bluuebunny/crossref_metadata_2025_split huggingface dataset:
384-P: Impact of Concurrent Use of Oral Antidiabetes Agents with Insulin in the Real-World Hospital Setting
Authors: PATHAM BHARGAVI , CHIKERMANE SOUMYA , VADHARIYA AISHA , JOHNSON MICHAEL L. , SADHU ARCHANA R. 
Published: June 2020

Guidelines recommend discontinuing oral antidiabetes drugs (OADs) on admission and initiating basal bolus insulin therapy. In the real world, concurrent OAD use with insulin is common and may affect outcomes. We conducted a large, retrospective study of 4558 patients age &gt;18, admission &gt;48 hours, and administered insulin &gt;75% of days. 847 (18.58%) were administered OADs along with insulin within the first 2 days. Insulin therapy was categorized into 3 groups based on observed prescribing practices: sliding scale (SS), basal and scheduled rapid acting bolus (BB), Basal and rapid acting as needed (B+). Each group was analyzed for glucose control by days with hypoglycemia (any &lt;70 mg/dl), hyperglycemia (mean &gt;180 mg/dl) or euglycemia (no hypo- or hyperglycemia). Clinical outcomes included length of stay, 30/60 day readmission, and hospital mortality. Previously identified patient and provider factors that influence the choice of therapy were controlled using propensity score adjusted models. There were no statistical significant differences in hyperglycemia, euglycemia or clinical outcomes between BB or B+ compared to SS. However, hypoglycemia occurred 2 times more in BB compared to SS. B+ also had a higher trend of hypoglycemia. In our hospital system, basal insulin along with OADs resulted in more hypoglycemia. Further investigation is needed on optimizing these choices of therapy.

Disclosure
B. Patham: None. S. Chikermane: None. A. Vadhariya: None. M.L. Johnson: None. A.R. Sadhu: None.
389-P: Ability for Detecting or Predicting Hypoglycemia with the Aid of Machine Learning Techniques: A Meta-analysis
Authors: KODAMA SATORU , YAMADA MAYUKO H. , YAGUCHI YUTA , KITAZAWA MASARU , KANEKO MASANORI , MATSUBAYASHI YASUHIRO , FUJIHARA KAZUYA , IWANAGA MIDORI , KATO KIMINORI , SONE HIROHITO 
Published: June 2020

Hypoglycemia is a major barrier to maintaining optimal glycemic control. Machine learning (ML) approaches have been applied to improve the identification of unrecognized hypoglycemia. This meta-analysis assessed current detective or predictive ability for hypoglycemia using ML techniques. Electronic literature searches were conducted using MEDLINE and EMBASE for detecting real-time hypoglycemia or predicting hypoglycemia subsequent to several features, where an index test is a model constructed by ML algorithms and the reference standard is a blood test to confirm the occurrence of hypoglycemia. Included studies were restricted to sample-based studies that examined both the ability to discriminate non-hypoglycemia events from hypoglycemia events and the ability to discriminate hypoglycemia events from non-hypoglycemia events. The 2x2 contingency data (i.e., true-positive, false-positive, false-negative, and true-negative) were pooled with a hierarchical summary receiver operating characteristic model. Pooled sensitivity/specificity (95% confidence interval (CI)) of 6 eligible studies for predicting hypoglycemia and 5 eligible studies for detecting hypoglycemia were 0.78 (0.70-0.85)/0.81 (0.69-0.89) and 0.78 (0.72-0.83)/0.84 (0.63-0.94), respectively. Consequently, the positive likelihood ratio (PLR) calculated as [sensitivity/(1-specificity)] and the negative likelihood ratio (NLR) calculated as [(1-sensitivity)/specificity] with 95% CI were 4.03 (2.26-7.18)/0.27 (0.17-0.42) and 4.90 (1.92-12.51)/0.27 (0.21-0.33), respectively. Considering that PLR&gt;5 moderately increases the probability of a disease given a positive test and NLR&lt;0.2 moderately decreases the probability of a disease given a negative test, it is concluded that current models have not yet attained satisfactory performance and that the algorithm may need further development before being implemented.

