12 ms·

From the results: “Of 50 patients treated with calcifediol, one required admission to the ICU (2%), while of 26 untreated patients, 13 required admission (50%)

From the results: “Of 50 patients treated with calcifediol, one required admission to the ICU (2%), while of 26 untreated patients, 13 required admission (50%) p value X2 Fischer test p < 0.001.” Which sounds like as strong a signal as a study of this scale could hope to show.

zamfi 6y ago
Yes, this is strong. Worth noting the limitations though: > Randomization generated groups with comparable percentage of unfavorable risk factors as there was no significant difference in subjects with at least one risk factor, except for high blood pressure and diabetes mellitus, known risk factors for unfavorable disease progression [2], which were more frequent in patients not treated with calcifediol. These are HUGE risk factors. Also: > This pilot study has several limitations as it is not double-blind placebo controlled. On the other hand, in the first studies evaluating risk factors for severe disease and/or death from COVID-19, the possible role of obesity was not considered. Therefore, given the isolation characteristics of the patients, we did not collect the BMI, which would have allowed us to add obesity as a risk factor for severe evolution of COVID-19 [37] It is striking to consider that obesity shares with aging and black or asian ethnicity a surprising overlap as risk factors for severe COVID-19 and vitamin D deficiency. Yeah, BMI would've been nice too. Still, check out table 2. Even with these limitations, seems powerful.
- acqq 6y ago
  The group receiving Calcifediol had more "no bad risk" patients: "At least one prognostic bad risk factor(@) Group receiving Calcifediol: 48% Group without Calcifediol: 61.54%" "@) Patients with at least one of the following risk factors (age >60, previous lung disease, chronic kidney disease, diabetes mellitus, hypertension, cardiovascular disease or Immunosuppressed and transplanted patients)." That's what can be concluded from "at least one": (52% had no bad risk in D group, but only 38.46% had no bad risk in the other group). But it is also not clear where there were more patients with "multiple" factors! Or if they were those who had more problems at the end. The whole paper contains neither raw data nor any graphs and only means and standard deviations, as far as I see? I would personally really like to see the graphs of distributions or to use raw data to check myself. The critical question is how good the randomization was done.
  - deleted 6y ago
    [deleted]
  - mlyle 6y ago
    Randomization doesn't ensure perfectly balanced groups-- it just ensures that the imbalances of variables you don't measure (including things that change after randomization not related to your intervention, with blinding) are drawn from a distribution that you can apply rigorous statistical reasoning about. Yes, we can see some things are a little unbalanced. But the effect is so massive: we might see 4/5 of the control's rate of ICU admissions if the "one prognostic bad risk factor" determined outcome entirely; instead, we see 1/50 of the rate.
    - acqq 6y ago
      > we might see 4/5 of the control's rate of ICU admissions if the "one prognostic bad risk factor" determined outcome entirely But we still don't know if the persons with multiple bad risk factors were those who ended with bad outcomes? As far as I understand, if it was like that or not can't be seen from the paper at all, and I can imagine that it could have happened. I would really prefer the more raw data to the tables with the selected means and deviations given.
      - mlyle 6y ago
