bluuebunny/crossref_metadata_2025_split huggingface dataset:
1088-P: Can Machine Learning Support Decision for Insulin Initiation in Patients with Type 2 Diabetes?
Authors: FUJIHARA KAZUYA , SONE HIROHITO 
Published: June 2021

We examined the ability of machine learning models to predict insulin initiation by specialists and examined whether the machine learning approach could support decision-making by general physicians for insulin initiation in patients with type 2 diabetes. Prescription data from diabetes specialists’ patient registries on antidiabetic agents from 2009 to 2015 were used for 4,860 patients who received initial monotherapy with either insulin (293 patients) or non-insulin (4,567 patients) and had laboratory data. Neural network output was insulin initiation ranging from 0 to 1 with a cutoff &gt;0.5 for the dichotomous classification. Accuracy, recall and area under the receiver operation characteristic curves (AUCs) were calculated to compare the ability of machine-learning decisions on insulin initiation to decisions by logistic regression and 22 general physicians. Then, in comparing the ability of machine-learning and logistic regression decisions to decisions made by general physicians, the gold standard was defined as 80% agreement among 9 diabetes specialists based on patients’ information. AUCs and accuracy according to logistic regression were higher than those of machine learning (AUC of logistic regression, 0.89-0.90; AUC of machine learning, 0.67-0.74). Recall (accuracy of the cases receiving insulin) in machine learning was similar to that of logistic regression analysis (recall of logistic regression, 0.05-0.68; recall of machine learning, 0.11-0.52). The accuracy of logistic regression and the machine learning model was 1.00 and 0.86, respectively, for down sampling ratios of 1:8, which was higher than that of general physicians (0.43) for 7 gold standard cases.
In conclusion, machine learning had higher accuracy in prediction of insulin initiation compared with that of general physicians defined by diabetes specialists’ choice of the gold standard. Assistance by machine learning may be beneficial to any general physician in deciding upon insulin initiation.

Disclosure
K. Fujihara: None. H. Sone: Research Support; Self; Astellas Pharma Inc., Eisai Co., Ltd., Kyowa Kirin Co., Ltd., Novo Nordisk, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co.

Funding
Japan Society for the Promotion of Science (19H04028)
1089-P: Abnormal Glucose Tolerance Consequences Depend on Etiology: Insulin Resistance vs. ß-Cell Failure
Authors: ISHIMWE MARIE CONSOLATRICE SAGE , HORMENU THOMAS , SHOUP ELYSSA M. , OSEI-TUTU NANA H. , PATTERSON ARIELLE , WENTZEL ANNEMARIE , BAGHERI MOHAMMAD-HADI , DUBOSE CHRISTOPHER , MABUNDO LILIAN , HA JOON , SHERMAN ARTHUR , SUMNER ANNE E. 
Published: June 2021

Abnormal glucose tolerance (Abnl-GT) is due to an imbalance between insulin resistance (IR) and β-cell function. Recent data from Africa suggest that β-cell failure contributes to the development of Abnl-GT more than previously recognized. Therefore in 490 African-born Blacks living in the United States (Male 64%, Age 38±10y (mean±SD), we compared the prevalence and metabolic characteristics of Abnl-GT due to IR (Abnl-GT-IR) to Abnl-GT due to β-cell-failure (Abnl-GT-β-cell-failure). Based on OGTT, Abnl-GT was defined as fasting glucose≥100 mg/dL or 2h glucose≥140 mg/dL. Visceral adipose tissue (VAT), triglyceride (TG) and 10y-Cardiovascular Risk-Score (CVD-Risk-Score) were measured. The cohort was divided into quartiles of HOMA-IR and quartiles of Matsuda Index. IR was defined by thresholds at the upper quartile of HOMA-IR (≥2.05) or the lowest quartile of the Matsuda index (≤2.97). Diagnosis of Abnl-GT-IR required both Abnl-GT and IR. Abnl-GT-β-cell failure was defined as Abnl-GT without IR. Abnl-GT occurred in 38% (181/490) of Africans. Of the Africans with Abnl-GT, insulin resistance occurred in 38% (68/181) and β-cell-failure occurred in 62% (113/181) of the Africans. Compared to Africans with Abnl-GT-β-cell-failure, Africans with Abnl-GT-IR had higher BMI (31.0±4.5 vs. 27.4±3.8 kg/m2), VAT (160±72 vs. 111±65 cm2), TG (106±52 vs. 77±39 mg/dL) (all P&lt;0.001) and CVD-Risk-Score (26±24 vs. 19±17) (P&lt;0.05). Independent of whether IR was defined by HOMA-IR or Matsuda index, results were similar. Alcohol intake was higher in the Abnl-GT-IR group (P=0.05), but other potential confounders such as years in the United States, income, education, sedentary behavior and fiber intake did not differ. Overall, Abnl-GT-IR was less common than Abnl-GT-β-cell-failure, but the metabolic profile was worse in Abnl-GT-IR. To determine the clinical course for these two types of Abnl-GT, prospective study design needs to include methodology to both diagnose Abnl-GT and elucidate the cause.

