Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program 2023 Lorman et al

Abstract

Objectives
Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC.

Materials and Methods
We used a propensity-matched cohort design comparing children identified using the new PASC ICD10CM diagnosis code (U09.9) (N = 1309) to children with (N = 6545) and without (N = 6545) SARS-CoV-2 infection. We used a tree-based scan statistic to identify potential condition clusters co-occurring more frequently in cases than controls.

Results
We found significant enrichment among children with PASC in cardiac, respiratory, neurologic, psychological, endocrine, gastrointestinal, and musculoskeletal systems, the most significant related to circulatory and respiratory such as dyspnea, difficulty breathing, and fatigue and malaise.

Discussion
Our study addresses methodological limitations of prior studies that rely on prespecified clusters of potential PASC-associated diagnoses driven by clinician experience. Future studies are needed to identify patterns of diagnoses and their associations to derive clinical phenotypes.

Conclusion
We identified multiple conditions and body systems associated with pediatric PASC. Because we rely on a data-driven approach, several new or under-reported conditions and symptoms were detected that warrant further investigation.

Open access, https://academic.oup.com/jamiaopen/article/6/1/ooad016/7071577

 

Though interesting, as I understand it this remains an exercise trawling through medical records which is dependent on the consistency, completeness, accuracy and objectivity of the people filling in the records. I would have thought there was an enormous capacity still for introducing biases:

Having said that, and although I am not up-to to reading the full article today, I think it is an important exercise to try to establish what patterns of symptoms might exist.

 

Listening to the patients yields the same, because this is almost all symptom-based and symptoms can only be self-reported by definition. Without the filter of what limited data ever get recorded. In fact the very first patient-led study found pretty much that. In fact this study is inferior to that, because of all the stuff that's missing from health records.

Pediatric, sure, but they're finding mostly the same things, or things that standard tests can find, if they were used competently. There are differences with adults but children aren't a different species, whatever the public messaging was initially about how children can't possibly infect other people or get sick, or whatever. The main differences are likely endocrine/hormonal, which should tell us something but no one's looking.

All this does is confirm what the amateurs found 3 years ago, cheaper, faster, better. Can the professionals do professional-grade stuff that amateurs can't now? No? Too much to ask? Gotta keep doing redundant entry-level studies that add no new knowledge and nothing else?