The Association of qSOFA, SOFA, and SIRS with Mortality in Emergency Department Pneumonia

I. Mecham, N. Dean, E. Wilson, A. Jephson, M. Lanspa
{"title":"The Association of qSOFA, SOFA, and SIRS with Mortality in Emergency Department\n Pneumonia","authors":"I. Mecham, N. Dean, E. Wilson, A. Jephson, M. Lanspa","doi":"10.18297/JRI/VOL2/ISS2/4/","DOIUrl":null,"url":null,"abstract":"Rationale: Sepsis scores are widely used and influence management decisions. Objective: To determine the association between 30-day mortality with Systemic Inflammatory Response Syndrome (SIRS), Sequential Organ Failure Assessment (SOFA), and quick SOFA (qSOFA) in emergency department patients with pneumonia. Secondary outcomes included the association of sepsis scores with hospital admission and direct ICU admission. Methods: This is a secondary analysis of a pneumonia population conducted in the emergency department of 3 tertiary care medical centers and 4 community hospitals. Adult immunocompetent patients diagnosed with pneumonia were included from 3 twelve-month periods spanning December 2009 to October 2015. We generated area under the receiver operating characteristic curve (AUC) values for each sepsis score for 30 day mortality and secondarily for hospital admission and direct ICU admission. We also created logistic regression models to assess associations of individual score components to the outcomes. Results: We studied 6931 patients with mean (SD) age 58 (20) years, and 30 day all-cause mortality rate 7%. Hospital and ICU admission rate was 63% and 16% respectively. Sepsis by SIRS was present in 70% of patients. Only respiratory rate and white blood count of the SIRS criteria were associated with 30-day mortality (OR=2.42 [1.94, 3.03] and 2.06 [1.68, 2.54] respectively, both p<0.001). Sepsis by qSOFA was present in 20%; all three components were associated with 30-day mortality (systolic blood pressure OR=1.36 [1.10, 1.68], respiratory rate OR=2.14 [1.72, 2.67], and altered mentation OR=6.53 [5.25, 8.09]; all p≤0.005). All six SOFA components were associated with 30-day mortality (all p≤0.001). qSOFA outperformed SIRS for 30-day mortality, (AUC=0.70 vs 0.61, p<0.001), hospital admission (AUC=0.70 vs 0.67, p<0.001), and intensive care unit admission (AUC=0.72 vs 0.64, p<0.001). SOFA significantly outperformed qSOFA for all outcomes except intensive care unit admission (AUC=0.74 vs 0.72, p=0.08). When compared to traditional pneumonia severity scores, the sepsis scores underperformed in prediction of mortality and ICU admission. Conclusions: In emergency department patients with pneumonia, qSOFA outperformed SIRS in relation to 30-day mortality, as well as hospital and ICU admission. SOFA performed better than qSOFA and SIRS for all outcomes except ICU admission. DOI: 10.18297/jri/vol2/iss2/4 Received Date: May 7, 2018 Accepted Date: July 10, 2018 Website: https://ir.library.louisville.edu/jri Copyright: ©2018 the author(s). This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Affiliations: 1Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah, Salt Lake City, Utah. 2Division of Pulmonary and Critical Care Medicine, Intermountain Medical Center, Murray, Utah. *Correspondence To: Ian D Mecham, MD Work Address: University of Utah Hospital 26N 1900E 701 Wintrobe Salt Lake City, UT 84132 Work Email: ian.mecham@gmail.com 12 ULJRI Vol 2, (2) 2018 ORIGINAL RESEARCH Materials and Methods Study Design & Population This is a secondary analysis of a large pneumonia database. We studied patients seen in the ED from seven Utah hospitals during 3 twelve-month time periods (December 2009 to November 2010, December 2011 to November 2012, and November 2014 to October 2015). Three of the hospitals are tertiary care centers, and four are community hospitals. The Intermountain Healthcare Institutional Review Board approved this study with waiver of informed consent. The study was funded by the Intermountain Research and Medical Foundation. We collected data from the highly detailed Intermountain electronic medical record. We included consecutive patients ≥18 years of age with pneumonia seen in the ED with at least one set of vital signs measured. We identified patients with pneumonia using the International Statistical Classification of Diseases, 9th edition discharge codes for a diagnosis of pneumonia (480487.1) as either primary diagnosis or secondary