I. Mecham, N. Dean, E. Wilson, A. Jephson, M. Lanspa
{"title":"qSOFA、SOFA和SIRS与急诊科肺炎死亡率的关系","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":"{\"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}","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
The Association of qSOFA, SOFA, and SIRS with Mortality in Emergency Department
Pneumonia
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