RT Journal Article
SR Electronic
T1 Decreased eosinophil counts and elevated lactate dehydrogenase predict severe COVID-19 in patients with underlying chronic airway diseases
JF Postgraduate Medical Journal
JO Postgrad Med J
FD The Fellowship of Postgraduate Medicine
SP 906
OP 913
DO 10.1136/postgradmedj-2021-139704
VO 98
IS 1166
A1 Chen, Dian
A1 Zhang, Shuchen
A1 Feng, Yuchen
A1 Wu, Wenliang
A1 Chang, Chenli
A1 Chen, Shengchong
A1 Zhen, Guohua
A1 Yi, Lingling
YR 2022
UL http://pmj.bmj.com/content/98/1166/906.abstract
AB Background Several predictors of COVID-19 severity have been reported. However, chronic airway inflammation characterised by accumulated lymphocytes or eosinophils may affect the pathogenesis of COVID-19.Methods In this retrospective cohort study, we reviewed the medical records of all patients with laboratory-confirmed COVID-19 with chronic bronchitis, chronic obstructive pulmonary disease (COPD) and asthma admitted to the Sino-French New City Branch of Tongji Hospital, a large regional hospital in Wuhan, China, from 26 January to 3 April. The Tongji Hospital Ethics Committee approved this study.Results There were 59 patients with chronic bronchitis, COPD and asthma. When compared with non-severe patients, severe patients were more likely to have decreased lymphocyte counts (0.6×10⁹/L vs 1.1×10⁹/L, p<0.001), eosinopaenia (<0.02×10⁹/L; 73% vs 24%, p<0.001), increased lactate dehydrogenase (LDH) (471.0 U/L vs 230.0 U/L, p<0.001) and elevated interleukin 6 level (47.4 pg/mL vs 5.7 pg/mL, p=0.002) on admission. Eosinopaenia and elevated LDH were significantly associated with disease severity in both univariate and multivariate regression models including the above variables. Moreover, eosinophil count and LDH level tended to return to normal range over time in both groups after treatment and severe patients recovered slower than non-severe patients, especially in eosinophil count.Conclusions Eosinopaenia and elevated LDH are potential predictors of disease severity in patients with COVID-19 with underlying chronic airway diseases. In addition, they could indicate disease progression and treatment effectiveness.Data sharing not applicable as no datasets generated and/or analysed for this study.