diagnosis with respiratory failure or sepsis (581.x, 038.x) as a primary diagnosis. We excluded patients without evidence for pneumonia on initial chest imaging reports, reviewed by physician authors. We previously reported that this method of pneumonia case definition was 68% sensitive and 99% specific when compared to the gold standard of physician review of ED case records in our study population. (6) We also identified additional pneumonia patients by ED physician completion of a real-time electronic clinical decision support tool called ePneumonia, introduced in 2012 at 4 of the study hospitals. (6, 7) We excluded patients who died while in the ED, those who had immunocompromised conditions including human immunodeficiency virus and acquired immunodeficiency syndrome, solid organ transplant, and hematologic malignancies. To exclude patients with recurrent pneumonia, often caused by chronic aspiration or structural lung disease, we included only the first episode in a given 12-month period. Data Collection & Measurements Data elements included age, gender, Charlson comorbidity score, lactate measurement, use of vasopressors, mechanical ventilation, and presence of septic shock by Sepsis-3 criteria. Our primary outcome was 30-day all-cause mortality. Mortality data was obtained from a combination of hospital records, social security records, and the Utah Population Database. Secondary outcomes were hospital admission, direct admission to ICU, hospital length of stay, in-hospital mortality, and secondary hospital admissions within seven days among those discharged home. Calculating SIRS and qSOFA: Each component of SIRS and qSOFA was calculated using the worst values while in the ED, except laboratory values could be up to 4 hours prior to ED admission. We extended the time frame to within 24 hours of ED admission if the white blood cell count (WBC) was missing. We used only the respiratory rate for the SIRS respiratory component, since partial pressure of carbon dioxide was measured in <5% of the study population. We assumed the presence of sepsis under the Sepsis-2 definition as SIRS ≥2. For qSOFA, altered mentation was defined as Glasgow Coma Score (GCS) ≤14, or clinician documentation of disorientation to person, place, or time. We also assumed the presence of sepsis under Sepsis-3 for qSOFA ≥2. Calculating SOFA: We calculated SOFA in accordance with our previously published methods and used the worst values for each component while in the ED plus 4 hours prior. (8) We extended our search to within 24 hours of ED admission where values for platelets, bilirubin, and creatinine were missing in the ED. For the respiratory component, calculation of the partial pressure of arterial oxygen/fraction of inspired oxygen (PaO2/FiO2) ratio was performed from arterial blood gas when available. When blood gas values were not available, we estimated PaO2/FiO2 from pulse oximetry (converting peripheral oxygen saturation SpO2 to PaO2 using the Ellis’s corrected version of the Severinghaus equation). (9-11) We adjusted the resultant PaO2/FiO2 for the usual atmospheric pressure (645 mmHg) of study hospitals (~1400 meters above sea level) in accordance with previously described methods. (12) Where necessary, we estimated FiO2 by the equation liter flow of oxygen/min multiplied by 0.03 plus 0.21. (10) For the cardiovascular component, we converted all vasopressors to norepinephrine equivalent dosing, in accordance with previously published methods. (13) We used the highest charted dose irrespective of length of time it was applied. If a patient received dobutamine at any dose, a score of 3 was given unless the patient received a vasopressor at a dose sufficient to assign a score of 4 or 5. For the renal component, we solely used creatinine, as urine output measurement was unreliable in the ED. Sepsis was defined as present under the Sepsis-3 definition for total SOFA score≥2. Missing Data: We had complete qSOFA data for all patients. The only component missing for SIRS determination was WBC count in 437 patients, all of whom were discharged home from the ED. We imputed the missing WBC count as normal. Patients were included for SOFA analyses if they had at least five of the six components measured, among whom we assigned a score of 0 for any missing components as directed by the Sepsis-3 definition. (14) We omitted the baseline SOFA calculation, as it is incomplete for many patients. Altered mentation and GCS were extracted via electronic query from nurse charting, supplemented by manual review of ED physician and admission notes. In patients missing both GCS and orientation status, we used the following rules: Patients discharged home from the ED were assigned a GCS of 15 and normal mentation (98 patients). We imputed missing GCS using Classification and Regression Trees (CART) for patients with altered orientation based on nurse charting or manual review. We built the CART using cases in which the patient was confused and the GCS was measured (see supplemental material). 