Nomogram for prediction of fatal outcome in patients with severe COVID-19: a multicenter study

Yun Yang1,2, Xiao-Fei Zhu2,3, Jian Huang1

  • 1The Third Affiliated Hospital of Second Military Medical University, 225 Changhai Road, Shanghai, 200438, China.

Insights

This study developed a nomogram to predict fatal outcomes in severe COVID-19 patients. Key risk factors include age, rapid breathing, low lymphocyte count, and high interleukin-6 levels, aiding clinical decision-making.

Area of Science:

  • Medical research
  • Infectious diseases
  • Critical care medicine

Background:

  • Severe coronavirus disease 2019 (COVID-19) poses a significant threat, necessitating accurate prediction of patient outcomes.
  • Effective models are crucial for identifying high-risk individuals and optimizing treatment strategies.

Purpose of the Study:

  • To develop and validate a predictive model for fatal outcomes in severe COVID-19 patients.
  • To identify independent high-risk factors associated with mortality in severe COVID-19.

Main Methods:

  • A cohort of 2541 COVID-19 patients was analyzed, with a focus on severe cases.
  • Multivariate Cox proportional hazard models were used to identify risk factors.
  • A prognostic nomogram was constructed and validated using independent cohorts.

Main Results:

  • Age ≥ 70 years, panting (respiratory rate ≥ 30/min), lymphocyte count < 1.0 × 109/L, and interleukin-6 (IL-6) > 10 pg/ml were identified as independent predictors of death.
  • The nomogram demonstrated high predictive accuracy (AUCs ranging from 0.811 to 0.900) across training and validation cohorts.
  • Tocilizumab showed a potential trend towards improved prognosis in severe COVID-19 patients with high IL-6 levels, though not statistically significant.

Conclusions:

  • The developed nomogram serves as a valuable tool for clinicians to identify severe COVID-19 patients at high risk of mortality.
  • The findings support the potential benefit of tocilizumab in managing severe COVID-19 cases with elevated IL-6.
  • Early identification and targeted interventions can potentially reduce mortality rates in severe COVID-19.
Abstract

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