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Comment by peytn | Hacker News Reader

Worth mentioning that the control group wasn’t matched for hospital admission status, while the study group was solely people who ended up in the hospital. I’m guessing that the authors likely could have acquired the data to match a control group of people who had been admitted to the hospital, so I’d be curious to see what the results would’ve been there.

According to the paper, this control group was picked because, essentially, that’s what the authors wanted to choose:

> We selected controls from the general population rather than matching to non-covid hospital admissions to determine the increased risk after hospital admission for covid-19 versus no hospital admission for covid-19 (that is, compared with the expected risk for people with similar personal and clinical characteristics in the general population).

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Yes, but that seems like a very relevant type of control group. If a person got COVID and ended up in the hospital, and that person wants to know what possible long-term harm that could cause them (that is, compared to had they not gotten COVID and not been hospitalized), then the article focused on exactly that.

Not really. The UK has been testing pretty much everyone who's admitted to hospital for COVID since the start of the outbreak regardless of why they were admitted, which means there's going to be quite a few people in the COVID and in hospital group who were actually admitted due to other, unrelated conditions. Particularly if they were being admitted to hospital regularly...

Good question to ask, but no, they didn't look at people who tested positive but were admitted for something else:

> Individuals were included if they had a hospital episode from 1 January to 31 August 2020 with a primary diagnosis of covid-19

(from the full paper)

And throughout their stay. My father was vaccinated in January, went into hospital after a siezure (not unknown) a in mid febuary, he was tested on arrival, and was negative. Continued to be tested, and by early march (2 weeks after admittance) he tested positive.

That’s what they attempt to focus on, but inadvertently introduce bias in terms of people’s proclivity to show up at the hospital for any given severity of issue.

People who present once for one thing are probably more likely to present a second time: either because they have a lower threshold for seeking help, they have overall poorer health and so present more often, or because they have a referring primary doctor who is biased towards admitting over treating outpatient.

That's a fair point. That could inflate the later admission numbers.

However, I don't think it can explain the far higher death rate.

The poorer general health one it seems would have a bias towards all-cause mortality rate, though perhaps not to the full magnitude as observed.

Possibly. But poorer general health is something they explicitly tried to account for with the control group, at least.

The most useful result here is to isolate the impact of covid hospital admission status on the probability of mortality, not the difference between covid and other hospitalizations.

Anyone who’s even dipped a toe in this policy area can tell you that when old people and hospitals meet, gaudy statistics follow. It’s common knowledge in the field. To not include that context or any points of comparison seems irresponsible to me given the publicity.

The excerpt from the study quoted above says "Rate ratios were greater for individuals aged less than 70 ... with the largest differences seen for respiratory disease (10.5 (95% confidence interval 9.7 to 11.4) for age less than 70 years v 4.6 (4.3 to 4.8) for age ≥70)"

Isn't that a clear indication that there's something besides "general trends in old people" going on here?

Age isn't the only factor, you need to control for underlying health conditions, which apparently they chose not to. Suppose you have COPD at age 50, for one you are less likely to live to 70, but also you are at a far greater risk with COVID. It would not be unexpected if such a person were readmitted to the hospital or die months later.

They did account for underlying health conditions. The control group was matched for relevant clinincal diagnoses, as well as general health factors like BMI and smoking (see "matching variables" section in the paper).

I see that they were matched now, still the control group wasn't hospitalized, which must skew the result.

Looking at the tables, you might get the idea that COVID hospitalization causes a lot of diabetes. The way they arrive at that is to count the diabetes diagnoses made after COVID admission.

However to me it seems far more likely that a diabetic without a diagnosis (which is common) gets hospitalized with COVID, then gets their diabetes diagnosis in the ensuing medical surveillance. Having an undiagnosed liver or heart issue is also common.

See the discussion above - it's very intentional that the control group wasn't hospitalized. It's the right approach for the question they are trying to answer, "how bad off is a person that got COVID and got hospitalized as a result of that".

