Infection with SARS-CoV-2, the cause of coronavirus infectious disease-19 , has caused a pandemic with >850,000 cases worldwide and increasing. Several studies report outcomes of COVID-19 in predominately well persons. There are also some data on COVID-19 in persons with predominately solid cancer but controversy whether these persons have the same outcomes. We conducted a cohort study at two centres in Wuhan, China, of 128 hospitalised subjects with haematological cancers, 13 (10%) of whom developed COVID-19. We also studied 226 health care providers, 16 of whom developed COVID-19 and 11 of whom were hospitalised. Co-variates were compared with the 115 subjects with haematological cancers without COVID-19 and with 11 hospitalised health care providers with COVID-19. There were no significant differences in baseline co-variates between subjects with haematological cancers developing or not developing COVID-19. Case rates for COVID-19 in hospitalised subjects with haematological cancers was 10% (95% Confidence Interval [CI], 6, 17%) compared with 7% (4, 12%; P = 0.322) in health care providers. However, the 13 subjects with haematological cancers had more severe COVID-19 and more deaths compared with hospitalised health care providers with COVID-19. Case fatality rates were 62% (32, 85%) and 0 (0, 32%; P = 0.002). Hospitalised persons with haematological cancers have a similar case rate of COVID-19 compared with normal health care providers but have more severe disease and a higher case fatality rate. Because we were unable to identify specific risk factors for COVID-19 in hospitalised persons with haematological cancers, we suggest increased surveillance and possible protective isolation.

We studied 1859 subjects with confirmed COVID-19 from seven centers in Wuhan 1651 of whom recovered and 208 died. We interrogated diverse covariates for correlations with risk of death from COVID-19. In multi-variable Cox regression analyses increased hazards of in-hospital death were associated with several admission covariates: (1) older age (HR = 1.04; 95% Confidence Interval [CI], 1.03, 1.06 per year increase; P < 0.001); (2) smoking (HR = 1.84 [1.17, 2.92]; P = 0.009); (3) admission temperature per °C increase (HR = 1.32 [1.07, 1.64]; P = 0.009); (4) Log 10 neutrophil-to-lymphocyte ratio (NLR; HR = 3.30 [2.10, 5.19]; P < 0.001); (5) platelets per 10 E + 9/L decrease (HR = 0.996 [0.994, 0.998]; P = 0.001); ( 6) activated partial thromboplastin (aPTT) per second increase (HR = 1.04 [1.02, 1.05]; P < 0.001); (7) Log 10 D-dimer per mg/l increase (HR = 3.00 [2.17, 4.16]; P < 0.001); and (8) Log 10 serum creatinine per μmol/L increase (HR = 4.55 [2.72, 7.62]; P < 0.001). In piecewise linear regression analyses Log 10 NLR the interval from ≥0.4 to ≤1.0 was significantly associated with an increased risk of death. Our data identify covariates associated with risk of in hospital death in persons with COVID-19.

We studied admission and dynamic demographic, hematological and biochemical co-variates in 1449 hospitalized subjects with coronavirus infectious disease-2019 (COVID-19) in five hospitals in Wuhan, Hubei province, China. We identified two admission co-variates: age (Odds Ratio [OR] = 1.18, 95% Confidence Interval [CI] [1.02, 1.36]; P = 0.026) and baseline D-dimer (OR = 3.18 [1.48, 6.82]; P = 0.003) correlated with an increased risk of death in persons with COVID-19. We also found dynamic changes in four co-variates, Δ fibrinogen (OR = 6. 45 [1.31, 31.69]; P = 0.022), Δ platelets (OR = 0.95 [0.90-0.99]; P = 0.029), Δ C-reactive protein (CRP) (OR = 1.09 [1.01, 1.18]; P = 0.037), and Δ lactate dehydrogenase (LDH) (OR = 1.03 [1.01, 1.06]; P = 0.007) correlated with an increased risk of death. The potential risk factors of old age, high baseline D-dimer, and dynamic co-variates of fibrinogen, platelets, CRP, and LDH could help clinicians to identify and treat subjects with poor prognosis. data of hematological abnormalities in persons with . We studied hematological co-variates in 1449 hospitalized persons with COVID-19 in five hospitals in Wuhan, China, interrogating correlations of admission parameters with COVID-19 outcomes. Methods Study design and subjectsWe studied subjects in seven centers of five hospitals of