, BMI 26 ± 5.2(Kg/m2), HbA1c 6.7 ± 2.5 and C-peptide 0.09 ng/ml. There are a total of 584 person-years of follow up to first MACE event and 632 person-years of graft failure, death or last follow-up. Nine patients developed 11 MACE events post-PTA. Therefore, the event rate is 1.5 MACE events per 100 person-years for first MACE event and the total event rate is 1.7 MACE events per 100 person-years of follow-up. Age, smoking (yes), gender, duration of diabetes, HTN and Hyperlipidemia presence did not show any significant impact on post-transplant MACE outcome based on univariate Cox regression but the pre-transplant BMI (HR = 1.14; CI = (1.04, 1.26); p = 0.008) and pre-transplant HbA1c (HR = 1.26; CI = (1.06, 1.51); p = 0.01) showed statistically significant impact. CONCLUSIONS: At our center, MACE is low in PTA recipients. There is no impact of presence of pre-transplant MACE on development of post-transplant MACE but pre-transplant BMI and HbA1c account for risk of MACE.

Abstract Background Immunosuppressant therapeutic drug monitoring (TDM) usually requires outpatient travel to hospitals or phlebotomy sites for venous blood collection; however Mitra® Microsampling Device (MSD) sampling could allow self-collection and shipping of samples to a laboratory for analysis. This study examined the feasibility of using volumetric microsampling by MSD for TDM of tacrolimus (TaC) and cyclosporin A (CsA) in transplant patients, along with their feedback on the process. Methods MSD was used to collect TaC and CsA from venous (VB) or capillary (CB) blood. The MSDs were rehydrated, extracted, and analyzed using on-line solid phase extraction coupled to tandem mass spectrometry (SPE-MS/MS). We report an abbreviated method validation of the MSD including: accuracy, precision, linearity, carry-over, and stability using residual venous whole blood (VB) samples. Subsequent clinical validation compared serially collected MSD + CB against VB (200 µL) from transplant patients. Results Accuracy comparing VB vs. MSD+VB showed high clinical concordance (TaC = 89% and CsA = 98%). Inter- and intra-precision was ≤11.5 %CV for TaC and CsA. Samples were stable for up to 7 days at room temperature with an average difference of <10%. Clinical validation with MSD+CB correlated well with VB for CsA (slope = 0.95, r2 = 0.88, n = 47) and TaC (slope = 0.98, r2 = 0.82, n = 49). CB vs. VB gave concordance of 94% for CsA and 79% for TaC. A satisfaction survey showed 82% of patients preferred having the capillary collection option. Conclusion Transplant patients favored having the ability to collect capillary samples at home for TaC/CsA monitoring. Our results demonstrate good concordance between MSD+CB and VB for TaC and CsA TDM, but additional studies are warranted.

Background. Glucagon-like peptide-1 receptor agonists (GLP1RA) have been shown to improve glucose control and diabetes-related comorbidities in patients without solid organ transplants. The effectiveness, safety, and tolerability of GLP1RA after kidney transplantation have not been adequately studied. Methods. We retrospectively reviewed data on kidney transplant recipients performed in our institution, who were initiated on GLP1RA either for the treatment of type 2 diabetes diagnosed before transplantation or posttransplant diabetes. We analyzed efficacy, safety, and the effect on kidney allograft function. Results. Seventeen kidney transplant recipients were initiated on GLP1RA therapy, 14 of which remained on the medication for at least 12 months. The use of GLP1RA had no significant impact on weight loss, but was associated with a significant reduction in the total daily insulin dose, from the median of 63 [interquartile range 43-113] IU to 44 [interquartile range 25-88] and reduction in the risk of hypoglycemia in patients who were on therapy for at least approximately 12 months. Kidney function remained stable and none of the recipients experienced acute rejection. Tacrolimus dose was not significantly changed. Five patients (29%) discontinued GLP1RA therapy—4 due to side effects and 1 due to uncontrolled hyperglycemia. Conclusions. GLP1RA may be a relatively safe and effective treatment for kidney transplant recipients with type 2 diabetes that allows for a reduction in insulin requirements. More studies are needed to determine whether the use of these agents will translate into an improvement in allograft and patient survival.

OBJECTIVE Assess the efficacy of inControl AP, a mobile closed-loop control (CLC) system. RESEARCH DESIGN AND METHODS This protocol, NCT02985866, is a 3-month parallel-group, multicenter, randomized unblinded trial designed to compare mobile CLC with sensor-augmented pump (SAP) therapy. Eligibility criteria were type 1 diabetes for at least 1 year, use of insulin pumps for at least 6 months, age ≥14 years, and baseline HbA1c <10.5% (91 mmol/mol). The study was designed to assess two coprimary outcomes: superiority of CLC over SAP in continuous glucose monitor (CGM)–measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L. RESULTS Between November 2017 and May 2018, 127 participants were randomly assigned 1:1 to CLC (n = 65) versus SAP (n = 62); 125 participants completed the study. CGM time below 3.9 mmol/L was 5.0% at baseline and 2.4% during follow-up in the CLC group vs. 4.7% and 4.0%, respectively, in the SAP group (mean difference −1.7% [95% CI −2.4, −1.0]; P < 0.0001 for superiority). CGM time above 10 mmol/L was 40% at baseline and 34% during follow-up in the CLC group vs. 43% and 39%, respectively, in the SAP group (mean difference −3.0% [95% CI −6.1, 0.1]; P < 0.0001 for noninferiority). One severe hypoglycemic event occurred in the CLC group, which was unrelated to the study device. CONCLUSIONS In meeting its coprimary end points, superiority of CLC over SAP in CGM-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L, the study has demonstrated that mobile CLC is feasible and could offer certain usability advantages over embedded systems, provided the connectivity between system components is stable.

