bluuebunny/crossref_metadata_2025 huggingface dataset:
1534-P: Relationship between Metabolic Syndrome Score and Insulin Resistance
Authors: ABBASI FAHIM , REAVEN PETER , KNOWLES JOSH
Published: June 2019

Metabolic syndrome (MS) identifies previously unrecognized individuals at risk for diabetes and cardiovascular disease. Although MS is defined as requiring ≥3 of 5 categorical factors, a continuous MS score (using race/ethnicity modified Z-scores) has been proposed to better predict outcomes and track changes with interventions. As insulin resistance (IR) may link the 5 MS factors and their risk to outcomes, we hypothesized that MS score may reflect IR and its change with different therapies. We therefore determined MS score and IR by steady-state plasma glucose (SSPG) during the Insulin Suppression Test in persons without diabetes at baseline (n=611) and before and after 3 interventions: weight loss (WL; n=29), pioglitazone (PIO; n=32), and atorvastatin (ATR; n=36). Baseline MS score correlated (r value) with SSPG (0.58), similar to the correlations of BMI with SSPG (0.54) and MS score (0.55). MS score and SSPG, respectively, correlated with HDL-C (-0.63 vs. -0.33), triglycerides (TG; 0.82 vs. 0.38), systolic BP (0.38 vs. 0.22), fasting glucose (0.46 vs. 0.38), and TG/HDL-C ratio (0.87 vs. 0.42); P<0.01 for all. After WL and PIO, SSPG and MS score decreased (P<0.05). In contrast, after ATR, SSPG increased (P<0.05), but MS score decreased (P<0.01). The change (Δ) in MS score did not correlate with ΔSSPG in any of the groups, but strongly correlated with ΔTG/HDL-C ratio: WL (r=0.94), PIO (r=0.92), and ATR (r=0.79).

In conclusion, MS score correlates modestly with SSPG, but strongly with TG and TG/HDL-C ratio. Changes in MS score in response to IR-modifying therapies do not appear to reflect changes in IR but rather changes in TG. This may limit use of MS score to evaluate change in IR or disease risk.

Disclosure

F. Abbasi: None. P. Reaven: Advisory Panel; Self; Boston Heart Diagnostics. Research Support; Self; AstraZeneca, Novo Nordisk Inc. J. Knowles: None.

Funding

Doris Duke Charitable Foundation
1537-P: Impact of Obesity on Outcomes of Diabetic Ketoacidosis: A Nationwide Analysis
Authors: MUDGAL MAYURI , GOEL AKSHAY
Published: June 2019

Background: Obesity is associated with better outcomes in diseases like myocardial infarction and heart failure, a phenomenon known as obesity paradox. However, the effect of obesity on healthcare outcomes after admission for diabetic ketoacidosis (DKA) has not been well characterized.

Objective: We aimed to explore the impact of obesity and morbid obesity on outcomes in patients hospitalized with DKA.

Methods: The National Inpatient Sample database for the year 2016 was queried. All admissions with a principal diagnosis of DKA were identified. Obesity (BMI 30-40 kg/m2) and morbid obesity (BMI >40 Kg/m2) were identified using their appropriate validated ICD-10 codes. Statistical analysis was performed using STATA. The Odds ratio adjusted for age and gender was calculated for obesity and morbid obesity respectively.

Results: The study included 210,455 hospitalizations with a principal diagnosis of DKA. Out of these, 19,341 (9.19%) were obese and 7,640 (3.63%) were morbidly obese. Obese DKA patients had a longer length of stay (3.79 vs. 3.14 days, p<0.001) and higher hospitalization costs ($34,643 vs. $28,976; p<0.001) compared to their non-obese counterparts. There was no significant difference in the adjusted in-hospital mortality rates in DKA patients with and without obesity (0.52% vs. 0.38%, adjusted odds ratio 1.25, p=0.34). However, DKA patients who were morbidly obese had increased mortality compared to those without morbid obesity (0.72% vs. 0.38%, adjusted odds ratio 1.85, p=0.04).

Conclusion: DKA patients with obesity have a longer length of stay and higher hospitalization costs, but similar inpatient mortality rates compared to those without obesity. Morbid obesity is associated with increased mortality in DKA patients.

Disclosure

M. Mudgal: None. A. Goel: None.
154-OR: Metabolomic Profiling and Diabetes Risk in U.S. Hispanics/Latinos: Hispanic Community Health Study/Study of Latinos
Authors: CHAI JIN CHOUL , LI JUN , YU BING , ISASI CARMEN , KHAMBATY TASNEEM , HORN LINDA VAN , VIDOT DENISE C. , CASTANEDA SHEILA , BOERWINKLE ERIC , QI QIBIN
Published: June 2019

Metabolomic profiling offers the potential to reveal metabolic pathways relevant to the development of diabetes and improve diabetes risk prediction. We examined serum metabolite profiles and their relationships with incident diabetes in Hispanic Community Health Study/Study of Latinos (HCHS/SOL). This analysis included 2010 participants (224 incident diabetes cases, 1786 control) without prevalent diabetes at baseline, aged 18-76 years with 60% female, from six Hispanic/Latino background groups in the HCHS/SOL. We profiled 624 metabolites from 8 metabolomic super-pathways. Survey Poisson regression was used to examine the associations of baseline metabolites with incident diabetes. After correcting for multiple testing (false-positive discovery rate), 134 metabolites were significantly associated with incident diabetes. For the 134 significant metabolites, network analysis identified multiple topological modules comprised of amino acids and lipids, such as BCAA metabolites, glycine, serine and threonine metabolites, sphingolipids and ceramides, monoacylglycerol and, diacylglycerol, associated with diabetes risk (Table). This study identified multiple metabolite modules related to diabetes risk in a large cohort of U.S. Hispanics/Latinos and provide new insights to metabolic pathways in the development of diabetes.

