A large multicenter evaluation of quick Sequential Organ Failure Assessment (qSOFA) and Systemic Inflammatory Response Syndrome (SIRS) performance among hospitalized US Emergency Department patients with suspected infection
Original Article

A large multicenter evaluation of quick Sequential Organ Failure Assessment (qSOFA) and Systemic Inflammatory Response Syndrome (SIRS) performance among hospitalized US Emergency Department patients with suspected infection

Marie-Carmelle Elie-Turenne1, Raghu R. Seethala2, Imoigele P. Aisiku2, Azra Bihorac3, Tezcan Ozrazgat-Baslanti3, Kemba Mark1, Naomi R. George4, Brandon R. Allen1, Shahab Bozorgmehri3, David Meurer1, Hasan Rasheed1, Ching-Fang Tzeng5, Peter C. Hou2; the USCIITG-LIPS Investigators

1Department of Emergency Medicine, University of Florida, Gainesville, Florida, USA; 2Division of Emergency Critical Care Medicine, Department of Emergency Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA; 3Division of Nephrology, Department of Medicine, University of Florida, Gainesville, Florida, USA; 4Department of Emergency Medicine, Center for Adulty Critical Care, University of New Mexico, Albuquerque, New Mexico, USA; 5Harvard T.H. Chan School of Public Health, Boston, MA, USA

Contributions: (I) Conception and design: MC Elie-Turenne, PC Hou; (II) Administrative support: MC Elie-Turenne, PC Hou; (III) Provision of study materials or patients: MC Elie-Turenne, PC Hou; (IV) Collection and assembly of data: MC Elie-Turenne, PC Hou; (V) Data analysis and interpretation: T Ozrazgat-Baslanti, S Bozorgmehri; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Peter C. Hou, MD. Division of Emergency Critical Care Medicine, Department of Emergency Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA. Email: phou@bwh.harvard.edu.

Background: Sepsis has caused a significant consumption of healthcare resources in the United States. Early recognition coupled with appropriate and timely therapy is critical for sepsis management. Systemic Inflammatory Response Syndrome (SIRS) and quick Sequential Organ Failure Assessment (qSOFA) have been recommended for rapid sepsis screening purposes but the optimal tool is still unclear. We sought to conduct the largest multicenter study of hospitalized US Emergency Department (ED) patients with suspected infection to evaluate the qSOFA ≥2 versus SIRS ≥2.

Methods: We conducted a secondary analysis of the United States Critical Illness and Injury Trials Group-Lung Injury Prevention Study (USCIITG-LIPS) cohort. Primary outcome was hospital mortality. Baseline characteristics, odds ratio (OR) and area under the receiver operating characteristic curve (AUROC) of secondary outcomes were assessed.

Results: Among 1,689 subjects with suspected infection, criteria for qSOFA ≥2 and SIRS ≥2 were met in 22% (372) and 90% (1,519), and in-hospital mortality rate 12.9% and 5.5%, respectively. After adjusting for SIRS ≥2 and qSOFA ≥2, the OR of qSOFA ≥2 vs. SIRS ≥2 for death was 4.6 (95% CI: 2.9–7.1, P=0.001) vs. 1.7 (95% CI: 0.6–4.9, P=0.29), and hospital mortality or intensive care unit (ICU) length of stay (LOS) ≥3 days, 5.3 (95% CI: 4.0–7.0, P=0.001) vs. 1.8 (95% CI: 1.1–3.2, P=0.02). Performance characteristics of qSOFA ≥2 plus SIRS ≥2 did not differ from qSOFA ≥2 alone for death [AUROC 0.67 (0.61–0.73) vs. 0.66 (0.60–0.73), P=0.55]. Sensitivity and specificity for death, was 55% and 80% for qSOFA ≥2 compared to 88% and 19% for SIRS ≥2.

Conclusions: In this multicenter ED cohort, qSOFA ≥2 had about a four-fold enhanced performance compared to SIRS ≥2 in predicting hospital mortality and other outcomes. However, qSOFA ≥2 lacks sensitivity compared to SIRS ≥2. Neither tool appears sufficient for independent use in the prognostication of the ED patient with suspected infection.

