Hidden driver of mortality. A new study makes an uncomfortable point very clear. Respiratory viruses are probably involved in far more deaths than we usually recognize in day-to-day clinical practice or in official cause-of-death statistics🧵
Across 4 influenza seasons, a respiratory virus was found post mortem in 36.4% of deceased people. Influenza alone was present in 11.0%. It was not just flu either - rhinoviruses, common human coronaviruses, and RSV were also frequent.
The most striking part is how much was missed before death. Among people with influenza detected post mortem, only 17% had been diagnosed with influenza while alive.
That matters because what gets recorded as cardiac death, respiratory failure, or general decline may, in many cases, have had a hidden viral trigger helping push a frail patient over the edge.
The study does not claim every virus detected was the direct cause of death - but it strongly suggests we are overlooking a major part of the story.
These viruses are not harmless background noise. They can worsen an already fragile situation, destabilize chronic illness, and become part of fatal outcomes even when they never make it into the headline diagnosis.
The signal was especially strong in long-term care facilities, where any respiratory virus was found in 52.3% of deceased residents!
That is exactly where transmission is easier, patients are more vulnerable, and missed infections can carry the heaviest consequences.
So ignoring such a high prevalence would be a mistake. These infections are being underdiagnosed in life and undercounted in death.
The practical takeaway is simple.
Test more, think of viral etiologies more often, and stop assuming that if a patient looks cardiac, pulmonary, or just frail, infection is no longer central to what is happening.
And this study comes from the pre-COVID era. Since then, SARS-CoV-2 arrived. More severe, poorly tested, devastating in care homes, and far too often met with delayed, limited, or badly implemented antiviral access.
If we were already underestimating how flu and other respiratory viruses contribute to fatal decline, COVID only made that blind spot bigger. We need better testing, earlier recognition, and much better treatment access for the people at highest risk.
Trobajo-Sanmartín at al., Prevalence of influenza and other respiratory viral infections in deceased persons: a population-based observational study over four influenza seasons. clinicalmicrobiologyandinfection.org/article/S1198-…
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This may be one of the more important long COVID papers in a while.
A new study in Frontiers in Immunology suggests that COVID can trigger new-onset insulin resistance - and that this may drive abnormal NETosis in neutrophils months after infection🧵
NETosis is the process where neutrophils release web like structures made of DNA, histones, enzymes.
Normally, this helps trap pathogens.
But when excessive, NETs can -
damage the endothelium
trigger microclots!
amplify inflammation
activate coagulation.
Exactly the kind of pathology seen in COVID.
The study followed 60 COVID patients.
Among 36 people without prior glucose metabolism problems, 24 developed insulin resistance 4 months after infection.
That alone is a striking finding.
Some children with Long COVID seem to fall into the same trap as adults - and medicine still doesn’t really know how to get them out.🧵
The UK CLoCk study followed young people who had already been living with post-COVID symptoms for two years. Another 1.5 years later, most of those who responded still met the definition of post-COVID condition.
Some describe years of exhaustion, brain fog, sleep problems, breathlessness, pain, and symptoms that come and go without warning.
No slow recovery after a virus.
A new study in Brain, Behavior, & Immunity - Health reports measurable white matter changes in people with neurological long COVID.
Symptoms had persisted for an average of 2.7 years after infection - almost three years. That points to a long-term neurobiological process in the CNS🧵
The study included 80 participants.
54 with neurological PASC and 26 controls.
Using diffusion MRI, the authors found abnormalities mainly in the fornix and forceps minor - pathways involved in memory, limbic circuits, and frontal connectivity.
The imaging pattern was lower FA and higher MD/RD/AD.
In simple terms - the microstructure of white matter looked disrupted. The study cannot prove the exact cause, but the pattern is compatible with neuroinflammation, demyelination, axonal injury, or microvascular damage.
A new population-based study from Japan on Long COVID is out - the Yao COVID-19 Study.
After quite a long gap, we finally have another useful community prevalence study - and importantly, it can distinguish Alpha/Delta from Omicron🧵
The study followed 2,314 adults after COVID-19 and compared them with 1,314 uninfected controls.
Post-COVID condition was defined broadly in line with WHO criteria. Symptoms lasting at least 2 months and present 3 months after infection.
Prevalence of PCC
3 months 14.3%
6 months 12.0%
12 months 6.3%
18 months 5.4%
So even 18 months after infection, about 1 in 20 infected people still reported persistent symptoms.
During the pandemic, physician @leanhealth reported something important.
COVID patients who slept next to bedside air filters often seemed to have milder disease - possibly because they were not re-inhaling virus-laden air for eight hours every night🧵
A new hypothesis paper now points in the same direction using CT data. Cleaner air may not only reduce transmission. It may also reduce how deeply SARS-CoV-2 affects the lungs.
The idea is simple. The virus first replicates in the upper airways. An infected person then exhales tiny virus-containing aerosols. In poorly ventilated indoor spaces, these particles can build up and be inhaled deep into the lungs.
A population-based study raises a concerning possibility - after COVID-19, the risk curves for newly detected diabetes may continue to drift apart over time🧵
The cohort included 248,176 adults without prior diabetes
124,150 SARS-CoV-2 positive and 124,026 test-negative controls.
The result was modest but statistically significant.
New diabetes was detected in
0.60% of the positive group
0.53% of the negative group
Hazard ratio 1.13, 95% CI 1.02-1.25