Disclosure

J. Chai: None. J. Li: None. B. Yu: None. C. Isasi: None. T. Khambaty: None. L. Van Horn: None. D.C. Vidot: None. S. Castaneda: None. E. Boerwinkle: None. Q. Qi: None.
1544-P: High Risk of Adverse Drug Reaction (ADR) in Older Adults with Type 1 Diabetes (T1D)
Authors: TOSCHI ELENA , SLYNE CHRISTINE , ATAKOV-CASTILLO ASTRID , SIFRE KAYLA , DUFOUR ALYSSA B. , CARL SAM , GREENBERG JORDAN , MUNSHI MEDHA
Published: June 2019

The three most common drugs with high risk of ADR in older adults are insulin, anticoagulants, and opioids. As all older adults with T1D are already on insulin, we evaluated how frequently they were on other medications with high risk of ADR. In addition we assessed age-related factors associated with poor outcomes including hypoglycemia risk, and compared with younger cohort with T1D.

Methods: The T1D Exchange Clinic network database was used to evaluate older≥65 years) adults with T1D and compare them with younger (18-35 years) cohort on and frequency of severe hypoglycemia (SH) within prior 3 month, ED visit for SH and use of anticoagulants, opiates drugs.

Results: We analyzed data from 569 older (72±5 years) and 2835 younger (23±5 years) adults with T1D. The results are shown in the Table. Overall 8% of older adults had fall within past 6 months, and 11% had an episode of lost consciousness.

Conclusion: Older adults with T1D are vulnerable to ADR due to polypharmacy. The risk of poor outcomes is exacerbated by presence of multiple comorbidities, higher hypoglycemia unawareness, and greater number of severe hypoglycemia ep Conclusion: Older adults with T1D are vulnerable to ADR due to polypharmacy. The risk of poor outcomes is exacerbated by presence of multiple comorbidities, higher hypoglycemia unawareness, and greater number of severe hypoglycemia episodes.

Disclosure

E. Toschi: Advisory Panel; Self; Lexicon Pharmaceuticals, Inc. C. Slyne: None. A. Atakov-Castillo: None. K. Sifre: None. A.B. Dufour: None. S. Carl: None. J. Greenberg: None. M. Munshi: Consultant; Self; Lilly Diabetes, Sanofi.

Funding

National Institute of Diabetes and Digestive and Kidney Diseases
1545-P: The Association between Type 2 Diabetes and Pain Severity in People with Localized Osteoarthritis: A Retrospective Study
Authors: ALENAZI AQEEL M. , OBAIDAT SAKHER M. , ALSHEHRI MOHAMMED , GRAY COREY M. , ALOTHMAN SHAIMA , RUCKER JASON L. , WAITMAN LEMUEL R. , KLUDING PATRICIA
Published: June 2019

Objective: Type 2 diabetes (T2D) has been associated with osteoarthritis (OA). However, research related to the impact of T2D on pain severity is limited. The purpose of this study was to examine the association between T2D and pain severity in people with localized OA (LOA) (e.g., OA restricted to only one or two joints), and to explore the association between glycosylated hemoglobin (A1c) level and pain severity in people with LOA and T2D.

Methods: A retrospective review of data from a tertiary medical center was performed. Records were selected based on diagnoses codes for LOA using international classification of disease 9th and 10threvisions. Index date was set as the first diagnosis date. Pain severity, measured by a 0 to 10 numeric rating scale, was obtained and linked to the index date. T2D was defined as having two diagnostic codes for T2D or using insulin. A1c was obtained for patients with T2D within six months of the index date. Covariates of age, sex, depression, hypertension, dyslipidemia, and medications (+/- 90 days of the index date) were included in linear regression analysis. Alpha level was 0.05.

Results: Data from 819 patients (mean age = 65.08±9.77, 54.3% women) included 671 patients with LOA only (n=671) and 148 patients with LOA+T2D. T2D was significantly associated with increased pain severity (B=1.08, 95% CI 0.23 -1.93, p=0.013) after controlling for covariates. For patients with LOA+T2D with data for A1C (n=87), higher A1c was significantly associated with increased pain severity (B=0.33, 95% CI 0.01 -0.64, p=0.045) after controlling for medications.

Conclusion: This study found that T2D was associated with higher pain severity in people with LOA, and that poorer glycemic control was associated with higher pain severity in people with LOA+T2D. Only T2D was associated with pain that exceeded the clinically meaningful difference (>1 score). Clinicians should consider T2D as a factor in the management of pain in people with LOA.

Disclosure

A.M. Alenazi: None. S.M. Obaidat: None. M. Alshehri: None. C.M. Gray: None. S. Alothman: None. J.L. Rucker: None. L.R. Waitman: None. P. Kluding: None.
155-OR: Are the American Diabetes Association Screening Guidelines Appropriate for the Racial/Ethnically Diverse U.S. Population? Evidence from the Multiethnic Study of Atherosclerosis
Authors: RODRIGUEZ LUIS A. , BRADSHAW PATRICK T. , SHIBOSKI STEPHEN , FERNANDEZ ALICIA , HERRINGTON DAVID M. , DING JINGZHONG , KANAYA ALKA M.
Published: June 2019

Objective: Current ADA screening guidelines recommend screening adults with a BMI ≥25 (or ≥23 for Asian Americans) who have at least one risk factor (e.g., belonging to a race/ethnic minority group, hypertension, dyslipidemia, physical inactivity) for diabetes. We determined if these guidelines are appropriate when applied to a multi-ethnic cohort of adults free of diabetes at baseline.

Research Design and Methods: We used data from the Multi-Ethnic Study of Atherosclerosis (exams 1-5 every 1.5 to 3 years between 2002-2013). Incident cases of diabetes were defined as fasting glucose ≥ 126 mg/dL and/or use of any diabetes medication. We used multivariable Weibull regression adjusting for age, sex, education, diet, exercise, hypertension, and dyslipidemia to estimate the differential association between BMI and incident diabetes by race/ethnicity.

