bluuebunny/crossref_metadata_2025_split huggingface dataset:
1124-P: Hemoglobin A1c and BMI Are Not Correlated in Patients with Prediabetes
Authors: SINGH GURDEEP , HOWLAND TIMOTHY , SHAKJIRI BURIM , BUSH BERNARD , FATTARUSSO LOUIS , STEIN SARAH 
Published: May 2022

The correlation between the hemoglobin A1C and BMI in patients with type 2 diabetes is well established. The present study was undertaken to examine whether a similar correlation is present in patients with prediabetes. Between 2017 and 2021, patients within the Ascension Lourdes primary care network were screened for prediabetes and diabetes using the hemoglobin A1C. Patients on any blood sugar lowering medication other than metformin were excluded from observation. A total of 5,1patients between the ages of 18 - 79 with an A1C between 5.7-6.4%.were identified. From this 5,1patient group, a subgroup of 2687 patients had at least two encounters where concurrent BMI and HbA1C values were recorded. A correlation analysis was performed where findings showed a low correlation between the BMI and A1C (n = 2,687, r =0.1, R Squared = 0.01, p &lt; 0.05) . Only 1.1% of the variance in A1C values is explained by the BMI. In addition, there was no significant correlation between the A1C and BMI in subgroups divided by BMI classification and age. Additionally, there was not a statistically significant correlation in patients who developed one A1C greater than 6.4. (n =322 , r = 0.17, R Squared=0.03, p &lt; 0.05)
Conclusion: Among patients with an A1C between 5.7 - 6.4%, BMI does not account for concurrent changes in the hemoglobin A1C. BMI may therefore be of limited utility in predicting which patients with prediabetes are most likely to develop diabetes.

Disclosure
G.Singh: Stock/Shareholder; Gilead Sciences, Inc., Pfizer Inc., Tandem Diabetes Care, Inc. T.Howland: None. B.Shakjiri: None. B.Bush: None. L.Fattarusso: None. S.Stein: None.
1128-P: Prevalence of Obstructive Sleep Apnea in T2DM
Authors: AYYAGARI USHA , NK NARAYANAN , RM MANIKANDAN , NATARAJAN KANNAN , THUMALA BOOCHANDRAN S. , SELVARAJAN RAJA , ERUKULAPATI RAVI S. , DAS SAMBIT , DUVURU SHANTHARAM , RP RAJESH , KRISHNAMOORTHY MOHAN , JAGANMOHAN BALAJI , ASWATHIAH SRINATH , KARUPPAN BALAMURUGAN , PANDIAN SELVA , DASH KALPANA , YR SRINIVAS , MADHAVDAS DEEPAKLAL M. , S VENKATARAMAN , SESHADRI KRISHNA 
Published: May 2022

Prevalence of Obstructive Sleep Apnea (OSA) is reported as 23% in T2DM. OSA and T2DM share a bidirectional relationship, the effects of which are exacerbated by obesity, a common, shared comorbidity. Diagnosis and treatment improve glycemic, CV, and other outcomes, including mortality. Therefore, ADA recommends screening for OSA at least annually as part of routine care in DM. Polysomnography, the gold standard for diagnosing OSA is cumbersome, expensive, resource intensive, and impractical to implement in daily clinical practice. The STOP-Bang questionnaire is a validated, 8 question, easy-to-use, reliable screening tool for OSA. A score ≥ 3 has sensitivity 93% and 100% to detect moderate-severe and severe OSA respectively. Risk scoring is as in fig 1. High risk can also be scored as YES to 2 or more STOP questions AND male gender/BMI &gt; 35/neck circumference &gt; 40cm. We present screening data and highlight the prevalence of OSA in T2DM in routine clinical practice. Median age 55, median BMI 26.03, male 55%. From this screening n=1358 (58.94%) have intermediate or high risk of OSA and should be further investigated with polysomnography. Our data suggest that intermediate to high risk of OSA occurs at a lower BMI (26) in the population screened, with a majority (91%) having a neck circumference &lt;40cm, and highlights the need to screen for OSA rigorously in daily clinical practice, even in people that would otherwise have been “eye-balled” as low risk

