> For the reduced logistic regression model, the score was given by the following formula:
S = 0.259503 × NumberSymptoms + 0.055457 × age − 0.633310 × sex − 3.20 (where sex is encoded as 1 − female/2 − male)
Where ‘NumberSymptoms’ corresponds to the sum of different symptoms experienced over the first week among the list of 14 symptoms reported on daily logs. This score was then transformed to a probability using the formula: 1/(1 + exp(−score))
> App users were disproportionately female, and those over 70 years of age were underrepresented, which could increase or decrease our estimate of the prevalence and duration of long COVID.
So basically if the patient is a 30 y.o man with 7 symptoms has almost twice more chance of having long covid than a woman on the same conditions ? Hmmmmmmmmmmm
> App users were disproportionately female, and those over 70 years of age were underrepresented, which could increase or decrease our estimate of the prevalence and duration of long COVID.
So basically if the patient is a 30 y.o man with 7 symptoms has almost twice more chance of having long covid than a woman on the same conditions ? Hmmmmmmmmmmm