Disclosure
S. Kodama: None. M.H. Yamada: None. Y. Yaguchi: None. M. Kitazawa: None. M. Kaneko: None. Y. Matsubayashi: None. K. Fujihara: None. M. Iwanaga: None. K. Kato: None. H. Sone: Research Support; Self; Kyowa Hakko Kirin Co., Ltd., Novartis AG, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co.
396-P: Investigating the Risk of Severe Hypoglycemia in Elderly Patients with Type 2 Diabetes Mellitus
Authors: HORII TAKESHI , ATSUDA KOICHIRO 
Published: June 2020

In Japan, The prevalence of type 2 diabetes mellitus (T2DM) is increasing, especially in the elderly population. Many of these patients have co-morbidities like renal insufficiency and personalized blood sugar goals, increasing the risk of hypoglycemia. This study was conducted to examine the associations of patients characteristics such as HbA1c level, BMI and use of glucose level-lowering medication with hypoglycemia-related hospitalizations.
This study was cross sectional study conducted over 6 years January 2014 and March 2019. We recruited 9,798 patients with elderly patients over 65 years with T2DM. To assess the odds ratio (OR) of hypoglycemia-related hospitalizations, we constructed a logistic regression analysis, having adjusting for age, gender, BMI, eGFR, baseline HbA1c levels, use of hypoglycemic agents.
Hypoglycemia was documented in 124 (1.27%) patients. In multivariate logistic regression analysis, age≧75years and gender were not significantly. DPP-4I (OR: 0.52, 95%CI: 0.28-0.96) showed lower odds ratio. BMI≦25kg/m2 (OR: 2.94, 95%CI: 1.26-6.86), baseline HbA1c&lt;6.0% (OR: 4.43, 95%CI: 2.25-8.73), eGFR 15-≦30 mL/min(OR: 2.54, 95%CI: 1.05-6.10), &lt;15mL/min(OR: 3.01, 95%CI: 1.26-7.16), Insulin (OR: 2.05, 95%CI: 1.22-3.43) showed higher odds ratio.
In this study of elderly patients with T2DM, the risk of hospitalization for hypoglycemia appeared to be highest among patients with too low Hba1c and BMI, decreased renal function, and sulfonylurea and/or insulin use. On the other hand, DPP-4I have been shown to reduce the risk of hospitalization for hypoglycemia. By leveraging the results of this study, at-risk elderly patients can benefit from individualized treatment plans to reduce the risk of hypoglycemia.

Disclosure
T. Horii: None. K. Atsuda: None.
399-P: Nurse-Driven Intervention Using Real-Time Data to Improve Hypoglycemia Rates in a Respiratory Care Unit
Authors: HASSE ANN MARIE , SCHULMAN RIFKA , CALDER TORI 
Published: June 2020

Background: Hypoglycemia is a known cause of morbidity and mortality in the hospital setting. Nursing initiated interventions to reduce hypoglycemia rates have rarely been reported.
Methods: At our institution, hypoglycemia rate is defined as the percentage of patients with diabetes mellitus (DM) with one or more blood glucose (BG) &lt; 70mg/dl after 24 hours of admission. Nursing units are given monthly hypoglycemia rates, retrospectively. An electronic hypoglycemia tracker tool was developed for hypoglycemia monitoring. This tool prompted nursing staff on the Respiratory Care Unit (RCU) to assess for causes of hypoglycemia. This study was a unit based quality improvement project.
Results: RCU’s baseline monthly hypoglycemia rates before intervention were: 23%, 38%, and 25% in January-March 2019, respectively. Hypoglycemia tracker results after 1 month of use demonstrated that &gt; 50% of hypoglycemia occurrences were preceded by BG &lt; 100mg/dl before becoming overtly hypoglycemic. Staff nurses accessed real-time data using the inpatient diabetes dashboard, beginning in April 2018, to assess BG trends on RCU patients currently admitted. Patients deemed at risk for hypoglycemia had the provider notified to intervene with reduced insulin dosage or another intervention if appropriate. Three months after intervention, monthly hypoglycemia rates decreased to 0%, 4% and 7% in April- June 2019, respectively. The RCU has been able to sustain improvement with an average hypoglycemia rate April-December 2019 of 9%.
Conclusion: Causes of hypoglycemia in the hospital setting need to be assessed in order to determine successful prevention strategies. Tools, like hypoglycemia tracker tool, has helped units assess the causes of hypoglycemia so that some events can be prevented. Traditionally providers are tasked with managing DM in the hospital. This quality improvement project showed that nurses can have an impact on preventing hypoglycemia.