Disclosure
U.Ayyagari: None. R.Rp: None. M.Krishnamoorthy: None. B.Jaganmohan: None. S.Aswathiah: None. B.Karuppan: None. S.Pandian: None. K.Dash: None. S.Yr: None. D.M.Madhavdas: Speaker's Bureau; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk, Sanofi. V.S: None. N.Nk: n/a. K.Seshadri: Speaker's Bureau; Abbott, Biocon, Boehringer Ingelheim International GmbH, Cipla Inc., Eli Lilly and Company, Merck & Co., Inc., Novartis AG, Novo Nordisk, USV Private Limited. M.Rm: None. K.Natarajan: None. B.S.Thumala: None. R.Selvarajan: None. R.S.Erukulapati: None. S.Das: n/a. S.Duvuru: None.
113-OR: The Best Insulin Delivery System Remains a Human Pancreas
Authors: MCCUNE KASI R. , DUBE GEOFFREY , RATNER LLOYD E. 
Published: May 2022

Purpose: Patients referred for pancreas transplantation represent a subset of difficult to treat diabetics, who may have clinical factors preventing them from achieving a goal Hgb A1C of ≤7%. Advanced insulin delivery systems with continuous glucose monitor (CGM) have been developed to offer less invasive treatment options in this population. We wanted to see how pancreas transplant performed compared to alternative modalities.
Methods: We conducted a retrospective review of pancreas transplantation at our institution from January 1, 20 through August 1, 2021. All patients were ≥18 years who underwent either simultaneous kidney pancreas (SPK) , pancreas after kidney (PAK) , or pancreas transplant alone (PTA) . Outcomes were assessed by HgbA1C level at evaluation (eval) , at transplant (pre) , between 3-5 months posttransplant (post) and the most recent (MR) (avg 62 months SD 75.4 months) .
Results: 133 patients underwent pancreas transplant during the study period, 85 SPK (62%) 39 PAK (30%) and PTA (8%) . (14%) patients suffered graft loss in the first year and were excluded from analysis. Overall, 1, and 5-year pancreas graft survival was 86% and 82%. 96 (84%) had type 1 diabetes (T1D) and 18 (16%) had type 2 diabetes (T2D) . Of the 114 patients, 33 (29%) utilized CGM with or without pump (CGM) prior to transplant and had a lower Hgb A1C (%) than those without (nonCGM) (8.18 SD 1.5 vs. 8.75 SD 1.9 p=0.04) . Hgb A1C then improved for the nonCGM group during their time on the waitlist (8.75 to 8.36 SD 1.8 p=0.004) but not the CGM group (8.18 to 8.SD 1.3 p=0.24) . Post-transplant saw significant improvement in CGM pre 8.to post 5.0 (SD.6 p=2.7E-17) and MR 5.3 (SD 0.7 p=9.9E-14) and in nonCGM pre 8.4 to post 5.2 (SD 0.62 p= 2.9E-29) and MR 5.4 (SD 0.7 p= 7.3E-29) .
Conclusion: Considering the clinical challenges of staying in range for difficult to treat diabetes, leading to HgbA1C goal of ≥7%, solid organ pancreas transplantation offers superior glycemic control compared to advanced insulin delivery systems with CGM.

Disclosure
K.R.Mccune: None. G.Dube: None. L.E.Ratner: Advisory Panel; CareDx, Immunocore, Ltd., Natera, Stock/Shareholder; Gilead Sciences, Inc., Hansa BioPharma.
1132-P: Classification and Prediction of Diabetes Using Electronic Health Records and Wearable Devices for Clinical Decision Support
Authors: SHAHIDEHPOUR ANDREW , FRITSCHI CYNTHIA , RASHID MUDASSIR , CINAR ALI , QUINN LAURIE T. 
Published: May 2022