(There are other good questions to ask too, of course.)

Given the discussion generated here and probably elsewhere, why do you believe the authors chose not to present a matched hospitalization control group alongside their control group? It’s pretty standard: that’s why they included a sentence saying they chose not to (albeit without any justification).

Why deviate?

As mentioned in the discussion above, their control group answers the question "if a person got COVID and was hospitalized because of it, how much worse off are they than had those things not happened?"

They do justify their choice in the actual paper (e.g. see the end of the "Study population" section).

(It's also interesting to compare COVID hospitalizations to other ones, say from a heart attack or allergic reaction, but those are different questions. For example, maybe a COVID hospitalization is less bad than one due to a heart attack, or worse than an allergy. Or maybe any hospital visit is just bad period. But given many people got hospitalized by COVID this year - something that never happened in the past - we need to know what that event cost them, that's the point of this study.)

I read the paper. That is not a justification. If you are unwilling to entertain the idea that this is a low-quality report, go ahead. I can only contribute some prior experience on an Internet forum in an attempt to shed light on a politically fraught result from what appears to be a government scientist and some collaborators.

> "if a person got COVID and was hospitalized because of it, how much worse off are they than had those things not happened?"

How do you then control for those with a chronic condition that is undiagnosed? If somebody is hospitalized, they'll perform all sorts of tests on them, that's how many people get their diabetes diagnosis in the first place.

Looking at the charts, you might get the idea that there's a staggering increase in new-onset diabetes following COVID infection, which doesn't seem plausible to me. Yet, right next to that, you see damage in heart, liver and kidneys, and this gets picked up uncritically as an outcome of COVID. The hypothesis that COVID causes organ damage is already well-established, so this just confirms what we expect. What we don't expect, we just ignore, even though it might point to a flaw in our methodology.

You're right that that's a possibility. A completely undiagnosed underlying condition would be missed by that type of control group.

But we know that COVID admittances caused a big increase in the total number of people hospitalized - to the point of overwhelming some health care systems. That strongly suggests that underlying conditions would not have sent as many people to the hospital anyhow if COVID had never appeared and infected them.

It is possible you explain the mechanism, though. Perhaps there are lots of people with undiagnosed underlying conditions, and getting a serious case of COVID is enough to worsen those conditions into life-threatening ones. (Perhaps this only hastens the inevitable for some of them.) If this is the mechanism then both you and the article's hypotheses would be correct.

> The increase in risk was not confined to the elderly and was not uniform across ethnicities

> Rate ratios comparing patients with covid-19 and matched controls were greater in individuals aged less than 70 than those aged 70 or more for all outcomes

> An alternative approach might have involved comparing outcomes after covid-19 and other hospital admissions; such research has recently been conducted with similar data sources to those in our own study (although with a smaller covid-19 cohort), and comparable rates of organ dysfunction were found between patients with covid-19 and patients with pneumonia who were discharged from hospital in 2019.36 We believe that our study design, where comparisons were made with the expected risk in the general population, was more relevant to public health policy, and complementary to the study that used non-covid hospital admissions as the comparison group. Also, the use of non-covid hospital admissions as the comparison group does not allow estimation of excess morbidity because non-covid admission does not necessarily represent an appropriate counterfactual situation to admission to hospital for covid-19, and the size and direction of the inferences will depend on the choice of control admissions.

That’s the number this study went for, but it also is a number that doesn’t tell us anything about whether the increased chance of hospitalization and increased death rate are due to COVID, due to the first hospitalization, or due to those being hospitalized in the first place already being weaker than the general population.

I wouldn’t call it the most useful one.

If those who were admitted to a hospital with COVID already were less healthy than those who weren’t before they got COVID (and that’s a given. Higher lung capacity can keep you out of the hospital, for example), I don’t think it is a surprise they still aren’t as healthy when they leave the hospital.

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