421 cases were imputed for the ED time frame using the predicted GCS from the CART. Statistical Methods The area under the receiver operating characteristic curve (AUC) for association of 30-day mortality was obtained for all three scores and compared using a bootstrap approach. We used a similar approach for the secondary outcomes of hospital admission and disposition to ICU among those admitted. Calibration was assessed using Spiegelhalter’s Z-test. The AUC for both CURB-65 (confusion, uremia, respiratory rate, blood pressure, age ≥65) and eCURB (an electronic version of CURB-65 using continuous, weighted variables) are reported for compa","PeriodicalId":91979,"journal":{"name":"The University of Louisville journal of respiratory infections","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The University of Louisville journal of respiratory infections","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18297/JRI/VOL2/ISS2/4/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Rationale: Sepsis scores are widely used and influence management decisions. Objective: To determine the association between 30-day mortality with Systemic Inflammatory Response Syndrome (SIRS), Sequential Organ Failure Assessment (SOFA), and quick SOFA (qSOFA) in emergency department patients with pneumonia. Secondary outcomes included the association of sepsis scores with hospital admission and direct ICU admission. Methods: This is a secondary analysis of a pneumonia population conducted in the emergency department of 3 tertiary care medical centers and 4 community hospitals. Adult immunocompetent patients diagnosed with pneumonia were included from 3 twelve-month periods spanning December 2009 to October 2015. We generated area under the receiver operating characteristic curve (AUC) values for each sepsis score for 30 day mortality and secondarily for hospital admission and direct ICU admission. We also created logistic regression models to assess associations of individual score components to the outcomes. Results: We studied 6931 patients with mean (SD) age 58 (20) years, and 30 day all-cause mortality rate 7%. Hospital and ICU admission rate was 63% and 16% respectively. Sepsis by SIRS was present in 70% of patients. Only respiratory rate and white blood count of the SIRS criteria were associated with 30-day mortality (OR=2.42 [1.94, 3.03] and 2.06 [1.68, 2.54] respectively, both p<0.001). Sepsis by qSOFA was present in 20%; all three components were associated with 30-day mortality (systolic blood pressure OR=1.36 [1.10, 1.68], respiratory rate OR=2.14 [1.72, 2.67], and altered mentation OR=6.53 [5.25, 8.09]; all p≤0.005). All six SOFA components were associated with 30-day mortality (all p≤0.001). qSOFA outperformed SIRS for 30-day mortality, (AUC=0.70 vs 0.61, p<0.001), hospital admission (AUC=0.70 vs 0.67, p<0.001), and intensive care unit admission (AUC=0.72 vs 0.64, p<0.001). SOFA significantly outperformed qSOFA for all outcomes except intensive care unit admission (AUC=0.74 vs 0.72, p=0.08). When compared to traditional pneumonia severity scores, the sepsis scores underperformed in prediction of mortality and ICU admission. Conclusions: In emergency department patients with pneumonia, qSOFA outperformed SIRS in relation to 30-day mortality, as well as hospital and ICU admission. SOFA performed better than qSOFA and SIRS for all outcomes except ICU admission. DOI: 10.18297/jri/vol2/iss2/4 Received Date: May 7, 2018 Accepted Date: July 10, 2018 Website: https://ir.library.louisville.edu/jri Copyright: ©2018 the author(s). This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Affiliations: 1Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah, Salt Lake City, Utah. 2Division of Pulmonary and Critical Care