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Record W4220679259 · doi:10.1101/2022.03.18.22272582

Validity of reported post-acute health outcomes in children with SARS-CoV-2 infection: a systematic review

2022· review· en· W4220679259 on OpenAlexaff
Julian Hirt, Perrine Janiaud, Viktoria Gloy, Stefan Schandelmaier, Tiago Pereira, Despina G. Contopoulos‐Ioannidis, Steven N. Goodman, John P. A. Ioannidis, Klaus Munkholm, Lars G. Hemkens

Bibliographic record

VenuemedRxiv · 2022
Typereview
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsSt. Michael's HospitalMcMaster UniversityImpact
FundersForeign and Commonwealth Office
KeywordsMedicineConfoundingSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Causality (physics)Coronavirus disease 2019 (COVID-19)PediatricsPsychiatryInternal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

ABSTRACT Importance There is concern that post-acute SARS-CoV-2 infection health outcomes (“post-COVID syndrome”) in children could be a serious problem but at the same time there is concern about the validity of reported associations between infection and long-term outcomes. Objective To systematically assess the validity of reported post-acute SARS-CoV-2 infection health outcomes in children. Evidence Review A search on PubMed and Web of Science was conducted to identify studies published up to January 22, 2022, that reported on post-acute SARS-CoV-2 infection health outcomes in children (<18 years) with follow-up of ≥2 months since detection of infection or ≥1 month since recovery from acute illness. We assessed the consideration of confounding bias and causality, and the risk of bias. Findings 21 studies including 81,896 children reported up to 97 symptoms with follow-up periods of 2-11.5 months. Fifteen studies had no control group. The reported proportion of children with post-COVID syndrome was between 0% and 66.5% in children with SARS-CoV-2 infection (n=16,986) and 2% to 53.3% in children without SARS-CoV-2 infection (n=64,910). Only 2 studies made a clear causal interpretation of an association of SARS-CoV-2 infection and the main outcome of “post-COVID syndrome” and provided recommendations regarding prevention measures. Two studies mentioned potential limitations in the conclusion of the main text but none of the 21 studies mentioned any limitations in the abstract nor made a clear statement for cautious interpretation. The validity of all 21 studies was seriously limited due to an overall critical risk of bias (critical risk for confounding bias [n=21]; serious or critical risk for selection bias [n=19]; serious risk for misclassification bias [n=3], for bias due to missing data [n=14] and for outcome measurement [n=12]; and critical risk for selective reporting bias [n=16]). Conclusions and Relevance The validity of reported post-acute SARS-CoV-2 infection health outcomes in children is critically limited. None of the studies provided evidence with reasonable certainty on whether SARS-CoV-2 infection has an impact on post-acute health outcomes, let alone to what extent. Children and their families urgently need much more reliable and methodologically robust evidence to address their concerns and improve care. KEY POINTS Question How valid are the reported results on health outcomes in children after acute SARS-CoV-2 infection? Findings We identified 21 studies with only 6 using a controlled design. Reported post-acute health-outcomes were numerous and heterogeneous. The reported proportion of children with post-COVID syndrome was up to 66.5% in children with and 53.3% in children without SARS-CoV-2 infection. All studies had seriously limited validity due to critical and serious risk of bias in multiple domains. Meaning The validity of reported post-acute SARS-CoV-2 infection health outcomes in children is critically limited and methodological robust evidence is urgently needed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.158
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.158
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.011
Bibliometrics0.0090.010
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.400
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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