Prognostic implications of comorbidity patterns in critically ill COVID-19 patients.

Abstract

<b>Introduction:</b> COVID-19 clinical heterogeneity suggests the existence of different phenotypes with prognostic implications. <b>Aims and objectives:</b> To analyse comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. <b>Methods:</b> Observational study in 55 Spanish intensive care units. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; hospital procedures/complications throughout the stay; and, persistent symptoms and lung function at 3, 6, and 12 months. <b>Results:</b> Latent class analysis identified 3 phenotypes: low-morbidity (LM) (n=3385; 58%), younger and with few comorbidities; high-morbidity (HM) (n=2074; 35%), with high comorbid burden; and renal-morbidity (RM) (n=407; 7%), with chronic kidney disease (CKD), high comorbid burden and the worst oxygenation profile. RM and HM had more in-hospital complications and higher mortality risk than LM (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in RM and HM. RM and HM showed the worst lung function throughout the follow-up, with RM having the highest risk of infectious complications (6%), emergency visits (29%) or hospital admissions (14%) at 6 months (p&lt;0.01). <b>Conclusions:</b> The 3 phenotypes showed different expression of in-hospital complications, mortality and sequelae. A key role of CKD was identified. A positive effect of corticosteroids, but not tocilizumab, on in-hospital mortality was found, with significant differences between phenotypes. Supported by ISCIII, UNESPA, CIBERES, FEDER, ESF.