161-OR: Trends in Glycemic Control between 2002 and 2016 among Youth Recently Diagnosed with Type 1 Diabetes: The SEARCH for Diabetes in Youth Study

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 161-OR
Author(s):  
DARIA IGUDESMAN ◽  
BETH A. REBOUSSIN ◽  
KATHERINE J. SOURIS ◽  
CATHERINE PIHOKER ◽  
LAWRENCE M. DOLAN ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Youth Study ◽  
Diabetes In Youth

scholarly journals Diabetic ketoacidosis at diagnosis of type 1 diabetes and glycemic control over time: The SEARCH for diabetes in youth study

2018 ◽  
Vol 20 (2) ◽  
pp. 172-179 ◽  
Author(s):  
Lindsey M. Duca ◽  
Beth A. Reboussin ◽  
Catherine Pihoker ◽  
Giuseppina Imperatore ◽  
Sharon Saydah ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Diabetic Ketoacidosis ◽  
Youth Study ◽  
Diabetes In Youth ◽  
Over Time

scholarly journals Trends in Glycemic among Youth with Diabetes: The SEARCH for Diabetes in Youth Study

2022 ◽  
Author(s):  
Faisal S. Malik ◽  
Katherine A. Sauder ◽  
Scott Isom ◽  
Beth A. Reboussin ◽  
Dana Dabelea ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Household Income ◽  
Age Groups ◽  
Race Ethnicity ◽  
Youth Study ◽  
Diabetes In Youth

<b>OBJECTIVES: </b>To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes. <p><b>RESEARCH DESIGN AND METHODS: </b>The study included 6,492 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods 2002-2007, 2008-2013 and 2014-2019, diabetes durations of 1-4, 5-9, and 10+ years, and age groups 1-9, 10-14, 15-19, 20-24, 25+ years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen and diabetes duration, overall and stratified for each duration and age group.</p> <p><b>RESULTS: </b>Adjusted mean HbA<sub>1c</sub> for the 2014-2019 cohort of YYA with type 1 diabetes was 8.8%±0.04%. YYA with type 1 diabetes in the 10-14, 15-19, and 20-24 age groups from the 2014-2019 cohort had worse glycemic control than the 2002-2007 cohort. Race/ethnicity, household income and treatment regimen predicted differences in glycemic control in 2014-2019 type 1 diabetes participants. Adjusted mean HbA1c was 8.6%±0.12% for 2014-2019 YYA with type 2 diabetes. Participants age 25+ with type 2 diabetes had worse glycemic control relative to the 2008-2013 cohort. Only treatment regimen was associated with differences in glycemic control in type 2 diabetes participants.</p> <p><b>CONCLUSIONS: </b>Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.</p> <br>

189-LB: Household Food Insecurity and Associations with Glycemic Control and Acute Diabetes-Related Complications in Youth and Young Adults with Type 1 Diabetes: The SEARCH for Diabetes in Youth Study

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 189-LB
Author(s):  
FAISAL MALIK ◽  
ANGELA D. LIESE ◽  
ALICE M. ELLYSON ◽  
LAUREN A. REID ◽  
KATHERINE A. SAUDER ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Glycemic Control ◽  
Household Food Insecurity ◽  
Household Food ◽  
Youth And Young Adults ◽  
Acute Diabetes ◽  
Youth Study ◽  
Diabetes In Youth

scholarly journals Trends in Glycemic Control Among Youth and Young Adults With Diabetes: The SEARCH for Diabetes in Youth Study

Diabetes Care ◽  
2022 ◽  
Author(s):  
Faisal S. Malik ◽  
Katherine A. Sauder ◽  
Scott Isom ◽  
Beth A. Reboussin ◽  
Dana Dabelea ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Age Groups ◽  
Youth And Young Adults ◽  
Race Ethnicity ◽  
Youth Study ◽  
Diabetes In Youth

OBJECTIVES To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes. RESEARCH DESIGN AND METHODS The study included 6,369 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods of 2002–2007, 2008–2013, and 2014–2019, diabetes durations of 1–4, 5–9, and ≥10 years, and age groups of 1–9, 10–14, 15–19, 20–24, and ≥25 years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A1c (HbA1c) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen, and diabetes duration, overall and stratified for each diabetes duration and age group. RESULTS Adjusted mean HbA1c for the 2014–2019 cohort of YYA with type 1 diabetes was 8.8 ± 0.04%. YYA with type 1 diabetes in the 10–14-, 15–19-, and 20–24-year-old age groups from the 2014–2019 cohort had worse glycemic control than the 2002–2007 cohort. Race/ethnicity, household income, and treatment regimen predicted differences in glycemic control in participants with type 1 diabetes from the 2014–2019 cohort. Adjusted mean HbA1c was 8.6 ± 0.12% for 2014–2019 YYA with type 2 diabetes. Participants aged ≥25 years with type 2 diabetes had worse glycemic control relative to the 2008–2013 cohort. Only treatment regimen was associated with differences in glycemic control in participants with type 2 diabetes. CONCLUSIONS Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.

scholarly journals Trends in Glycemic among Youth with Diabetes: The SEARCH for Diabetes in Youth Study

