Article in Diabetes care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
17 authors.
Raymond J KreienkampDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital, Boston, MA.ORCID 0000-0002-1683-323X
Kirk SmithCenter for Genomic Medicine and Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA.
Thinley Yidzin WangdenCenter for Genomic Medicine and Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA.
Aaron J DeutschCenter for Genomic Medicine and Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA.ORCID 0000-0001-6750-5335
Steven D GageCenter for Genomic Medicine and Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA.
Anna BellatorreLifecourse Epidemiology of Adiposity and Diabetes Center, University of Colorado, Aurora, CO.
Dana M DabeleaLifecourse Epidemiology of Adiposity and Diabetes Center, University of Colorado, Aurora, CO.ORCID 0000-0001-9514-8929
Ralph B D'AgostinoDepartment of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC.
Lawrence M DolanDepartment of Pediatrics, Division of Endocrinology, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH.
Jose C FlorezCenter for Genomic Medicine and Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA.ORCID 0000-0002-1730-9325
Elizabeth T JensenDepartment of Epideminology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC.ORCID 0000-0003-2704-6634
Catherine PihokerDepartment of Pediatrics, Division of Endocrinology, Seattle Children's Hospital, Seattle, WA.ORCID 0000-0001-9074-7770
Amy S ShahDepartment of Pediatrics, Division of Endocrinology, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH.ORCID 0000-0001-7297-139X
Lukasz SzczerbinskiCenter for Genomic Medicine and Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA.ORCID 0000-0002-6201-0605
Miriam S UdlerCenter for Genomic Medicine and Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA.ORCID 0000-0003-3824-9162
Shylaja SrinivasanDepartment of Pediatrics, Division of Endocrinology, University of California San Francisco, San Francisco, CA.ORCID 0000-0002-8049-6370
Funding
Institute of Translational Health SciencesUL1TR000423 · NCATS · UNIVERSITY OF WASHINGTON · PI DISIS, MARY L. · 2012 to 2016
$49.4M
South Carolina Clinical & Translational Research Institute (SCTR)UL1TR001450 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T., FLUME, PATRICK A · 2015 to 2024
$41.1M
LCenter for Clinical and Translational Science and TrainingUL1TR001425 · NCATS · UNIVERSITY OF CINCINNATI · PI MEINZEN-DERR, JAREEN, STRAWN, JEFFREY ROBERT · 2015 to 2024
$37.5M
PILOT STUDY--SUBSTRATE METABOLISM IN EXTREMELY LOW BIRTH WEIGHT INFANTSP30DK048520 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI Edward L Melanson · 1995 to 2026
$32.6M
Colorado Clinical and Translational Science Institute (UL1)UL1TR000154 · NCATS · UNIVERSITY OF COLORADO DENVER · PI SOKOL, RONALD J. · 2012 to 2013
$20.4M
Einstein-Montefiore Clinical and Translational Science Award HubUM1TR004400 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI Jessica Kahn, Mimi Y Kim · 2023 to 2026
$17.3M
Diabetes-Docs: Physician-Scientist Career Development Program (DiabDocs)K12DK133995 · NIDDK · STANFORD UNIVERSITY · PI LINDA A DIMEGLIO, David Matthew Maahs · 2022 to 2026
$16.0M
Limited Competition for the Continuation of the SEARCH for Diabetes in Youth Cohort Study (UC4)SEARCH for Diabetes in Youth Cohort StudyUC4DK108173 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI DAGOSTINO, RALPH B. · 2015 to 2016
$14.8M
UCHSC DIABETES ENDOCRINOLOGY RESEARCH CENTERP30DK057516 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI HUTTON, JOHN C · 2000 to 2010
$14.0M
Center for Clinical and Translational Science and TrainingUM1TR005265 · NCATS · UNIVERSITY OF CINCINNATI · PI Jareen Meinzen-Derr, Jeffrey Robert Strawn · 2025 to 2026
$10.6M
Cincinnati Center for Clinical and Translational Sciences and TrainingUL1TR000077 · NCATS · UNIVERSITY OF CINCINNATI · PI HEUBI, JAMES E., TSEVAT, JOEL · 2012 to 2014
$9.9M
South Carolina Clinical & Translational Research Institute (SCTR)UL1TR000062 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T. · 2012 to 2014
$9.4M
