Evidence map›Paper›PMID 39511637›Full record

ArticleBMC medicine2024

Predicting post-COVID-19 condition in children and young people up to 24 months after a positive SARS-CoV-2 PCR-test: the CLoCk study.

Manjula D Nugawela, Terence Stephenson, Roz Shafran, Trudie Chalder, Emma Dalrymple, Tamsin Ford, Lana Fox-Smith, Anthony Harnden, Isobel Heyman, Shamez N Ladhani and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Long COVID in children and young people: then and now.Current opinion in infectious diseases · 2025
    Review
  6. Article
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

16 authors.

Manjula D NugawelaUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Terence StephensonUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Roz ShafranUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Trudie ChalderDepartment of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De'Crespigny Park, London, SE5 8AF, UK.
Emma DalrympleUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Tamsin FordDepartment of Psychiatry, University of Cambridge, Hershel Smith Building Cambridge Biomedical Campus, Cambridge, CB2 0SZ, UK.
Lana Fox-SmithUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Anthony HarndenNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
Isobel HeymanUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Shamez N LadhaniImmunisations and Vaccine Preventable Diseases, UK Health Security Agency, 61 Colindale Avenue, London, NW9 5EQ, UK.
Kelsey McOwatImmunisations and Vaccine Preventable Diseases, UK Health Security Agency, 61 Colindale Avenue, London, NW9 5EQ, UK.
Ruth SimmonsImmunisations and Vaccine Preventable Diseases, UK Health Security Agency, 61 Colindale Avenue, London, NW9 5EQ, UK.
Olivia SwannCentre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4TL, UK.
Elizabeth WhittakerDepartment of Paediatric Infectious Diseases, Imperial College Healthcare NHS Trust, London, W2 1NY, UK.
CLoCk Consortium
Snehal M Pinto PereiraDivision of Surgery & Interventional Science, Faculty of Medical Sciences, University College London, London, WC1E 6BT, UK. snehal.pereira@ucl.ac.uk.

Funding

Medical Research Council MR/P020372/1National Institute for Health and Care Research COVLT0022
6 · The paper itself

Abstract

backgroundPredicting which children and young people (CYP) are at the highest risk of developing post-COVID-19 condition (PCC) could improve care pathways. We aim to develop and validate prediction models for persistent PCC up to 24 months post-infection in CYP.

methodsCYP who were PCR-positive between September 2020 and March 2021, with follow-up data up to 24-months post-infection, were analysed. Persistent PCC was defined in two ways, as PCC at (a) 3, 6, 12 and 24 months post-infection (N = 943) or (b) 6, 12 and 24 months post-infection (N = 2373). Prediction models were developed using logistic regression; performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping; the final model was adjusted for overfitting.

resultsWhile 24.7% (233/943) of CYP met the PCC definition 3 months post-infection, only 7.2% (68/943) continued to meet the PCC definition at all three subsequent timepoints, i.e. at 6, 12 and 24 months. The final models predicting risk of persistent PCC (at 3, 6, 12 and 24 months and at 6, 12 and 24 months) contained sex (female), history of asthma, allergy problems, learning difficulties at school and family history of ongoing COVID-19 problems, with additional variables (e.g. older age at infection and region of residence) in the model predicting PCC at 6, 12 and 24 months. Internal validation showed minimal overfitting of models with good calibration and discrimination measures (optimism-adjusted calibration slope: 1.064-1.142; C-statistic: 0.724-0.755).

conclusionsTo our knowledge, these are the only prediction models estimating the risk of CYP persistently meeting the PCC definition up to 24 months post-infection. The models could be used to triage CYP after infection. CYP with factors predicting longer-term symptomology, may benefit from earlier support.

Indexed as

COVID-19SARS-CoV-2AdolescentChildChild, PreschoolCOVID-19 Nucleic Acid TestingFemaleHumansInfantMalePost-Acute COVID-19 SyndromeRisk FactorsYoung AdultChildren and young peopleCohort studyPost-COVID-19 conditionPrediction model

Identifiers

PMID39511637
PMCPMC11545583

What OpenQuestion holds

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Registered trials

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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.