ABSTRACT
BACKGROUND: Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis. METHODS: Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method. RESULTS: Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio [HR] 3.10, 95% confidence interval [CI] 1.81-5.30, p < 0.001) and for phenotype C vs. B (HR 2.20, 95% CI 1.50-3.23, p < 0.001). A non-statistically significant trend towards higher mortality was also observed for phenotype B vs. A (HR 1.41; 95% CI 0.92-2.15, p = 0.115). By means of cluster analysis, three different phenotypes were also identified in our cohort, with an overall similar gradient in terms of prognostic impact to that observed when patients were assigned to FEN-COVID-19 phenotypes. CONCLUSIONS: The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study.
Hospitalized patients with COVID-19 can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory featuresIn this study, we externally confirmed the prognostic impact of clinical phenotypes previously identified by Gutierrez-Gutierrez and colleagues in a Spanish cohort of hospitalized patients with COVID-19, and the usefulness of their simplified probabilistic model for phenotypes assignmentThis could indirectly support the validity of both phenotype's development and their extrapolation to other hospitals and countries for management decisions during other possible future viral pandemics.
Subject(s)
COVID-19 , Humans , COVID-19/diagnosis , Prognosis , SARS-CoV-2 , Reproducibility of Results , Proportional Hazards Models , Retrospective StudiesABSTRACT
BACKGROUND: Chest CT on coronavirus disease (COVID-19) has been extensively investigated. Acute kidney injury (AKI) has been widely described among COVID patients, but the role of kidney imaging has been poorly explored. The aim of this study is to clarify the role of opportunistic kidney assessment on non-enhanced chest CT. METHODS: We collected data on patients with COVID-19 consecutively admitted to our institution who underwent chest CT (including the upper parts of kidneys as per protocol). Three ROIs of 0.5-0.7 cm2 were positioned in every kidney. The values of renal parenchyma attenuation (RPA) and the presence of perirenal fat stranding (PFS) were analyzed. The primary and secondary outcomes were the occurrence of AKI and death. RESULTS: 86 patients with COVID-19 and unenhanced chest CT were analyzed. The cohort was split into CT RPA quartiles. Patients with a CT RPA <24 HU were more likely to develop AKI when compared with other patients (χ2 = 2.77, p = 0.014): at multivariate logistic regression analysis, being in the first quartile of CT RPA was independently associated with a four times higher risk of AKI (HR 4.56 [95% CI 1.27-16.44, p = 0.020). Within a mean 22 ± 15 days from admission, 32 patients died (37.2%). Patients with PFS were more likely to die as compared to patients without it (HR 3.90 [95% CI 1.12-13.48], p = 0.031). CONCLUSIONS: Detection of low RPA values and of PFS in COVID-19 patients independently predicts, respectively, the occurrence of AKI and an increased risk for mortality. Therefore, opportunistic kidney assessment during chest CT could help physicians in defining diagnostic and therapeutic strategies.