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, 2024, Pereira+

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.

Link | PDF (BMC Medicine, November 2024, open access)

 

Great news everyone, only 1 in 14 infected children will suffer at least 2 years of problems with mobility, self-care, doing their usual activities etc ...

 

A prediction model that cannot predict anything in individual cases is not a prediction model, it's epidemiological data. Not entirely useless, just almost entirely useless. So far no such attempt has yielded anything more than generic noise, and they rarely find the exact same things other than a predominance in women, which is a 50:50 thing so of exactly zero use. Largely because they either ask the same generic questions, or vary in how they ask, frame, rate and analyze those answers.

But I assume there will be many more, even many more that will also claim to be the first such attempt, and none will yield anything either. Might as well be burning this money at casinos.

The overall effort is basically a search & rescue operation with zero coordination or strategy. People just wander around looking where they are interested in looking at, and don't bother integrating much of the various bits of data. And not even randomly. If only. No they all mostly follow the same paths, or stay at the pub drinking. Just in case, you know.

Given some early, although possibly misleading, potential for dogs identifying LC cases, maybe it'd just better letting dogs loose and see what happens. It can't be much worse than this.

Normally this could have some use in that it more or less confirms, yet again, an overall close-to-10% incidence, but clearly there's plenty more denial to go on and nothing matters anyway.