bluuebunny/crossref_metadata_2025_split huggingface dataset:
844-P: Impact of Hypoglycemic Awareness on Diabetes Care during the SARS CoV Pandemic
Authors: WATT CHARLES , KNIGHT MARI-LYNET , RANGEL ELIZABETH SANCHEZ , GUNAWAN FELONA , HWANG JANICE J. 
Published: June 2021

A recent report by Potier et al found that patients with T1DM had improved glycemic control during the pandemic, possibly due to changes in behavioral and lifestyle patterns. However, very little is known regarding how patients with normal hypoglycemia unawareness (NAH) or impaired awareness (IAH) have responded to changes in diabetes management during the pandemic.
Fifteen participants with T1DM from the Greater New Haven area participated in this study, which is part of a larger ongoing clinical study. Participants completed questionnaires measuring awareness (Clarke Score), current quality of diabetes care (Diabetes Treatment Satisfaction), and symptom severity (Hypo AQ) twice, pre-pandemic (prior to March 2020) and during pandemic (September to November 2020). Nine individuals had NAH (3F/6M, Clarke mean 1.00 ± SEM 0.4, age 32 ± 12 yrs, A1C 8.2 ± 1.3%, BMI 24.7 ± 4.7) and six had IAH, (4F/2M, Clarke 4.33 ± .3, age 39 ± 14, A1C 7.3 ± 0.9%, BMI 30.1 ± 7.4). There were no significant demographic differences between groups except for Clarke score.
Among IAH patients, symptom severity (pre: 13.8 ± 0.910, during: 11.50 ± 0.957, p = 0.04) and treatment satisfaction (pre: 26.17 ± 1.99, during: 31.33 ± 1.542, p = 0.013) were significantly improved during the pandemic. Self-reported frequency of hypoglycemic episodes was unchanged (p = 0.741). In contrast, among NAH participants, there were no changes in severity of symptoms (p = 0.822), satisfaction of treatment (p = 0.407), or frequency of hypoglycemic episodes (p = 1.000).
Our results indicate that pandemic associated changes in diabetes care and management had differential effects on patients with and without hypoglycemic unawareness. Further studies to identify the specific factors driving these differences will be beneficial to improving the clinical care of patients with IAH.

Disclosure
C. Watt: None. M. Knight: None. E. Sanchez rangel: None. F. Gunawan: None. J. J. Hwang: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (DK020495)
857-P: A Risk Stratification Approach to Diabetes Care Delivery Services
Authors: ZUPA MARGARET , KRALL JODI S. , COLLINS KEVIN , NG JASON , SIMINERIO LINDA M. 
Published: June 2021

Diabetes self-management education and support (DSMES) is known to improve diabetes treatment outcomes, but this limited resource is not always targeted toward the highest risk patients in current models of care. Predictive modeling, which relies on large data sets to predict outcomes, is one tool which can be used to direct resources to patients with the greatest need for these services.
University of Pittsburgh Medical Center (UPMC) diabetes care providers along with members of the clinical analytics team created a predictive model, including patient age, HbA1c, and insulin use among other factors, to assess individual patient risk of future poor glycemic control. The model was applied to patients who received DSMES via diabetes care and education specialists (DCES) from December 2018 to December 2020 to evaluate the impact of DSMES according to risk strata. Patients were categorized into high, medium and low risk groups based on clinical data prior their initial DSMES encounter. HbA1c change was calculated using the HbA1c prior to DSMES and most recent HbA1c.
Of 1,247 patients eligible for retrospective assessment, 50% were categorized as low risk (n=621), 4% (n=55) medium, and 46% high risk (n=571). Mean HbA1c change after DSMES was -0.54% for low risk, -0.72% for medium risk, and -1.19% for the high risk group. Mean HbA1c after DSMES was 7.6% for low risk, 9.7% for medium risk and 9.6% for high risk patients. 57.5% of low, 59% of medium and 46.6% of high risk patients were seen by an endocrinologist.
In this analysis, high risk patients who received DSMES had larger improvement in HbA1c and were less likely to be seen by an endocrinologist. To optimize utilization of diabetes care regarding DCES, predictive modeling can be used to target resources to the highest risk patients.

