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How do we know Long COVID has subgroups? Nearly every disease does, even those with far more precise diagnostics. A catch-all diagnosis for anyone sick after a virus likely has even more. This shows a few known subgroups in well-known diseases and how they change treatment.

The LDN Long COVID trial failing comes down to two things for me: 1. Long COVID and ME/CFS are likely multiple diseases. Lots of diseases are post-viral. A friend of mine developed lupus after the flu. If that had been COVID, would he have Long COVID? 2. Within each disease, only some people respond to any given drug, same as every other disease. Some rough assumptions, just to show how the maths works (hypothetical): - Long COVID is 10 diseases - LDN works in 1 or 2 of them - It helps 40% of people in those, roughly what approved drugs manage elsewhere - The trial has 160 people, 80 on the drug That gives 8 people per disease, and only 3 to 6 responders out of 80. Too few for a trial to detect. Even if LDN's group made up a quarter of all patients, that's still only 8 responders. Across 1 million patients, the same maths means 40,000 to 80,000 people helped by a drug that "failed". This also makes it complicated when a drug genuinely doesn't work. The result looks the same, so you can't tell a drug that works in a subgroup from one that doesn't work at all. BC007, efgartigimod, daratumumab, JAK inhibitors and mast cell drugs probably all work for a subgroup. Put people with viral persistence, autoimmunity, metabolic dysfunction, endothelial damage, herpesvirus reactivation and mast cell issues in one trial and any drug will fail. We need to split patients by their dominant biology, use what they already respond to in self-trials to match treatment concepts to groups, and recruit by blood test, not symptoms. Until then, every trial will fail and pharma won't enter Long COVID. It's why this is the only thing we work on at @amaticahealth.