        You have to get very, very unlucky on the dice rolls to get samples that are so tilted-- to pick 26 people out of 76, and somehow come up with 13/14 of those requiring ICU in the smaller group, if vitamin D has no effect. Outside of deliberate rigging... (it might even be difficult to deliberately sort and get this much of an imbalance). Indeed, checking that the two groups look similar after randomization is completely optional. This study does an OK job of doing so. There's both known and unknown reasons why someone might be predisposed to have a bad outcome. The reason we randomize, rather than try and make "balanced" groups, is that it addresses both unknown and known factors. Yes, you can, by chance, get more people who are going to have a bad outcome in one group; about 5% of the time you'll get a p<0.05 finding this way. :P
- altvali 6y ago
  Is BMI a good indicator of obesity, though?
  - purec 6y ago
    It works for the average person but becomes distorted when you look at athletes, especially those that need to put on more muscle.
  - SketchySeaBeast 6y ago
    I understand the objections to BMI comparisons at an individual level (though I believe people think themselves a bit too exceptional too often), but as part of a larger study, I would think it'd make a good additional data point, no?
    - altvali 6y ago
      It most definitely would, but measuring body fat percentage would be better.
      - SketchySeaBeast 6y ago
        But then you couldn't easily extrapolate to the population. Well, you could, but you'd require the population to have an understanding of their body fat percentages. BMI isn't ideal, but it's quick and dirty, easy to collect and it should be relatively reliable for the population.
        greenbush 6y ago
        It's not that straightforward as the BMI thresholds vary by ethnicity: https://www.hsph.harvard.edu/obesity-prevention-source/ethnic-differences-in-bmi-and-disease-risk/ https://www.hsph.harvard.edu/obesity-prevention-source/ethni...
  - graeme 6y ago
    It’s actually pretty decent. It can make errors in the case of people with extreme muscle mass, or very low muscle mass for their size, or the very short, or the very tall. But for most people, if you’re over 25 bmi you probably could lose some weight. And at a population levels the errors above average out, even in a smaller group. People make a big deal over the exceptions to it while ignoring that it is broadly accurate and that exceptions are not as common.
- Alex3917 6y ago
  > These are HUGE risk factors. Given that Vitamin D deficiency can cause high blood pressure, their decision not to correct for this might be the better option.
  - zamfi 6y ago
    Good point. Confounds all the way down!
    - deleted 6y ago
      [deleted]
Animats 6y ago
Yes, this is encouraging. Management of this disease has improved over the last few months. More people hospitalized are surviving.[1] [1] https://www.latimes.com/california/story/2020-08-09/covid-19-coronavirus-survival-rate-improves https://www.latimes.com/california/story/2020-08-09/covid-19...
- jacquesm 6y ago
  Important to note that surviving is something else than 'making a full recovery'. It's an obvious improvement, and it clearly shows in the day-to-day statistics, the ratio of fatalities to positive tests has been - very slowly - dropping.
- andruby 6y ago
  And it's also summertime in the northern hemisphere, which means less vitamin-D deficiency. Coincidence?
  - gnulinux 6y ago
    Does it work the same way if you take oral vitamin D supplement? My skin is allergic to the sun (it hurts it bad) but I take daily vit D supplement.
    - graeme 6y ago
      Probably? At least in part. This study involved supplementation rather than skin production. However, for those who can get skin production it is probably better, as there may be other effects we don’t know of. Plus it self limits, whereas one can overdo supplements.
    - Jommi 6y ago
      It's actually a lot better. Even in countries with near constant sunlight, d vitamin deficiency bus prevalent. It's more related to our lifestyle than just geographic location.
ellyagg 6y ago
