Cohort Analysis for COVID-19

The therapeutic effect of drugs is a very interesting analysis in medical research. One example medication analysis is as follows:

Select the patients with COVID-19 as the main group. Divide this group by treatment locations (isolation ward or ICU). Find different recovering time among the patients in different age groups from taking a certain medication.

Here, we can explore the average healing time from taking medication to recovery among patients of different age groups. From these visualization results (Figure 1 and Figure 2), we could find that this kind of drug works well on the age 60-69 group. ​


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Figure 1: Heat map for the healing time of the patient in ICU after taking the medication​

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Figure 2: Line chart for the healing time of the patient in ICU after taking the medication​

Besides, with COOL system, we could explore the risk factors in the COVID19 patients (time-series features such as vital signs, lab tests), and we could directly see the difference.

Here, we take the D-dimer as an example and explore the difference between the patients who are survival or not in the ICU.

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Figure 3: D_dimer Analysis​

From Figure 3, we could find that the fluctuation of the vital sign (D dimer) among the survival patients is more stable than the patients who are not.