Nomogram to predict risk of developing severe COVID-19 pneumonia: a multicenter study from Wuhan and Guangdong, China. DOI: https://doi.org/10.1101/2020.03.17.20037515
To which patients does this tool apply?
Patients with a confirmed case of COVID-19, defined as an individual with laboratory confirmation of SARS-CoV-2 RNA, irrespective of clinical signs and symptoms.
What information will you need?
Age and serological indicators (serum lactate dehydrogenase, C-reactive protein, the coefficient of variation of red blood cell distribution width (RDW), blood urea nitrogen, albumin, direct bilirubin).
How was this tool developed?
A total of 372 COVID-19 patients (189 for training) were enrolled after admission from three centers in Guangzhou and Wuhan. All patients with non-severe COVID-19 during hospitalization were followed for more than 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and patients who kept non-severe state were assigned to the severe and non-severe group, respectively. For diagnosis of severe COVID-19 group, at least one of the following conditions should be met: (1) Shortness of breath, Respiratory rate (RR) ≥ 30 times/min, (2) Arterial oxygen saturation (Resting status) ≤ 93%, or (3) the ratio of Partial pressure of oxygen to Fraction of inspiration O-2 (PaO-2/FiO-2) ≤ 300 mm Hg. Among all cases, 72 (19%) patients developed severe COVID-19. LASSO was used for feature selection; features were combined into a multivariable logistic regression model. In validation cohort, AUC was 0.853 [0.790-0.916] with a sensitivity of 77.5 % and specificity of 78.4%. RDW plays an important role in predicting severe COVID-19, implying that the role of RBC in severe disease is underestimated.