Keywords: Quick Sequential Organ Failure Assessment (qSOFA); Systemic Inflammatory Response Syndrome (SIRS); Emergency Department (ED)


Received: 08 June 2021; Accepted: 01 September 2021; Published: 25 October 2021.

doi: 10.21037/jeccm-21-56


Introduction

Sepsis has caused significant consumption of healthcare resources in the United States, with at least 1.7 million adults developing sepsis and nearly 270,000 Americans died from sepsis annually (1). The mortality from sepsis was up to 38% (2-4). Sepsis has accounted for more than 20 billion dollars in annual charges, making it the single most expensive cause of hospitalization in the United States (5).

Early recognition coupled with appropriate and timely therapy is critical for sepsis management (6,7). In 1991, sepsis was defined as the Systemic Inflammatory Response Syndrome (SIRS) with infection in the presence of two or more of the following SIRS criteria: (I) a body temperature greater than 38 °C or less than 36 °C; (II) a heart rate greater than 90 beats per minute; (III) tachypnea, manifested by a respiratory rate greater than 20 breaths per minute, or hyperventilation, as indicated by a PaCO2 of less than 32 mmHg; and (IV) an alteration in the white blood cell count, such as a count greater than 12,000/mm, a count less than 4,000/mm, or the presence of more than 10% immature neutrophils (“bands”) (8). While SIRS has become a widespread tool for screening, an evolving understanding of the pathobiology behind sepsis and the limitations of the SIRS criteria has fueled calls for refining the definition of sepsis (9,10) and better screening and prediction tools (10).

In 2015, the Third International Consensus Definitions for Sepsis and Septic Shock Task Force was convened. The revised definitions recommended discarding the term SIRS due to the overly sensitive inclusion of patients at low risk of poor outcomes and the adoption of sequential organ failure assessment (SOFA) in place of SIRS. The revised definitions focus on organ dysfunction as a marker of sepsis severity with a total SOFA score of 2 or greater meeting the criteria for sepsis (11). Sepsis-3 also introduced the quick sequential organ failure assessment (qSOFA), a simplified version of the SOFA score, for rapid bedside screening and prognostication of patients (11). The qSOFA score is determined by the presence of the following clinical criteria: (I) respiratory rate equal to or greater than 22 breaths per minute; (II) systolic blood pressure equal to or less than 100 mmHg; and (III) an alteration in mentation defined by a Glasgow coma score (GCS) less than 15 (11). The Sepsis-3 guidelines recommend qSOFA over SIRS for rapid screening purposes; however, the optimal tool for sepsis screening is still under debate (12,13).

Importance

qSOFA score could be used for the prediction of in-hospital mortality among the patients with suspected infection at Emergency Department (ED) (14). Compared to other prognostic scores, qSOFA offers similar or even better accuracy for screening of patients with sepsis for critical illness (15,16). Recognizing sepsis in ED patients, particularly those at high risk for poor outcomes, is critical to advancing sepsis care and improving patient outcomes (17). As the incidence of sepsis and resource utilization continue to increase, early and accurate identification of sepsis is essential in improving patient outcomes, resource allocation, and healthcare expenditures.

Goals of this investigation

Utilizing multicentered registry of hospitalized ED patients with suspected infection, the goal was to compare the prognostic performance of qSOFA ≥2 and SIRS ≥2 to predict clinically important outcomes using area under the receiver operating characteristic curve (AUROC) (18).

We present the following article in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting checklist (available at https://dx.doi.org/10.21037/jeccm-21-56) (19).


Methods

Study design

A subgroup analysis of data from a multicenter, observational cohort study, the United States Critical Injury and Illness Trial Group-Lung Injury Prevention Study 1 (USCIITG-LIPS 1), was performed (18).

Study setting

From March through August 2009, 22 centers (20 US and 2 non-US hospitals) enrolled patients, admitted from EDs and hospitalized for elective surgery, with at least one or more a priori defined conditions predisposing to acute lung injury (ALI), as previously described (18).

