Disentangling the Association of Hydroxychloroquine Treatment with Mortality in Covid-19 Hospitalized Patients through Hierarchical Clustering

<div>Characteristics of sample according to the two clusters identified.Comparison of the continuous variables used for hierarchical clustering—including (a) age (years), (b) BMI (Kg/m<sup>2</sup>), (c) eGFR (mL/min/1.73 m<sup>2</sup>), and (d) C-reactive protein plasma levels (mg/L, log-scale) between the two clusters of Covid-19 patients identified, namely, the low (green) and the high risk (red) cluster. Here, these variables are represented through boxplots, with boxes showing the interquartile ranges (IQR = <i>Q</i>1-Q3), continuous lines showing the whole distribution range from Q1 – 1.5∗IQR through <i>Q</i>3 + 1.5∗IQR, and dots showing more extreme values in the dataset.</div>

Journal of Healthcare Engineering

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Figure 2: Disentangling the Association of Hydroxychloroquine Treatment with Mortality in Covid-19 Hospitalized Patients through Hierarchical Clustering 

Figure 2 | Disentangling the Association of Hydroxychloroquine Treatment with Mortality in Covid-19 Hospitalized Patients through Hierarchical Clustering 