Medicine, Intermountain Medical Center, Murray, Utah. *Correspondence To: Ian D Mecham, MD Work Address: University of Utah Hospital 26N 1900E 701 Wintrobe Salt Lake City, UT 84132 Work Email: ian.mecham@gmail.com 12 ULJRI Vol 2, (2) 2018 ORIGINAL RESEARCH Materials and Methods Study Design & Population This is a secondary analysis of a large pneumonia database. We studied patients seen in the ED from seven Utah hospitals during 3 twelve-month time periods (December 2009 to November 2010, December 2011 to November 2012, and November 2014 to October 2015). Three of the hospitals are tertiary care centers, and four are community hospitals. The Intermountain Healthcare Institutional Review Board approved this study with waiver of informed consent. The study was funded by the Intermountain Research and Medical Foundation. We collected data from the highly detailed Intermountain electronic medical record. We included consecutive patients ≥18 years of age with pneumonia seen in the ED with at least one set of vital signs measured. We identified patients with pneumonia using the International Statistical Classification of Diseases, 9th edition discharge codes for a diagnosis of pneumonia (480487.1) as either primary diagnosis or secondary diagnosis with respiratory failure or sepsis (581.x, 038.x) as a primary diagnosis. We excluded patients without evidence for pneumonia on initial chest imaging reports, reviewed by physician authors. We previously reported that this method of pneumonia case definition was 68% sensitive and 99% specific when compared to the gold standard of physician review of ED case records in our study population. (6) We also identified additional pneumonia patients by ED physician completion of a real-time electronic clinical decision support tool called ePneumonia, introduced in 2012 at 4 of the study hospitals. (6, 7) We excluded patients who died while in the ED, those who had immunocompromised conditions including human immunodeficiency virus and acquired immunodeficiency syndrome, solid organ transplant, and hematologic malignancies. To exclude patients with recurrent pneumonia, often caused by chronic aspiration or structural lung disease, we included only the first episode in a given 12-month period. Data Collection & Measurements Data elements included age, gender, Charlson comorbidity score, lactate measurement, use of vasopressors, mechanical ventilation, and presence of septic shock by Sepsis-3 criteria. Our primary outcome was 30-day all-cause mortality. Mortality data was obtained from a combination of hospital records, social security records, and the Utah Population Database. Secondary outcomes were hospital admission, direct admission to ICU, hospital length of stay, in-hospital mortality, and secondary hospital admissions within seven days among those discharged home. Calculating SIRS and qSOFA: Each component of SIRS and qSOFA was calculated using the worst values while in the ED, except laboratory values could be up to 4 hours prior to ED admission. We extended the time frame to within 24 hours of ED admission if the white blood cell count (WBC) was missing. We used only the respiratory rate for the SIRS respiratory component, since partial pressure of carbon dioxide was measured in <5% of the study population. We assumed the presence of sepsis under the Sepsis-2 definition as SIRS ≥2. For qSOFA, altered mentation was defined as Glasgow Coma Score (GCS) ≤14, or clinician documentation of disorientation to person, place, or time. We also assumed the presence of sepsis under Sepsis-3 for qSOFA ≥2. Calculating SOFA: We calculated SOFA in accordance with our previously published methods and used the worst values for each component while in the ED plus 4 hours prior. (8) We extended our search to within 24 hours of ED admission where values for platelets, bilirubin, and creatinine were missing in the ED. For the respiratory component, calculation of the partial pressure of arterial oxygen/fraction of inspired oxygen (PaO2/FiO2) ratio was performed from arterial blood gas when available. When blood gas values were not available, we estimated PaO2/FiO2 from pulse oximetry (converting peripheral oxygen saturation SpO2 to PaO2 using the Ellis’s corrected version of the Severinghaus equation). (9-11) We adjusted the resultant PaO2/FiO2 for the usual atmospheric pressure (645 mmHg) of study hospitals (~1400 