Disclosure
A. Hasse: None. R. Schulman: None. T. Calder: None.
40-LB: The Effect of Continuous Diffusion of Oxygen (CDO) Treatment on Cytokines and Healing in Patients with Diabetic Foot Ulcers
Authors: LAVERY LAWRENCE A. , KILLEEN AMANDA L. , FONTAINE JAVIER LA , AKGUL YUCEL , CRISOLOGO PETER 
Published: June 2020

Objective: To evaluate the effect of topical oxygen therapy on cytokines and healing in patients with diabetic foot ulcers.
Methods: This prospective cohort study evaluated 23 patients with diabetic foot ulcers that received Continuous Diffusion of Oxygen treatment over four visits. Wound size, hyperspectral imaging, transcutaneous oxygen measurements, cytokines (CXCL8, PDGF, IGF-1β, TGF-β, IL6, VEGF, and TNF-α), and bacterial cultures were obtained weekly. We used analysis of variance to test for differences in continuous variables. For this pilot study we used an α = 0.10.
Results: The results of this study show there is no significant difference between transcutaneous oxygen on plantar and dorsal foot (53.91 ± 13.97) and (57.81 ± 13.59), oxygenated or deoxygenated hemoglobin (Hgb) (64.50 ± 33.94) and (61.86 ± 23.80), or quantitative cultures at the time points. 60% of people had percent wound area reduction There is a significant difference between the levels of TGF-β and TNF-α between visits 1 and 2, p values 0.006 and 0.01 respectively. For VEGF p=0.00508 and IL6 p=0.11. The results were analyzed by patients with percent wound area reduction &gt;50% (healers N=12, 52%) and non-healers (N=11, 48%). The median concentrations of cytokines between healers and non-healers for the four visits are shown in Figure 1.

Disclosure
L.A. Lavery: Advisory Panel; Self; Acelity, Bayer AG. Consultant; Self; Boehringer Ingelheim International GmbH. Research Support; Self; AstraZeneca, Cardinal Health, EO2 Concepts, Integra LifeSciences, MedImmune, Smith & Nephew. A.L. Killeen: None. J. La Fontaine: None. Y. Akgul: None. P. Crisologo: None.

Funding
EO2 Concepts (19069)
405-P: Relationship between NAFLD and Cardiac Complications and Function in T2DM
Authors: LAVRYNENKO OLGA , ZEMLIANITSYNA OLHA , DUNAEVA INNA , KRAVCHUN NONNA , SINAIKO VADYM , DEFRONZO RALPH A. 
Published: June 2020

