Department of Respiratory Medicine, Tokyo Medical and Dental University, 1-5-45, Yushima, Bunkyo-ku, Tokyo, 113-8519, Japan.
Trauma and Acute Critical Care Center, Tokyo Medical and Dental University, 1-5-45, Yushima, Bunkyo-ku, Tokyo, 113-8519, Japan.
J Infect Chemother. 2021 Feb;27(2):284-290. doi: 10.1016/j.jiac.2020.10.013. Epub 2020 Oct 13.
The prediction of COVID-19 disease behavior in the early phase of infection is challenging but urgently needed. MuLBSTA score is a scoring system that predicts the mortality of viral pneumonia induced by a variety of viruses, including coronavirus, but the scoring system has not been verified in novel coronavirus pneumonia. The aim of this study was to validate this scoring system for estimating the risk of disease worsening in patients with COVID-19.
This study included the patients who were treated between April 1 st and March 13 th , 2020. The patients were classified into mild, moderate, and severe groups according to the extent of respiratory failure. MuLBSTA score was applied to estimate the risk of disease worsening in each severity group and we validated the utility of the scoring system.
A total of 72 patients were analyzed. Among the 46 patients with mild disease, 17 showed disease progression to moderate or severe disease after admission. The model showed a sensitivity of 100% and a specificity of only 34.5% with a cut-off value of 5 points. Among the 55 patients with mild or moderate disease, 6 deteriorated to severe disease, and the model showed a sensitivity of 83.3% and a specificity of 71.4% with a cut-off value of 11 points.
This study showed that MuLBSTA score is a potentially useful tool for predicting COVID-19 disease behavior. This scoring system may be used as one of the criteria to identify high-risk patients worsening to life-threatening status.
预测新冠病毒感染早期的疾病行为具有挑战性，但又非常迫切需要。MuLBSTA 评分是一种预测多种病毒引起的病毒性肺炎死亡率的评分系统，包括冠状病毒，但该评分系统尚未在新型冠状病毒肺炎中得到验证。本研究旨在验证该评分系统在评估 COVID-19 患者疾病恶化风险中的作用。
本研究纳入了 2020 年 4 月 1 日至 3 月 13 日期间接受治疗的患者。根据呼吸衰竭程度将患者分为轻症、中度和重症三组。应用 MuLBSTA 评分评估各严重程度组疾病恶化的风险，并验证该评分系统的实用性。
共分析了 72 例患者。46 例轻症患者中，有 17 例在入院后病情进展为中重度。该模型的敏感性为 100%，特异性仅为 34.5%，截断值为 5 分。55 例轻症或中度患者中，有 6 例病情恶化至重症，模型的敏感性为 83.3%，特异性为 71.4%，截断值为 11 分。
本研究表明，MuLBSTA 评分是一种预测 COVID-19 疾病行为的潜在有用工具。该评分系统可作为识别病情恶化至危及生命状态的高危患者的标准之一。
