Predictors of fatality including radiographic findings in adults with COVID-19

Link to article at PubMed

Li K, et al. Respir Res 2020.


BACKGROUND: Older age and elevated d-dimer are reported risk factors for coronavirus disease 2019 (COVID-19). However, whether early radiographic change is a predictor of fatality remains unknown.

METHODS: We retrospectively reviewed records of all laboratory-confirmed patients admitted to a quarantine unit at Tongji Hospital, a large regional hospital in Wuhan, China, between January 31 and March 5, 2020. Confirmed cases were defined by positive RT-PCR detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in throat-swab specimens. Chest CT images were reviewed independently by two radiologists. The Tongji Hospital ethics committee approved this study.

RESULTS: A total of 102 patients were confirmed to have SARS-CoV-2 infection. As of March 25, 85 confirmed patients were discharged, 15 died, and 2 remained hospitalized. When compared with survivors, non-survivors were older (median age, 69 [interquartile range, 58-77] vs. 55 [44-66], p = 0.003), and more likely to have decreased lymphocyte count (0.5 vs. 0.9 × 109/L, p = 0.006), elevated lactate dehydrogenase (LDH) (569.0 vs. 272.0 U/L, p < 0.001), elevated d-dimer (> 1 μg/mL, 86% vs. 37%, p = 0.002) on admission. Older age and elevated LDH were independent risk factors for fatality in a multivariate regression model included the above variables. In a subset of patients with CT images within the first week, higher total severity score, and more involved lung lobes (5 involved lobes) in CT images within the first week were significantly associated with fatality. Moreover, in this subset of patients, higher total severity score was the only independent risk factor in a multivariate analysis incorporating the above mentioned variables.

CONCLUSIONS: Older age, elevated LDH on admission, and higher severity score of CT images within the first week are potential predictors of fatality in adults with COVID-19. These predictors may help clinicians identify patients with a poor prognosis at an early stage.

PMID:32527255 | PMC:PMC7289230 | DOI:10.1186/s12931-020-01411-2

Leave a Reply

Your email address will not be published.