BMC Infectious Diseases (Apr 2021)

Development and validation of a simple-to-use nomogram to predict the deterioration and survival of patients with COVID-19

  • Zhiyong Zeng,
  • Chaohui Wu,
  • Zhenlv Lin,
  • Yong Ye,
  • Shaodan Feng,
  • Yingying Fang,
  • Yanmei Huang,
  • Minhua Li,
  • Debing Du,
  • Gongping Chen,
  • Dezhi Kang

DOI
https://doi.org/10.1186/s12879-021-06065-z
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 10

Abstract

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Abstract Background COVID-19 pandemic has forced physicians to quickly determine the patient’s condition and choose treatment strategies. This study aimed to build and validate a simple tool that can quickly predict the deterioration and survival of COVID-19 patients. Methods A total of 351 COVID-19 patients admitted to the Third People’s Hospital of Yichang between 9 January to 25 March 2020 were retrospectively analyzed. Patients were randomly grouped into training (n = 246) or a validation (n = 105) dataset. Risk factors associated with deterioration were identified using univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression. The factors were then incorporated into the nomogram. Kaplan-Meier analysis was used to compare the survival of patients between the low- and high-risk groups divided by the cut-off point. Results The least absolute shrinkage and selection operator (LASSO) regression was used to construct the nomogram via four parameters (white blood cells, C-reactive protein, lymphocyte≥0.8 × 109/L, and lactate dehydrogenase ≥400 U/L). The nomogram showed good discriminative performance with the area under the receiver operating characteristic (AUROC) of 0.945 (95% confidence interval: 0.91–0.98), and good calibration (P = 0.539). Besides, the nomogram showed good discrimination performance and good calibration in the validation and total cohorts (AUROC = 0.979 and AUROC = 0.954, respectively). Decision curve analysis demonstrated that the model had clinical application value. Kaplan-Meier analysis illustrated that low-risk patients had a significantly higher 8-week survival rate than those in the high-risk group (100% vs 71.41% and P < 0.0001). Conclusion A simple-to-use nomogram with excellent performance in predicting deterioration risk and survival of COVID-19 patients was developed and validated. However, it is necessary to verify this nomogram using a large-scale multicenter study.

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