Disclosure
M. Zupa: None. J. S. Krall: Research Support; Self; Becton, Dickinson and Company, Sanofi. K. Collins: None. J. Ng: Research Support; Self; Sanofi-Aventis. L. M. Siminerio: Advisory Panel; Self; Abbott Diabetes, Bayer U. S., Research Support; Self; Becton, Dickinson and Company.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (5T32DK007052-45)
864-P: Treatment Burden and Quality of Life Conversations during Clinical Encounters: A Videographic Analysis
Authors: HAIDER SHANZAY , EL KAWKGI OMAR M. , CLARK JENNIFER , BRESLIN MAGGIE , BOEHMER KASEY , MONTORI VICTOR M. , LIPSKA KASIA J. 
Published: June 2021

Aim: Patients with diabetes mellitus (DM) experience significant burden of disease and poorer quality of life compared with patients without diabetes. Yet, data on how these aspects are raised, discussed, and addressed during clinical encounters are sparse. We aimed to analyze the nature of discussions about quality of life (QoL), treatment burden (TB), hypoglycemia, sexual function, and social support during clinician-patient encounters focused on diabetes care.
Methods: A total of 41 previously recorded patient-clinician encounters were used for videographic analysis. Encounters were recorded primarily from family medicine and internal medicine clinics, and all patients had a diagnosis of DM. Two coders analyzed the videos for discussions about QoL, TB, hypoglycemia, sexual function, and social support using an a priori developed codebook that defined the domains. When a topic was raised, coders evaluated the nature of the conversation, provider response, time spent on topic, and any solutions proposed by the clinician.
Results: Of the 41 videos analyzed, 85.4% included some discussion regarding QoL (58.5%), TB (51.2%), social support (9.8%) or hypoglycemia (2.4%). Sexual function was not brought up in any of the encounters. On average, 15% of the clinical encounter time was spent on QoL, TB, social support, or hypoglycemia. In contrast, 4.5% of the encounter focused on HbA1c. When an aspect arose within the encounter, clinicians acknowledged the patient’s concern without providing a solution in 45.8% of the cases.
Conclusion: Consistent with patient experiences, we found that a significant portion of clinical encounters conversations were devoted to QoL and TB, with a greater amount of time spent on these than HbA1c goals. Yet, when these topics arose during encounters, solutions were seldom provided. Sexual dysfunction, a common complication of DM, was not discussed in our sample.

Disclosure
S. Haider: None. O. M. El kawkgi: None. J. Clark: None. M. Breslin: None. K. Boehmer: None. V. M. Montori: None. K. J. Lipska: None.
867-P: Variation in the Setting of Type 2 Diabetes Diagnosis Disclosure
Authors: GU KRISTINE , GONG CHELSEA , BLATCHINS MARUTA A. , MISHRA PRANITA , GRANT RICHARD W. , GOPALAN ANJALI 
Published: June 2021

The disclosure of a new type 2 diabetes (T2D) diagnosis shapes patients’ T2D-related experiences, with more supportive approaches linked with better self-care and lower diabetes distress. Given changes in patient-provider communication and greater use of telemedicine, we examined the setting of T2D disclosures among adults in a large, integrated healthcare delivery system.
Physicians reviewed charts of a random sample of 200 adults diagnosed with T2D between 2014-2018 to determine the diagnosis disclosure setting. Identified settings were an in-person visit, telemedicine visit (telephone/video), secure message via the online patient portal, mailed letter, or voicemail. These settings were further categorized into 2-way synchronous communication (in-person/telemedicine), 2-way asynchronous communication (secure message), and 1-way asynchronous communication (letter/voicemail). We examined differences in disclosure setting by patient demographics.
The disclosure setting was discernible for 197/200 individuals; 55.3% received the diagnosis via 2-way synchronous communication (25.4% in-person, 29.9% telemedicine), 23.9% via 2-way asynchronous communication, and 20.8% via 1-way asynchronous communication (18.8% letter, 2% voicemail). Disclosure setting did not differ by age, gender, or level of neighborhood deprivation. Latinx individuals were overrepresented among those receiving the diagnosis via 1-way asynchronous communication (42.5% vs. 17.1% 2-way synchronous vs. 8.7% 2-way asynchronous, p=0.001) and had lower online patient portal enrollment (59%).
The heterogeneity in T2D diagnosis disclosure setting suggests a lack of standard practices for communicating a T2D diagnosis. The common use of asynchronous modalities is concerning given the gravity of the diagnosis, especially when established best practices for communicating bad news to patients exist.

Disclosure
K. Gu: None. C. Gong: None. M. A. Blatchins: None. P. Mishra: None. R. W. Grant: None. A. Gopalan: None.