meters above sea level) in accordance with previously described methods. (12) Where necessary, we estimated FiO2 by the equation liter flow of oxygen/min multiplied by 0.03 plus 0.21. (10) For the cardiovascular component, we converted all vasopressors to norepinephrine equivalent dosing, in accordance with previously published methods. (13) We used the highest charted dose irrespective of length of time it was applied. If a patient received dobutamine at any dose, a score of 3 was given unless the patient received a vasopressor at a dose sufficient to assign a score of 4 or 5. For the renal component, we solely used creatinine, as urine output measurement was unreliable in the ED. Sepsis was defined as present under the Sepsis-3 definition for total SOFA score≥2. Missing Data: We had complete qSOFA data for all patients. The only component missing for SIRS determination was WBC count in 437 patients, all of whom were discharged home from the ED. We imputed the missing WBC count as normal. Patients were included for SOFA analyses if they had at least five of the six components measured, among whom we assigned a score of 0 for any missing components as directed by the Sepsis-3 definition. (14) We omitted the baseline SOFA calculation, as it is incomplete for many patients. Altered mentation and GCS were extracted via electronic query from nurse charting, supplemented by manual review of ED physician and admission notes. In patients missing both GCS and orientation status, we used the following rules: Patients discharged home from the ED were assigned a GCS of 15 and normal mentation (98 patients). We imputed missing GCS using Classification and Regression Trees (CART) for patients with altered orientation based on nurse charting or manual review. We built the CART using cases in which the patient was confused and the GCS was measured (see supplemental material). 421 cases were imputed for the ED time frame using the predicted GCS from the CART. Statistical Methods The area under the receiver operating characteristic curve (AUC) for association of 30-day mortality was obtained for all three scores and compared using a bootstrap approach. We used a similar approach for the secondary outcomes of hospital admission and disposition to ICU among those admitted. Calibration was assessed using Spiegelhalter’s Z-test. The AUC for both CURB-65 (confusion, uremia, respiratory rate, blood pressure, age ≥65) and eCURB (an electronic version of CURB-65 using continuous, weighted variables) are reported for compa
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qSOFA、SOFA和SIRS与急诊科肺炎死亡率的关系
理由:脓毒症评分被广泛使用并影响管理决策。目的:探讨急诊科肺炎患者30天死亡率与全身炎症反应综合征(SIRS)、顺序器官衰竭评估(SOFA)和快速SOFA (qSOFA)的关系。次要结局包括脓毒症评分与住院和直接进入ICU的相关性。方法:对3个三级医疗中心和4个社区医院急诊科的肺炎人群进行二次分析。从2009年12月至2015年10月的3个12个月期间纳入诊断为肺炎的成人免疫功能正常患者。我们生成了30天死亡率、住院和直接ICU住院的每个脓毒症评分的受试者工作特征曲线下面积(AUC)值。我们还创建了逻辑回归模型来评估个体得分成分与结果的关联。结果:6931例患者的平均(SD)年龄为58(20)岁,30天全因死亡率为7%。住院率为63%,ICU住院率为16%。70%的患者存在SIRS引起的脓毒症。只有SIRS标准的呼吸频率和白细胞计数与30天死亡率相关(OR分别为2.42[1.94,3.03]和2.06 [1.68,2.54],p均<0.001)。由qSOFA引起的脓毒症占20%;所有三项指标均与30天死亡率相关(收缩压OR=1.36[1.10, 1.68],呼吸率OR=2.14[1.72, 2.67],精神状态改变OR=6.53 [5.25, 8.09];所有p≤0.005)。所有6个SOFA成分均与30天死亡率相关(均p≤0.001)。qSOFA在30天死亡率(AUC=0.70 vs 0.61, p<0.001)、住院率(AUC=0.70 vs 0.67, p<0.001)和重症监护病房住院率(AUC=0.72 vs 0.64, p<0.001)方面优于SIRS。除重症监护病房入院外,SOFA在所有结果中均显著优于qSOFA (AUC=0.74 vs 0.72, p=0.08)。与传统的肺炎严重程度评分相比,败血症评分在预测死亡率和ICU入院率方面表现不佳。结论:在急诊科肺炎患者中,qSOFA在30天死亡率、住院率和ICU住院率方面优于SIRS。除ICU入院外,SOFA的所有结果均优于qSOFA和SIRS。DOI: 10.18297/jri/vol2/iss2/4收稿日期:2018年5月7日接收日期:2018年7月10日网站:https://ir.library.louisville.edu/jri版权所有:©2018作者。这是一篇在知识共享署名4.0国际许可协议(CC BY 4.0)下发布的开放获取文章,该协议允许在任何媒体上不受限制地使用、分发和复制,前提是要注明原作者和来源。隶属单位:1犹他州盐湖城犹他大学医学系呼吸、重症监护和职业肺部医学部;2犹他州默里山间医疗中心肺部和重症监护医学部。*通讯作者:Ian D . Mecham, MD工作地址:犹他大学医院26N 1900E 701 Wintrobe Salt Lake City, UT 84132工作邮箱:ian.mecham@gmail.com 12 ULJRI Vol 2,(2) 2018原始研究材料和方法研究设计与人群这是对大型肺炎数据库的二次分析。我们研究了3个12个月期间(2009年12月至2010年11月,2011年12月至2012年11月,2014年11月至2015年10月)在犹他州7家医院急诊室就诊的患者。其中三家是三级保健中心,四家是社区医院。山间医疗机构审查委员会批准了这项研究,并放弃了知情同意。这项研究由山间研究和医学基金会资助。我们从非常详细的山间电子病历中收集数据。我们纳入了在急诊科看到的连续≥18岁的肺炎患者,并测量了至少一组生命体征。我们使用国际疾病统计分类第9版出院代码对肺炎患者进行诊断(480487.1),作为主要诊断或呼吸衰竭或败血症的次要诊断(581)。X, 038.x)作为初步诊断。我们排除了由医师作者审查的初始胸部影像学报告中没有肺炎证据的患者。我们之前报道过,在我们的研究人群中,与内科医生审查ED病例记录的金标准相比,这种肺炎病例定义方法的敏感性为68%,特异性为99%。(6)我们还通过急诊医生完成名为“肺炎”的实时电子临床决策支持工具(该工具于2012年在4家研究医院推出),确定了额外的肺炎患者。
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