ArticleThe Journal of pediatrics2023
Leveraging Serologic Testing to Identify Children at Risk For Post-Acute Sequelae of SARS-CoV-2 Infection: An Electronic Health Record-Based Cohort Study from the RECOVER Program.
Article in The Journal of pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Long-Term Complications of Multisystem Inflammatory Syndrome in Children and Adults Post-COVID-19: A Systematic Review.International journal of molecular sciences · 2025Pooled it
- Functional outcomes of children after SARS-CoV-2 infection: An EHR-based cohort study.Journal of pediatric rehabilitation medicine · 2026Article
- Identifying Pediatric Long COVID: Comparing an EHR Algorithm to Manual Review.Applied clinical informatics · 2025Article
- EHR-based Case Identification of Pediatric Long COVID: A Report from the RECOVER EHR Cohort.medRxiv : the preprint server for health sciences · 2024Article
- Postacute Sequelae of SARS-CoV-2 in Children.Pediatrics · 2024Review
- Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program.JAMIA open · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 8 institutions in 1 country.
Funding
Abstract
Using an electronic health record-based algorithm, we identified children with Coronavirus disease 2019 (COVID-19) based exclusively on serologic testing between March 2020 and April 2022. Compared with the 131 537 polymerase chain reaction-positive children, the 2714 serology-positive children were more likely to be inpatients (24% vs 2%), to have a chronic condition (37% vs 24%), and to have a diagnosis of multisystem inflammatory syndrome in children (23% vs <1%). Identification of children who could have been asymptomatic or paucisymptomatic and not tested is critical to define the burden of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 infection in children.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.