It's useful to note that this study doesn't need to stand on its own as evidence. It contributes to a growing body. As most of you may have already seen, there is a lot of observational evidence that people with low vitamin D have the worst C19 outcomes. Obviously, correlation by itself doesn't mean causation. But it is a hint. On top of the hint, we already have dozens of RCTs that vitamin D supplements suppress respiratory infections. https://www.bmj.com/content/356/bmj.i6583 https://www.bmj.com/content/356/bmj.i6583 And now we have this study. Every study and line of evidence has flaws, which is why you look at the totality of the evidence. From the evidence I've seen, low vitamin D is a bigger problem in modern societies than vitamin D toxicity. Vitamin D is available OTC and many people use it apparently responsibly. I would expect that to continue with appropriate messaging. It would be great if we could pursue a consensus on this while it can still make a difference, even in the absence of perfect data. It was a mistake in the early US messaging to downplay the importance of masks even though we didn't have perfect data on it.
- JshWright 6y ago
  > there is a lot of observational evidence that people with low vitamin D have the worst C19 outcomes. Obviously, correlation by itself doesn't mean causation. But it is a hint. It's a pretty useless one in this case. Old people are much more likely to have vitamin D deficiency. They are also more likely to die of COVID. The low vitamin D is a marker of frailty, not a cause.
  - elliekelly 6y ago
    How can you say that with such certainty?
    - harry8 6y ago
      Randomized trial. This was not simply observational. There will be no correlation between being given higher dose vitamin D and age in this trial, the results appear at first blush to be showing Vitamin D is working independant of age. By the by this /exactly/ why a randomised trial has been the gold standard for medical treatment for so long. False correlations, confounding factors etc are all vastly less likely to skew the results. 2 groups chosen at random, nobody in the groups or treating them knows which is which. 1 group given treatment, 1 given a placebo. How much difference do we see in the 2 groups as a result of treatment. It's a good question. It's always worth asking. It's always worth checking. The rabbit hole of stat analysis of treatments goes pretty deep from there. Ethical issues come in. Expense. But we all need to make the effort to understand it on some level or we're marks for snake-oil.
wrycoder 6y ago
Note that all patients received HCQ and azithromycin. Quoting the article (which I hope all here will read), "[typically] more than 40 % of patients hospitalized because of COVID‐19 pneumonia developed ARDS of which more than 50 % ultimately died." That's a 20% fatality rate. Of the 76 patients in this study - regardless of vitamin D treatment - only 2 died, and the rest were eventually discharged. This is an outstanding result. None (!) of the hospitalized patients died in the vitamin D / HCQ / AZ group. I will say that the average age - 58 - is rather young. Only 19 out of 76 were over 60. "All hospitalized patients received as best available therapy the same standard care, (per hospital protocol), of a combination of hydroxychloroquine (400 mg every 12 hours on the first day, and 200 mg every 12 hours for the following 5 days), azithromycin (500 mg orally for 5 days) and for patients with pneumonia and NEWS score≥5, a broad spectrum antibiotic (ceftriaxone2 g intravenously every 24 hours for 5 days) was added to hydroxychloroquine and azithromycin." They have since discontinued HCQ because they felt that studies had shown that it was ineffective. We shall see. As with AIDS, it's the cocktail of drugs that appears to matter. What is effective pre-hospitalization (i.e. prophylactic) is different from the best protocol post-admission. And that, in turn, differs from the best course of treatment in the ICU. The improvement in outcomes over the last few months is a result of experience: https://covid19criticalcare.com/wp-content/uploads/2020/07/FLCCC_Alliance-MATHplus_Protocol_v5-2020-07-14.pdf https://covid19criticalcare.com/wp-content/uploads/2020/07/F... (pdf)

