危重症甲型H1N1流感临床初期危险因素的早期快速识别探讨

Recognition of early risky factors in patients suffering from critical influenza A H1N1

目的 探讨提高临床急诊医师对甲型H1N1流感危重症病例的快速识别能力.方法 回顾性分析65例甲型H1N1流感重症病例初期的临床特征,采用成组比较的病例对照研究方法,通过单因素分析筛选及多因素Logistic回归分析确定危重症病例发生的高危因素;拟定预测危重病例发生的预测重症甲型H1N1流感评分系统（PCIS）并进行拟合优度检验.结果 65例甲型H1N1流感重症病例中危重症（22例）和重症（43例）两组年龄、合并1个以上基础疾病、存在慢性心血管疾病、合并肿瘤性疾病、咯痰、肌肉或关节酸痛、呼吸困难、入院时脉搏血氧饱和度（SpO2）8个因素比较差异均有统计学意义.多因素Logistic回归分析显示,合并1个以上基础疾病[相对比值比（OR）=7.611,95%可信区间（95%CI）1.635～35.429]、肌肉或关节酸痛（OR=7.523,95%CI 1.462～38.716）、呼吸困难（OR=11.090,95%CI 1.373～89.565）、入院时SpO2＜0.95（OR=8.088,95%CI 1.019～84.969）是发生危重症的独立危险因素（均P＜0.05）;受试者工作特征曲线（ROC）下面积（AUC）为0.922（95%CI 0.860～0.985,P=0.000）.PCIS分级（低危0～1分、中危2分、高危3分、极高危≥4分）与实际危重病例吻合度良好,判定系数（R2）为0.940 6,P=0.030 1.结论 急诊临床医师可以根据基础疾病的多少、有无肌肉或关节酸痛、呼吸困难、入院时SpO2水平的综合评分（PCIS）早期快速识别易发生危重症甲型H1N1流感患者.

Objective To investigate clinical risky factors and improve the ability to discover critically ill patients suffering from influenza A H1N1 in emergency department. Methods A retrospective study of 65 cases with severe influenza A H1N1 was conducted. Univariate analysis and multivariate Logistic regression analysis were used to identify independent predictors of critically ill cases. Goodness of Fit test was performed on an established clinical predicting scoring （prediction of critically ill with influenza score,PCIS） system. Results Univariate analysis showed that significant difference between critically ill and severe group consisted of eight factors including age distribution, more than one comorbidity, chronic cardiovascular disease, oncologic diseases, sputum, myalgia/arthralgia, dyspnea and oxygen saturation at admission. A multivariate Logistic regression showed an association between development of critical illness and more than one comorbidity [odds ratio （OR） = 7. 611, 95% confidence interval （95%CI） 1. 635 -35. 429], myalgia/arthralgia （OR=7. 523, 95%CI 1.462 - 38. 716）, dyspnea （OR= 11. 090, 95%CI 1. 373 -89. 565）, and oxygen saturation〈0. 95 at admission （OR=8. 088, 95%CI 1. 019 - 84. 969, all P〈0. 05）.The prognostic criteria had a good discriminative ability [area under receiver operating characteristic curve （AUC） was 0. 922, 95 %CI 0. 860 - 0. 985, P = 0. 000]. The PCIS scoring system was established according to the level of four high risk factors. Low risk （PCIS 0 - 1）, intermediate risk （PCIS 2）, high risk （PCIS 3）, and very high risk （PCIS≥4） were categorized for predicting the occurrence of critical illness, and the Goodness of Fit test was good （R2= 0. 940 6, P = 0. 030 1）. Conclusion Emergency physician can predict the development of critical condition in patients with influenza A H1N1 by using clinical characteristics including comorbidity, myalgia/arthralgia, dyspnea, and oxygen saturation at admission, and it is helpful in making clinical decision.