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Published on: December 19, 2020
Predicting post-COVID-19 condition in children and young people up to 24 months after a positive SARS-CoV-2 PCR-test:
Manjula D Nugawela1, Terence Stephenson1, Roz Shafran1
1UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Insights
Researchers developed prediction models to identify children and young people (CYP) at high risk of persistent post-COVID-19 condition (PCC) for up to 24 months. Factors like asthma and learning difficulties predict longer-term symptoms, enabling earlier support.
Area of Science:
- Pediatric Health
- Infectious Diseases
- Epidemiology
Background:
- Post-COVID-19 condition (PCC) affects children and young people (CYP), necessitating identification of those at high risk.
- Improved prediction of persistent PCC can optimize care pathways for affected CYP.
Purpose of the Study:
- To develop and validate prediction models for persistent PCC in CYP up to 24 months post-infection.
- To identify key risk factors associated with long-term PCC in pediatric populations.
Main Methods:
- Analysis of CYP with PCR-positive results (Sept 2020-Mar 2021) with up to 24-month follow-up.
- Development of logistic regression models for persistent PCC, defined at 3, 6, 12, 24 months or 6, 12, 24 months.
- Internal validation using bootstrapping, assessing calibration and discrimination, with adjustments for overfitting.
Main Results:
- Persistent PCC prevalence was 24.7% at 3 months, decreasing to 7.2% at 6, 12, and 24 months.
- Key predictors for persistent PCC included female sex, asthma history, allergies, learning difficulties, and family history of ongoing COVID-19.
- Models demonstrated good calibration (slope 1.064-1.142) and discrimination (C-statistic 0.724-0.755) with minimal overfitting.
Conclusions:
- Novel prediction models identify CYP at risk for persistent PCC up to 24 months post-infection.
- These models can aid in triaging CYP and facilitating early support for those with predicted longer-term symptomology.
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.
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