Developing a model for predicting impairing physical symptoms in children 3 months after a SARS-CoV-2 PCR-test: The CLoCk Study
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Abstract
Importance
Predictive models can help identify SARS-CoV-2 patients at greatest risk of post-COVID sequelae and direct them towards appropriate care.
Objective
To develop and internally validate a model to predict children and young people most likely to experience at least one impairing physical symptom 3 months after a SARS-CoV-2 PCR-test and to determine whether the impact of these predictors differed by SARS-CoV-2 infection status.
Design
Potential pre-specified predictors included: SARS-CoV-2 status, sex, age, ethnicity, deprivation, quality of life/functioning (5 EQ-5D-Y items), physical and mental health, and loneliness (all prior to SARS-CoV-2 testing), and number of physical symptoms at testing. Logistic regression was used to develop the model. Model performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping; the final model was adjusted for overfitting.
Setting
National cohort study of SARS-CoV-2 PCR-positive and PCR-negative participants matched according to age, sex, and geographical area.
Participants
Children and young people aged 11-17 years who were tested for SARS-CoV-2 infection in England, January to March 2021.
Main outcome measure
one or more physical symptom 3 months after initial PCR-testing which affected physical, mental or social well-being and interfered with daily living.
Results
A total of 50,836 children and young people were approached; 7,096 (3,227 test-positives, 3,869 test-negatives) who completed a questionnaire 3 months after their PCR-test were included. 39.6% (1,279/3,227) of SAR-CoV-2 PCR-positives and 30.6% (1,184/3,869) of SAR-CoV-2 PCR-negatives had at least one impairing physical symptom 3 months post-test. The final model contained predictors: SARS-COV-2 status, number of symptoms at testing, sex, age, ethnicity, self-rated physical and mental health, feelings of loneliness and four EQ-5D-Y items before testing. Internal validation showed minimal overfitting with excellent calibration and discrimination measures (optimism adjusted calibration slope:0.97527; C-statistic:0.83640).
Conclusions and relevance
We developed a risk prediction equation to identify those most at risk of experiencing at least one impairing physical symptom 3 months after a SARS-CoV-2 PCR-test which could serve as a useful triage and management tool for children and young people during the ongoing pandemic. External validation is required before large-scale implementation.
Key Points
Question
Which children have impairing physical symptoms during the COVID-19 pandemic?
Findings
Using data from a large national matched cohort study in children and young people (CYP) aged 11-17 years (N=7,096), we developed a prediction model for experiencing at least one impairing physical symptom 3 months after testing for SARS-COV-2. Our model had excellent predictive ability, calibration and discrimination; we used it to produce a risk estimation calculator.
Meaning
Our developed risk calculator could serve as a useful tool in the early identification and management of CYP at risk of persisting physical symptoms in the context of the COVID-19 pandemic.
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SciScore for 10.1101/2022.04.01.22273117: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:We acknowledge study limitations. Baseline measures (at/or before testing) were subject to recall bias because they were not taken at the time of acute infection. We were unable to assess whether symptoms waxed and waned between testing and questionnaire. …
SciScore for 10.1101/2022.04.01.22273117: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:We acknowledge study limitations. Baseline measures (at/or before testing) were subject to recall bias because they were not taken at the time of acute infection. We were unable to assess whether symptoms waxed and waned between testing and questionnaire. The CLoCk study response rate (13.4%)4 is typical of surveys of this type;33 additionally, our participants are largely representative of the target population as a whole.4 Nevertheless, the possibility of selection bias in both directions (CYP more likely to participate if they have persistent symptoms, or less likely to participate if too unwell) among respondents cannot be ruled out. Furthermore, as the background epidemiological situation in relation to SARS-COV-2 infection prevalence changes, there is a need to reassess possible differences in our model’s predictive value over time. Finally, caution is required for predictions based on data extrapolation/situations where there are only a very small number of observations for different predictor combinations. To our knowledge, no other study has explicitly aimed to develop a risk prediction model for experiencing impairing physical symptoms several months after SARS-COV-2 testing. Moreover, the majority of previous studies lack a SARS-CoV-2 test-negative comparison group and so distinguishing long-term symptoms predicted by SARS-CoV-2 infection from background rates or pandemic-related effects remains a challenge.5 More recent studies include control groups and, thus, br...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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