Woah woah woah. Decrease ICU admission by 97%? When you see numbers like this, you can be assured that this is probably the result of either a small sample size or misleading statistics.
Let’s look at the paper:
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. Eligible patients were allocated at a 2 calcifediol:1 no calcifediol ratio through electronic randomization on the day of admission to take oral calcifediol (0.532 mg), or not. Patients in the calcifediol treatment group continued with oral calcifediol (0.266 mg) on day 3 and 7, and then weekly until discharge or ICU admission. Outcomes of effectiveness included rate of ICU admission and deaths.
This seems okay, it’s not a placebo control trial but they have a clear end goal of what they are studying and only aimed to vary one thing. So how many patients did they look at?
Of 50 patients treated with calcifediol, one required admission to the ICU (2%), while of 26 untreated patients, 13 required admission
So these seem like remarkable results, but how similar were the two groups in general? Some potential problems looking at the ‘control’ and 'calcifediol ’ groups:
- Control group was 70% male compared to 54% male in calcifediol group
- 60% of the control group compared to 25% of the calcifediol group had previously high blood pressure
- 61% of the control group compared to had “one prognostic bad risk factor” compared to 48% of the calcifediol group
So, something like this could warrant further study, but there could be other underlying factors here and/or the results could just be due to chance with the small sample size and various risk factors that could impact the data. It could also be the people involved in the study were deficient in vitamin D and this could be something to help certain populations or people, but wouldn’t cause much of an effect in a different population.