Hello everybody
As you know, due to the high cost and time-consuming of laboratory assays, like PCR, for the suspected cases of COVID-19, doing this type of investigation is not possible for all the referrals to medical centers with COVID-like symptoms. Even though in middle and low-income countries this issue will be more critical. As a result, the infection may be confirmed by the practitioners based on the manifested signs and symptoms, without requesting a laboratory assay, i.e. clinically confirmation of COVID-19.
Accordingly, my question is that if we have the COVID-19 data in both forms of "PCR confirmed and Clinically confirmed patients" in our dataset:
1.Should we ignore or analyze those who didn't confirm by PCR test?
2.Can doing so cause bias in the reporting results?
3.How should these two types be reported together in a paper? Merged or separated?!
I dont think so you rely on symptoms of covid instead of assay. This can obviously creating bias coz the symotoms of covid also overlaps with other diseases as well
Dear Shahab!
There may be a situation when the PCR test is negative, and the patient has clinical symptoms of COVid-19, it is better not to ignore such a patient. A PCR test can also give a false negative result - for example, when a biomaterial was taken poorly. It is best to report on paper separately for PCR tests and clinically established cases for each patient.
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