Autor/es reacciones

Erik Cobo

Statistician and doctor at the Universitat Politècnica de Catalunya - BarcelonaTech (UPC)

We must always be careful with observational studies like this one in which they stun with quantity without analysing quality.

1) They have millions of cases, but claim to have the necessary information on all of them: "No data were missing in our analysis". Can they assure me that they studied an inpatient with the same intensity as the same patient during other periods?

2) They have unrealistic numbers, with ratios of 30 to 50. A 50 times higher risk exceeds that of tobacco, which is hard to believe.

3) They do not discuss the weaknesses of the method: is it useful to take periods of the same patient without covid as a control? A carry-over effect between periods (e.g. the one who has fallen ill is protected for the future) would invalidate these estimates.

4) Most importantly, they do not discuss the different interpretations: "He who has fallen ill will fall ill again" (it is a relationship without causality, with predictive value only: it predicts that there will be complications but does not induce them, it does not "cause thrombus") versus "the fact of falling ill changes, increases, his predisposition to fall ill again" (causal relationship, "covid induces thrombi", which would anticipate a possible intervention: if you eliminate covid, you will eliminate thrombi) As an example, we ask the weatherman to anticipate it, not to change it.

They end up recommending thromboprophylaxis as if it follows from their study, although they have not studied it. It is a wish (thromboprophylaxis will prevent these thrombi), not a result; but they do not warn about it.

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