不同时点序贯器官衰竭评估评分对重症医学科患者院内死亡的预测价值比较
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摘要
目的比较不同时点序贯器官衰竭评估(SOFA)评分对重症医学科(ICU)患者院内死亡的预测价值,以期为实际临床工作中合理选用SOFA评分指标提供一定的研究证据。方法从美国重症监护数据库中选择住院时间> 72 h的成年ICU患者,提取其基本信息与相关检验指标并计算不同时点SOFA评分,以院内死亡为结局指标,采用多因素Logistic回归分析不同时点SOFA评分与院内死亡的关联,绘制受试者工作特征(ROC)曲线并计算曲线下面积(AUC)以评价各指标的预后预测价值。结果共有11 968例患者纳入最终分析,其中男性患者占56.15%,平均年龄为(64.75±16.63)岁,院内病死率为10.41%(1246/11 968)。多因素Logistic回归分析显示不同时点SOFA评分均与院内死亡密切相关(P均<0.0001),ROC曲线分析显示不同时点SOFA评分预测院内死亡的能力存在差异,以T72最高(AUC=0.7246,95%CI:0.7101～0.7391)。结论对于住院时间>72 h的成年ICU患者,入院后72 h的SOFA评分可能具有更好的预后预测价值。
Objective To compare the predictive value of sequential organ failure assessment(SOFA) scores at different time points for hospital mortality of patients in intensive care unit(ICU) and to provide research evidence for the rational selection of SOFA scores in actual clinical work. Methods Adult ICU patients with a length of hospital stay greater than 72 h were included from the American Critical Care Database. The basic information and related indicators were extracted and SOFA scores at different time points were calculated. Hospital mortality was chosen as the outcome and multivariable logistic regression analysis was performed to assess the associations between SOFA scores at different time points and the outcome. ROC curve analysis was also conducted and the area under the curve was calculated to evaluate their prognostic value. Results A total of 11 968 patients were included finally, of which male patients accounted for 56.15%with an average age of(64.75±16.63) years old and a hospital mortality rate of 10.41%(1246/11 968).Multivariable logistic regression analysis showed that SOFA scores at different time points were all closely related to hospital mortality(P < 0.0001). ROC curve analysis showed that SOFA scores at different time points had different predictive value for hospital mortality and T72(AUC=0.7246, 95%CI: 0.7101-0.7391)had the highest AUC. Conclusion For adult ICU patients whose length of hospital stay is greater than 72 h,SOFA scores at 72 h after admission may have better prognostic value.
Objective To compare the predictive value of sequential organ failure assessment(SOFA) scores at different time points for hospital mortality of patients in intensive care unit(ICU) and to provide research evidence for the rational selection of SOFA scores in actual clinical work. Methods Adult ICU patients with a length of hospital stay greater than 72 h were included from the American Critical Care Database. The basic information and related indicators were extracted and SOFA scores at different time points were calculated. Hospital mortality was chosen as the outcome and multivariable logistic regression analysis was performed to assess the associations between SOFA scores at different time points and the outcome. ROC curve analysis was also conducted and the area under the curve was calculated to evaluate their prognostic value. Results A total of 11 968 patients were included finally, of which male patients accounted for 56.15%with an average age of(64.75±16.63) years old and a hospital mortality rate of 10.41%(1246/11 968).Multivariable logistic regression analysis showed that SOFA scores at different time points were all closely related to hospital mortality(P < 0.0001). ROC curve analysis showed that SOFA scores at different time points had different predictive value for hospital mortality and T72(AUC=0.7246, 95%CI: 0.7101-0.7391)had the highest AUC. Conclusion For adult ICU patients whose length of hospital stay is greater than 72 h,SOFA scores at 72 h after admission may have better prognostic value.
引文
1 Vincent JL,Moreno R,Takala J,et al.The SOFA(Sepsis-related Organ Failure Assessment)score to describe organ dysfunction/failure.On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine[J].Intensive Care Med,1996,22(7):707-710.
2 Vincent JL,de Mendonca A,Cantraine F,et al.Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units:results of a multicenter,prospective study.Working group on″sepsis-related problems″of the European Society of Intensive Care Medicine[J].Crit Care Med,1998,26(11):1793-1800.
3 Ferreira FL,Bota DP,Bross A,et al.Serial evaluation of the SOFAscore to predict outcome in critically ill patients[J].JAMA,2001,286(14):1754-1758.
