Evidence map›Paper›PMID 34581790›Full record

ArticleThe Journal of clinical endocrinology and metabolism2022

Age and Hospitalization Risk in People With Type 1 Diabetes and COVID-19: Data From the T1D Exchange Surveillance Study.

Carla Demeterco-Berggren, Osagie Ebekozien, Saketh Rompicherla, Laura Jacobsen, Siham Accacha, Mary Pat Gallagher, G Todd Alonso, Berhane Seyoum, Francesco Vendrame, J Sonya Haw and 3 more

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in The Journal of clinical endocrinology and metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
6.9field-weighted citation impact, top 2% of its field
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.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.

  1. Risk Factors for Pediatric Critical COVID-19: A Systematic Review and Meta-Analysis.Journal of the Pediatric Infectious Diseases Society · 2024
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  5. Risk Factors for Pediatric Critical COVID-19: A Systematic Review and Meta-Analysis.medRxiv : the preprint server for health sciences · 2024
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4 · The record

Corrections and comments

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

13 authors at 11 institutions in 1 country.

Carla Demeterco-BerggrenRady Children's Hospital, University of California, San Diego, San Diego, California 92123, USA.ORCID 0000-0002-1140-644X
Osagie EbekozienT1D Exchange, Boston, Massachusetts 02111, USA.ORCID 0000-0002-8473-249X
Saketh RompicherlaT1D Exchange, Boston, Massachusetts 02111, USA.
Laura JacobsenUniversity of Florida, Gainesville, Florida 32611, USA.
Siham AccachaNYU Langone, New York, New York 10016, USA.
Mary Pat GallagherNYU Langone, New York, New York 10016, USA.
G Todd AlonsoBarbara Davis Center, University of Colorado, Aurora, Colorado 80045, USA.
Berhane SeyoumWayne State University, Detroit, Michigan 48202, USA.
Francesco VendrameUniversity of Miami, Miami, Florida 33136.
J Sonya HawGrady Hospital, Atlanta, Georgia 30303, USA.
Marina BasinaStanford University, Stanford, California 94305, USA.
Carol J LevyIcahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
David M MaahsStanford University, Stanford, California 94305, USA.ORCID 0000-0002-4602-7909
NYU Langone Health · USStanford University · USGrady Memorial Hospital · USIcahn School of Medicine at Mount Sinai · UST1D Exchange · USUniversity of California San Diego · USUniversity of Colorado Anschutz Medical Campus · USUniversity of Florida · USUniversity of Miami · USUniversity of Mississippi Medical Center · USWayne State University · US

Funding

Translational Research CoreP30DK020541 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI STREAMSON C CHUA · 2015 to 2026
$27.7M
NIDDK NIH HHS P30 DK020541
6 · The paper itself

Abstract

contextCOVID-19 morbidity and mortality are increased in type 1 diabetes (T1D), but few data focus on age-based outcomes.

objectiveThis work aimed to quantify the risk for COVID-19-related hospitalization and adverse outcomes by age in people with T1D.

methodsFor this observational, multisite, cross-sectional study of patients with T1D and laboratory-confirmed COVID-19 from 56 clinical sites in the United States, data were collected from April 2020 to March 2021. The distribution of patient factors and outcomes across age groups (0-18, 19-40, and > 40 years) was examined. Descriptive statistics were used to describe the study population, and multivariate logistic regression models were used to analyze the relationship between age, adverse outcomes, and hospitalization. The main outcome measure was hospitalization for COVID-19.

resultsA total of 767 patients were analyzed. Fifty-four percent (n = 415) were aged 0 to 18 years, 32% (n = 247) were aged 19 to 40 years, and 14% (n = 105) were older than 40 years. A total of 170 patients were hospitalized, and 5 patients died. Compared to the 0- to 18-years age group, those older than 40 years had an adjusted odds ratio of 4.2 (95% CI, 2.28-7.83) for hospitalization after adjustment for sex, glycated hemoglobin A1c, race, insurance type, and comorbidities.

conclusionAge older than 40 years is a risk factor for patients with T1D and COVID-19, with children and younger adults experiencing milder disease and better prognosis. This indicates a need for age-tailored treatments, immunization, and clinical management of individuals affected by T1D.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsChildChild, PreschoolCOVID-19Cross-Sectional StudiesDiabetes Mellitus, Type 1FemaleHospitalizationHumansInfantMaleMiddle AgedageCOVID-19hospitalizationtype 1 diabetes

Identifiers

PMID34581790
PMCPMC8500098
OpenAlexW3204892751

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.