Results: Among 4,541 MESA participants without prevalent diabetes, 1,860 were white, 539 Chinese American, 1,167 African American, and 975 Hispanic. In a median 9.1 years of follow-up, 557 new cases of diabetes occurred (166 in whites, 66 in Chinese Americans, 169 in African Americans, and 156 in Hispanics). Incidence rates were 11.4 (95% CI 9.8 to 13.2), 15.9 (12.5 to 20.3), 19.9 (17.1 to 23.1) and 22 (18.8 to 25.7) per 1,000 person-years among whites, Chinese Americans, African Americans and Hispanics, respectively. The race/ethnic-specific BMI for participants without any additional diabetes risk factors, compared to whites with a BMI of 25 and one or more diabetes risk factor was 29.2 in whites, 22.8 in Chinese Americans, 26.2 in African Americans and 25.4 in Hispanics.

Conclusions: Our findings show that the current American Diabetes Association diabetes screening guidelines are appropriate for the ethnically and racially diverse populations, and suggest that a higher BMI cut point, such as 29, may be appropriate for screening whites without other risk factors.

Disclosure

L.A. Rodriguez: None. P.T. Bradshaw: None. S. Shiboski: None. A. Fernandez: None. D.M. Herrington: None. J. Ding: None. A.M. Kanaya: None.

Funding

National Institute of Diabetes and Digestive and Kidney Diseases (F31DK115029)
1550-P: Trends in Cancer Mortality among U.S. Adults With and Without Diabetes, 1988-2015
Authors: HARDING JESSICA L. , ANDES LINDA J. , CHENG YILING J. , BULLARD KAI M. , GREGG EDWARD , WEIR HANNAH K. , BURROWS NILKA RÍOS , IMPERATORE GIUSEPPINA
Published: June 2019

Cancer-related mortality is higher among people with diabetes (DM) than people without DM. However, it is not known if this excess risk has changed over time. To estimate rates of cancer mortality in people with and without self-reported DM, we used data from adults aged ≥18 years who participated in the 1985-2012 National Health Interview Survey. Participants were linked to the National Death Index to determine vital status through the end of 2015. Cancer deaths were classified according to underlying cause of death. Death rates for five time periods (1988-1994, 1995-1999, 2000-2004, 2005-2009, 2010-2012) were estimated by survival analysis using Poisson regression models adjusted for age, sex and race/ethnicity with p for trend reported. Among people with DM, overall cancer mortality (per 1,000 person-years) declined 34.1% from 4.1 (95% CI: 3.0-5.3) in 1988-1994 to 2.7 (2.3-3.2) in 2010-2015, ptrend<0.01. Among people without DM, overall cancer mortality declined 26.7% from 3.0 (2.8-3.2) to 2.2 (2.0-2.3), respectively for the 1988-1994 and 2010-2015 periods, ptrend<0.01. The excess rate of cancer mortality in people with vs. without DM did not change over time (from rate ratio 1.4 (1.0-1.8) in 1988-1994, to 1.3 (1.2-1.4) in 2010-2015). In this nationally representative study, cancer mortality rates declined in people with and without DM but cancer mortality rates remain 30% higher in people with DM. Future research could identify risk factors and prevention strategies for this excess risk.

Disclosure

J.L. Harding: None. L.J. Andes: None. Y.J. Cheng: None. K.M. Bullard: None. E. Gregg: None. H.K. Weir: None. N. Burrows: None. G. Imperatore: None.
1553-P: Hyperglycemic Crisis Mortality Trends, U.S., 2000-2015
Authors: BENOIT STEPHEN R. , HORA ISRAEL A. , ZHANG YAN , GREGG EDWARD
Published: June 2019

Hyperglycemic crisis, including diabetic ketoacidosis and hyperglycemic hyperosmolar state, is a life-threatening but preventable complication of diabetes. Despite national decreases in rates of hyperglycemic crisis and other diabetes complications, recent U.S. surveillance system reports raise concern about a potential stagnation of improvements in complication rates. We assembled 2000-2015 data from CDC’s National Vital Statistics System to examine trends in hyperglycemic crisis mortality. We calculated rates as the number of deaths due to hyperglycemic crisis using the .0 and .1 E10-E14 ICD-10 codes as the underlying cause of death, divided by the U.S. civilian, noninstitutionalized population with diagnosed diabetes estimated from the National Health Interview Survey. The age-adjusted rate of hyperglycemic crisis deaths among people with diabetes declined from 2000 to 2009 (Figure) but from 2009 to 2015 increased 54.1%, from 15.7 to 24.2 per 100,000 persons with diabetes (p=.005). This reversal in trend was apparent in the 0-44 year age group (68.3% increase); males (76.9% increase) and females (39.5% increase); and blacks (34.7% increase) and whites (60.8% increase), but not among those aged 45 and older. The increase in hyperglycemic crisis mortality rates in the young population is concerning. Identification of factors contributing to the increase may help target efforts to prevent this complication.

Disclosure

S.R. Benoit: None. I.A. Hora: None. Y. Zhang: None. E. Gregg: None.
1557-P: Nonalcoholic Fatty Liver Disease Is an Independent Risk Factor for Macrovascular and Microvascular Complications in Patients with Type 2 Diabetes
Authors: ZHANG LEI , WANG NA , WANG JUN , YIN XIAOYAN , YANG YUXIU , GAO WEIGUO , DONG YANHU
Published: June 2019

Nonalcoholic fatty liver disease (NAFLD) is independently associated with cardiovascular disease and chronic kidney disease. Among patients with type 2 diabetes (T2DM), the relationship between NAFLD and diabetic macrovascular and microvascular complications is unclear. The study population consisted of 2504 patients (M/F: 1520/984, mean age 60.8 ± 10.4 years) with T2DM who have been hospitalized between 2007 and 2011. All subjects had data on anthropometric parameters, total cholesterol (TC), low-density lipoprotein cholesterol, HbA1C, creatinine (Scr), tumor necrosis factor- α (TNF-α), and 24h urine albumin exerting rate (24hUAER). Doppler ultrasound examination was used to diagnose fatty liver and to measure carotid artery intima-media thickness (IMT). Carotid artery intimal thickening was diagnosed as IMT≧1mm. Diabetic nephropathy (DN) was diagnosed if 24hUAER≧30mg/24h. NAFLD accounted for 57.4% of all patients. After adjusting for age, gender, disease duration, systolic blood pressure (SBP), waist and other factors, patients with NAFLD had increased carotid artery IMT (1.11 ± 0.25 vs. 0.87 ±0.18 mm, P <0.001) and increased 24hUAER (27.53 ± 19.70 vs. 20.34 ± 13.92 mg/24h, P <0.01) compared with those without NAFLD. In the multivariate logistic regression model with Carotid artery intimal thickening as the dependent variable, NAFLD was an independent risk factor for IMT thickening, the corresponding OR (95% CI) was 1.89 (1.42, 2.52) after adjusting for age, gender, disease duration, waist, SBP, HbA1C, TC, and TNF-α; In the similar analysis for DN, NAFLD was also independently associated with risk of DN, with an OR (95% CI) of 1.67 (1.25, 2.26). In patients with T2DM, NAFLD is not only associated with increased risk for macro-vascular but also for micro-vascular complications. Intervention and prevention of NAFLD may be addressed for prevention of macro-vascular and micro-vascular complications.