Disclosure
M. Ishimwe: None. J. Ha: None. A. Sherman: None. A. E. Sumner: None. T. Hormenu: None. E. M. Shoup: None. N. H. Osei-tutu: None. A. Patterson: None. A. Wentzel: None. M. Bagheri: None. C. Dubose: None. L. Mabundo: None.
1094-P: Attrition Rates among Participants in the National Diabetes Prevention Program: Variation by Organization Type, State, and Region
Authors: ZHANG XUANPING , CANNON MICHAEL , NG BOON PENG , ELY ELIZABETH 
Published: June 2021

The National Diabetes Prevention Program (National DPP) has been implemented nationwide, but it remains unclear how implementation varies by organization type, state, and region. To better understand this issue, we examined participant attrition rates using data from the CDC’s Diabetes Prevention Recognition Program. We included those who enrolled from March 2018 through February 2019 and had the opportunity to attend for at least one year in the study population. We limited our analyses to live-delivery organizations (i.e., in-person, distance learning, and combination) to minimize variation by delivery mode. Cumulative attrition rates were calculated by organization type (community centered entities, higher education/extensions, government, medical providers, for-profit and insurers, other), state, and region (West, Southwest, Midwest, Northeast, Southeast). We used cross-tabulation method with chi-square tests. The study population (N=70,194) was 80.8% female, 71.6% white, with a mean age of 55.4 years (SD: 13.0) and mean BMI of 35.5 kg/m2 (SD: 7.3). We found that for-profit and insurer organizations had significantly higher cumulative attrition rates compared to other organization types (through Session 5: 30.3% in for-profit and insurer organizations vs. 10.8%-17.4% in the other types, p&lt;0.05). This pattern continued until Session 16 when similar attrition rates emerged from all organization types. Attrition rates across states also demonstrated large variations (through Session 5: highest (CA): 31.9% vs. lowest (ND): 2.2%, nation average: 17.9%). Northeast and West had higher attrition rates compared to the other three regions (through Session 5: 25.9% in Northeast and 22.6% in West vs. 8.7%-16.2% in the other three regions, p&lt;0.05). Our findings can be used to evaluate program performance and help improve program implementation at the organization, state, and region levels.

Disclosure
X. Zhang: None. M. Cannon: None. B. Ng: None. E. Ely: None.

Funding
Centers for Disease Control and Prevention
110-LB: Efficacy, Safety, and Appropriateness of iGlarLixi, a Fixed-Ratio Combination (FRC) in Type 2 Diabetes (T2D) in Real-World Settings: Results from the ENSURE Study
Authors: CANDIDO RICCARDO , MODUGNO MONICA , GABELLIERI ENRICO , NICOLUCCI ANTONIO , ROSSI MARIA CHIARA , LAROSA MONICA ,   ON BEHALF OF ENSURE STUDY GROUP
Published: June 2021

Randomized clinical trials (RCT) showed benefits of FRC of basal insulin (BI) and GLP1-RAs in terms of glycemic target, no weight gain, low risk of hypoglycemia, and gastrointestinal side effects. Real-world evidence (RWE) complements RCT to assess effectiveness and safety of drugs in clinical practice. The study evaluated the impact of iGlarLixi [once-daily FRC of basal insulin glargine 100 U/mL and GLP1-RA lixisenatide] in T2D. This was a retrospective, multicenter study, based on electronic medical records. All subjects initiating iGlarLixi in May 2018-July 2020 were analyzed. Overall, 25 centers provided data on 675 subjects with the following baseline characteristics (mean and standard deviation or proportion): age: 66.4±10.1 years, 54.2% men, T2DM duration 15.5±11.5 years, HbA1c 8.6±1.4%, and BMI 30.8±5.3 Kg/m2. Before starting iGlarLixi, 67.3% of subjects were treated with BI and 9.9% with GLP1-RA (5.5% as free combinations). Drugs associated with iGlarLixi were not only metformin and SGLT2 inhibitors, as by summary of product characteristics (SmPC); off-label combinations were found in 32.4% of patients (21.4% sulphonylureas). Effectiveness data (N=184) showed that HbA1c decreased by -0.77% [95%CI -1.00;-0.54] after 6 months and by -0.92% [95%CI -1.22;-0.62] in patients treated as by SmPC. Weight significantly decreased by 1.21 Kg. iGlarLixi dose increased by 5.14 U. Rates of blood glucose ≤70 and &lt;54 mg/ml (N=171) were 0.26 and 0.05 events per person-month, respectively. No severe hypoglycemic events occurred. Participants discontinuing iGlarLixi within 6 months were 122 (18.1%). After discontinuation, 45.1% of patients started BI plus short acting insulin. In predominantly overweight/obese T2D people with poor metabolic control and long-lasting disease, effectiveness and safety of iGlarLixi are documented in real life, but improvements in treatment appropriateness are required.

