New Czech dataset has ICD10 codes of vaccinated vs. unvaccinated female deaths
This new Czech record-level dataset includes vaccination status and the ICD10 code of the underlying cause of death. This may be useful to the few honest researchers who think the shots weren't safe.
Executive summary
The Czech Republic has published a record-level dataset of data of women only.
Upsides:
goes back in time to deaths happening from 1994 onwards so 30 years of death data
has actual birth year
has ICD10 code for underlying cause of death (
umrti_diagnoza)has recordID# and sequence number of events for that record number including all COVID vaccinations (date and manufacturer)
Downsides:
Women only
All events (deaths and COVID vaccinations) have month resolution, not week
NOTE: they subsequently removed the yearly and monthly resolution from the database so that it is impossible to now find any safety signals. This allows governments to continue to kill people without anyone finding out. I have a copy of the original database if anyone needs it.
I didn’t have time to fully analyze this data, but I did write a ton of code which did a lot of analysis and created a lot of charts which is all posted to my KCOR Github in the Czech2 folder.
The new Czech record level dataset
You can download the 1GB dataset here.
Or just clone my KCOR repo on Github to get all the output files found in the data/Czech2 directory (minus the input file).
Here is a top level summary of what is there
Note: The database records deaths a decade before the vaccines rolled out so the unvaccinated deaths are far higher than vaccinated deaths. And there was a higher percentage of elderly who are vaccinated. And unvaccinated people have higher baseline mortality. So it’s tricky to interpret the aggregate data summarized below. You have to take much narrower samples (time and age) to be meaningful.
ICD-10 Cause of Death Analysis Summary
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Total death records analyzed: 1,637,653
Vaccinated deaths: 114,127 (7.0%)
Unvaccinated deaths: 1,523,526 (93.0%)
Unique ICD-10 codes: 951
Top 10 ICD codes (vaccinated deaths):
1. I25: 16847 (14.76%)
2. I50: 7627 (6.68%)
3. E11: 4771 (4.18%)
4. U07: 3793 (3.32%)
5. C34: 3740 (3.28%)
6. G30: 3648 (3.20%)
7. C50: 3191 (2.80%)
8. J18: 2809 (2.46%)
9. I63: 2753 (2.41%)
10. J44: 2643 (2.32%)
Top 10 ICD codes (unvaccinated deaths):
1. I25: 251596 (16.51%)
2. I70: 109041 (7.16%)
3. I21: 91373 (6.00%)
4. I64: 86325 (5.67%)
5. I67: 56019 (3.68%)
6. C50: 50095 (3.29%)
7. I50: 43161 (2.83%)
8. C34: 41135 (2.70%)
9. I63: 39687 (2.60%)
10. J18: 33963 (2.23%)
Top 10 ICD codes with largest differences (vaccinated - unvaccinated):
1. I70: -5.87% (vacc: 1.29%, unvacc: 7.16%)
2. I64: -4.55% (vacc: 1.12%, unvacc: 5.67%)
3. I21: -3.97% (vacc: 2.02%, unvacc: 6.00%)
4. I50: +3.85% (vacc: 6.68%, unvacc: 2.83%)
5. E11: +2.67% (vacc: 4.18%, unvacc: 1.51%)
6. I67: -2.65% (vacc: 1.03%, unvacc: 3.68%)
7. U07: +2.34% (vacc: 3.32%, unvacc: 0.98%)
8. G30: +2.01% (vacc: 3.20%, unvacc: 1.19%)
9. I25: -1.75% (vacc: 14.76%, unvacc: 16.51%)
10. I10: +1.32% (vacc: 2.17%, unvacc: 0.85%)
Organ system distribution:
cardio: vacc 42.4% vs unvacc 54.3% (diff: -11.9%)
endocrine: vacc 5.5% vs unvacc 2.7% (diff: +2.8%)
neurologic: vacc 4.5% vs unvacc 2.1% (diff: +2.4%)
covid: vacc 3.4% vs unvacc 1.0% (diff: +2.4%)
respiratory: vacc 6.6% vs unvacc 5.0% (diff: +1.6%)
other: vacc 8.3% vs unvacc 6.9% (diff: +1.4%)
mental: vacc 2.1% vs unvacc 0.7% (diff: +1.4%)
infection: vacc 2.1% vs unvacc 0.9% (diff: +1.2%)
oncology: vacc 21.6% vs unvacc 22.6% (diff: -1.0%)
injury: vacc 1.7% vs unvacc 2.5% (diff: -0.7%)
renal: vacc 1.9% vs unvacc 1.5% (diff: +0.4%)For more info, see the README for the analysis which describes the code I created.
Acknowledgement
Thank you to Stanislav Veselý for bringing this dataset to my attention. He’s the guy who did the original FOIA request to the Czech government that got everything going.
He wrote me:
Until now, we only had aggregated data, which clearly showed that vaccinated women have about 30% fewer children than would correspond to their numbers. The row dataset could show much more than aggregate data. This is official data from Czech government.
AKI doesn’t jump out in the Czech data because it is UCOD and not MCOD
John Beaudoin, for example, has found acute kidney injury (AKI), which is ICD10 code N17, was strongly elevated post-vaccine rollout in all 50 states except Maine. We don’t see this in the Czech data because it is underlying cause of death (UCOD), not multiple causes of death (MCOD).
In the US, John estimates 250K excess deaths from AKI due to the COVID shots.
There were 4,655 N17 deaths in the Czech data.
Here are the 18,000 excess deaths in Florida.
Summary
This is a new Czech dataset with both upsides (record ID tied to individual, underlying cause of death ICD10 code) and downsides (monthly instead of weekly resolution).
A preliminary ICD10 code analysis didn’t find a smoking gun, but it doesn’t mean it isn’t there.
Hopefully, this article will motivate someone other than me to look at the data. I have my hands full at the moment.
It would be interesting to see the mortality rate by year and age group, vax vs unvax. Also: Kaplan-Meier survival curves.
Great data for the coming lawsuits against big pharma. This will bring an end to the vaccine religion.