CDC HHS 00097CDC HHS DP-05-069CDC HHS DP-10-001CDC HHS DP-15-002Division of Diabetes, Endocrinology, and Metabolic Diseases 1R01DK127208-01Division of Diabetes, Endocrinology, and Metabolic Diseases 1U18DP002709Division of Diabetes, Endocrinology, and Metabolic Diseases 1UC4DK108173Division of Diabetes, Endocrinology, and Metabolic Diseases K12DK133995Division of Diabetes, Endocrinology, and Metabolic Diseases K23DK120932Division of Diabetes, Endocrinology, and Metabolic Diseases K23DK140643Division of Diabetes, Endocrinology, and Metabolic Diseases R03DK138213Division of Diabetes, Endocrinology, and Metabolic Diseases T32DK007699Division of Diabetes, Endocrinology, and Metabolic Diseases U18DP000247-06A1Division of Diabetes, Endocrinology, and Metabolic Diseases U18DP002708Division of Diabetes, Endocrinology, and Metabolic Diseases U18DP002710-01Division of Diabetes, Endocrinology, and Metabolic Diseases U18DP002714Division of Diabetes, Endocrinology, and Metabolic Diseases U48/CCU419249Division of Diabetes, Endocrinology, and Metabolic Diseases U48/CCU519239Division of Diabetes, Endocrinology, and Metabolic Diseases U48/CCU819241-3Division of Diabetes, Endocrinology, and Metabolic Diseases U48/CCU919219Division of Diabetes, Endocrinology, and Metabolic Diseases U58/CCU019235-4EPA EP-C-15-002Eunice Kennedy Shriver National Institute of Child Health and Human Development U24HD112205HSRD VA HIR 10-001Kaiser Foundation Health PlanNCATS NIH HHS UL1 TR000062NCATS NIH HHS UL1 TR000077NCATS NIH HHS UL1 TR000154NCATS NIH HHS UL1 TR000423NCATS NIH HHS UL1 TR001425NCATS NIH HHS UL1 Tr001450NCATS NIH HHS UL1 TR001450NCATS NIH HHS UL1 TR00423NCATS NIH HHS UM1 TR004400NCATS NIH HHS UM1 TR005265NCCDPHP CDC HHS U01 DP000244NCCDPHP CDC HHS U01 DP000246NCCDPHP CDC HHS U01 DP000247NCCDPHP CDC HHS U01 DP000248NCCDPHP CDC HHS U01 DP000250NCCDPHP CDC HHS U01 DP000254NCCDPHP CDC HHS U18 DP002708NCCDPHP CDC HHS U18 DP002709NCCDPHP CDC HHS U18 DP002710NCCDPHP CDC HHS U18 DP002714NCCDPHP CDC HHS U18 DP006131NCCDPHP CDC HHS U18 DP006133NCCDPHP CDC HHS U18 DP006134NCCDPHP CDC HHS U18 DP006136NCCDPHP CDC HHS U18 DP006138NCCDPHP CDC HHS U18 DP006139NHLBI NIH HHS K24 HL157960NHLBI NIH HHS K24HL157960NICHD NIH HHS U24 HD112205NIDDK NIH HHS 1U18DP002709NIDDK NIH HHS 200-2010-35171NIDDK NIH HHS K12 DK133995NIDDK NIH HHS K23 DK120932NIDDK NIH HHS K23 DK140643NIDDK NIH HHS L30 DK106874NIDDK NIH HHS P30 DK048520NIDDK NIH HHS P30 DK057516NIDDK NIH HHS R01 DK127208NIDDK NIH HHS R03 DK138213NIDDK NIH HHS T32 DK007699NIDDK NIH HHS U01 DP000244NIDDK NIH HHS U01 DP000246NIDDK NIH HHS U01 DP000247NIDDK NIH HHS U01 DP000248NIDDK NIH HHS U01 DP000250NIDDK NIH HHS U01 DP000254NIDDK NIH HHS U18DP000247-06A1NIDDK NIH HHS U18DP002708NIDDK NIH HHS U18DP002710-01NIDDK NIH HHS U18DP002714NIDDK NIH HHS U48/CCU419249NIDDK NIH HHS U48/CCU519239NIDDK NIH HHS U48/CCU819241-3NIDDK NIH HHS U48/CCU919219NIDDK NIH HHS U58/CCU019235-4NIDDK NIH HHS UC4 DK108173
6 · The paper itself
Abstract
objectiveClinical heterogeneity in youth-onset type 2 diabetes is less understood than that of adult-onset type 2 diabetes. We performed phenotypic clustering of youth-onset type 2 diabetes to determine whether clusters provided clinical utility. RESEARCH DESIGN AND
methodsWe performed data-driven clustering in a diverse subset of autoantibody-negative, clinician-diagnosed type 2 diabetes before age 20 years in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) (n = 525) and the SEARCH for Diabetes in Youth (SEARCH) (n = 333) studies. Participants were clustered using 1) similar variables as previously described in adults and 2) novel routinely available clinical variables. We assessed the effectiveness of the clusters, as well as that of simple clinical measures, to predict treatment response in the TODAY clinical trial.
resultsThere were three youth-onset type 2 diabetes clusters: 1) youth-onset insulin-deficient diabetes (YIDD-T2), 2) youth-onset insulin-resistant diabetes, and 3) intermediate youth-onset diabetes. These clusters had differential responses to therapies and risk of treatment failure in the TODAY study, with those in the YIDD-T2 cluster experiencing the highest rate of treatment failure, regardless of treatment arm. YIDD-T2 also had high rates of type 2 diabetes complications. We then generated three novel clusters, with different rates of treatment failure, using variables available in routine clinical practice. Compared with both clustering methods, simple clinical measures performed comparably or better at predicting treatment response and complications.
conclusionsYouth-onset type 2 diabetes can be characterized into reproducible clusters that demonstrate differential response to treatments and risk of complications. Nevertheless, cluster membership did not add clinical utility beyond simple clinical measures for predicting outcomes.
Indexed as
Diabetes Mellitus, Type 2AdolescentAge of OnsetChildCluster AnalysisFemaleHumansMalePhenotypePrognosisYoung Adult
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Novel Phenotypic Clusters of Youth-Onset Type 2 Diabetes Offer No Added Prognostic Value to Simple Clinical Measures. · full record | OpenQuestion