4 Jones AE,Trzeciak S,Kline JA.The Sequential Organ Failure Assessment score for predicting outcome in patients with severe sepsis and evidence of hypoperfusion at the time of emergency department presentation[J].Crit Care Med,2009,37(5):1649-1654.
5 Singer M,Deutschman CS,Seymour CW,et al.The Third International Consensus Definitions for Sepsis and Septic Shock(Sepsis-3)[J].JAMA,2016,315(8):801-810.
6 Johnson AE,Pollard TJ,Shen L,et al.MIMIC-Ⅲ,a freely accessible critical care database[J].Sci Data,2016,3:160035.
7陈静,李保萍.MIMIC-Ⅲ电子病历数据集及其挖掘研究[J].信息资源管理学报,2017,7(4):29-37.
8 Johnson AE,Stone DJ,Celi LA,et al.The MIMIC Code Repository:enabling reproducibility in critical care research[J].J Am Med Inform Assoc,2018,25(1):32-39.
9 Thompson NR,Fan Y,Dalton JE,et al.A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality[J].Med Care,2015,53(4):374-379.
10 Faber J,Fonseca LM.How sample size influences research outcomes[J].Dental Press J Orthod,2014,19(4):27-29.
11 Power GS,Harrison DA.Why try to predict ICU outcomes?[J].Curr Opin Crit Care,2014,20(5):544-549.
12 Salluh JI,Soares M.ICU severity of illness scores:APACHE,SAPSand MPM[J].Curr Opin Crit Care,2014,20(5):557-565.
13 Francois B,Clavel M,Vignon P,et al.Perspective on optimizing clinical trials in critical care:how to puzzle out recurrent failures[J].J Intensive Care,2016,4:67.
14 Johnson AE,Kramer AA,Clifford GD.A new severity of illness scale using a subset of Acute Physiology and Chronic Health Evaluation data elements shows comparable predictive accuracy[J].Crit Care Med,2013,41(7):1711-1718.
15 Sanchez-Pinto LN,Luo Y,Churpek MM.Big data and data science in critical care[J].Chest,2018,154(5):1239-1248.
2 Vincent JL,de Mendonca A,Cantraine F,et al.Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units:results of a multicenter,prospective study.Working group on″sepsis-related problems″of the European Society of Intensive Care Medicine[J].Crit Care Med,1998,26(11):1793-1800.
3 Ferreira FL,Bota DP,Bross A,et al.Serial evaluation of the SOFAscore to predict outcome in critically ill patients[J].JAMA,2001,286(14):1754-1758.
4 Jones AE,Trzeciak S,Kline JA.The Sequential Organ Failure Assessment score for predicting outcome in patients with severe sepsis and evidence of hypoperfusion at the time of emergency department presentation[J].Crit Care Med,2009,37(5):1649-1654.
5 Singer M,Deutschman CS,Seymour CW,et al.The Third International Consensus Definitions for Sepsis and Septic Shock(Sepsis-3)[J].JAMA,2016,315(8):801-810.
6 Johnson AE,Pollard TJ,Shen L,et al.MIMIC-Ⅲ,a freely accessible critical care database[J].Sci Data,2016,3:160035.
7陈静,李保萍.MIMIC-Ⅲ电子病历数据集及其挖掘研究[J].信息资源管理学报,2017,7(4):29-37.
8 Johnson AE,Stone DJ,Celi LA,et al.The MIMIC Code Repository:enabling reproducibility in critical care research[J].J Am Med Inform Assoc,2018,25(1):32-39.
9 Thompson NR,Fan Y,Dalton JE,et al.A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality[J].Med Care,2015,53(4):374-379.
10 Faber J,Fonseca LM.How sample size influences research outcomes[J].Dental Press J Orthod,2014,19(4):27-29.
11 Power GS,Harrison DA.Why try to predict ICU outcomes?[J].Curr Opin Crit Care,2014,20(5):544-549.
12 Salluh JI,Soares M.ICU severity of illness scores:APACHE,SAPSand MPM[J].Curr Opin Crit Care,2014,20(5):557-565.
13 Francois B,Clavel M,Vignon P,et al.Perspective on optimizing clinical trials in critical care:how to puzzle out recurrent failures[J].J Intensive Care,2016,4:67.
14 Johnson AE,Kramer AA,Clifford GD.A new severity of illness scale using a subset of Acute Physiology and Chronic Health Evaluation data elements shows comparable predictive accuracy[J].Crit Care Med,2013,41(7):1711-1718.
15 Sanchez-Pinto LN,Luo Y,Churpek MM.Big data and data science in critical care[J].Chest,2018,154(5):1239-1248.
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