NAFLD is common in T2DM patients and has been proposed to be part of the cardiometabolic syndrome.
Aim: To determine the relationship between hepatic fibrosis and cardiovascular abnormalities in T2DM.
Subjects: 72 T2DM patients with NAFLD and 38 T2DM without NAFLD were studied. Based upon liver elastography and Bonacini and Metavir scores T2DM patients with NAFLD were divided into 3 groups: (I) NAFLD with hepatic fibrosis ≥F2 (n=29); (II) NAFL without fibrosis/inflammation (n=11); (III) NASH (n=32). All subjects had cardiac echo to quantitate ventricular volumes, ejection fraction, and diastolic function.
Results: Incidence of cardiovascular complications was higher in patients with hepatic fibrosis: prevalence of arterial hypertension was 40% in T2DM without NAFLD vs. 44 % in NAFL, 69 % in NASH (p&lt;0.01) and 70 % in hepatic fibrosis (p&lt;0.001). Coronary heart disease was present in 20% of T2DM patients without NAFLD, 37% with NAFL, 36 % with NASH and 53 % with hepatic fibrosis (p&lt;0.001). No patient with T2DM without NAFLD had non-fatal myocardial infarction; MI was present in 3.7% of patients with NAFL, 1.7 % with NASH and 15 % with hepatic fibrosis. 3.2% of patients with hepatic fibrosis had stroke; no other patient had stroke. Ejection fraction was decreased (p&lt;0.05) in patients with NASH (57 ±3%) and hepatic fibrosis (54 ±2%) vs. NAFL patients (66 ±2%) and T2DM without NAFLD (63 ±1%). End-diastolic volume was increased in patients with NAFL (189 ±6 ml) and NASH (125±8 ml) vs. hepatic fibrosis (106±3ml) and T2DM patients without NAFLD (110±6 ml). End-systolic volume was increased in patients with NAFL (58±5 ml), NASH (55±3 ml) and hepatic fibrosis (48±4 ml) vs. T2DM without NAFLD (42±4 ml).
Conclusion: Liver fibrosis in T2DM is associated with impaired cardiac function and increased cardiovascular complications. The results demonstrate that hepatic inflammation and fibrosis in T2DM patients with NAFLD is an important risk factor for cardiovascular disease and is associated with cardiac dysfunction.

Disclosure
O. Lavrynenko: None. O. Zemlianitsyna: None. I. Dunaeva: None. N. Kravchun: None. V. Sinaiko: None. R.A. DeFronzo: None.
41-OR: Single Cell RNA-Sequencing Reveals the Developmental Heterogeneity of Brown Adipocytes
Authors: SHAMSI FARNAZ , PIPER MARY , HO LI-LUN , HUANG TIAN LIAN , TSENG YU-HUA 
Published: June 2020

Brown adipose tissue (BAT) is the major thermogenic organ, which promotes energy expenditure through a process called adaptive thermogenesis. Central to the inherent thermogenic activity of brown adipocytes is uncoupling protein 1(UCP1). Other than mature adipocytes, several other cell types form the adipose niche and play important roles in BAT function and remodeling. Prolonged cold exposure increases BAT mass and activity through de novo recruitment of brown adipocytes as well as coordinated expansion of other cells within the adipose niche to enable maximal thermogenic activity. However, the source of cold-induced brown adipocytes and the molecular mechanism regulating BAT expansion is not known. To determine the cellular composition of BAT and its remodeling in response to ambient temperature, we performed single-cell RNA-sequencing (scRNA-seq) of the stromal vascular fraction of BAT from mice housed at different temperatures. The unsupervised clustering identified 19 major cell types, including several sub-populations of adipose progenitors, endothelial cells, immune cells, vascular smooth muscles, and Schwann cells. The transcriptional profile of each cell type in mice housed at different temperatures revealed the dynamic remodeling of brown adipocyte niche in response to environmental challenges. Among them, we identified a novel population of brown adipose progenitors derived from BAT endothelium. These endothelial-derived adipose progenitors have a distinct gene expression profile, which distinguishes them from the previously known Pdgfra-expressing adipose progenitors. Using an inducible genetic reporter, we validated the induction of UCP1 and other thermogenic gene program in the endothelial-derived adipose progenitors upon cold exposure.
In summary, scRNA-seq of BAT provides a high-resolution map of brown adipose niche and suggests the critical contribution of each cell type to BAT functions, homeostasis, and turn-over.

Disclosure
F. Shamsi: None. M. Piper: None. L. Ho: None. T. Huang: None. Y. Tseng: Consultant; Self; Boehringer Ingelheim International GmbH.

