Fig. 5: Survival analysis in the BQC19 cohort (n = 438 patients). | Nature Communications

Fig. 5: Survival analysis in the BQC19 cohort (n = 438 patients).

From: Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality

Fig. 5

Note that 44 patients of the 482 patients of the BQC19 cohort did not have information on the number of hospitalized days, yet had information on in-hospital mortality. A Forest plot of the Hazard Ratio (HR) from Cox regression analysis shows a higher risk of death for older patients and a lower risk for patients with higher LEF1-AS1 expression level. The dots and the error bars display the HR and the confidence interval, respectively. The p values are from a two-sided Wald test. B Kaplan–Meier curves using the stratified LEF1-AS1 expression with the first quartile (Q1), the median and the third quartile (Q3), respectively. Patients with LEF1-AS1 expression levels below or equal to the first quartile (Q1) are at a high risk of death. The p values are from a two-sided log-rank test.

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