2022 ◽  
Author(s):  
Faisal S. Malik ◽  
Katherine A. Sauder ◽  
Scott Isom ◽  
Beth A. Reboussin ◽  
Dana Dabelea ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Household Income ◽  
Age Groups ◽  
Race Ethnicity ◽  
Youth Study ◽  
Diabetes In Youth

<b>OBJECTIVES: </b>To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes. <p><b>RESEARCH DESIGN AND METHODS: </b>The study included 6,492 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods 2002-2007, 2008-2013 and 2014-2019, diabetes durations of 1-4, 5-9, and 10+ years, and age groups 1-9, 10-14, 15-19, 20-24, 25+ years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen and diabetes duration, overall and stratified for each duration and age group.</p> <p><b>RESULTS: </b>Adjusted mean HbA<sub>1c</sub> for the 2014-2019 cohort of YYA with type 1 diabetes was 8.8%±0.04%. YYA with type 1 diabetes in the 10-14, 15-19, and 20-24 age groups from the 2014-2019 cohort had worse glycemic control than the 2002-2007 cohort. Race/ethnicity, household income and treatment regimen predicted differences in glycemic control in 2014-2019 type 1 diabetes participants. Adjusted mean HbA1c was 8.6%±0.12% for 2014-2019 YYA with type 2 diabetes. Participants age 25+ with type 2 diabetes had worse glycemic control relative to the 2008-2013 cohort. Only treatment regimen was associated with differences in glycemic control in type 2 diabetes participants.</p> <p><b>CONCLUSIONS: </b>Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.</p> <br>

scholarly journals Insulin Regimens and Clinical Outcomes in a Type 1 Diabetes Cohort: The SEARCH for Diabetes in Youth study

Diabetes Care ◽  
2012 ◽  
Vol 36 (1) ◽  
pp. 27-33 ◽  
Author(s):  
C. Pihoker ◽  
A. Badaru ◽  
A. Anderson ◽  
T. Morgan ◽  
L. Dolan ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Clinical Outcomes ◽  
Youth Study ◽  
Diabetes In Youth

scholarly journals Detection of Diabetes Status and Type in Youth using Electronic Health Records (EHRs): The SEARCH for Diabetes in Youth Study

2020 ◽  
Author(s):  
Brian J. Wells ◽  
Kristin M. Lenoir ◽  
Lynne E. Wagenknecht ◽  
Elizabeth J. Mayer-Davis ◽  
Jean M. Lawrence ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Multinomial Regression ◽  
Rule Based ◽  
Diabetes Status ◽  
Icd 10 ◽  
Youth Study ◽  
Diabetes In Youth

<u>Objective:</u> Diabetes surveillance often requires manual medical chart reviews to confirm status and type. This project aimed to create an electronic health record (EHR)-based procedure for improving surveillance efficiency through automation of case identification. <p><u> </u></p> <p><u>Research Design and Methods:</u> Youth (< 20 years) with potential evidence of diabetes (N=8,682) were identified from EHRs at three children’s hospitals participating in the SEARCH for Diabetes in Youth Study. True diabetes status/type was determined by manual chart reviews. Multinomial regression was compared with an ICD-10 rule-based algorithm in the ability to correctly identify diabetes status and type. Subsequently, the investigators evaluated a scenario of combining the rule based algorithm with targeted chart reviews where the algorithm performed poorly.</p> <p> </p> <p><u>Results:</u> The sample included 5308 true cases (89.2% type 1 diabetes). The rule-based algorithm outperformed regression for overall accuracy (0.955 vs 0.936). Type 1 diabetes was classified well by both methods: sensitivity (<i>Se</i>) (>0.95), specificity (<i>Sp</i>) (>0.96), and positive predictive value (PPV) (>0.97). In contrast, the PPVs for type 2 diabetes were 0.642 and 0.778 for the rule-based algorithm and the multinomial regression, respectively. Combining the rule-based method with chart reviews (n=695, 7.9%) of persons predicted to have non type 1 diabetes resulted in perfect PPV for the cases reviewed, while increasing overall accuracy (0.983). The sensitivity, specificity, and PPV for type 2 diabetes using the combined method were >=0.91. </p> <p> </p> <p><u>Conclusions</u>: An ICD-10 algorithm combined with targeted chart reviews accurately identified diabetes status/type and could be an attractive option for diabetes surveillance in youth. </p> <br>

scholarly journals Association of metformin and statin medications with surrogate measures of cardiovascular disease in youth with type 1 diabetes: the SEARCH for diabetes in youth study

2019 ◽  
Vol 24 (3) ◽  
pp. 187-194 ◽  
Author(s):  
Evgenia Gourgari ◽  
Jeanette M. Stafford ◽  
Ralph D'Agostino Jr ◽  
Lawrence M. Dolan ◽  
Jean M. Lawrence ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Type 1 Diabetes ◽  
Youth Study ◽  
Surrogate Measures ◽  
Diabetes In Youth

scholarly journals Adiponectin and arterial stiffness in youth with type 1 diabetes: the SEARCH for Diabetes in Youth Study

2012 ◽  
Vol 25 (7-8) ◽  
Author(s):  
Amy S. Shah ◽  
Lawrence M. Dolan ◽  
Abigail Lauer ◽  
Cralen Davis ◽  
Dana Dabelea ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Arterial Stiffness ◽  
Youth Study ◽  
Diabetes In Youth
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