Disclosure

L. Zhang: None. N. Wang: None. J. Wang: None. X. Yin: None. Y. Yang: None. W. Gao: None. Y. Dong: None.
1558-P: BMI and Long-Term Mortality in a Population with Young and Older-Onset Diabetes
Authors: CONWAY BAQIYYAH , BLOT WILLIAM J.
Published: June 2019

Obesity is a dominant risk factor for type 2 diabetes, but its relation with mortality among those with pre-existing chronic illnesses like diabetes, regardless of type, is controversial. Using the Southern Community Cohort Study, we conducted a mortality follow-up (2002-2014) of a cohort of mostly low income black and white participants aged 40-79 with young-onset (diagnosed < age 30, n=1,378) and older onset (diagnosed ≥ 30, n= 15,707) diabetes. Cox analysis with age as the time scale was used to compute HRs (95% CIs) for all-cause mortality by BMI at cohort entry. Mean baseline age and diabetes duration were 50.1 and 29.4 years and 55.3 and 7.7 years among those with young and older onset diabetes, respectively. During an average of 9.4 years of follow-up, 24% of the patients died. Regardless of age at diabetes onset, excess mortality was observed in the underweight, but the overweight or obese had lower death rates than those of normal weight. In analyses controlling for diabetes duration, sex, race, use of insulin, hyperlipidemia and cholesterol meds, hypertension, a history of stroke/tia, coronary heart disease, education, income, and health insurance coverage, compared to a normal BMI of 18-<25 kg/m2,, HRs (95% CIs) were 4.13 (1.48-11.54), 0.56 (0.41-0.77), 0.71 (0.51-0.97), 0.46 (0.31-0.67), 0.59 (0.40-0.86) for BMI categories <18.5, 25-<30, 30-<35, 35-<40, 40+ kg/m2 among those with young-onset diabetes, with similar estimates observed for both blacks and whites. For older onset diabetes, corresponding HRs (95% CIs) were 1.96 (1.42-2.71), 0.70 (0.62-0.78), 0.65 (0.58-0.73), 0.72 (0.64-0.81), 0.99 (0.88-1.12); however, some differences by race (p interaction= 0.01) emerged, with increased risk of mortality for those with a BMI ≥ 40 among whites (HR=1.36, 1.07-1.71) but not blacks (HR=0.89, 0.76-1.03). Among this indigent population of blacks and whites with diabetes, overweight and obesity appear to be protective against mortality, particularly among those with young-onset diabetes and among blacks with older-onset diabetes.

Disclosure

B. Conway: None. W.J. Blot: None.

Funding

National Cancer Institute
1563-P: Multimorbidity and Its Associations with All-Cause Mortality in People with Type 2 Diabetes: A Prospective Analysis of the UK Biobank
Authors: CHIANG JASON I. , HANLON PETER , JANI BHAUTESH D. , MANSKI-NANKERVIS JO-ANNE E. , FURLER JOHN , NICHOLL BARBARA I. , MAIR FRANCES S.
Published: June 2019

Introduction: The emerging interest in multimorbidity (MM) in people with type 2 diabetes (T2D), which can be concordant (T2D-related) or discordant (unrelated), suggests the need to understand the burden of MM in T2D, and its association with all-cause mortality. We explored associations between MM conditions counts (total, concordant and discordant) and all-cause mortality in people with T2D in the UK Biobank.

Methods: We examined data from a longitudinal cohort of 20,569 people with T2D in the UK Biobank recruited between 2006-2010. The number of MM conditions in addition to T2D was the primary independent variable based on self-report and hospital admissions data. All-cause mortality was the primary outcome. Multivariable Cox proportional hazard regression was used to examine associations between each of the MM counts and mortality.

Results: A significant association between increasing MM and mortality was found. Compared to those with T2D with no additional chronic conditions, having 1, 2, 3 and 4+ conditions in addition to T2D, the HRs (95% CI) for all-cause mortality were 1.23 (0.90-1.68), 1.84 (1.36-2.49), 1.91 (1.40-2.60), and 3.13 (2.33-4.20), respectively. Both concordant and discordant conditions were significantly associated with mortality. For 1, 2, 3 and 4+ concordant conditions in addition to T2D, the HRs (95% CI) were 1.23 (1.04-1.48), 1.76 (1.46-2.13), 2.78 (2.22-3.48), and 4.25 (3.23-5.59), respectively and for discordant conditions 1.32 (1.13-1.55), 1.46 (1.23-1.74), 1.77 (1.45-2.17), and 2.44 (2.01-2.99), respectively.

Conclusions: The association between MM and mortality is significant for total, concordant and discordant condition count, but was strongest for concordant. Our findings emphasize the need for clinical guidelines and future MM measures to consider MM in people with T2D, both concordant and discordant.

Disclosure

J.I. Chiang: None. P. Hanlon: None. B.D. Jani: None. J.E. Manski-Nankervis: Research Support; Self; Australian National Health and Medical Research Council, Boehringer Ingelheim International GmbH, Diabetes Australia, Eli Lilly and Company. Speaker's Bureau; Self; RACGP. J. Furler: Research Support; Self; Abbott, Sanofi. B.I. Nicholl: None. F.S. Mair: None.
1565-P: Gender Differences in Clinical Predictors of Nonalcoholic Steatohepatitis in Type 2 Diabetes
Authors: PANICKER SHASHI , STEPHENS JEFFREY W.
Published: June 2019

Introduction: Nonalcoholic steatohepatitis (NASH) associated with type 2 diabetes (T2D) increases the risk for cardiovascular disease, cirrhosis and hepatocellular carcinoma. Several clinical predictors of NASH are known but gender differences in subjects with T2D are unknown.