Introduction: Diagnosis of T2DM necessitates clinical tests that are time-consuming and expensive. Machine learning (ML) techniques can accelerate the diagnosis and classification of T2DM and allow clinicians to personalize treatments based on blood glucose concentrations (BGC) , physical fitness (PF) , and diabetes distress patterns observed in daily life. Analyzing electronic health records (EHR) , physiological variables collected with wearable devices, and patient-reported outcomes (PROs) using ML techniques can lead to the development of clinical decision support tools that provide a comprehensive picture of an individual’s diabetes management needs.
Methods: Clinical experimental data (n=85, F:40/M:45, HbA1c: 7.83±2.16; age: 57±7.72: BMI: 33.kg/m2±6.72; means and SDs) were used to identify clusters of subjects based on medical tests, and ML models were developed using readily measured data to classify new subjects to the identified clusters. Latent variable methods and k-means clustering were used to identify clusters based on HbA1c, physical performance tests, and PROs. ML models, including logistic regression (LR) and support vector machines (SVM) , were developed to assign new subjects to the identified clusters using the readily measured input variables from wearable devices, EHR and PROs.
Results: Three distinct subject clusters were identified within the study cohort based on the descriptive variables. New subjects were assigned to the identified clusters with 87% and 91% accuracy for LR and SVM, respectively.
Conclusion: EHRs, wearable device data, and PROs can be used to accurately and conveniently identify a person’s overall BGC, PF, and diabetes distress to aid in clinical decision-making. In the future, clinical decision support tools can be developed for personalized treatment suggestions based on cluster membership.

Disclosure
A.Shahidehpour: None. C.Fritschi: None. M.Rashid: None. A.Cinar: None. L.T.Quinn: n/a.
1143-P: Lifetime Risk, Life Expectancy, and Years of Life Lost to Type 2 Diabetes in a Global Modelling Study of Six Countries
Authors: TOMIC DUNYA , CHEN LEI , MORTON JEDIDIAH I. , GREGG EDWARD W. , PAVKOV MEDA E. , ARFFMAN MARTTI , CHENG YILING J. , HA KYOUNG HWA , KIM DAE JUNG , PILDAVA SANTA , SHAW JONATHAN E. , MAGLIANO DIANNA J. 
Published: May 2022

Lifetime risk, life expectancy and years of life lost provide a meaningful perspective on the burden of type 2 diabetes to guide public health interventions. We estimated these metrics using population datasets from six high income countries, for two time-points five years apart per country in the period 2009-2019. We included 96,718,000 person-years and 448,1incident diabetes cases in life-table models. Each life-table simulated progression of a cohort of 20-year-olds free of diabetes, followed until death or age 100. Poisson regression was used to estimate incidence and mortality rates for each single year of age in males and females. Using microsimulation, 95% uncertainty intervals around lifetime risk, life expectancy and years of life lost were produced. Lifetime risk of diabetes decreased for both sexes in all countries (Table) , most notably in Israeli females from 58.1% (57.0 - 59.1) in 2010-to 45.9% (44.7 - 47.1) in 2015-16. Life expectancy for people with diabetes increased for both sexes in all countries, generally in line with the increase seen in those without diabetes. Years of life lost to diabetes at age 20 varied from 2.4 (1.4 - 3.4) in Latvian males in 2015-16 to 8.6 (8.3 - 8.9) in Israeli males in 2015-16. These findings show declining lifetime risk of type 2 diabetes in many countries, however, years of life lost to the disease remains substantial for the average person with diabetes.

Disclosure
D.Tomic: None. S.Pildava: None. J.E.Shaw: Advisory Panel; Abbott Diagnostics, AstraZeneca, Eli Lilly and Company, Pfizer Inc., Roche Diagnostics, Research Support; AstraZeneca, Boehringer Ingelheim International GmbH, Speaker's Bureau; AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi. D.J.Magliano: None. L.Chen: None. J.I.Morton: None. E.W.Gregg: None. M.E.Pavkov: None. M.Arffman: None. Y.J.Cheng: None. K.Ha: None. D.Kim: None.
1146-P: SGLT2 Inhibitors and the Risk of Early Bladder Cancer Events
Authors: ABRAHAMI DEVIN , TESFAYE HELEN , YIN HUI , YU ORIANA HOI YUN , PLATT ROBERT W. , SCHNEEWEISS SEBASTIAN , PATORNO ELISABETTA , AZOULAY LAURENT 
Published: May 2022