Funding
American Diabetes Association (1-18-PDF-169 to F.S.); National Institutes of Health (R01DK077097, R01DK102898, P30DK036836); Harvard Stem Cell Institute
410-P: Effects of Palmitate and Oleate on Apoptosis, Autophagy, Stress, Kinase Phosphorylation, and Enzymes of Fatty Acid Oxidation in Human Cardiac Progenitor Cells from Control and Diabetic Subjects
Authors: LAVIOLA LUIGI , SCHIPANI ROSSELLA , DORIA ROSSELLA , CACCIOPPOLI CRISTINA , LEONARDINI ANNA , NATALICCHIO ANNALISA , PERRINI SEBASTIO , CIGNARELLI ANGELO , GIORGINO FRANCESCO 
Published: June 2020

Elevated circulating levels of palmitate are associated with high cardiovascular risk in diabetes. In contrast, oleate prevents palmitate-induced cytotoxic stress in multiple cell types. The viability of cardiac progenitor cells (CPC) is essential for tissue renewal in the heart. In this study, the ability of palmitate and oleate to induce apoptosis, autophagy and stress kinase phosphorylation, as well as the effects on enzymes involved in fatty acid oxidation, were investigated in human CPC isolated from control subjects or type 2 diabetic patients. Palmitate, but not oleate, induced apoptosis in control and diabetic CPC, as assessed by caspase-3 cleavage and ELISA assay (p&lt;0.05). Exposure of control and diabetic CPC to 0.25 mM palmitate for 16 h also resulted in increased autophagy, evidenced by light chain 3-II immunoblotting (p&lt;0.05). In contrast, oleate did not induce autophagy. Palmitate, but not oleate, also induced p38 MAPK and c-Jun phosphorylation (p&lt;0.05), in control and diabetic CPC. Importantly, the palmitate effects on apoptosis and autophagy, as well as stress kinase activation, were prevented in control and diabetic CPC co-treated with 0.1 mM oleate for 16 h (p&lt;0.05). However, palmitate, alone or with oleate, increased the mRNA levels of carnitine palmitoyltransferase 1B (CPT1B) (p&lt;0.05), one of the enzymes of mitochondrial fatty acid oxidation, in control CPC but not in diabetic CPC.
In conclusion, oleate prevents palmitate-induced apoptosis, autophagy and p38 MAPK and JNK signaling in CPC from control subjects and diabetic patients. Since palmitate increases CPT1B expression only in control CPC, a selective impairment in metabolic signaling appears to occur in diabetic CPC. Hence, oleate supplementation might preserve the viability of cardiac progenitors from the lipotoxic damage in both control and diabetic subjects.

Disclosure
L. Laviola: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk Inc., Roche Diabetes Care, Sanofi-Aventis. Speaker’s Bureau; Self; Abbott, Medtronic. R. Schipani: None. R. Doria: None. C. Caccioppoli: None. A. Leonardini: None. A. Natalicchio: Consultant; Self; AstraZeneca, Novo Nordisk Inc., Sanofi-Aventis. S. Perrini: None. A. Cignarelli: None. F. Giorgino: Advisory Panel; Self; AstraZeneca, Eli Lilly and Company, Novo Nordisk Inc., Roche Diabetes Care, Sanofi. Consultant; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., LifeScan, Inc., MedImmune, Merck Sharp & Dohme Corp., Roche Diabetes Care, Sanofi. Research Support; Self; Eli Lilly and Company, LifeScan, Inc., Takeda Development Centre Europe Ltd.
412-P: Lipoprotein(a) and Vascular Risk in Patients with Established Cardiovascular Disease
Authors: SAELY CHRISTOPH H. , SPRENGER LUKAS , VONBANK ALEXANDER , LARCHER BARBARA , MADER ARTHUR , MAECHLER MAXIMILIAN , PURIN DANIELA , LEIHERER ANDREAS , MUENDLEIN AXEL , DREXEL HEINZ 
Published: June 2020