Disclosure
R. Candido: None. M. Modugno: None. E. Gabellieri: None. A. Nicolucci: Advisory Panel; Self; AstraZeneca, Research Support; Self; Novo Nordisk, Pikdare, Sanofi, Shionogi & Co., Ltd., SOBI. M. Rossi: Research Support; Self; Novo Nordisk, Sanofi, Shionogi & Co., Ltd., Swedish Orphan Biovitrum AB. M. Larosa: Employee; Self; Sanofi. On behalf of ensure study group: n/a.

Funding
Sanofi
1108-P: Care Cascade Engagement and Characteristics of Diabetes Awareness in Adult Samoans in 2010 and 2018
Authors: RIVARA ANNA C. , RUSSELL EMILY M. , VIALI SATUPAITEA , REUPENA MUAGUTUTIA SEFUIVA , NASERI TAKE K. , POMER ALYSA , MINSTER RYAN L. , WEEKS DANIEL E. , MCGARVEY STEPHEN T. , HAWLEY NICOLA 
Published: June 2021

We describe diabetes care cascade engagement in 2010 and 2018 in adult Samoans and identify the characteristics of diabetes awareness. Participants were from a 2010 study of Samoans (n=2980, 24.5-&lt; 65 years old), n= 500 of whom were followed-up in 2018 (32.5-72.5 years old). At follow-up individuals with a genetic variant associated with lower fasting glucose were oversampled by design. Care cascade components included diabetes prevalence (fasting glucose ≥ 126 mg/dL or diabetes medication use), self-report of doctor’s diagnosis of diabetes (awareness), diabetes medication use, and meets recommended glycemic control (fasting glucose ≤ 130 mg/dL). Percentage loss (proportion of individuals lost from each preceding stage) and unmet need of care (total prevalence - proportion of participants with controlled diabetes) were estimated. Characteristics associated with awareness were examined with logistic regression. In 2010, 469/2980 (15.7%) participants had diabetes, 242 (48.4% loss) were aware, 215 (11.1% loss) reported medication use, and 33 (84.6% loss) met glycemic control (unmet need of 92.9%). In 2018, 146 (29.2%) had diabetes; 61 (57.8% loss) were aware; 48 reported medication use (22.6% loss), and 7 (85.4% loss) met glycemic control (unmet need of 95.2%). Each year of added age (OR 1.07 [1.04-1.10] in 2010 and OR 1.06 [1.01-1.11] in 2018), and higher material lifestyle scores, a proxy for socioeconomic position, (OR 1.16 [1.02-1.33] in 2018) were associated with higher odds of diabetes awareness, and higher BMI (OR 0.93 [0.90-0.96] in 2018) and OR 0.94 [0.89-0.99] in 2018) and smoking (OR 0.49 [0.31-0.78] in 2010) with lower odds of awareness. We observed a very high level of unmet need in diabetes care and a high proportion of participants lost within the care cascade at both time points. Greater odds of disease awareness with increasing socioeconomic position in 2018 suggest that socioeconomic constraints may limit care engagement.

Disclosure
A. C. Rivara: None. N. Hawley: None. E. M. Russell: None. S. Viali: None. M. Reupena: None. T. K. Naseri: None. A. Pomer: None. R. L. Minster: None. D. E. Weeks: None. S. T. Mcgarvey: None.

