应用临床评分预测Covid-19患者重症监护住院率和死亡率

Simone Zanella, Mancosu Alena, Brugnolli Anna, Franceschi Francesco, Carrara Alessandro, C. Ramponi, Bevilacqua Anita, Marinelli Elisa, Ricci Nicola, F. Buccelletti
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摘要

简介:SARS-Cov2全球大流行迄今已造成2.7亿例病例和500万人死亡。对于到达急诊科的Covid-19患者,有许多临床评分,许多前瞻性和回顾性研究已经证明了它们的有效性。在文献中,没有进行任何研究和荟萃分析来评估重症监护病房(ICU)的入院率和死亡率,并建立可使用的最佳评分。材料与方法:调查关键词为临床评分、风险分层、患者、急诊科。最终选定的文章完全是在PubMed数据库中找到的。在我们的荟萃分析中,我们评估了研究Covid-19疾病患者获得的分数,以及临床实践中已知并随后用于Covid大流行的分数。计算各评分的敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)、诊断准确性、受试者工作特征(ROC)曲线和曲线下面积(AUC)。我们评估了meta分析所涵盖的所有研究的同质性,最后我们创建了一个漏斗图来比较分数。结果:共纳入8项研究,其中回顾性观察性研究5项,前瞻性研究3项。当考虑元分析时,最高的LR + 9.1(4.76 - 17.5)指的是NEWS。在考虑ICU入院和死亡率时,参考NEWS的AUC值分别为0.9(0.9 - 1.00)和0.9(0.72 - 1.00)。重症监护和死亡率的LR +、AUC值分别为3.3(2.4-4.3)、0.8(0.72-0.88)和0.8(0.72-0.88)。评价固定效果,q-SOFA的LR +值为2.816。死亡率的AUC值为0.8(0.76 ~ 0.85),重症监护入院的AUC值为0.8(0.64 ~ 0.93)。讨论:NEWS和NEWS2是预测死亡率和ICU入院最有效的临床评分,可能在疾病的第一阶段更实用,因为患者在家并且监测是自我管理的。
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The Use of Clinical Scores to Predict Intensive Care Admission and Mortality in Patients with Covid-19 Disease
Introduction: The SARS-Cov2 pandemic worldwide has to date caused 270,000,000 cases and 5,000,000 deaths. Many clinical scores are available for patients who arrive at the Emergency Department with Covid-19 disease and many studies carried out prospectively and retrospectively have demonstrated their effectiveness. In literature no study and no meta-analysis have been performed to evaluate the admission to intensive care unit (ICU) and mortality rates and to establish the best score to be used. Materials and Methods: The keywords used for the investigation were clinical scores, risk stratifications, Covid patients and Emergency Department. Ultimately the selected articles were entirely found using the PubMed database. In our meta-analysis we evaluated scores obtained studying patients with Covid-19 disease and also scores already known in clinical practice and subsequently used in Covid pandemic. Sensitivity, specificity, positive (PPV) and negative predicting value (NPV), diagnostic accuracy, the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) were calculated for each score. We assessed the homogeneity of all studies covered by our meta-analysis and at the end we created a Funnel Plot diagram in order to compare the scores. Results: A total of 8 studies, 5 retrospective observational and 3 prospective, were analyzed. When considering meta-analyzes the highest value, LR + 9.1 (4.76 - 17.5), refers to NEWS. When considering ICU admission and mortality, the AUC values referring to NEWS are 0.9 (0.9 - 1.00) and 0.9 (0.72 - 1.00) respectively. The LR +, AUC values for intensive care and mortality are 3.3 (2.4-4.3), 0.8 (0.72-0.88) and 0.8 (0.72-0.88) for NEWS2. Evaluating the fixed effect, the LR + value of q-SOFA is 2.816. The AUC value is 0.8 (0.76 - 0.85) for mortality and 0.8 (0.64 - 0.93) for intensive care admission. Discussions: NEWS and NEWS2 are the most effective clinical scores to predict mortality and admission to ICU and are probably more practical during the first phase of the disease when the patient is at home and monitoring is self-managed.
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