Lipoprotein(a) [Lp(a)] is an important cardiovascular risk factor especially in young individuals. However, data on the vascular risk conferred by Lp(a) in patients with established cardiovascular disease (CVD) are controversial. In particular, the power of Lp(a) as a predictor of cardiovascular events in CVD patients with type 2 diabetes (T2DM) is unclear and is addressed in the present study. Lp(a) was measured in a cohort of 1543 patients with established CVD, 1246 patients with angiographically proven CAD and 297 patients with sonographically proven PAD. Vascular events were recorded over a mean follow-up of 9.6±4.6 years. At baseline, 517 patients had T2DM and 1026 did not have diabetes. During follow-up, 49.8% of our patients suffered vascular events. Lp(a) proved to be a strong and independent predictor of vascular events in the total study cohort (standardized adjusted HR=1.12 [1.04-1.20]; p=0.002). In subgroup analyses by diabetes status Lp(a) significantly predicted vascular events both in T2DM patients (HR=1.16 [1.02-1.31]; p=0.021) and in nondiabetic patients (HR=1.10 [1.01-1.20]; p=0.021). We conclude that over a mean follow-up of 9.6 years, Lp(a) among CVD patients predicts cardiovascular events both among those with T2DM and among those who do not have diabetes.

Disclosure
C.H. Saely: None. L. Sprenger: None. A. Vonbank: None. B. Larcher: None. A. Mader: None. M. Maechler: None. D. Purin: None. A. Leiherer: None. A. Muendlein: None. H. Drexel: None.
418-P: Chronic Kidney Disease Is a Type 2 Diabetes Risk Equivalent in Patients with Established Coronary Artery Disease
Authors: SAELY CHRISTOPH H. , SPRENGER LUKAS , VONBANK ALEXANDER , LARCHER BARBARA , MADER ARTHUR , MAECHLER MAXIMILIAN , PURIN DANIELA , LEIHERER ANDREAS , MUENDLEIN AXEL , DREXEL HEINZ 
Published: June 2020

Both type 2 diabetes (T2DM) and chronic kidney disease (CKD) confer a high risk of cardiovascular disease (CVD). We aimed at investigating the single and joint effects of T2DM and of CKD on cardiovascular event risk in high-risk patients with established coronary artery disease (CAD). We prospectively investigated 1460 patients with angiographically proven CAD over 10.3±4.8 years. Cardiovascular events occurred more frequently in T2DM patients (n=449) than in nondiabetic subjects (56.2% vs. 44.5%; p&lt;0.001) and in patients with CKD (eGFR &lt;60ml/min/1.73m²; n=264) than in those with an eGFR ≥60ml/min/1.73m² (61.7% vs. 45.1%; p&lt;0.001). When both, T2DM and CKD were considered, 856 subjects had neither T2DM nor CKD, 340 had T2DM but not CKD, 155 did not have diabetes but had CKD, and 109 had both T2DM and CKD. When compared with the cardiovascular event rate among patients with neither T2DM nor CKD (42.5%), cardiovascular risk was significantly higher in patients with T2DM who did not have CKD (51.5%; p=0.002) as well as in nondiabetic patients with CKD (55.2%; p=0.009) and was highest in patients with both, T2DM and CKD (71.0%; p&lt;0.001), in whom the event risk was higher than in those with T2DM but no CKD (p&lt;0.001) or those without T2DM but with CKD (p=0.005); event risk however was did not differ significantly between nondiabetic CKD patients and T2DM patients who did not have CKD (p=0.692). We conclude that CKD is a T2DM risk equivalent in patients with established CAD.

Disclosure
C.H. Saely: None. L. Sprenger: None. A. Vonbank: None. B. Larcher: None. A. Mader: None. M. Maechler: None. D. Purin: None. A. Leiherer: None. A. Muendlein: None. H. Drexel: None.