New Czech dataset has ICD10 codes of vaccinated vs. unvaccinated female deaths

The Czech Republic has published a record-level dataset of data of women only.

Upsides:

1. goes back in time to deaths happening from 1994 onwards so 30 years of death data

2. has actual birth year

3. has ICD10 code for underlying cause of death (umrti_diagnoza)

4. has recordID# and sequence number of events for that record number including all COVID vaccinations (date and manufacturer)

Downsides:

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.

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).

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
==================================================

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.

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.

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.

John Beaudoin, Sr., The Real CdC, The Last Boomer@JohnBeaudoinSr

@FLSurgeonGen @GovRonDeSantis @TracyBethHoeg
> 18,000 Sudden Kidney Failure deaths in Florida
NIH/CDC fed protocols & vaccines did this
Covid did NOT do this

What is FL DoH’s Mission?

5 to 10 physicians can conclusively determine actual & proximate cause in 2 wks

Ask me how

8:03 PM · Dec 17, 2025 · 107K Views

26 Replies · 206 Reposts · 401 Likes

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.

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