bluuebunny/crossref_metadata_2025_split huggingface dataset:
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&lt;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&lt;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 &lt;0.001) and increased 24hUAER (27.53 ± 19.70 vs. 20.34 ± 13.92 mg/24h, P &lt;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 &lt; 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-&lt;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 &lt;18.5, 25-&lt;30, 30-&lt;35, 35-&lt;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 &lt; 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&lt;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&lt;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: &lt;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&lt;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&lt;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