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. 2024 Nov 7;22(1):520.
doi: 10.1186/s12916-024-03708-1.

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  1 , Terence Stephenson  1 , Roz Shafran  1 , Trudie Chalder  2 , Emma Dalrymple  1 , Tamsin Ford  3 , Lana Fox-Smith  1 , Anthony Harnden  4 , Isobel Heyman  1   3 , Shamez N Ladhani  5   6 , Kelsey McOwat  5 , Ruth Simmons  5 , Olivia Swann  7 , Elizabeth Whittaker  8 ; CLoCk Consortium; Snehal M Pinto Pereira  9
Collaborators, Affiliations

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 et al. BMC Med. .

Abstract

Background: Predicting 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.

Methods: CYP 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.

Results: While 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).

Conclusions: To 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.

Keywords: Children and young people; Cohort study; Post-COVID-19 condition; Prediction model.

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Conflict of interest statement

TS is Chair of the Health Research Authority and therefore recused himself from the Research Ethics Application. TC is a member of the National Institute for Health and Care Excellence committee for long COVID. She has written self-help books on chronic fatigue and has done workshops on chronic fatigue and post infectious syndromes. RS co-authored a book published in August 2020, titled Oxford Guide to Brief and Low Intensity Interventions for Children and Young People. TF’s research group receives funding for research consultancy from Place2Be, a third sector organisation providing mental health training, support, and interventions to schools across the UK. All remaining authors have no conflicts of interest.

Figures

Fig. 1
Fig. 1
Data flow diagrams for the analytical samples under consideration*. *For a detailed overview of the CLoCk sampling strategy see Nugawela et al. Int J Epidemiol 2024 53(1); ** we excluded 2 CYP from the final analytical sample because they had missing data on one of two questions: (i) family history of hospital attendance due to COVID-19 and/or (ii) family history of ongoing problems due to COVID-19
Fig. 2
Fig. 2
Number and prevalence (n (%)) of CYP continuing to meet the PCC definition over time. NB: the prevalence of persistent PCC up to 24 months (shown as the bar at 24 months since a PCR positive test) is the outcome that is predicted in the subsequent models
Fig. 3
Fig. 3
Area under the curve for the final shrunken models
See this image and copyright information in PMC

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