Article in Pediatric diabetes, 2025. 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
14 authors.
Rachel WongDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA, stonybrook.edu.ORCID 0000-0003-3108-7324
Talia WiggenClinical and Translational Science Institute, University of Minnesota, Minneapolis, Minnesota, USA, umn.edu.ORCID 0000-0002-5234-3238
Margaret A HallDepartment of Hematology and Medical Oncology, Emory University, Atlanta, Georgia, USA, emory.edu.ORCID 0000-0002-6263-440X
Steven G JohnsonInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA, umn.edu.ORCID 0000-0002-2983-6384
Jared D HulingDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA, umn.edu.ORCID 0000-0003-0670-4845
Lindsey E TurnerDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA, umn.edu.ORCID 0000-0003-2839-901X
Kenneth J WilkinsBiostatistics Program, Office of Clinical Research Support, Office of the Director, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA, nih.gov.ORCID 0000-0003-0531-7165
Hsin-Chieh YehDepartment of Medicine, Johns Hopkins University, Baltimore, Maryland, USA, jhu.edu.ORCID 0000-0002-5738-0652
Til StürmerDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA, unc.edu.ORCID 0000-0002-9204-7177
Carolyn T BramanteDivision of General Internal Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, USA, umn.edu.ORCID 0000-0001-5858-2080
Zachary Butzin-DozierDivision of Biostatistics, University of California, Berkeley, Berkeley, California, USA, berkeley.edu.ORCID 0000-0001-6419-0008
John B BuseDivision of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA, unc.edu.ORCID 0000-0002-9723-3876
Jane ReuschDivision of Endocrinology, Metabolism and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA, ucdenver.edu.ORCID 0000-0001-8620-1003
N3C Consortium
Funding
Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
North Carolina Translational and Clinical Sciences Institute (NC TraCS)UM1TR004406 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NICHOLAS J SHAHEEN · 2023 to 2026
$37.5M
TASK ORDER NO. 4, STSS PROGRAM SUPPORT AND TRANSITION-IN (4)75N95021D00001 · NIDA · AXLE INFORMATICS, LLC · PI MAYS, GARY · 2021 to 2022
$27.9M
TUBERCULOSIS PREVENTION IN CHILDREN TWO TO LESS THAN 13 YEARS OF AGE WITH AND WITHOUT HIV75N94023D00001 · NICHD · WESTAT, INC. · PI DRIVER, BARBARA · 2023 to 2025
$19.9M
Pilot & Feasibility ProgramP30DK124723 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Nicholette D. Allred · 2020 to 2026
$11.0M
RADX INNOVATION FUNNEL FOR HIV DIAGNOSTICS - AWARD MANAGEMENT75N92023D00001 · NHLBI · VENTUREWELL · 2024 to 2025
$10.0M
Use of Artificial Intelligence/Machine Learning (AI/ML) to Enhance the STEP Pediatric Excipient Database75N93023D00001 · NIAID · ADVANCED BIOSCIENCE LABORATORIES, INC. · PI SILVERA, PETER · 2023 to 2025
$9.6M
Propensity scores and preventive drug use in the elderlyR01AG056479 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Til Sturmer · 2017 to 2026
$5.0M
Incidence and severity of new onset diabetes associated with SARS-CoV-2 infectionR01DK130351 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI DOUGLAS, IVOR SAMUEL, REUSCH, JANE E · 2021 to 2023
$1.5M
Applying causal inference methods to improve estimation of the real-world benefits and harms of lung cancer screening - NCI Diversity SupplementR01CA277756 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Louise Henderson, Jennifer Lund · 2023 to 2026
$1.5M
Self-weighing for Weight Management in Adolescents with ObesityK23DK124654 · NIDDK · UNIVERSITY OF MINNESOTA · PI BRAMANTE, CAROLYN T · 2021 to 2024
Objective: Studies showing increased diabetes incidence in pediatric patients after COVID-19 are from data early in the pandemic, and some studies found conflicting results. Our objective was to evaluate trends in pediatric diabetes incidence and whether COVID-19 was associated with increased risk across viral variant periods. Research Design and Methods: We conducted a retrospective cohort study using National COVID-19 Cohort Collaborative data to evaluate incident diabetes risk among COVID-19-positive pediatric patients compared to COVID-19-negative patients or controls with acute respiratory illness. Cohorts were weighted on demographics, data site, and body mass index percentile. The primary outcome was the cumulative incidence ratio (CIR) of incident diabetes for each viral variant era. Results: There was no difference in the risk of incident diabetes in pediatric patients after COVID-19 compared to patients in COVID-19 negative or ARI control groups during any of the viral variant periods (e.g., ancestral period CIR 1.03, 95% CI 0.65-1.41). The predominant subtype of incident diabetes was T2D. Incidence rates over time followed a U-shaped curve, with the highest incidence in the ancestral variant period. Conclusions: COVID-19 was not associated with an increased risk of diabetes in pediatric patients. Incidence rates were highest early in the pandemic, and mirrored patterns of pandemic-era healthcare utilization. The predominance of incident T2D subtype is concerning for the adverse effects of pandemic-related lifestyle changes among pediatric patients.
Indexed as
COVID-19Diabetes MellitusAdolescentChildChild, PreschoolCohort StudiesFemaleHumansIncidenceInfantMaleRetrospective StudiesSARS-CoV-2United States
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.
The Effect of COVID-19 on Incident Diabetes in Pediatric Patients: Findings From the National COVID-19 Cohort Collaborative (N3C). · full record | OpenQuestion