Evidence map›Paper›PMID 39837828›Full record

ArticleNature communications2025

Racial/ethnic differences in post-acute sequelae of SARS-CoV-2 in children and adolescents in the United States.

Dazheng Zhang, Bingyu Zhang, Qiong Wu, Ting Zhou, Jiayi Tong, Yiwen Lu, Jiajie Chen, Huiyuan Wang, Deena J Chisolm, Ravi Jhaveri and 9 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Dazheng Zhang *The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-1431-0785
Bingyu Zhang *The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Qiong WuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0001-5747-1899
Ting ZhouThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Jiayi TongThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-1213-6699
Yiwen LuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Jiajie ChenThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Huiyuan WangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Deena J ChisolmAbigail Wexner Research Institute Nationwide Children's Hospital, Columbus, OH, USA.
Ravi JhaveriDivision of Infectious Diseases, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
Rachel C KenneyDepartment of Neurology, New York University Grossman School of Medicine, New York, NY, USA.
Russell L RothmanVanderbilt Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Suchitra RaoDepartment of Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA.
David A WilliamsDepartment of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
Mady HornigDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.ORCID http://orcid.org/0000-0001-7572-3092
Linbo WangDepartment of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada.
Jeffrey S MorrisDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-8520-6088
Christopher B ForrestApplied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0003-1252-068X
Yong ChenThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA. ychen123@upenn.edu.ORCID http://orcid.org/0000-0003-0835-0788

Funding

OTA-21-015A Post-Acute Sequelae of SARS-CoV-2 Infection Initiative: NYU Langone Health Clinical Science Core, Data Resource Core, and PASC Biorepository CoreOT2HL161847 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GROSS, RACHEL SHARON, HORWITZ, LEORA · 2021 to 2025
$651.0M
Phenotypic Diversity in COVID-19UL1TR001878 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2016 to 2025
$102.4M
PANDA-MSD: Predictive Analytics via Networked Distributed Algorithms for Multi-System DiseasesU01TR003709 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI BIAN, JIANG, CHEN, YONG · 2022 to 2025
$4.7M
TRiPOD: Toward Reusable Phenotypes in Observational Data for AD/ADRD - managing definitions and correcting biasR01AG073435 · NIA · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG, XU, HUA · 2021 to 2025
$3.9M
Dynamic learning for post-vaccine event prediction using temporal information in VAERSR01AI130460 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CHEN, YONG, TAO, CUI · 2017 to 2021
$3.4M
PheBC: bias correction methods for EHR derived phenotypeR01LM013519 · NLM · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG, XU, HUA · 2021 to 2024
$1.6M
Advancing Drug Repositioning for Alzheimer’s Disease using Real-world DataR56AG069880 · NIA · UNIVERSITY OF FLORIDA · PI BIAN, JIANG, CHEN, YONG · 2021 to 2022
$1.6M
CICADA: clinical informatics and computational approaches for drug-repositioning of AD/ADRDR56AG074604 · NIA · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG, TAO, CUI · 2021 to 2022
$1.5M
A General Framework to Account for Outcome Reporting Bias in Systematic ReviewsR01LM012607 · NLM · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG · 2017 to 2020
$1.4M
AI-ADRD: Accelerating interventions of AD/ADRD via Machine learning methodsR01AG077820 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Jiang Bian, Yong Chen · 2026 to 2026
$737k
NCATS NIH HHS U01 TR003709NCATS NIH HHS UL1 TR001878NHLBI NIH HHS OT2 HL161847NIAID NIH HHS R01 AI130460NIA NIH HHS R01 AG073435NIA NIH HHS R01 AG077820NIA NIH HHS R56 AG069880NIA NIH HHS R56 AG074604NLM NIH HHS R01 LM012607NLM NIH HHS R01 LM013519Patient-Centered Outcomes Research Institute (PCORI) ME-2018C3-14899U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R01AG073435U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R01AG077820U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R01AI130460U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R01LM013519U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R56AG069880U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R56AG074604U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1U01TR003709U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) OT2HL161847-01
6 · The paper itself

Abstract

Racial/ethnic differences are associated with the symptoms and conditions of post-acute sequelae SARS-CoV-2 infection (PASC) in adults. These differences may exist among children and warrant further exploration. We conducted a retrospective cohort study with difference-in-differences analyzes to assess these differences in children and adolescents under the age of 21. The study utilized data from the RECOVER Initiative in the United States, which aims to learn about the long-term effects of COVID-19. The cohort included 225,723 patients with SARS-CoV-2 infection or COVID-19 diagnosis between March 2020 and October 2022. The study compared minority racial/ethnic groups to Non-Hispanic White (NHW) individuals, stratified by severity during the acute phase of COVID-19. Within the severe group, Asian American/Pacific Islanders (AAPI) had a higher prevalence of fever/chills and respiratory signs and symptoms, Hispanic patients showed greater hair loss prevalence in severe COVID-19 cases, while Non-Hispanic Black (NHB) patients had fewer skin symptoms in comparison to NHW patients. Within the non-severe group, AAPI patients had increased POTS/dysautonomia and respiratory symptoms, and NHB patients showed more cognitive symptoms than NHW patients. In conclusion, racial/ethnic differences related to COVID-19 exist among PASC symptoms and conditions in pediatrics, and these differences are associated with the severity of illness during acute COVID-19.

Indexed as

COVID-19EthnicityPost-Acute COVID-19 SyndromeAdolescentBlack or African AmericanChildChild, PreschoolFemaleHispanic or LatinoHumansInfantMalePrevalenceRacial GroupsRetrospective StudiesSeverity of Illness Index

Identifiers

PMID39837828
PMCPMC11751291

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.