SGLT2 inhibitors (SGLT2is) have been shown to reduce the risk of cardiovascular and mortality events in large cardiovascular outcome trials in patients with type 2 diabetes. However, their safety profile is controversial, with some trials reporting imbalances in bladder cancer events, all of which occurred relatively soon after randomization. To address this safety concern, we used 3 US healthcare claims databases and 1 UK primary care database (01/2013-12/2020) . In each database, we identified adults newly treated with either SGLT2is (total n=453,726) or GLP-1 receptor agonists (GLP1RAs, n=375,990) (comparison #1) , and SGLT2is (n=347,055) or DPP-4 inhibitors (DPP4is, n=854,141) (comparison #2) . Propensity score-based fine stratification was used to reweigh the cohorts, adjusting for a wide range of patient characteristics at baseline. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for bladder cancer in each database using Cox proportional hazards models. After a median follow-up of 1.8 years, use of SGLT2is may slightly reduce the risk of bladder cancer, compared to GLP1RAs [HR (95% CI) =0.90 (0.81-1.00) ]. Compared to use of DPP4is, SGLT2is are not associated with bladder cancer incidence [HR (95% CI) : 1.00 (0.91-1.11) ] after a median follow-up of 2.0 years (Table) . Overall, the results of this large international cohort study provide reassurance on the short-term effects of SGLT2is on bladder cancer incidence.

Disclosure
D.Abrahami: None. H.Tesfaye: None. H.Yin: None. O.Yu: None. R.W.Platt: Consultant; Amgen Inc., Biogen, Merck & Co., Inc., Nant Pharma, Pfizer Inc. S.Schneeweiss: None. E.Patorno: Research Support; Boehringer Ingelheim International GmbH, National Institutes of Health, Patient-Centered Outcomes Research Institute. L.Azoulay: Consultant; Pfizer Inc.

Funding
Canadian Institutes of Health Research (PJT-169040)
1149-P: Stress Hyperglycemia Is an Independent Marker of Both Acute Illness and Diabetes Risk
Authors: SUKKARI MOHAMAD ANAS , FANG SHUYANG , AIYEDIPE SAMUEL , KHAKHARIA ANJALI , EASLEY KIRK A. , PHILLIPS LAWRENCE S. , RHEE MARY K. 
Published: May 2022

Stress hyperglycemia [inpatient hyperglycemia in patients without known diabetes (DM) ] is associated with poor outcomes, but not well characterized. To fill this gap in knowledge, we evaluated a retrospective national cohort of 240,047 Veterans, hospitalized ≥3d in 2002-14, with regular care before/after admission, and without pre-admission (preAdm) DM [defined by ICD code + DM Rx use, or A1c ≥6.5% or random plasma glucose (RPG) ≥200 mg/dl) . Mean age was 74 yr and BMI 28 kg/m2; 96% were male; 76% white, 16% black. Inpatient RPG was analyzed as ordinal mg/dl categories of the second highest inpatient RPG (iRPG) . We found that 44% had iRPG ≤1mg/dl, 37% had iRPG 111-140 mg/dl, and 19% had ≥ 141 mg/dl. Demographic factors were not clinically different between iRPG groups, but those with second highest preAdm RPG (paRPG) ≥115 mg/dl were more likely to have iRPG ≥140 mg/dl than those with paRPG ≤1mg/dl (26% vs. 16%, p&lt;0.001) . The prevalence of inpatient composite cardiovascular disease (CVD) and organ damage (acute MI, acute kidney injury, acute respiratory failure) , but not infection, increased with higher iRPG (CVD: OR 1.for iRPG 140-149 mg/dl and OR 1.62 for iRPG ≥200 mg/dl; organ damage: OR 1.and 1.96, respectively, p&lt;0.001, compared to iRPG ≤1mg/dl, adjusted for demographics, Elixhauser score, glucocorticoid use) . The prevalence of inpatient critical illness and incident DM post-discharge also rose with iRPG, (critical illness: OR 1.15 for iRPG 110-1 and OR 4.for iRPG ≥200 mg/dl; 3 yr incident DM: OR 1.81 and 11.06, respectively, p&lt;0.001) . iRPG &gt;140 mg/dl was associated with 9.6% 3yr DM incidence. Compared to those without incident DM, the incident DM group had a 21 mg/dl higher mean iRPG (p &lt;0.001) and more CVD at lower iRPGs (38% CVD for iRPG ≤120 vs. 29%) . Conclusion: Stress hyperglycemia is associated with inpatient CVD, critical illness and organ damage, as well as incident DM post-discharge. Moreover, iRPG &gt;140 mg/dl identifies high risk patients for DM who should undergoing close screening.