Funding
National Institutes of Health (R01HL093093, R01HL140570, R01HL133040)
1109-P: The Effect of Neighborhood Food Environment on Diabetes Risk: A Multilevel Analysis of the Veterans Administration Diabetes Risk Cohort
Authors: KANCHI RANIA , LOPEZ PRISCILLA M. , RUMMO PASQUALE E. , LEE DAVID C. , ADHIKARI SAMRACHANA , SCHWARTZ MARK D. , AVRAMOVIC SANJA , SIEGEL KAREN R. , ROLKA DEBORAH B. , IMPERATORE GIUSEPPINA , ELBEL BRIAN , THORPE LORNA 
Published: June 2021

Diabetes causes significant morbidity and mortality among adults in the US, yet incidence varies across the country, suggesting that neighborhood factors may contribute to geographic disparities in diabetes. In this longitudinal study, we examined the association between neighborhood food environment and risk of newly diagnosed (“incident”) diabetes in different communities (high density urban, low density urban, suburban, and rural).
We created a retrospective dynamic, national cohort of 6,082,018 diabetes free US veterans identified from the Veterans Affairs electronic health records, enrolled between 2008 and 2016, and followed through 2018. Incident diabetes was defined as: 2 clinical encounters with diabetes ICD codes, a documented prescription for diabetes medication other than metformin or acarbose alone, or 1 clinical encounter with diabetes ICD codes and 2 elevated A1C (≥6.5%). Five-year average counts of fast-food restaurants and supermarkets relative to all other food outlets were used to generate two census tract-level neighborhood measures. We examined the association between food environment and incident diabetes using piecewise exponential survival models with county-level random effects.
The average age of cohort participants was 59 years; the majority were non-Hispanic white (76.3%) and male (92.2%). Relative density of fast-food restaurants was associated with a modest increased risk of diabetes in all community types; adjusted hazard ratios (aHR) in high density urban, low density urban, and suburban communities were each 1.1, in rural communities was 1.2 (p &lt; 0.05 for all). Relative density of supermarkets was associated with lower diabetes risk in suburban and rural communities only (aHR 0.7, 0.8, respectively, p &lt;0.05).
Neighborhood fast food and supermarkets influenced diabetes risk among US veterans in multiple community types, suggesting potential avenues for action to address the diabetes burden.

Disclosure
R. Kanchi: None. G. Imperatore: None. B. Elbel: None. L. Thorpe: None. P. M. Lopez: None. P. E. Rummo: None. D. C. Lee: None. S. Adhikari: Research Support; Self; Johnson & Johnson. M. D. Schwartz: None. S. Avramovic: None. K. R. Siegel: None. D. B. Rolka: None.

Funding
Centers for Disease Control and Prevention
112-LB: Pulsatile Insulin Treatment as a Treatment Option for Patients with Type 2 Diabetes and Stage 3 Kidney Failure
Authors: QUACH SOPHIA , MANESSIS ANASTASIOS 
Published: June 2021

In healthy individuals, insulin is secreted by the pancreatic ß-cells in a pulsatile fashion with about 10-12 pulses/hour. Loss of this pulsatility is one of the first indications of ß-cell dysfunction leading to type 2 diabetes. This pulsatility of insulin secretion is considered a trigger mechanism for the regulation of hepatic gluconeogenesis and for maintaining the sensitivity of peripheral metabolic and vascular insulin receptors. Various attempts have been made over the last 30 years to use pulsatile i.v. insulin infusion therapy for treatment of diabetes and secondary complications. The purpose of this prospective randomized pilot study was to investigate the effect of once weekly PIT (2 h vs. 3 h procedures) over a period of 3 months on parameters of kidney function in patients with type 2 diabetes and chronic renal failure. Of the 22 enrolled type 2 patients, 17 performed the trial per protocol. They received a total of 10 PIT procedures. Observation parameters measured at baseline and endpoint were HbA1c, GFR, body weight, blood pressure, creatinine, nerve perception thresholds, and treatment satisfaction. At endpoint, there were no significant differences between the two groups. GFR improved by 10.8 % and creatinine decreased by 6.8 %. Stable results were seen for HbA1c, body weight and blood pressure. No changes were seen in nerve perception thresholds for any of the investigated sensory fiber qualities. The treatments were well tolerated. However, 8 treatment events of muscle cramps were reported for 5 patients during the PIT procedures. In conclusion, an improvement in kidney function and treatment satisfaction was observed after 3 months of PIT in patients with type 2 diabetes and renal failure, irrespective of the duration of the procedure. The results of this pilot trial will now be used to design an appropriate confirmatory study to investigate the effect of PIT when given in addition to standard of care treatment vs. standard of care alone.