Funding
Kaiser Permanente Northern California
872-P: Impact of Telemedicine Consultations during the COVID-19 Pandemic on Glycemic Control of Diabetes Patients
Authors: DISSANAYAKE ASHINI , PAWLOWSKA MONIKA , SCHROEDER BENJAMIN , MACKENZIE-FEDER JESSICA , WHITE ADAM 
Published: June 2021

Due to the COVID-19 pandemic, our endocrinology clinic transitioned to virtual care on March 18, 2020. The literature suggests that self-monitoring of blood glucose paired with telemedicine consultations is an effective strategy for diabetes management, however it is unclear whether telemedicine remains effective in the context of the sudden lifestyle changes caused by the pandemic, including non-essential service closures, travel restrictions, lockdowns, and psychosocial impacts. Patients with diabetes are uniquely affected by these restrictions, as glycemic control is heavily dependent on lifestyle and access to essential medications and supplies. The purpose of this project is to determine the impact of telemedicine consultations in the context of the COVID-19 pandemic on the glycemic control of patients seen at our clinic. A retrospective chart review was performed on 300 type 1 and 2 diabetes patients seen at least once within the 6 months preceding (pre-COVID) and following (post-COVID) March 18, 2020. The primary outcome measure was hemoglobin A1c. For patients with more than 1 A1c value in each time frame, the most recent A1c was used. Demographic information was also collected. There was no significant difference in the pre-COVID and post-COVID A1c values (p=0.40) of the entire sample. There was no significant difference in the pre-COVID and post-COVID A1c values when the sample was stratified by age, diabetes duration, use of CGM, or use of pump. However, there was a significant increase in A1c for females post-COVID (p&lt;0.05). This difference was not observed for males (p=0.22). Our data suggests that telemedicine is an overall effective strategy for optimizing glycemic control of patients with type 1 and type 2 diabetes during the pandemic, with no significant difference in A1c. However, the gender-specific effect of telemedicine consultations during COVID-19 on the glycemic control of females with diabetes indicates a need for further study and intervention.

Disclosure
A. Dissanayake: None. M. Pawlowska: Advisory Panel; Self; Novo Nordisk. B. Schroeder: Advisory Panel; Self; AstraZeneca, Novartis Pharmaceuticals Canada Inc. J. Mackenzie-feder: None. A. White: Advisory Panel; Self; Abbott Diabetes, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Canada Inc.
878-P: The Association between Demographics, Insulin Rationing, and Glycemic Control Assessed by Hemoglobin A1c
Authors: MENON TRISHA , ZHANG MENG , MYERS ALYSON 
Published: June 2021

Introduction: Insulin cost continues to rise, making affordability difficult for patients. This study looks at the relationship between demographic variables, insulin rationing and glycemic control.
Methods: Patients with a diagnosis of type 2 diabetes who use insulin in a resident primary care practice were approached to participate. 131 surveys were conducted by phone (two patients declined), with questions about demographics, medical history, and insulin rationing. Data was summarized using frequency and percentage. Chi-squared/Fisher’s exact test was performed to evaluate the relationship between insulin rationing and variables including age, gender, race, insurance, smoking status, duration of diabetes and insulin use, insulin type, and history of hypertension, hyperlipidemia, obesity, cardiovascular disease, anemia, malignancy, or autoimmune disease. Logistic regression analysis was performed to determine if there is relationship between insulin rationing and hemoglobin A1c (HbA1c) greater than or equal to 8% (Yes/No).
Results: Race, gender, smoking status and diabetes duration were associated with insulin rationing. Specifically, black and Asian (vs. white) (p=0.012), males (p=0.049), smoking (yes) (p=0.032) and longer diabetes duration (more than 10 years) (p=0.025) were more likely to ration insulin. Insurance type (p=0.054), age (p = 0.419), and duration of insulin use (p=0.804) were not associated with rationing. Interestingly, comorbidities that confound diabetes control did not affect rationing. There was no association between insulin rationing and HbA1c values greater than or equal to 8% (p = 0.205, Odds ratio 0.37, 95%CI = 0.08 to 1.72).
Conclusions: This study did not show an association between insulin rationing and glycemic control, but demonstrated an association with rationing in demographic variables like race and gender. The results of this study were limited by sample size, cross-sectional design and possibly response bias.