Disclosure
M.Sukkari: None. S.Fang: None. S.Aiyedipe: None. A.Khakharia: None. K.A.Easley: None. L.S.Phillips: Other Relationship; Cystic Fibrosis Foundation, Diasyst Inc., Research Support; Abbott Diabetes, AbbVie Inc., Janssen Pharmaceuticals, Inc., Janssen Scientific Affairs, LLC, Pfizer Inc. M.K.Rhee: Research Support; Kowa Company, Ltd.
115-OR: The Impact of Pretransplant and Posttransplant Diabetes on the Incidence of Cardiovascular Events in Kidney Transplant Recipients
Authors: LEE SEJEONG , HONG SUKCHUL , LEE MINYOUNG , KIM YOUNG-EUN , KIM HAE KYUNG , LEE HYANGKYU , LEE JAE GEUN , KANG EUN SEOK 
Published: May 2022

Diabetes mellitus (DM) and cardiovascular disease (CVD) are major public health challenges and also leading causes of post-transplant mortality following renal transplantation. In transplant patients, pre-transplant diabetes as well as newly developed diabetes after transplantation is associated with poor post-transplant outcomes. In this study, we aimed to investigate the effect of pre-transplant diabetes (Pre-DM) and post-transplant diabetes (PTDM) on cardiovascular events in kidney transplant recipients. We analyzed 1930 patients who underwent kidney transplantation at tertiary care hospital between 1979 and 2020. Subjects were classified into the 3 groups (Pre-DM, PTDM, Non-DM) according to whether diabetes was diagnosed and the date of diagnosis was before or after surgery. A Cox proportional hazard model was used to investigate the association between the type of DM (vs. Non-DM) and the incidence of four-point major adverse cardiovascular events (4P-MACE) . During the study follow-up period (median 6.5 years) , 4P-MACE occurred in 36 (3.1%) patients with Non-DM, 65 patients (14.3%) with Pre-DM and 33 (10.7%) patients with PTDM. Pre-DM was significantly associated with increasing risk of cardiovascular events after adjustment for confounding factors including age, sex, BMI, waiting time, ABO incompatibility, number of HLA mismatch, previous cardiovascular disease, donor age and donor type (living or deceased) (hazard ratio (HR) 3.62, 95% confidence interval (CI) 2.29-5.74, p&lt;0.001) . In the Kaplan-Meier curve of the cumulative incidence of 4P-MACE, subjects with Pre-DM had the highest risk of cardiovascular events and those with PTDM had intermediate risk of events. The presence of both Pre-DM or PTDM significantly increased the risk of cardiovascular events in kidney transplant recipients. This suggests the need for management to minimize the long-term impact of pre-existing DM and PTDM in transplant patients.

Disclosure
S.Lee: None. S.Hong: None. M.Lee: None. Y.Kim: None. H.Kim: None. H.Lee: None. J.Lee: None. E.Kang: None.

Funding
Severance Hospital Research fund for Clinical excellence (SHRC) (C-2021-0007)
1151-P: Improved Liver Steatosis Scores in T2DM after Randomization to Bariatric Surgery Related to Improvement in Insulin Sensitivity and Cardiometabolic Risk
Authors: KODALI ALIMITHA MONALI , LUNDHOLM MICHELLE D. , VANGOITSENHOVEN ROMAN , KIRWAN JOHN P. , AMINIAN ALI , SCHAUER PHILIP , KASHYAP SANGEETA 
Published: May 2022

NAFLD is common in T2DM, linked to insulin resistance and beta-cell dysfunction, and can be assessed with validated liver scores for steatosis and fibrosis. The longitudinal impact of weight loss with or without bariatric/metabolic surgery (BMS) on NAFLD in T2DM is not clear. Patients with T2DM (N=52, age 48±9 yrs, 30 (58%) female, BMI 36.3±2.9 kg/m2, T2DM duration of 8.3±5.0 yrs, A1c 9.7±1.7%) were randomized to intensive medical therapy (IMT, n=15) alone or IMT with laparoscopic Roux-en-Y gastric bypass (RYGB, n=18) or sleeve gastrectomy (SG, n=19) . The hepatic steatosis index (HSI) , NAFLD/liver fat score, FIB-4 index, and AST-to-platelet ratio index (APRI) were calculated at baseline and 24 months and correlated to baseline and change in weight, body fat percent (assessed with iDXA) , insulin sensitivity, beta-cell function (DI) and adipocytokine measurements during mixed meal tolerance testing. Baseline steatosis liver scores were abnormal in 52 patients (100%) by HSI and 38 (73%) by NAFLD/LFS. Abnormal liver scores at baseline were correlated with higher HOMA-IR, lower adiponectin levels, and higher blood pressure. At 24 months, HSI only normalized in 10/37 (27%) BMS patients (p=0.046) . NAFLD/LFS normalized in 21/27 (78%) BMS patients and 1/ (9%) medical patients (p=0.001) . Normalization of HSI and NAFLD/LFS were associated with weight and body fat reduction (p&lt;0.001) . Normalization of HSI was associated with improvement in Disposition index (DI) (P = 0.08) , CRP (p=0.001) , and leptin levels (p=0.016) ; change in NAFLD/LFS was associated with HOMA-IR (p&lt;0.001) . Liver steatosis was prevalent in all T2DM undergoing BMS and medical therapy and improved in a majority of subjects who underwent BMS but not IMT. Normalization of liver scores was associated with improvement in body weight, insulin sensitivity, beta-cell function, and markers of CVD risk. These data support the use of liver scores when assessing T2DM for BMS.