Aims: To determine gender differences in clinical predictors of NASH in Asian Indians with T2D.

Methods: This one-year prospective study was conducted after institutional approval and informed consent. Recruited participants had no history of liver disease, hepatotoxic drugs or alcohol intake. Transient elastography by FibroScan, validated for diagnosis of fibrosis by liver stiffness measurement (LSM), was used in this study. NASH was diagnosed when LSM was ≥7 kPa.

Results are tabulated below.

Conclusions: In subjects with T2D, women had significantly higher prevalence of NASH (34.7%) compared to men (26.3%), with a 50% higher risk. Obesity, hypertriglyceridemia and hypoalbuminemia were strong predictors of NASH in both genders. Systolic hypertension doubled the risk in women but was not significant in men, while hyperglycemia was a significant predictor in men but not in women. Raised Waist/Height Ratio conferred much higher risk of NASH in women compared to men, while the high risk due to raised BMI and waist circumference was similar in both genders. Predictors of NASH are crucial targets for intervention but vary by gender.

Disclosure

S. Panicker: Speaker's Bureau; Self; Abbott, AstraZeneca, Biocon, Dr. Reddys Laboratories, Eli Lilly and Company, Intas Pharmaceuticals Ltd., Johnson & Johnson, Novartis AG, Novo Nordisk A/S, Sanofi India Pvt Ltd; Speaker's Burea; Self; SUN Pharma Self.J.W. Stephens: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc. Speaker's Bureau; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes, NAPP Pharmaceuticals Limited.
1570-P: The Haptoglobin 2 Allele Is Associated with Cardiac Autonomic Neuropathy in Both Type 1 Diabetes and Controls: The Retro HDLc Study
Authors: JU JINGHUI , TOMASZEWSKI ERIN L. , ORCHARD TREVOR J. , COSTACOU TINA
Published: June 2019

The Haptoglobin (Hp) 2-2 genotype has been shown to increase the risk of coronary artery disease (CAD), kidney dysfunction and mortality from cardiovascular and renal causes in type 1 diabetes (T1D), although similar associations have not been observed in nondiabetic persons. However, whether the Hp 2 allele is associated with cardiac autonomic neuropathy (CAN), a CAD predictor, has not been previously studied. We thus assessed the presence of such an association in participants with childhood onset T1D (EDC study, n=216, mean 51 years) and age and gender matched nondiabetic controls (RETRO HDLc study, n=200). CAN was defined as a history of abnormal heart rate response to deep breathing (expiration-inspiration ratio < 1.1). The proportion of Hp 2 allele carriers did not differ by T1D (87% in T1D vs. 84% in controls, p=0.13), although participants with T1D had a greater CAN prevalence compared with controls (49% vs. 12%, respectively, p<0.0001). In multivariable logistic regression models, adjusting for traditional risk factors (age, BMI, hypertension, HDL and non-HDL cholesterol, albumin to creatinine ratio, estimated glomerular filtration rate (eGFR), white blood cell count), and T1D status, participants with any Hp 2 allele had significantly higher odds of CAN compared with participants with the Hp 1-1 genotype (OR=2.91, p=0.01). Age (OR=1.04, p=0.02), the presence of T1D (OR=5.17, p<0.0001), hypertension (OR=1.76, p=0.05) and eGFR (OR=0.98, p=0.003) were also associated with CAN. No significant interaction was found between T1D and Hp genotype (p=0.73); thus, stratifying by T1D, Hp 2 increased the odds of CAN in both T1D (OR=2.50, p=0.07) and controls (OR=6.70, p=0.08).

In conclusion, unlike the restriction of the Hp - kidney disease association to individuals with diabetes, the Hp 2 allele appears to be independently associated with greater odds of CAN in both T1D and nondiabetic controls.

Disclosure

J. Ju: None. E.L. Tomaszewski: None. T.J. Orchard: Consultant; Self; Boehringer Ingelheim International GmbH. T. Costacou: None.

Funding

National Institutes of Health (R01HL130153, DK34818)
1577-P: Dietary Intake Trends Associated with Breakfast Skipping in U.S. Adults by Diabetes Status
Authors: KELLY OWEN , FANELLI STEPHANIE M. , KROK-SCHOEN JESSICA L. , TAYLOR CHRISTOPHER A.
Published: June 2019

Skipping breakfast is considered an unhealthy behavior and has been associated with an increased risk of diabetes and poor glycemic control in people with diabetes. Little is known regarding the impact of breakfast skipping on daily energy and nutrient intakes, as well as at eating occasions in people with versus without diabetes. National Health and Nutrition Examination Survey data (2005-16), and hemoglobin A1c data, were used to examine differences in dietary intakes of those who self-reported consuming or skipping breakfast. Adults over 30 years (n=23708) were stratified using A1c values into diabetes status: <5.7% (nondiabetes, n=14841); 5.7-6.4% (prediabetes, n=5923); ≥6.5% (diabetes, n=2944). Mean dietary intakes were calculated from the total daily intake, including snacking occasions across diabetes status for those consuming or skipping breakfast. Data analyses were weighted to create a nationally representative sample. The rate of breakfast skipping was similar across diabetes status (10.6-12%). Overall, mean intakes of energy, carbohydrates and added sugars were lower in adults with diabetes, yet were greater in those who skipped breakfast. Those with nondiabetes and prediabetes who skipped breakfast had lower mean intakes of energy, protein, and saturated fat, yet the total intakes were higher in adults with diabetes. Mean intakes of added sugars were higher in adults who skipped breakfast, with adults with diabetes consuming 25% more added sugars if they skipped breakfast. For those that skipped breakfast, higher mean intakes of energy, carbohydrates, saturated fat, refined grains and added sugar from snacks were observed. For people with diabetes, skipping breakfast was associated with poorer total daily dietary intakes, especially the percent of energy from added sugars. Breakfast skippers consumed snacks with more energy, carbohydrate and sugar. These data suggest skipping breakfast has a negative relation to overall dietary intakes for people with diabetes.

