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用于识别因感染 2009 年大流行甲型 H1N1 流感住院的成年患者中重症病例的预测规则。

A prediction rule to identify severe cases among adult patients hospitalized with pandemic influenza A (H1N1) 2009.

机构信息

Department of Internal Medicine, Kangwon National University School of Medicine, Chucheon, Korea.

出版信息

J Korean Med Sci. 2011 Apr;26(4):499-506. doi: 10.3346/jkms.2011.26.4.499. Epub 2011 Mar 28.

Abstract

The purpose of this study was to establish a prediction rule for severe illness in adult patients hospitalized with pandemic influenza A (H1N1) 2009. At the time of initial presentation, the baseline characteristics of those with severe illness (i.e., admission to intensive care unit, mechanical ventilation, or death) were compared to those of patients with non-severe illnesses. A total of 709 adults hospitalized with pandemic influenza A (H1N1) 2009 were included: 75 severe and 634 non-severe cases. The multivariate analysis demonstrated that altered mental status, hypoxia (PaO(2)/FiO(2) ≤ 250), bilateral lung infiltration, and old age (≥ 65 yr) were independent risk factors for severe cases (all P < 0.001). The area under the ROC curve (0.834 [95% CI, 0.778-0.890]) of the number of risk factors were not significantly different with that of APACHE II score (0.840 [95% CI, 0.790-0.891]) (P = 0.496). The presence of ≥ 2 risk factors had a higher sensitivity, specificity, positive predictive value and negative predictive value than an APACHE II score of ≥ 13. As a prediction rule, the presence of ≥ 2 these risk factors is a powerful and easy-to-use predictor of the severity in adult patients hospitalized with pandemic influenza A (H1N1) 2009.

摘要

本研究旨在建立一个预测成人甲型 H1N1 大流行流感住院患者严重疾病的规则。在初始表现时,将严重疾病患者(即入住重症监护病房、机械通气或死亡)的基线特征与非严重疾病患者进行比较。共纳入 709 例甲型 H1N1 大流行流感住院成人患者:75 例严重病例和 634 例非严重病例。多变量分析表明,意识改变、缺氧(PaO2/FiO2≤250)、双侧肺部浸润和高龄(≥65 岁)是严重病例的独立危险因素(均 P<0.001)。风险因素数量的 ROC 曲线下面积(0.834 [95%CI,0.778-0.890])与 APACHE II 评分(0.840 [95%CI,0.790-0.891])(P=0.496)无显著差异。存在≥2 个危险因素的患者的敏感性、特异性、阳性预测值和阴性预测值均高于 APACHE II 评分≥13 分。作为预测规则,存在≥2 个这些危险因素是成人甲型 H1N1 大流行流感住院患者严重程度的有力且易于使用的预测指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c588/3069568/f571a759057f/jkms-26-499-g001.jpg

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