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Wow for 18-49 the only “deaths while hospitalized” were in the vaccinated group. No deaths in the unvaccinated in that age group. Over all age groups paints a different picture entirely, with more deaths for unvaccinated. Glad the broke out the results by age group.
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They read the figure correctly.

Unfortunately the study authors didn’t provide the underlying data that created the figure in a consumable format, so it’s hard to draw conclusions.

Table 1 tells us that there were 6 total Omicron-period deaths while hospitalized in the fully vaccinated group. It is almost certainly a single death. It's conceivable that it's two deaths, but more than that appears mathematically impossible.
Precisely, but what gp said is technically correct.

Honestly it was fairly irresponsible for the study authors not to contextualize that graphic better.

Hey, even if he's wrong, you're not going to convince anyone with personal attacks. I was surprised at the data too.
Unless I'm reading the report wrong, it's from a single hospital. We shouldn't be taking any lessons from such a limited dataset as there are far too many possible confounding factors that would be ameliorated in a larger dataset from more hospitals.
That's a fair point, but the literature here does say what the original comment stated, which makes the whole reading-comprehension thing excessive.
I wouldn’t read too much into one figure that may represent 1-2 total observations (there were a grand total of 6 deaths in the vaccinated group, not broken out by age, and 14 in the unvaccinated). It doesn’t even explicitly state if they died due to Covid.
Might read something from the zero unvaccinated deaths, though.
Vaccination status has a ton of confounding variables, including age, immunocompromised status/other comorbidities, immunity from prior infection etc.

This was at one singular hospital with unknown population level immunity. The fact that there were zero deaths in what was likely a small subgroup is not something to base a broad likelihood estimate off of.

There is more to it than that one bar. One example, note (from Table 1)

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Unvaccinated (n = 657)

Death while hospitalized

¶¶ Denominator excludes 129 patients who remained hospitalized as of January 27, 2022

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Approximately 20% cannot be assigned either way for this outcome yet.

I thought we don't editorialize titles here.
How do you fit the huge title?

> Clinical Characteristics and Outcomes Among Adults Hospitalized with Laboratory-Confirmed SARS-CoV-2 Infection During Periods of B.1.617.2 (Delta) and B.1.1.529 (Omicron) Variant Predominance — One Hospital, California, July 15–September 23, 2021, and December 21, 2021–January 27, 2022

I tried to pick something from their summary which might fit here

> What are the implications for public health practice?

> COVID-19 vaccination, particularly a booster dose, continues to be critical in mitigating the health care burden of the Omicron variant.

"Outcomes Among Adults Hospitalized with Covid during Delta/Omicron waves"

Does that fit?

Yeah that would but not sure why it is better than what I have already put there

> editorialize:

> 1 : to express an opinion in the form of an editorial. 2 : to introduce opinion into the reporting of facts.

I didn't add any personal opinion but picked up directly from the summary itself.

It doesn't really capture what the paper encompasses, it highlights a specific part as if that was even a primary observation. The one I propose is dull as hell but its captures the extent of the study mostly trimming from the original and substituting synonyms for character constraint.