Disclosure
T. Menon: None. M. Zhang: None. A. Myers: None.
886-P: Impact of Endocrine E-Consultation on SGLT2i and GLP-1 RA Prescription
Authors: RASHEED AMNA , KOMPALA TEJASWI , NEINSTEIN AARON B. 
Published: June 2021

Background: Though GLP1 receptor agonists (GLP1RA) and SGLT2 inhibitors (SGLT2i) decrease risk of cardiovascular and renal complications in DM2, uptake has been slow. The impact of specialist care and electronic consultation (e-consult) on prescribing of these medications is unknown.
Methods: We performed a case-control study to determine predictors for real-world prescription of GLP1RA and SGLT2i at an academic medical center. From 1/1/2017 to 8/19/2020, all patients with DM2 and known atherosclerotic cardiovascular disease (ASCVD) were identified. We randomly selected 177 patients with a current prescription for SLGT2i and/or GLP1RA, and 177 with no current or prior SGLT2i or GLP1RA use. Demographics, clinical characteristics, and healthcare utilization data were obtained.
Results: Patients with active SGLT2i and GLP1RA prescriptions were younger (66.5 vs. 70.7, p &lt; 0.01), had higher BMI (31.8 vs. 28.8, p&lt;0.01), higher A1c (8.3 vs. 7.0, p&lt;0.01) and more likely male (56.5 % vs. 43.5 %, p &lt;0.01). There were no differences in insurance type, language, patient portal enrollment, or diabetes complications severity index scores. Patients with current prescriptions were more likely to have either an endocrinology visit or e-consult (OR 5.6, p&lt;0.01), and more likely to have an endocrinology e-consult alone (OR 2.4, p=0.03) as compared to patients without current prescriptions. Endocrinology (4.1 vs. 1.1, p&lt; 0.01) and cardiology (3.1 vs. 2.1, p &lt; 0.01) visits were higher among patients with active prescriptions, whereas the number of primary care and nephrology visits were similar in the two groups.
Conclusions: Although diabetes complications, including prior ASCVD, were similar between the two groups, patients prescribed SGLT2i or GLP1RA were more likely to have seen an endocrinologist or have had an endocrinology e-consult. Targeted, proactive outreach from endocrinologists to primary care providers via e-consults should be explored as a method to increase guideline-based prescribing of SGLT2i and GLP1RA.

Disclosure
A. Rasheed: None. T. Kompala: Consultant; Self; Eli Lilly and Company, Employee; Self; Livongo. A. B. Neinstein: Consultant; Self; Eli Lilly and Company, Intuity Medical , Medtronic, Roche Diabetes Care, Steady Health.
888-P: Food Insecurity and Type 2 Diabetes in Children: A Systematic Literature Review
Authors: BLACKBURN JYE , BRES HANNAH , DEVENISH GEMMA , HARRAY AMELIA 
Published: June 2021

Background and Aim: The incidence of children and adolescents being diagnosed with type 2 diabetes (T2D) in Western Australia is increasing, with approximately three in five of these children from Aboriginal or Torres Strait Islander descent. The ability to afford, access and acquire nutritionally adequate and culturally appropriate foods could play a role in the risk of developing T2D. Internationally, studies have looked at the association between T2D and food insecurity, yet no systematic review of the literature has been conducted. This systematic review aims to determine the relationship between food insecurity and T2D in children and adolescents, including Indigenous and culturally and linguistically diverse groups.
Research Method: PubMed, MEDLINE (Ovid), CINHAL Plus with full text (EBSCO) and Cochrane Library databases were searched to identify the available literature. The search was restricted by publication date of 1990 - present, English language and human studies. Children (aged 1-18 years) diagnosed with either impaired glucose tolerance (IGT) or T2D and experience food insecurity, were included in the systematic review. Study selection, data extraction and synthesis and risk of bias assessment was completed by two independent reviewers.
Results: A total of 10 studies comprising of 47,085 participants were included in the systematic review. Eight studies found an association between food insecurity and T2D, however, this association varied between studies. Different methodologies were used to measure food insecurity, IGT and T2D prevalence, which is a potential factor for the variation in the association within the selected studies.
Conclusion: Evidence suggests the ability to afford, access and acquire nutritionally adequate and culturally appropriate foods is associated with IGT and T2D in children and adolescents. More longitudinal cohort studies on a larger, more representative sample need to be conducted to determine the extent of this relationship.

