Evidence map›Paper›PMID 41565009›Full record

ArticleThe Journal of pediatrics2026

Post-Acute Dyslipidemia and Abnormal Body Mass Index in Children and Adolescents with COVID-19: A Cohort Study from the RECOVER Initiative.

Yuqing Lei, Ting Zhou, Bingyu Zhang, Dazheng Zhang, Huilin Tang, Jiajie Chen, Qiong Wu, Lu Li, L Charles Bailey, Michael J Becich and 18 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

28 authors.

Yuqing LeiThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Ting ZhouThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Bingyu ZhangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA.
Dazheng ZhangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Huilin TangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Jiajie ChenThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Qiong WuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA.
Lu LiThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA.
L Charles BaileyApplied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, PA; Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Michael J BecichDepartment of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Saul BleckerDepartment of Population Health, NYU Grossman School of Medicine, New York, NY.
Dimitri A ChristakisCenter for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA.
Daniel FortCenter for Outcomes Research, Ochsner Health, New Orleans, LA.
Sharon J HerringDepartment of Population Health and Urban Bioethics, Program for Maternal Health Equity, Center for Urban Bioethics, Center for Obesity Research and Education, College of Public Health, Lewis Katz School of Medicine at Temple University, Philadelphia, PA.
Wenke HwangDepartment of Public Health Sciences, Penn State University College of Medicine, Hershey, PA.
Amrik Singh KhalsaDivision of Primary Care Pediatrics, Center for Child Health Equity and Outcomes Research, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, OH; Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, OH.
Susan KimDivision of Rheumatology, University of California, San Francisco, Benioff Children's Hospital, San Francisco, CA.
David M LiebovitzDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
Abu Saleh Mohammad MosaClinical Research Informatics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL.
Suchitra RaoDepartment of Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO.
Soumitra SenguptaDepartment of Biomedical Informatics, Columbia University, New York, NY.
Xing SongHealth Management and Informatics, University of Missouri School of Medicine, Columbia, MO.
Yacob G TedlaDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.
Ravi JhaveriDivision of Advanced Pediatrics and Primary Care, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL.
Caren MangarelliDivision of Advanced General Pediatrics and Primary Care, Northwestern University Feinberg School of Medicine, Chicago, IL.
Christopher B ForrestApplied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, PA; Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Yong ChenThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA; The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA; Penn Medicine Center for Evidence-Based Practice (CEP), Philadelphia, PA; Penn Institute for Biomedical Informatics (IBI), Philadelphia, PA. Electronic address: ychen123@pennmedicine.upenn.edu.
RECOVER Consortium

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
NHLBI NIH HHS OT2 HL161847
6 · The paper itself

Abstract

objectiveTo evaluate the risks of incident dyslipidemia and abnormal body mass index (BMI) during the 28-179-day postacute phase after documented SARS-CoV-2 infection in a large pediatric sample. STUDY

designA retrospective cohort study using the Researching COVID to Enhance Recovery pediatric electronic health record datasets from 25 US children's hospitals and health institutions, from March 2020 to September 2023. This study included 384 289 COVID-19-positive patients aged 0-21 years for dyslipidemia analyses and 285 559 aged 2-21 years for BMI analyses, each with at least 6 months of follow-up. COVID-19-negative controls included 1 080 413 and 817 315 patients, respectively. SARS-CoV-2 infection was defined by a positive polymerase chain reaction, antigen, or serologic test; a clinical diagnosis of COVID-19; or a documented diagnosis of post-acute sequelae of SARS-CoV-2. Incident dyslipidemia and abnormal BMI were identified using age-specific laboratory or anthropometric thresholds. Adjusted relative risks (aRRs) were estimated using propensity-score-stratified modified Poisson regression with multiple sensitivity analyses.

resultsDuring the postacute phase, the COVID-19-positive cohort had higher rates of new-onset composite dyslipidemia (aRR 1.24; 95% CI 1.18-1.29) and abnormal BMI (aRR 1.15; 95% CI, 1.12-1.18). Results were robust to sensitivity and stratified analyses.

conclusionsChildren and adolescents with documented COVID-19 infection were associated with an increased risk of new-onset dyslipidemia and abnormal BMI during the postacute phase, highlighting the need for metabolic monitoring after infection.

Indexed as

Body Mass IndexCOVID-19DyslipidemiasAdolescentChildChild, PreschoolCohort StudiesFemaleHumansInfantMalePost-Acute COVID-19 SyndromeRetrospective StudiesSARS-CoV-2United StatesYoung AdultdyslipidaemiaEHRmetabolic healthobesitypediatric populationpostacute sequelae of SARS-CoV-2 (PASC)

Identifiers

PMID41565009
PMCPMC13221949

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.