Patient and public involvement

This study is a subgroup analysis of a larger multi-center cohort study, so patient or the public were not involved in this study.

Selection of participants

Subjects from the LIPS 1 study were considered appropriate for inclusion if they were 18 years or older, admitted to US academic and community acute care hospitals EDs, and diagnosed with sepsis or pneumonia (9). Pneumonia patients were included if chest radiographs demonstrated new or progressive infiltrates, consolidation, cavitation, or pleural effusion and either presence of new onset or change in character of purulent sputum change. Positive cultures were used when available (18). Patients were excluded if ALI was present at initial assessment, transferred from another institution from the inpatient setting, died in the ED, admitted for palliative, hospice care, or elective surgery, or readmitted during the study period. In addition, subjects were excluded if the GCS or vital signs were not recorded. A study flow diagram is illustrated in Figure S1. The SIRS definition of sepsis was applied and recorded as part of the original study criteria. The qSOFA score was applied retrospectively to all patients with suspected or diagnosed infection.

Data collection and processing

Baseline characteristics, including demographics, comorbidities, and clinical variables, were collected during the first 6 hours of initial ED evaluation. Prior to study initiation at each site, investigators and study coordinators received structured training. The principal investigators from each site were responsible for data collection, data entry, and quality control. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Institutional Review Board of Mass General Brigham (NO. IRB00012706) and individual consent for this retrospective analysis was waived.

Outcome measures

The primary outcome was hospital mortality among patients with suspected or diagnosed infection. Secondary outcomes included a composite of hospital mortality or intensive care unit (ICU) length of stay (LOS) ≥3 days, ICU LOS ≥3 days alone, overall ICU utilization, invasive mechanical ventilation, non-invasive ventilation, vasopressor use, and hemodialysis secondary to acute renal failure.

Statistical analysis

Baseline demographics and clinical characteristics were examined using one-way analysis of variance (ANOVA) and Kruskal-Wallis tests for normally and non-normally distributed continuous variables, respectively, and chi-square or Fisher’s exact tests for categorical variables. We assessed the association between qSOFA ≥2 and SIRS ≥2 for each clinical outcome using generalized linear mixed-effects regression models, accounting for the correlation among ED patients from the same study site. Additionally, we assessed the prognostic performance of qSOFA ≥2 and SIRS ≥2 criteria to predict the primary and secondary clinical outcomes using AUROC. Odds ratios (ORs) and AUROC were reported along with 95% confidence intervals. AUROC comparisons were made using the DeLong test (20). We additionally calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV) for each cut-off. All significance tests were two-sided, with a P value <0.05 considered statistically significant. All of the statistical analyses were performed using Statistical Analysis Software (SAS) version 9.4 (SAS Institute Inc., Cary, North Carolina, USA).


Results

Characteristics of study population

Between March and August 2009, 5,584 patients with at least one predisposing condition for ALI at the time of hospital ED evaluation or admission for elective surgery were enrolled. After exclusion criteria were applied, the final cohort comprised of 1,689 patients who met inclusion criteria for presumed or documented infection and complete data to calculate the qSOFA score (Figure S1). The median age of the study population was 57 years [interquartile range (IQR), 45, 71 years]. Males accounted for 50.7% of the cohort (P=0.012) (Table 1).