Disclosure
J. Blackburn: None. H. Bres: None. G. Devenish: None. A. Harray: None.
90-LB: Soliqua (Lixilan): Sustained Long-Term Cost Efficacy and Safety When Used in Combination with Metformin and Glimepiride
Authors: KABADI UDAYA M. , EXLEY SARAH 
Published: June 2021

Background: Rx with SU and Metformin lowered daily dose of insulin glargine with desirable glycemia. However, Soliqua trials excluded SU and subjects with morbid obesity. Objective: Assess long term efficacy and safety of Soilqua with Glimepiride and Metformin in subjects with type 2 diabetes. Subjects: 31 adults with type 2 diabetes wre identified as currently using Soliqua via EMR. One is excluded as therapy &lt; 3 months. A1c &gt;7.5% with 1) Glimepiride, Metformin and Basal insulin , 2) Metformin and/or DPP 4 inhibitors and/or other SUs and /or GLP1 RA and/or Basal and/or prandial insulin. Subjects with gastroparesis, Triglycerides &gt; 300 mg/dl and pancreatitis are excluded.
Methods: Oral drugs besides Glimepiride and Metformin, Basal and prandial insulin and GLP1 RA were stopped. Glimepiride 8 mg, Metformin 1000-2000 mg were started with Soliqua daily dose pre-breakfast based on previous basal insulin dose and increased by 2 units every 3 days until AM sugar &gt;80&lt;130 mg/dl was attained or dose of 60 units was reached. Comparisons are conducted forBW (kg), fasting glucose (mg/dl) and A1c (%) prior to initiation of therapy and at the time of analysis.
Results: BMI ranged between 22-67. Duration of diabetes is 4-24 years. Duration of therapy range, 5-47 (mean 16± 6 )months. Fasting glucose declined from 167±15 to 118± 4 and A1c dropped from 9.7±0.8 to 7.6±0.3. No severe hypoglycemia was reported. In 4 morbidly obese subjects, fasting glucose and A1c declined though not achieving desirable goals despite receiving maximal dose, 60 units. Mean daily dose of Soliqua was lower (0.38±0.08 units /kg BW compared to pivotal trials (0.44 units /kg BW).
Conclusion: Soliqua is cost effective and safe in the long term in all subjects irrespective of BMI, when administered in combination with glimepiride and metformin. Moreover, it may be useful when administered with Glimepiride and Metformin in more subjects with higher BMI without attaining maximum daily dose in comparison to pivotal trials.

Disclosure
U. M. Kabadi: None. S. Exley: None.
900-P: Continuous Glucose Monitoring in Youth with Type 2 Diabetes: A Pilot and Feasibility Study
Authors: CHESSER HANNAH , SRINIVASAN SHYLAJA , WONG JENISE C. 
Published: June 2021

Objective: Real-time continuous glucose monitoring (CGM) is effective for diabetes management in T1D and adults with T2D, but has not been assessed in youth with T2D. The objective of this study was to assess the feasibility and acceptability of CGM use in youth with T2D.
Methods: Youth (13- 21 years old) with T2D ≥ 6 months and A1c &gt; 7%, on any FDA approved treatment regimen were included. After a blinded run-in period, participants were given a Dexcom G6 CGM system for 12 weeks. The use and acceptability of the real-time CGM were evaluated by sensor usage, surveys, and focus group qualitative data.
Results: Youth (n=8) had median age 19.4 (IQR 15.5-20.6) years, were 75% female, 50% hispanic/latino ethnicity, 50% non-English speaking at home, and 91% had public insurance. Baseline A1c was 11.7 (±2.8)% with mean diabetes duration of 2.5 (IQR 1.4 - 5.1) years and 75% were on basal insulin. Of the 7 participants who have completed the CGM intervention, all reported CGM was a positive experience (50% very positive, 50% slightly positive), easy to use (50% very easy, 50% easy), and useful (83% useful, 17% useful). All participants desired to continue to use real-time CGM in the future. 85% were “extremely” likely to recommend real-time CGM to friends. 67% of participants self-reported eating fewer meals while using CGM. All participants used sensors for the duration of the study.
Conclusion: Real-time CGM is feasible and acceptable for youth with type 2 diabetes. Larger randomized controlled trials are needed to assess effects on glycemic control, healthy lifestyle changes, and diabetes distress.

Disclosure
H. Chesser: None. S. Srinivasan: None. J. C. Wong: Advisory Panel; Self; Provention Bio, Inc., Research Support; Self; Dexcom, Inc., Tandem Diabetes Care.