zamfi 6y ago

Yes, this is strong. Worth noting the limitations though: > Randomization generated groups with comparable percentage of unfavorable risk factors as there was no significant difference in subjects with at least one risk factor, except for high blood pressure and diabetes mellitus, known risk factors for unfavorable disease progression [2], which were more frequent in patients not treated with calcifediol. These are HUGE risk factors. Also: > This pilot study has several limitations as it is not double-blind placebo controlled. On the other hand, in the first studies evaluating risk factors for severe disease and/or death from COVID-19, the possible role of obesity was not considered. Therefore, given the isolation characteristics of the patients, we did not collect the BMI, which would have allowed us to add obesity as a risk factor for severe evolution of COVID-19 [37] It is striking to consider that obesity shares with aging and black or asian ethnicity a surprising overlap as risk factors for severe COVID-19 and vitamin D deficiency. Yeah, BMI would've been nice too. Still, check out table 2. Even with these limitations, seems powerful.

acqq 6y ago
The group receiving Calcifediol had more "no bad risk" patients: "At least one prognostic bad risk factor(@) Group receiving Calcifediol: 48% Group without Calcifediol: 61.54%" "@) Patients with at least one of the following risk factors (age >60, previous lung disease, chronic kidney disease, diabetes mellitus, hypertension, cardiovascular disease or Immunosuppressed and transplanted patients)." That's what can be concluded from "at least one": (52% had no bad risk in D group, but only 38.46% had no bad risk in the other group). But it is also not clear where there were more patients with "multiple" factors! Or if they were those who had more problems at the end. The whole paper contains neither raw data nor any graphs and only means and standard deviations, as far as I see? I would personally really like to see the graphs of distributions or to use raw data to check myself. The critical question is how good the randomization was done.
- deleted 6y ago
  [deleted]
- mlyle 6y ago
  Randomization doesn't ensure perfectly balanced groups-- it just ensures that the imbalances of variables you don't measure (including things that change after randomization not related to your intervention, with blinding) are drawn from a distribution that you can apply rigorous statistical reasoning about. Yes, we can see some things are a little unbalanced. But the effect is so massive: we might see 4/5 of the control's rate of ICU admissions if the "one prognostic bad risk factor" determined outcome entirely; instead, we see 1/50 of the rate.
  - acqq 6y ago
    > we might see 4/5 of the control's rate of ICU admissions if the "one prognostic bad risk factor" determined outcome entirely But we still don't know if the persons with multiple bad risk factors were those who ended with bad outcomes? As far as I understand, if it was like that or not can't be seen from the paper at all, and I can imagine that it could have happened. I would really prefer the more raw data to the tables with the selected means and deviations given.
    - mlyle 6y ago
      You have to get very, very unlucky on the dice rolls to get samples that are so tilted-- to pick 26 people out of 76, and somehow come up with 13/14 of those requiring ICU in the smaller group, if vitamin D has no effect. Outside of deliberate rigging... (it might even be difficult to deliberately sort and get this much of an imbalance). Indeed, checking that the two groups look similar after randomization is completely optional. This study does an OK job of doing so. There's both known and unknown reasons why someone might be predisposed to have a bad outcome. The reason we randomize, rather than try and make "balanced" groups, is that it addresses both unknown and known factors. Yes, you can, by chance, get more people who are going to have a bad outcome in one group; about 5% of the time you'll get a p<0.05 finding this way. :P
altvali 6y ago
Is BMI a good indicator of obesity, though?
- purec 6y ago
  It works for the average person but becomes distorted when you look at athletes, especially those that need to put on more muscle.
- SketchySeaBeast 6y ago
  I understand the objections to BMI comparisons at an individual level (though I believe people think themselves a bit too exceptional too often), but as part of a larger study, I would think it'd make a good additional data point, no?
  - altvali 6y ago
    It most definitely would, but measuring body fat percentage would be better.
    - SketchySeaBeast 6y ago
      But then you couldn't easily extrapolate to the population. Well, you could, but you'd require the population to have an understanding of their body fat percentages. BMI isn't ideal, but it's quick and dirty, easy to collect and it should be relatively reliable for the population.
      - greenbush 6y ago
        It's not that straightforward as the BMI thresholds vary by ethnicity: https://www.hsph.harvard.edu/obesity-prevention-source/ethnic-differences-in-bmi-and-disease-risk/ https://www.hsph.harvard.edu/obesity-prevention-source/ethni...
- graeme 6y ago
  It’s actually pretty decent. It can make errors in the case of people with extreme muscle mass, or very low muscle mass for their size, or the very short, or the very tall. But for most people, if you’re over 25 bmi you probably could lose some weight. And at a population levels the errors above average out, even in a smaller group. People make a big deal over the exceptions to it while ignoring that it is broadly accurate and that exceptions are not as common.
Alex3917 6y ago
> These are HUGE risk factors. Given that Vitamin D deficiency can cause high blood pressure, their decision not to correct for this might be the better option.
- zamfi 6y ago
  Good point. Confounds all the way down!
  - deleted 6y ago
    [deleted]

Animats 6y ago

Yes, this is encouraging. Management of this disease has improved over the last few months. More people hospitalized are surviving.[1] [1] https://www.latimes.com/california/story/2020-08-09/covid-19-coronavirus-survival-rate-improves https://www.latimes.com/california/story/2020-08-09/covid-19...

jacquesm 6y ago
Important to note that surviving is something else than 'making a full recovery'. It's an obvious improvement, and it clearly shows in the day-to-day statistics, the ratio of fatalities to positive tests has been - very slowly - dropping.
andruby 6y ago
And it's also summertime in the northern hemisphere, which means less vitamin-D deficiency. Coincidence?
- gnulinux 6y ago
  Does it work the same way if you take oral vitamin D supplement? My skin is allergic to the sun (it hurts it bad) but I take daily vit D supplement.
  - graeme 6y ago
    Probably? At least in part. This study involved supplementation rather than skin production. However, for those who can get skin production it is probably better, as there may be other effects we don’t know of. Plus it self limits, whereas one can overdo supplements.
  - Jommi 6y ago
    It's actually a lot better. Even in countries with near constant sunlight, d vitamin deficiency bus prevalent. It's more related to our lifestyle than just geographic location.

