Thread by @ZdenekVrozina

Another study where long COVID does not look like a small residual problem after infection, but like broad chronic illness scattered across everyday medicine.
And that is exactly why the system often fails to see it🧵

The study analyzed data from 58 US hospitals.
The algorithm identified PASC in 16.28% of patients after COVID.
Roughly 1 in 6!

The most important part is not only how many people have long COVID.
It is that most of the detected manifestations were not short acute episodes.
They were mostly chronic or potentially chronic conditions.

The more important number is this -
14.54% of all post-COVID patients had chronic PASC burden!
That is not a few weeks of cough after a virus.
That means long-term care, follow-ups, specialists, tests, medication, and work limitations.

The cumulative prevalence of PASC did not decline.
It slightly increased through mid-2024.
The authors interpret this as an accumulating burden, not just the fading tail of early pandemic waves.

Long COVID often does not appear in the system as long COVID.
Instead, the patient shows up
to primary care with fatigue,
to cardiology with dysautonomia or palpitations,
to endocrinology with a new metabolic problem,
to neurology with cognitive symptoms.

And this is the coding problem.
Many of these patients are not coded as long COVID/PASC. They are coded under the specific diagnosis they present with. Fatigue, palpitations, dysautonomia, cognitive symptoms, respiratory problems, abnormal glucose, prediabetes, or other chronic conditions.

Without a connecting code, the burden fragments into many ordinary diagnoses.
The system then fails to see it as post-infectious chronic disease, even while it is already carrying it clinically.

That is the real strength of this study.
It challenges the illusion we don’t see long COVID, so it isn’t there.
The opposite is true.
Part of the burden is already inside the system, just split across diagnoses and specialties.

Healthcare does not need to report a collapse of long COVID clinics to be under pressure.
The burden can show up as more prediabetes/diabetes, more fatigue syndromes, more neurology visits, more cardiology complaints, and more respiratory problems.

The system is treating it.
It just often cannot see the common denominator.
Long COVID does not have to overwhelm healthcare under one label.
It can burden it as thousands of ordinary diagnoses without a shared code.

There was no COVID-negative control group, and some variation may reflect coding practices.
But the signal is large.

After COVID, we are seeing broad, long-term, poorly coded illness.
And if we cannot name it properly, that does not mean it does not exist.
It means we are measuring it badly.

And it may also mean we are treating it poorly.
If post-COVID illness is fragmented across specialties without a shared framework, patients may receive treatment for isolated symptoms while the underlying post-infectious process remains unrecognized. @szupraha @ZdravkoOnline @adamvojtech86

Fragmented recognition often leads to fragmented care.

Tian at al., Long COVID Persistence and Surveillance Gaps Across 58 US Hospitals. jamanetwork.com/journals/jaman…