Disclosure

O. Kelly: Employee; Self; Abbott. Employee; Spouse/Partner; Abbott. S.M. Fanelli: None. J.L. Krok-Schoen: None. C.A. Taylor: Consultant; Self; Abbott Laboratories. Research Support; Self; Abbott Laboratories. Other Relationship; Self; Elsevier.

Funding

Abbott Nutrition
1586-P: Impact of Hurricane Matthew on Diabetes Self-Management and Outcomes
Authors: TRAVIA KEVIN , KAHKOSKA ANNA R. , SOURIS KATHERINE J. , BEASLEY CHERRY M. , MAYER-DAVIS ELIZABETH
Published: June 2019

Introduction: Individuals with diabetes require extensive self-management. Little is known about how a hurricane impacts diabetes self-management or outcomes and how it perpetuates health disparities in Robeson County, NC, a county where there is a high proportion of minority racial groups.

Methods: Mixed methods were used to assess the impact of hurricanes on diabetes outcomes. Mean hemoglobin A1c (HbA1c) and frequency of diabetic ketoacidosis (DKA) from the Southeastern Regional Medical Center from 6 months before and after Hurricane Matthew (HM) were compared using student t-tests. Individuals with diabetes ≥ age 18 in Robeson County were recruited for focus groups and administered questionnaires to understand the perceived impact of the hurricane on diabetes self-management. Healthcare providers were recruited for parallel key informant interviews.

Results: 7,550 and 6,715 individuals had HbA1c measures available before and after HM, respectively. A demographic breakdown of 34.3% white, 21.7% black or African American, and 21.4% American Indian or Alaska Native was observed in the sample representing 6 months after HM. No significant differences were found between mean HbA1c values before and after HM (before HM: mean HbA1c 8.34 ± 1.87%; after HM: mean HbA1c 8.31 ± 1.93%; p=0.366). The period prevalence (PP) of DKA was more frequent in the 6 months after HM than before (before HM: 69 cases out of 9,094 visits, PP=0.00759; after HM: 87 cases out of 8,042 visits, PP=0.0108; p=0.028). Significant themes from preliminary qualitative results highlight a lack of access to a balanced diet and diabetes medications that occurs during hurricanes in Robeson County, NC, especially for those of low socioeconomic position (SEP).

Conclusions: Individuals with diabetes were more likely to experience poor diabetes outcomes after Hurricane Matthew than before. Future interventions may improve outcomes via increased access to healthful foods and diabetes medications, particularly for those of low SEP.

Disclosure

K. Travia: None. A.R. Kahkoska: None. K.J. Souris: None. C.M. Beasley: None. E. Mayer-Davis: None.

Funding

Honors Carolina
1592-P: Prediction Method for Infection Risk in Perioperative Patients with Diabetes
Authors: KOSHIZAKA MASAYA , ISHIBASHI RYOICHI , MAEDA YUKARI , ISHIKAWA TAKAHIRO , MAEZAWA YOSHIRO , TAKEMOTO MINORU , YOKOTE KOUTARO
Published: June 2019

Background/Purpose: Perioperative blood glucose management is important for complication prevention and early hospital discharge. The relation between blood glucose fluctuations and infection is few reported. This study aimed to find predictive risk factors to identify high-risk patients with diabetes requiring more extensive management.

Methods: A retrospective study was performed on the perioperative blood glucose management of 105 patients. The presence of infection within one month after surgery was the primary outcome, and the predictive factors were identified. For statistical analysis, analysis of variance or Wilcoxon rank sum test was used. Based on univariate analysis, principle component analysis and logistic analysis were performed to prepare a prediction model of infection onset within one month after surgery using predictive risk factors. The area under the receiver operating characteristic curve (AUC) was evaluated.

Results: Patients with infection within one month after surgery had higher mean blood glucose levels (185.1±28.7 vs. 168.3±33.6 mg/dL, P=0.013), larger preoperative blood glucose fluctuations (54.9±24.1 vs. 37.7±23.1 mg/dL, P=0.006), lower albumin level (3.6±0.6 vs. 3.9±0.6 g/dL, P=0.046), longer operation time (432.5±179.6 vs. 282.5±178.3 minute, P<0.001), more bleeding (972.3±920.1 vs. 436.4±795.8 mg/dL, P=0.003), and longer postoperative hospitalization periods (51.9±56.1 vs. 22.4±24.3 days, P<0.001) than patients without infection. They also had greater frequency of adverse events (hazard ratio (HR)=3.19, P=0.013) and mortality within 1 year (HR=4.03, P=0.026). Preoperative blood glucose fluctuation and operation time were considered as more reliable factors of the prediction model. The model had high prediction accuracy with AUC 0.801.

Discussion: Preoperative blood glucose fluctuations and long operation time were risk factors for infection in perioperative patients with diabetes. This prediction model can detect these high-risk patients.

Disclosure

M. Koshizaka: Research Support; Self; Astellas Pharma Inc., Pfizer Health Research Foundation, Taisho Pharmaceutical Co., Ltd. R. Ishibashi: None. Y. Maeda: None. T. Ishikawa: None. Y. Maezawa: None. M. Takemoto: None. K. Yokote: None.