Disclosure
A.Kodali: None. M.D.Lundholm: None. R.Vangoitsenhoven: Speaker's Bureau; Boehringer Ingelheim International GmbH, Goodlife Pharma, Lilly, Mundipharma, Novo Nordisk, Sanofi. J.P.Kirwan: None. A.Aminian: Consultant; Medtronic, Research Support; Medtronic. P.Schauer: Advisory Panel; GI Dynamics, Keyron Ltd., Persona Nutrition, Consultant; Ethicon, Inc., Medtronic, Research Support; Ethicon, Inc., Medtronic, Pacira BioSciences, Inc., Stock/Shareholder; Mediflix, Inc., SE Healthcare LLC. S.Kashyap: Advisory Panel; Fractyl Health, Inc., GI Dynamics, Research Support; Janssen Pharmaceuticals, Inc.
1154-P: Leisure-Time Physical Activity Environment and Odds of Glycemic Control over Time among Veterans with New-Onset Type 2 Diabetes
Authors: ORSTAD STEPHANIE L. , LOPEZ PRISCILLA M. , ADHIKARI SAMRACHANA , LEE DAVID C. , KANCHI RANIA , SCHWARTZ MARK D. , ALEMI FARROKH , ELBEL BRIAN , THORPE LORNA 
Published: May 2022

Physical activity is protective against type 2 diabetes (T2D) incidence and supports T2D management. Access to local facilities such as gyms and parks enables leisure-time physical activity (LTPA) . We examined associations between T2D patients’ access to LTPA facilities and parks and whether repeated A1C follow-up tests were within a desired range. We analyzed data on 271,5 patients from the Veterans Administration Diabetes Risk Cohort who developed T2D from 2008-2018. We measured an A1C test as in-range if 5.0-7.0 (&lt;80 years of age) or 5.0-8.5 (≥80 years of age) , density of facilities within street network buffers, and population-weighted distance to the closest 7 parks. We used generalized estimating equations with a logit link function to predict the log odds of an in-range vs. out-of-range A1C test. We tested environment-by-time interactions, controlling for individual and neighborhood demographics and baseline A1C. On average, patients were 60 years of age, male (95%) , white (71%) , and had A1C tests during follow-up. Higher facility density, but not park distance, was narrowly associated with lower odds ofan in-range A1C test (ORdensity=.99, 95% CI=.98, 1.0) . As years since T2D diagnosis increased, the odds of an in-range A1C test decreased (ORtime=.88, 95% CI=.88, .88) . For those living in higher facility density, the odds of an in-range A1C decreased over time by only a slightly lower factor than for those living in lower facility density (P&lt;.0 for interaction term) . For those living farther from parks, the odds of an in-range A1C decreased over time by only a slightly higher factor than for those living closer to parks (P=.001) . As odds of in-range A1C tests decline over time, broader access to facilities and parks may not soften the decline since the modified effects were clinically negligible. Viable interventions for maintaining healthy A1C after diagnosis may include efforts to both increase access to and promote the use of the LTPA environment.

Disclosure
S.L.Orstad: None. P.M.Lopez: None. S.Adhikari: Research Support; Johnson & Johnson. D.C.Lee: None. R.Kanchi: None. M.D.Schwartz: None. F.Alemi: None. B.Elbel: None. L.Thorpe: None.

Funding
This study was funded by the Centers for Disease Control and Prevention (5 U01DP006299-02-00; PI: Lorna Thorpe)