Delineating COVID-19 subgroups using routine clinical data identifies distinct in-hospital outcomes

Abstract

The COVID-19 pandemic has been a great challenge to healthcare systems worldwide. It highlighted the need for robust predictive models which can be readily deployed to uncover heterogeneities in disease course, aid decision-making and prioritise treatment. We adapted an unsupervised data-driven model-SuStaIn, to be utilised for short-term infectious disease like COVID-19, based on 11 commonly recorded clinical measures. We used 1344 patients from the National COVID-19 Chest Imaging Database (NCCID), hospitalised for RT-PCR confirmed COVID-19 disease, splitting them equally into a training and an independent validation cohort. We discovered three COVID-19 subtypes (General Haemodynamic, Renal and Immunological) and introduced disease severity stages, both of which were predictive of distinct risks of in-hospital mortality or escalation of treatment, when analysed using Cox Proportional Hazards models. A low-risk Normal-appearing subtype was also discovered. The model and our full pipeline are available online and can be adapted for future outbreaks of COVID-19 or other infectious disease.

Figure 1

COVID-19 subtypes and disease severity progression. The warm colours represent disease stages progressing towards positive z-scores (z = 1, z = 2) and the cold colours—towards negative z-scores (z = − 1, z = − 2). Increased colour transparency signifies greater uncertainty. The f-value next to each subtype represents the fraction of the training population which was classified as belonging to this subtype.

Figure 2

Kaplan–Meier plots for 6-month in-hospital escalation of treatment for the training (left) and validation (right) population. wstage—weighted SuStaIn stage.

Figure 3

SuStaIn stage provides better discrimination of time to escalation than age or sex: left—training population, right—validation population. wstage—weighted SuStaIn stage. sex 0—female, sex 1—male.

Figure 4

Kaplan–Meier plots for 6-month in-hospital mortality for the training (left) and validation (right) population. Wstage—weighted SuStaIn stage.

Figure 5

SuStaIn stage provides better discrimination for 6-month in-hospital mortality than age or sex (left—training population, right—validation population. wstage—weighted SuStaIn stage. sex 0—female, sex 1—male.