Disclosure
S. Quach: None. A. Manessis: Advisory Panel; Self; Medtronic, Research Support; Self; IQVIA, Novo Nordisk, Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc., MannKind Corporation, Sanofi US.
1131-P: Clinical Prediction Models for MODY Genetic Testing in the United States Monogenic Diabetes Registry
Authors: MULLIGAN ROBERT P. , LETOURNEAU-FREIBERG LISA R. , BOWDEN TIANA L. , TIAN PERSEPHONE , KANDASAMY BALAMURUGAN , PHILIPSON LOUIS H. , GREELEY SIRI ATMA W. , NAYLOR ROCHELLE N. 
Published: June 2021

The University of Chicago National Monogenic Diabetes Registry houses a novel dataset of people presenting with possible or known monogenic diabetes and has over a decade of data points, despite the rarity of the disease relative to T1DM and especially T2DM. Currently, determination of genetic testing, including which specific panel or genes is most appropriate to sequence, is a manual process introducing variability and subjectivity.
Aim: To test and compare performance of several models against the manual process and each other in identifying maturity-onset diabetes of the young (MODY) from available clinical information.
Methods: Statistical models for prediction of monogenic diabetes were applied to clinical data for cases suspected of having MODY. The models tested in the study with this dataset ranged from the traditional methods of regression to more modern approaches of neural nets, classification trees, clustering, and other machine learning algorithms for classification of MODY against type 1 and type 2 and a possible subset of monogenic diabetes subtypes.
Results: Using a sample size of N=330, with 70 testing positive for either GCK, HNF1A, or HNF4A, exploratory data models were able to achieve 75-80% validation accuracy (random validation data set at 10-20% of N) while internal human classification accuracy was roughly 42% over the same samples. The traditional logistic regression and neural net had equivalent performance.
Conclusions: The 3750 participants within the Registry and more than a decade of follow-up presents a unique opportunity to assess which clinical features are most predictive in identifying those with monogenic diabetes. The results of this work will direct future testing efforts within the Registry to assist in efficient diagnosis of these uncommon yet clinically important forms of diabetes.

Disclosure
R. P. Mulligan: None. L. R. Letourneau-freiberg: None. T. L. Bowden: None. P. Tian: None. B. Kandasamy: None. L. H. Philipson: Advisory Panel; Self; Nevro Corp., Research Support; Self; Provention Bio, Inc. S. W. Greeley: None. R. N. Naylor: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK104942, P30DK020595)
1134-P: Polygenic Risk Score of Type 2 Diabetes as a Predictive Factor for Macrovascular Complications: A Prospective Population-Based UK Biobank Study
Authors: JUNG SANGHYUK , KIM DOKYOON , SHIVAKUMAR MANU , WON HONG-HEE , YUN JAE-SEUNG 
Published: June 2021

Background: We aimed to investigate the associations between polygenic risk score (PRS) for T2DM and future risk of cardiovascular disease (CVD) in middle-aged UK Biobank participants of European ancestry.
Methods: We used data from UK Biobank participants aged 40-69 years at baseline, registered from 22 assessment centers across the United Kingdom with standardized procedures. Genome-wide PRSs were constructed using &gt;9 million genetic variants, and newly developed myocardial infarction (MI), ischemic stroke, and cardiovascular (CV) mortality were considered as outcomes. Cox proportional hazard models were used to analyze the relationship between PRSs and CV mortality with stratification by age, sex, and lifestyle behavior.
Results: Of 362,405 participants having European ancestry, 8,787 (2.4%) experienced cardiovascular events and 2,414 (0.7%) died due to CVD during a median follow-up of 8.9 years. Risk of CV mortality and of myocardial infarction (MI) were both significantly associated with T2DM PRS (low vs. very high T2DM genetic risk groups, hazard ratio [HR] of CV mortality 1.73 [1.23-2.44] and HR of MI 1.55 [1.24-1.96], P &lt;0.001). By contrast, the risk of ischemic stroke was not associated with T2DM PRS (low vs. very high T2DM genetic risk groups, hazard ratio [HR] of CV mortality 1.24 [0.87-1.79], P =0.232). Adherence to an unfavorable lifestyle in the very high genetic risk group was further associated with a substantially increased risk of CV mortality (HR 6.38 [3.46-11.77]) and with risk of MI (HR 3.28 [2.02-5.32]). There was no evidence of significant interaction between PRS and lifestyle behavior in predicting the risk of CVD.
Conclusion: PRS for T2DM is an independent predictive factor for future CVD and associated mortality in the white, middle-aged population. PRS-based genetic risk assessment could be useful to identify individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CVD.

Disclosure
S. Jung: None. D. Kim: None. M. Shivakumar: None. H. Won: None. J. Yun: None.