My heart had wild palpitations for several days in the midst of having covid and post covid my resting heart rate is ~20bpm higher during the day and ~30 bpm higher during the night.
I had a very similar reaction that correlates to getting the vaccine. It took months for my resting heart rate to return to pre-vaccination levels. Maybe this means I would have died had I caught covid, maybe not, no way to know. It's scary how much this spike protein / immune response / etc seems to provoke adverse cardiovascular responses, even if there is full recovery in most of us.
I had already had covid 2x prior to general vaccine availability. I got totally owned in the short term but was back to working out pretty quick. The second Moderna shot completely wrecked me in a way having covid didn't, I had severe heart palps/skips for weeks. Sitting/standing at my desk and just having one after the other and would lose my breath between them. After that decided boosters could fuck off.
The vaccine is the safer controlled introduction to it in comparison to getting a full covid exposure. In a full covid case w/o being vaccinated would introduce more spike protein as well as a exposure to the sequences of the rest of the virus which could cause all sorts of other issues.
> It's scary how much this spike protein / immune response / etc seems to provoke adverse cardiovascular responses, even if there is full recovery in most of us.
Honestly I am wondering if this is sampling bias. Have we ever paid this much concentrated attention to a disease? When you consider what a virus does to the body, it seems likely that many other viruses that have been endemic for millennia have been wreaking pernicious havoc on our bodies and we just... shrugged it off.
Anyplace the body heals from a significant physical injury, there is a scar. It's never a perfect restoration. It seems almost intuitive that the damage from a virus would be similar, and there is documented evidence that COVID will attack neurons.
If you look at Fig1, describing the cohort selection, this study has two control groups. A historical as well as a contemporary control group. This gives an two different sample sources to reason about sampling bias. The data presented here are very likely not bias in the way your describing as it because of the contrast to both controls that would capture "it's always been that way" effect.
> If you look at Fig1, describing the cohort selection, this study has two control groups. A historical as well as a contemporary control group. This gives an two different sample sources to reason about sampling bias.
There's a clear difference in health between the cohorts.
Supplementary table 1 breaks down the cohorts and summarizes co-variates. Disturbingly, the COVID cohort is significantly fatter than the contemporary control group:
54% of the COVID cohort has BMI > 30, vs 42% of the contemporary controls, and 40% of the historical controls. They also have a higher percentage in long-term care (4% vs. 0.6%), a higher percentage with cancer (8% vs. 6%), chronic kidney disease (19.5% vs 16.7%), lung disease (15% vs. 11%), dementia (6% vs. 3%), diabetes (32% vs 22%) and hyperlipidemia (34% vs 25%).
The Covid cohort is basically a much sicker population, in almost every way. Re-weighting the populations doesn't correct for this disparity.
The authors have attempted to hide this by burying the data in the supplementary material, and presenting an "absolute standardized difference" that makes it look smaller than it is.
No that figure is the study being transparent on how it controlled for imbalances of selected input conditions showing raw numbers then the post processed reweighting of the samples. How does that fail as a way to account for differences in those conditions?
What would be your preferred technique of accounting for the differences of characteristics in those groups?
Look at supplementary figure 2. Their attempts to normalize the data do not eliminate the bias. The Covid-19 cohort is significantly sicker, even after adjustment.
This paper is discussing small differences in small numbers, and the single biggest difference between groups is the baseline level of health for the study participants. About the only thing you can say from this is that old, sick people are sicker after Covid-19 severe enough to put them in the hospital.
> The data presented here are very likely not bias in the way your describing as it because of the contrast to both controls that would capture "it's always been that way" effect.
That's not really what I said -- I'm not actually taking a stance on the conclusions of this paper. COVID has obviously been infecting massive numbers of people in the last couple of years, and if it is responsible for long-term cardiovascular sequelae as the paper concludes, of course it would be a more acute contributor over that period as compared to other historical causes simply by virtue of its pervasiveness.
Rather what I said is that the disease itself may not be causing "havoc" in the body at rates significantly different than other endemic viruses ("havoc" writ large: not only confined to cardiovascular sequelae, but among any long-term systemic harms). The bias that I am proposing is that we are _noticing_ these sequelae because A) so many people are getting sick at the same time, and B) because we are paying this much attention for the first time ever.
Like I just emphasized, they may not show up as statistically significant because
A) they are not pandemic, so the effect is of course much smaller
B) their impact is not necessarily primarily cardiovascular
Here's a non-exhaustive list of viruses with potentially overlooked sequelae.
Shingles (herpes zoster)
Rubella
Rotavirus
RSV
Norovirus
HPV
Hepatitis
Influenza
This is totally orthogonal to any possible defects in this study, which again I am not taking any stance on. It's merely a question of whether this study is anomalous for having been conducted in the first place. If we assume that the study is flawless, that means that COVID has long term health impacts -- fine -- but do we actually know if that's unusual for a virus?
