npj Primary Care Respiratory Medicine (Jun 2021)

A predictive score for progression of COVID-19 in hospitalized persons: a cohort study

  • Jingbo Xu,
  • Weida Wang,
  • Honghui Ye,
  • Wenzheng Pang,
  • Pengfei Pang,
  • Meiwen Tang,
  • Feng Xie,
  • Zhitao Li,
  • Bixiang Li,
  • Anqi Liang,
  • Juan Zhuang,
  • Jing Yang,
  • Chunyu Zhang,
  • Jiangnan Ren,
  • Lin Tian,
  • Zhonghe Li,
  • Jinyu Xia,
  • Robert P. Gale,
  • Hong Shan,
  • Yang Liang

DOI
https://doi.org/10.1038/s41533-021-00244-w
Journal volume & issue
Vol. 31, no. 1
pp. 1 – 6

Abstract

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Abstract Accurate prediction of the risk of progression of coronavirus disease (COVID-19) is needed at the time of hospitalization. Logistic regression analyses are used to interrogate clinical and laboratory co-variates from every hospital admission from an area of 2 million people with sporadic cases. From a total of 98 subjects, 3 were severe COVID-19 on admission. From the remaining subjects, 24 developed severe/critical symptoms. The predictive model includes four co-variates: age (>60 years; odds ratio [OR] = 12 [2.3, 62]); blood oxygen saturation (5.75 mg/L; OR = 9.3 [1.5, 58]); and prothrombin time (>12.3 s; OR = 6.7 [1.1, 41]). Cutoff value is two factors, and the sensitivity and specificity are 96% and 78% respectively. The area under the receiver-operator characteristic curve is 0.937. This model is suitable in predicting which unselected newly hospitalized persons are at-risk to develop severe/critical COVID-19.