Abstract

Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries. Early finding of this pneumonia from huge numbers of suspects gives clinicians a big challenge. The aim of the study was to develop a rapid screening model for early predicting NCP in a Zhejiang population, as well as its utility in other areas. A total of 880 participants who were initially suspected of NCP from January 17 to February 19 were included. Potential predictors were selected via stepwise logistic regression analysis. The model was established based on epidemiological features, clinical manifestations, white blood cell count, and pulmonary imaging changes, with the area under receiver operating characteristic (AUROC) curve of 0.920. At a cut-off value of 1.0, the model could determine NCP with a sensitivity of 85% and a specificity of 82.3%. We further developed a simplified model by combining the geographical regions and rounding the coefficients, with the AUROC of 0.909, as well as a model without epidemiological factors with the AUROC of 0.859. The study demonstrated that the screening model was a helpful and cost-effective tool for early predicting NCP and had great clinical significance given the high activity of NCP.

Highlights

  • Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries

  • To detect 2019-nCoV by the accurate real-time reverse transcription polymerase chain amplification (RT-PCR) assessment has been regarded as the golden diagnostic ­standard[9]

  • Of the 880 subjects enrolled in the study, 21 subjects were excluded due to missing data, and 859 participants were eligible for evaluation

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Summary

Introduction

Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries Finding of this pneumonia from huge numbers of suspects gives clinicians a big challenge. The aim of the study was to develop a rapid screening model for early predicting NCP in a Zhejiang population, as well as its utility in other areas. The time-consuming process, short supply of kits, and difficulty in qualified sampling prevented us from early-stage diagnosis and treatment, as well as prompt isolation of patients. It necessitates establishment of a rapid diagnostic model to screen high-risk patients with 2019-nCoV infection

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