Background: Knowledge regarding the burden and predictors of hypoglycemia among older adults with type 1 diabetes (T1D) is limited. Methods: We analyzed baseline data from the Wireless Innovations for Seniors with Diabetes Mellitus (WISDM) study, which enrolled participants at 22 sites in the United States. Eligibility included clinical diagnosis of T1D, age ≥60 years, no real-time continuous glucose monitoring (CGM) use in prior three months, and HbA1c <10.0%. Blinded CGM data from 203 participants with at least 240 hours were included in the analyses. Results: Median age of the cohort was 68 years (52% female, 93% non-Hispanic white, and 53% used insulin pumps). Mean HbA1c was 7.5%. Median time spent in the glucose range <70 mg/dL was 5.0% (72 min/day) and <54 mg/dL was 1.6% (24 min/day). Among all factors analyzed, only reduced hypoglycemia awareness was associated with greater time spent <54 mg/dL (median time of 2.7% vs 1.3% [39 vs 19 minutes per day] for reduced awareness vs aware/uncertain, respectively, P = .03). Participants spent a mean 56% of total time in target glucose range of 70-180 mg/dL and 37% of time above 180 mg/dL. Conclusions: Over half of older T1D participants spent at least an hour a day with glucose levels <70 mg/dL. Those with reduced hypoglycemia awareness spent over twice as much time than those without in a serious hypoglycemia range (glucose levels <54 mg/dL). Interventions to reduce exposure to clinically significant hypoglycemia and increase time in range are urgently needed in this age group.

Abstract Background: PTLD is the most common malignancy, other than non-melanoma skin cancer, complicating solid organ transplantation (SOT) and has been one of the most commonly observed fatal consequences in SOT. The clinical presentations, management strategies, histologies, causes of death and outcomes are diverse (Dierickx D, Habermann TM. N Engl J Med 2018;378:549-62). The 2017 WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues has redefined the categories as non-destructive PTLDs (plasmacytic hyperplasia, infectious mononucleosis, and florid follicular hyperplasia), polymorphic PTLD, monomorphic PTLD: B-cell neoplasms (diffuse large B-cell lymphoma, Burkitt lymphoma, high-grade B-cell lymphoma, plasmablastic lymphoma, plasma cell myeloma, plasmacytoma, and other) and T-cell neoplasms (peripheral T-cell lymphoma NOS, hepatosplenic T-cell lymphoma, other), and classic Hodgkin lymphoma (CHL) PTLD. We report the outcomes and long-term follow-up of patients from a single institution based on these categories whose pathology was retrospectively reviewed and reclassified based on the WHO 2017 classification. Methods: Patients with SOT who were diagnosed with PTLD at Mayo Clinic (Rochester, MN) were identified through the Mayo Clinic Lymphoma Data base and the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER). The histology was re-reviewed in 80% of the cases (RLK) and classified according to the WHO Classification of Tumours of Haematopoietic an Lymphoid Tissues 2017. Cases were considered "PTLD, unclassified" if the histology could not be confidently classified based on pathology material available for review. Indolent small B-cell lymphomas were not included among the PTLDs except for EBV-positive marginal zone lymphoma. Cox proportional hazards models were used to assess the association of clinical factors in overall survival (OS). Results: 233 patients diagnosed with PTLD between 1987 and 2017 were identified. The median age at the time of diagnosis of PTLD was 54 years (range 16 to 84) with 85 patients (36%) over the age of 60. 156 (67%) were male. The transplanted organs were kidney (41%), kidney/pancreas (5%), liver (29%), heart (9%), lung (7%), and other (8%). PTLD occurred late (more than one year after transplantation) in 66%. There were 69 stage I, 19 stage II, 8 stage III, and 128 stage IV patients. 84% presented with extranodal disease. 21% had involvement of the engrafted organ. 64% of the patients developed a PTLD that was EBV positive by in situ hybridization. Initial approaches to management included reduction of immunosuppression (N=55), chemotherapy/immunochemotherapy (N=71), reduction in immunosuppression with rituximab (N=58), single agent rituximab (N=14), and radiation therapy (N=5). At a median follow-up of 87 months (range 9-289), 139 (60%) patients had died. All six CHL-PTLD patients are alive, two of whom had an event. The median overall survival (OS) was 85 months (95% CI: 39-144) in 177 monomorphic B-cell lymphoma PTLD, 95.5 months (95% CI: 40-not reached) in 24 polymorphic PTLD, and 60 months in 8 non-destructive PTLD cases. In contrast, the median overall survival was 12 months (95% CI: 4-200) in 8 monomorphic T cell and 3 months (95% CI: 1-unreached) in 9 unclassified PTLD cases. Conclusion: PTLD is a heterogeneous group of immunodeficiency-associated lymphoproliferative disorders. The overall survival in non-destructive, polymorphic, and monomorphic PTLD were similar. Monomorphic T/NK cell types had inferior outcomes. Figure. Figure. Disclosures Maurer: Morphosys: Research Funding; Nanostring: Research Funding; Celgene: Research Funding. Ansell:Celldex: Research Funding; Merck & Co: Research Funding; Takeda: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Pfizer: Research Funding. Cerhan:Celgene: Research Funding; Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board.