Funding

Pfizer Health Research Foundation
1594-P: The Impact of Diabetes on Productivity in China
Authors: HIRD THOMAS R. , ZOMER ELLA , OWEN ALICE J. , CHEN LEI , ADEMI ZANFINA , MAGLIANO DIANNA J. , LIEW DANNY
Published: June 2019

Diabetes increases the risk of premature death and reduces work productivity. We estimated the impact of diabetes in China in terms of mortality, years of life lost, and productivity-adjusted life years (PALYs) lost in the Chinese population. Life table modelling was used with simulated follow-up of those with diabetes in the Chinese population of working age (20-49 years in women and 20-59 years in men) until retirement age (50 years for women and 60 years for men). Data regarding the prevalence of diabetes, as well as excess mortality, labor force drop out and productivity loss attributable to diabetes, were taken from published sources. Models were constructed for the cohort with diabetes and repeated for the same cohort assuming that they had no diabetes. The differences in number of deaths, years of life lived and PALYs lived between the two models reflected the impact of diabetes. The World Health Organization standard 3% annual discount rate was applied to years of life and PALYs lived. In 2017, an estimated 56.4 million people of working age in China (7.1%) had diabetes. With simulated follow-up, those with diabetes were predicted to experience an estimated 4.1 million more deaths, the loss of 22.7 million years of life (3.7%) and the loss of 75.8 million PALYs (15.3%). This was equivalent to an average of 1.4 PALYs lost per person with diabetes. Based on gross domestic product (GDP) per full time worker in 2017, the loss in PALYs equated to a total of CNY ¥17.4 trillion (USD $2.6 trillion) in lost GDP due to reduced productivity, with an average of ¥307,923 ($45,959) lost per person with diabetes. Our study demonstrates the significant cumulative impact of diabetes on productivity across the working lifetime in the Chinese population, highlighting the potential economic payoff of diabetes prevention in the longer term.

Disclosure

T.R. Hird: None. E. Zomer: Consultant; Self; Amgen Inc., AstraZeneca, Pfizer Inc., Shire. A.J. Owen: None. L. Chen: None. Z. Ademi: None. D.J. Magliano: None. D. Liew: Advisory Panel; Self; AstraZeneca, Bayer AG. Research Support; Self; AbbVie Inc., AstraZeneca, Bristol-Myers Squibb Company, CSL Behring, Pfizer Inc.
1596-P: Triglyceride and Glucose (TyG) Index Is an Effective Predictor of Nonalcoholic Fatty Liver Disease/Nonalcoholic Steatohepatitis
Authors: KIM KYUNG-SOO , HWANG YOU CHEOL , AHN HONG-YUP , PARK SUNG-WOO , PARK CHEOL-YOUNG
Published: June 2019

Nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) is associated with insulin resistance and considered as a liver manifestation of metabolic syndrome. Triglycerides and glucose (TyG) index is a useful marker of insulin resistance but there are few studies about association between TyG index and NAFLD/NASH. The aim of this study was to investigate the ability of TyG index to identify NAFLD/NASH through comparing with fatty liver index (FLI) in a Korean population using a large health study database. We enrolled 187,725 subjects (107,246 men and 80,479 women) in the Kangbuk Samsung Health Study cohort. All subjects were completed a comprehensive annual or biennial health examination from 2007 through 2013. The presence of NAFLD was ascertained by ultrasonography in the absence of other known liver diseases. NASH was defined as NAFLD with FIB-4 index > 1.3. Mean age was 37 years and mean body mass index (BMI) was 23.26 m/kg2. The prevalences of NAFLD and NASH were 35.66% (n = 66,946) and 3.06% (n = 5,749), respectively. During a median 3.92-year follow-up, the hazard ratios (HR) of TyG index and FLI for NAFLD were 1.772 (95% CI 1.747-1.798) and 1.424 (95% CI 1.411-1.438), respectively. After adjusting for age, sex, and BMI, there were still elevated HRs for NAFLD (TyG index: 1.322, 95% CI 1.301-1.344; FLI: 1.094, 95% CI 1.073-1.116). The area under the ROC curve for identifying NAFLD of TyG index and FLI were 0.799 and 0.873, respectively. In non-obese subjects (BMI < 23 kg/m2), higher TyG index was associated with an increased risk of NASH (HR 1.222; 95% CI 1.095-1.363) but FLI was not (HR 1.056; 95% CI 0.922-1.209). In addition, there were similar results in obese subject (TyG index: 1.085, 95% CI 1.046-1.126; FLI: 0.994, 95% CI 0.942-1.049). These results suggested that TyG index was superior to FLI in association with NAFLD/NASH risk. The TyG index is effective to identify subjects at risk for NAFLD/NASH.

Disclosure

K. Kim: None. Y. Hwang: None. H. Ahn: None. S. Park: None. C. Park: None.
160-OR: Pretreatment Diabetes Has Lower Mortality Rate, Independent of Immune-Related Adverse Events, in Cancer Patients with Immune-Check Point Inhibitor
Authors: HISANAGA KAORI , UCHINO HIROSHI , YOSHIKAWA FUKUMI , SHIGIYAMA FUMIKA , KUMASHIRO NAOKI , HIROSE TAKAHISA , ANDO YASUYO , MIYAGI MASAHIKO , ISOBE KAZUTOSHI , HOMMA SAKAE
Published: June 2019

Objective: Immune checkpoint inhibitors (ICIs) are novel anticancer agents, also generate peculiar dysimmune toxicities, related to immune-related adverse events (irAEs) that might potentially prolong the survival rate. Our aim was to evaluate diabetes prior to ICIs has any effect on mortality rate, associated with irAEs, to the response in patients inappropriate to operation lung cancer.

Methods: Subjects diagnosed during Sep 1, 2015 to Jul 31, 2018 were retrospectively enrolled and followed until Jan 20, 2018, using Toho University NEPTUNE database. Hazard ratios were estimated using Cox regression weighted for propensity scores. Odds ratios (ORs [95% CI]) were calculated with logistic regression and adjusted for imbalanced variables (standardized difference more than 0.2). The Kaplan-Meier method was used to overall survival, and the generalized Wilcoxon test was used to compare median survivals.

Results: A total of 88 patients participated, of whom 22 (25.0%) had pre-ICIs diabetes (DM) and 57 (75.0%) were not pre-ICIs diabetes (nonDM). The irAEs was observed in 12.2% of DM and 9.1% of nonDM (p=0.33). Both nonDM and DM has not been associated to irAE’s status for baseline characteristics (age, sex, clinical stage, thyroid status, and renal function) and propensity score matching. Multiple logistic regression analyses revealed that the risk of overall survival was significantly lower in subjects with male than those with female (OR = 0.11, 95% CI = 0.01-0.94, p = 0.044). During a mean follow-up of 21.1 months (adherence rate, 88%), overall 37-month post-ICIs survival was significantly lower in the DM group (Kaplan-Meier estimates 77% vs. 66%; p=0 043), resulting in a 38% reduction in the mortality hazard ratio (0 62 [95% CI 0 40-0 95]).