Table 1

Characteristics of study cohort

Variables All (n=1,689) qSOFA SIRS
qSOFA ≥2 (n=372, 22%) qSOFA <2 (n=1,317, 78%) P value (qSOFA ≥2 vs. qSOFA <2) SIRS ≥2 (n=1,519, 90%) SIRS <2 (n=170, 10%) P value (SIRS ≥2 vs. SIRS <2)
Demographics
   Age, median [25th, 75th IQR] 57 [45, 71] 60 [19] 56 [18] <0.001 56 [18] 64 [18] <0.001
   Males, n (%) 857 (50.7) 193 (51.9) 664 (50.4) 0.639 755 (49.7) 102 (60.0) 0.012
   Caucasian, n (%) 937 (57.3) 241 (66.8) 696 (54.7) 0.004 836 (56.8) 101 (62.7) 0.410
   African American, n (%) 559 (34.2) 100 (27.7) 459 (36.1) 0.004 508 (34.5) 51 (31.7) 0.410
   Ethnicity (Hispanic), n (%) 150 (10.8) 23 (7.5) 127 (11.8) 0.037 136 (11.0) 14 (9.5) 0.675
Clinical variables
   Smoking, n (%) 522 (33.3) 119 (34.6) 403 (32.9) 0.561 467 (33.3) 55 (33.1) 1.000
   Alcohol use, n (%) 367 (24.1) 88 (26.0) 279 (23.5) 0.349 334 (24.5) 33 (20.4) 0.285
   Systemic steroids, n (%) 242 (14.3) 58 (15.6) 184 (14.0) 0.451 218 (14.4) 24 (14.1) 1.000
   Ace inhibitors, n (%) 377 (22.3) 82 (22.0) 295 (22.4) 0.944 333 (21.9) 44 (25.9) 0.244
   Shock, n (%) 144 (8.5) 104 (28.0) 40 (3.0) 0.001 142 (9.4) 2 (1.2) 0.001
   APACHE II [25th, 75th IQR] 11 [7, 16] 16 [12, 22] 10 [6, 14] <0.001 11 [7, 16] 10 [7, 13] 0.009
Comorbidities
   Metastatic solid cancer, n (%) 104 (6.2) 25 (6.7) 79 (6.0) 0.625 94 (6.2) 10 (5.9) 1.000
   Immunosuppression, n (%) 273 (16.2) 66 (17.7) 207 (15.7) 0.340 258 (17.0) 15 (8.8) 0.006
   COPD, n (%) 233 (13.8) 66 (17.7) 167 (12.7) 0.017 200 (13.2) 33 (19.4) 0.034
   Asthma, n (%) 183 (10.8) 38 (10.2) 145 (11.0) 0.706 163 (10.7) 20 (11.8) 0.700
   CHF NYHA Class IV, n (%) 84 (5.0) 27 (7.3) 57 (4.3) 0.030 69 (4.5) 15 (8.8) 0.024
   Chronic hemodialysis, n (%) 115 (6.8) 33 (8.9) 82 (6.2) 0.080 105 (6.9) 10 (5.9) 0.748
   Cirrhosis, n (%) 53 (3.1) 13 (3.5) 40 (3) 0.617 53 (3.5) 0 0.005
   Diabetes mellitus, n (%) 506 (30.0) 113 (30.4) 393 (29.8) 0.848 441 (29.0) 65 (38.2) 0.017
Vitals, median [25th, 75th IQR]
   Temperature (°C) 37.2 [36.6, 38.4] 37.2 [36.6, 38.4] 37.3 [36.6, 38.4] 0.451 37.4 [36.6, 38.5] 36.8 [36.5, 37.2] <0.001
   Respiratory rate (breaths/minute) 20 [18, 24] 25 [22, 30] 20 [18, 22] <0.001 21 [18, 25] 19 [18, 20] <0.001
   Heart rate (beats/minute) 105.5 [92, 120] 110 [95, 128] 105 [92, 118] <0.001 108 [96, 121] 85 [77, 90] <0.001
   SBP (mmHg) 117 [99, 139] 91 [79, 99] 125 [108, 143] <0.001 116 [98, 138] 125.5 [106, 149] <0.001
   DBP (mmHg) 67 [56, 79] 53 [45, 63] 70 [60, 81] <0.001 66 [55, 78] 70.5 [60, 80] 0.003
   Oxygen saturation (%) 96 [94, 98] 95 [92, 98] 96 [94, 98] <0.001 96 [94, 98] 95 [93, 98] 0.023