ellyagg 6y ago

It's useful to note that this study doesn't need to stand on its own as evidence. It contributes to a growing body. As most of you may have already seen, there is a lot of observational evidence that people with low vitamin D have the worst C19 outcomes. Obviously, correlation by itself doesn't mean causation. But it is a hint. On top of the hint, we already have dozens of RCTs that vitamin D supplements suppress respiratory infections. https://www.bmj.com/content/356/bmj.i6583 https://www.bmj.com/content/356/bmj.i6583 And now we have this study. Every study and line of evidence has flaws, which is why you look at the totality of the evidence. From the evidence I've seen, low vitamin D is a bigger problem in modern societies than vitamin D toxicity. Vitamin D is available OTC and many people use it apparently responsibly. I would expect that to continue with appropriate messaging. It would be great if we could pursue a consensus on this while it can still make a difference, even in the absence of perfect data. It was a mistake in the early US messaging to downplay the importance of masks even though we didn't have perfect data on it.

JshWright 6y ago
> there is a lot of observational evidence that people with low vitamin D have the worst C19 outcomes. Obviously, correlation by itself doesn't mean causation. But it is a hint. It's a pretty useless one in this case. Old people are much more likely to have vitamin D deficiency. They are also more likely to die of COVID. The low vitamin D is a marker of frailty, not a cause.
- elliekelly 6y ago
  How can you say that with such certainty?
  - harry8 6y ago
    Randomized trial. This was not simply observational. There will be no correlation between being given higher dose vitamin D and age in this trial, the results appear at first blush to be showing Vitamin D is working independant of age. By the by this /exactly/ why a randomised trial has been the gold standard for medical treatment for so long. False correlations, confounding factors etc are all vastly less likely to skew the results. 2 groups chosen at random, nobody in the groups or treating them knows which is which. 1 group given treatment, 1 given a placebo. How much difference do we see in the 2 groups as a result of treatment. It's a good question. It's always worth asking. It's always worth checking. The rabbit hole of stat analysis of treatments goes pretty deep from there. Ethical issues come in. Expense. But we all need to make the effort to understand it on some level or we're marks for snake-oil.

wrycoder 6y ago

Note that all patients received HCQ and azithromycin. Quoting the article (which I hope all here will read), "[typically] more than 40 % of patients hospitalized because of COVID‐19 pneumonia developed ARDS of which more than 50 % ultimately died." That's a 20% fatality rate. Of the 76 patients in this study - regardless of vitamin D treatment - only 2 died, and the rest were eventually discharged. This is an outstanding result. None (!) of the hospitalized patients died in the vitamin D / HCQ / AZ group. I will say that the average age - 58 - is rather young. Only 19 out of 76 were over 60. "All hospitalized patients received as best available therapy the same standard care, (per hospital protocol), of a combination of hydroxychloroquine (400 mg every 12 hours on the first day, and 200 mg every 12 hours for the following 5 days), azithromycin (500 mg orally for 5 days) and for patients with pneumonia and NEWS score≥5, a broad spectrum antibiotic (ceftriaxone2 g intravenously every 24 hours for 5 days) was added to hydroxychloroquine and azithromycin." They have since discontinued HCQ because they felt that studies had shown that it was ineffective. We shall see. As with AIDS, it's the cocktail of drugs that appears to matter. What is effective pre-hospitalization (i.e. prophylactic) is different from the best protocol post-admission. And that, in turn, differs from the best course of treatment in the ICU. The improvement in outcomes over the last few months is a result of experience: https://covid19criticalcare.com/wp-content/uploads/2020/07/FLCCC_Alliance-MATHplus_Protocol_v5-2020-07-14.pdf https://covid19criticalcare.com/wp-content/uploads/2020/07/F... (pdf)