Conclusion: Pre-ICIs treatment diabetes per se, diminish mortality rate in inappropriate to operation lung cancer patients, independently to irAEs on immune-check point inhibitor.

Disclosure

K. Hisanaga: None. H. Uchino: None. F. Yoshikawa: None. F. Shigiyama: None. N. Kumashiro: Speaker's Bureau; Self; Novo Nordisk Inc., Sanofi, Takeda Pharmaceutical Company Limited. T. Hirose: None. Y. Ando: None. M. Miyagi: None. K. Isobe: None. S. Homma: None.
1608-P: Suboptimal Management of Diabetes in India: Findings from a Large Community-Based Study
Authors: MOHAN SAILESH , VENKATESHMURTHY NIKHIL SRINIVASAPURA , JARHYAN PRASHANT , SHARNNGADHARAN GANESH KUMAR
Published: June 2019

Over the past few decades diabetes prevalence has rapidly increased across India. However, limited information is available on the levels of awareness, treatment and control, particularly in epidemiologically transitioning communities. We estimated the prevalence, awareness, treatment and control rates of diabetes in a large representative population sample aged ≥ 30 years, selected using a multistage cluster random sampling technique, residing in rural and urban areas of North and South India. Trained interviewers administered a questionnaire to collect data on socio-demographics, lifestyle characteristics and phlebotomists collected venous blood samples to estimate fasting plasma glucose (FPG) and HbA1C. Diabetes was defined as FPG ≥ 126 mg/dl or HbA1C ≥ 6.5% or self-report of physician diagnosis or being on treatment. Participants were considered to be aware of diabetes if they reported a diagnosis or being on treatment. Control was defined as HbA1C < 7%. In total 12243 participants (6208 in North and 6035 in South) were surveyed. The mean (±SD) age was 47.7 (±12.5) years. Women constituted 54%. The age-standardized prevalence of diabetes was 14.2 (95% CI: 13.6 - 14.9), with significant difference between urban (21.4%; 20.4-22.5) and rural (7.5%; 6.8-8.2) areas. Among those with diabetes, the awareness, treatment and control rates were 49.4% (46.6-52.2), 38.6% (35.9-41.3) and 12.6% (10.9-14.5) respectively. Compared to urban residents, rural counterparts were less likely to be aware (35% Vs. 55%), treated (26% Vs. 43%) and controlled (8% Vs. 14%). Similarly, patients in the lowest tertile of wealth index had lower awareness (33% Vs. 55%), treatment (22% Vs. 43%) and control rates (5% Vs. 15%) compared to those in the highest tertile. Despite a high burden, management of diabetes is sub-optimal in India. Health system strengthening to better manage diabetes with a focus on rural residents and the poor is imperative to stem the rising burden and improve diabetes related health outcomes.

Disclosure

S. Mohan: None. N.S. Venkateshmurthy: None. P. Jarhyan: None. G. Sharnngadharan: None.
1610-P: On the Combined Effect of C-Reactive Protein (CRP) and Serum Amyloid Component P (SAP) on Mortality Risk in Type 2 Diabetes
Authors: SCARALE MARIA GIOVANNA , COPETTI MASSIMILIANO , GAROFOLO MONIA , SALVEMINI LUCIA , CSOMO SALVATORE DE , LAMACCHIA OLGA , PENNO GIUSEPPE , TRISCHITTA VINCENZO , MENZAGHI CLAUDIA
Published: June 2019

CRP and SAP are the two short, strongly homologous pentraxins produced in response to inflammation. Though their common contribution to innate immunity, they seem to differently affect atherosclerosis and related clinical outcomes. In the specific context of mortality rate i) CRP is a recognized risk biomarker; ii) data on SAP are sparse and conflicting; iii) no data are available on their possibly combined effect. Accordingly, the combined effect of CRP and SAP on mortality risk was investigated in the high-risk subset of patients with type 2 diabetes (T2D). Four cohorts of patients with T2D [i.e., Gargano Heart Study (GHS; n=358; follow-up (f-u)=5±3 years; 81 events); Gargano Mortality Study (n=650; f-u=11±4 years; 190 events); Foggia Mortality Study (n=530; f-u=7±3 years; 146 events) and Pisa Mortality Study (n=986; f-u=13±3 years; 230 events)] were analyzed by Cox proportional hazard models. In the pooled sample, with a total of 2,524 individuals experiencing 647 events, hs-CRP was positively [HR=1.53 (95% CI 1.41-1.66)] whereas SAP was negatively [HR=0.80 (95% CI 0.74-0.86)] associated with all-cause mortality. Similar results were observed on cardiovascular death in GHS: HR (95% CI) being 1.90 (1.48-2.44) and 0.78 (0.61-0.98) for hs-CRP and SAP, respectively. The whole sample was then stratified according to relatively low and high hs-CRP and SAP (< or > the median value), so to obtain four groups: low/high (1), low/low (2), high/high (3), and high/low (4) hs-CRP/SAP levels. As compared to group 1, group 2, 3 and 4 had HRs (95% CIs) of 1.25 (0.96-1.64), 1.80 (1.39-2.33) and 2.40 (1.81-3.17) for all-cause mortality (p for trend=1.1x10-11 or, in a model comprising study sample, age, sex, smoking habit, BMI, HbA1c, diabetes duration and all ongoing treatments, p=4.1x10-8).

In conclusion, in patients with T2D, hs-CRP and SAP show a combined effect on all-cause death. Whether their simultaneous use may prove to be useful in predicting mortality in T2D needs further investigation.

Disclosure

M. Scarale: None. M. Copetti: None. M. Garofolo: None. L. Salvemini: None. S. De Csomo: None. O. Lamacchia: None. G. Penno: None. V. Trischitta: None. C. Menzaghi: None.

Funding

Italian Ministry of Health (RF-2013-02356459)