The mNCP-SPI Score Predicting Risk of Severe COVID-19 among Mild-Pneumonia Patients on Admission

Infect Drug Resist. 2020 Oct 14:13:3593-3600. doi: 10.2147/IDR.S263157. eCollection 2020.

Abstract

Purpose: To predict the risk of developing severe pneumonia among mild novel coronavirus pneumonia (mNCP) patients on admission.

Methods: A retrospective cohort study was conducted at three hospitals in Shanghai and Wuhan from January 2020 to February 2020. Real-time polymerasechain-reaction assays were used to detect COVID-19. A total of 529 patients diagnosed with NCP were recruited from three hospitals and classified by four severity types during hospitalization following the standards of the Chinese Diagnosis and Treatment of Pneumonia Caused by New Coronavirus Infection (eighth version). Patients were excluded if admitted by ICU on admission (n=92, on a general ward while meeting the condition of severe or critical type on admission (n=25), or there was insufficient clinical information (n=64). In sum, 348 patients with mNCP were finally included, and 68 developed severe pneumonia.

Results: mNCP severity prognostic index values were calculated based on multivariate logistic regression: history of diabetes (OR 2.064, 95% CI 1.010-4.683; p=0.043), time from symptom onset to admission ≥7 days (OR 1.945, 95% CI 1.054-3.587; p=0.033), lymphocyte count ≤0.8 (OR 1.816, 95% CI 1.008-3.274; p=0.047), myoglobin ≥90 mg/L (OR 2.496, 95% CI 1.235-5.047; p=0.011), and D-dimer ≥0.5 mg/L (OR 2.740, 95% CI 1.395-5.380; p=0.003). This model showed a c-statistics of 0.747, with sensitivity and specificity 0.764 and 0.644, respectively, under cutoff of 165.

Conclusion: We designed a clinical predictive tool for risk of severe pneumonia among mNCP patients to provided guidance for medicines. Further studies are required for external validation.

Keywords: novel coronavirus pneumonia; predicting score; severe pneumonia.

Grants and funding

The funders had no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. This work was supported by the National Key R&D Program of China (2017YFC1309700 and 2017YFC1309701), Shanghai Shenkang Hospital Development Center Clinical Science and Technology Innovation Project (SHDC12018102), Shanghai Key Discipline for Respiratory Diseases (2017ZZ02014), and the Clinical NCP Focused Research Program (Translational Medicine Funding of Shanghai Jiao Tong University). This work was also funded in part by a grant from the Innovative Research Team from of high-level local universitiesin Shanghai and by the Institute of Respiratory Disease, School of Medicine, Shanghai Jiao Tong University.