重症流感患者致死性结局的相关因素

Prilozi Pub Date : 2016-11-01 DOI:10.1515/prilozi-2016-0018
M. Cvetanovska, Zvonko Milenkovik, Valerija Kirova Uroshevik, I. Demiri, V. Cvetanovski
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引用次数: 4

摘要

摘要简介:流感的临床表现从较轻的自限性呼吸道感染到严重的临床表现,发病率和死亡率都很高。了解流感致命后果的预测指标,对于及时、准确地决定适当的治疗具有特别重要的意义。本研究的目的是确定导致致命结果的严重流感患者的因素。材料与方法:本研究为前瞻性组比较,于2012年1月1日至2015年1月1日在马其顿共和国斯科普里大学传染病诊所进行。该研究包括患有严重流感的成年患者,他们被进一步分为存活患者组和死亡患者组。所有纳入研究的患者在入院时均记录了人口学、临床和生化数据。单变量分析中显示结果有显著差异的变量被用于创建结果的多变量逻辑和回归分析作为依赖因素。使用逻辑回归确定了严重流感病例致死性结局的独立预测因子。结果:该研究包括87例临床和实验室确诊的严重流感患者。患者分为存活组(n = 75)和死亡组(n = 75)。总死亡率为13.79%。入院时进行的多因素分析确定心血管合并症(p = 0.014)、尿素值高于8.3 U/L (p = 0.045)和SAPS评分(p = 0.048)是重症流感患者预后的独立预测因子。合并心血管疾病的流感患者死于流感的风险是无流感病史的流感患者的2.024倍(OR = 2.024, 95% CI 1.842-17.337)。血清尿素高于8.3 U/L患者的死亡几率是正常者的1.89倍(OR = 1.89, 95% CI 1.091 ~ 11.432)。SAPS评分每增加1分,流感患者的死亡机会增加1.2% (OR = 1.12 95% CI 1.01-2.976)。ROC分析表明,心血管疾病、尿素值升高和SAPS评分联合作为致命结局的良好预后模型。该预测模型预测致命结果的整体真实性为80%,敏感性为82%,特异性为70%。结论:心血管疾病、尿素升高超过8.3 mmol/l和SAPS评分是预测重症流感致死结局的独立指标。早期确定严重流感患者的预后预测因素将有助于实施适当的医疗,并有助于降低严重流感患者的死亡率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Associated with Lethal Outcome in Patients with Severe Form of Influenza
Abstract Introduction: Clinical manifestations of influenza range from relatively mild and self-limiting respiratory infections to severe clinical manifestations with significant morbidity and mortality. The awareness of predictive indicators for the lethal outcome of influenza is of particular significance in making timely and exact decision for adequate treatment. The aim of this study was to identify the factors in patients with a severe form of influenza, resulting in lethal outcome. Materials and methods: The investigation was a prospective group comparison conducted at the University Clinic for Infectious Diseases in Skopje, R. Macedonia in the period from January 01, 2012 to January 01, 2015. The study included adult patients with a severe form of influenza who were further categorized into a group of either survived patients or a group of deceased patients. Demographic, clinical and biochemical data were noted in all patients included in the study on admission. The variables of the univariate analysis that showed a significant difference in terms of the outcome were used for creating multivariate logistic and regression analysis of the outcome as dependent factors. The independent predictors for lethal outcome in severe cases of influenza were identified by using logistic regression. Results: The study included 87 patients with a severe form of clinical and laboratory confirmed influenza. The patients were divided in two groups: survived (n = 75) and deceased (n = 75). The overall mortality was 13.79%. Multivariate analysis conducted on admission to hospital identified cardiovascular comorbid diseases (p = 0.014), urea values higher than 8.3 U/L (p = 0.045) and SAPS score (p = 0.048) as independent predictors of the outcome in patients with severe form of influenza. Influenza patients with cardiovascular diseases had 2.024 times greater risk of death from influenza in comparison to the patients having influenza without history of such a disease (OR = 2.024 95% CI 1.842–17.337). Patients with serum urea values higher than 8.3 U/L had 1.89 times higher chance of death compared to patients with normal values (OR = 1.89 95% CI 1.091–11.432). The increase of the SAPS score in one point increased the chance of death in patients with influenza by 1.2% (OR = 1.12 95% CI 1.01–2.976). The ROC analysis indicated that cardiovascular diseases, increased urea values and SAPS score in combination act as a good prognostic model for the fatal outcome. The global authenticity of this predictive model to foresee lethal outcome amounts to 80%, sensitivity being 82%, and specificity 70%. Conclusion: Cardiovascular diseases, increased values of urea over 8.3 mmol/l and SAPS score are independent predictive indicators for lethal outcome in severe influenza. Early identification of the outcome predictors in patients with severe influenza will allow implementation of adequate medical treatment and will contribute to decreasing of mortality in patients with severe form of influenza.
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