   BMI (kg/m2) 26.5[22.5, 31.9] 25.6 [22.2, 30.7] 26.7 [22.7, 32.3] 0.013 26.5 [22.7, 32.0] 26.8 [21.5, 30.9] 0.292
   GCS =15, n (%) 1,450 (85.8) 203 (54.6) 1,247 (94.7) <0.001 1,303 (85.8) 147 (86.5) 0.908
Laboratory results, median [25th, 75th IQR]
   WBC (×109/L) 12.4 [7.9, 17.0] 12.4[8.0, 18.6] 12.4 [7.8, 16.8] 0.446 12.9[8.3, 17.5] 8.9 [6.7, 11.1] <0.001
   Platelet count (×109/L) 233 [166, 316] 211 [147, 288] 239 [172, 325] <0.001 235 [166, 317] 220 [167, 286] 0.301
   Hematocrit (%) 35.2 [30.8, 39.7] 34.0 [30.0, 39.1] 35.6 [31.0, 39.8] 0.003 35.2 [30.9, 39.7] 35.2 [30.5, 40.0] 0.641
   Glucose (mg/dL) 121.0 [101.0, 162.5] 127.0 [103.0, 173.5] 120.0 [101.0, 159.0] 0.068 121.0 [101.0, 163.0] 121.0 [100.0, 155.5] 0.525
   Sodium (mEq/L) 136 [133, 139] 136 [133, 139] 136 [134, 139] 0.313 136 [133, 139] 137 [134, 139] 0.001
   Potassium (mEq/L) 4.1 [3.7, 4.5] 4.2 [3.7, 4.8] 4.0 [3.7, 4.5] 0.012 4.0 [3.7, 4.5] 4.1 [3.8, 4.6] 0.117
   HCO3 (mEq/L) 25.0 [22.0, 27.0] 23.0 [19.0, 27.0] 25.0 [22.0, 27.5] <0.001 25.0 [21.4, 27.0] 26.0 [24.0, 29.0] <0.001
   Albumin (µg/dL) 3.4 [2.8, 3.9] 3.2 [2.6, 3.7] 3.5 [3.0, 4.0] <0.001 3.4 [2.8, 3.9] 3.4 [2.8, 3.7] 0.456
   Creatinine (mg/dL) 1.0 [0.8, 1.7] 1.3 [0.9, 2.5] 1.0 [0.8, 1.5] <0.001 1.1 [0.8, 1.7] 1.0 [0.8, 1.4] 0.134
   pH 7.4 [7.3, 7.4] 7.4 [7.2, 7.4] 7.4 [7.3, 7.4] 0.123 7.4 [7.3, 7.4] 7.3 [7.2, 7.4] 0.165
   PaCO2 (mmHg) 38.0 [30.0, 47.9] 38.0 [29.1, 45.1] 39.3 [31.0, 52.0] 0.145 37.2 [29.0, 46.0] 51.1 [39.7, 56.5] 0.004
   PaO2 (mmHg) 81.9 [63.6, 122.5] 88.8 [65.0, 136.0] 77.8 [62.0, 116.0] 0.082 81.8 [63.2, 122.5] 82.4 [66.2, 152.0] 0.498

Percentages in the table represent column percentages. APACHE II, Acute Physiology and Chronic Health Evaluation II; BMI, Body mass index; COPD, chronic obstructive pulmonary disease; DBP, diastolic blood pressure; GCS, Glasgow Coma Score; HCO3, bicarbonate; IQR, interquartile range; PaCO2, partial pressure of carbon dioxide; PaO2, partial pressures of oxygen; qSOFA, quick Sequential Organ Failure Assessment; SIRS, Systemic Inflammatory Response Syndrome; WBC, white blood cells.

Main results

Overall, 22% (372/1,689) of patients met qSOFA ≥2 and 90% (1,519/1,689) met SIRS ≥2. The distribution of qSOFA elements among those with qSOFA ≥2 (n=372) for GCS <15, SBP <100 mmHg, and respiratory rate ≥22 were 45.4%, 80.9%, and 89.8% respectively. SIRS elements were distributed among SIRS ≥2 (n=1,519) for respiratory rate >20 or PaCO2 >32 mmHg, heart rate >90, temperature >38° or <36°, white blood cell count >12 or <4 (×109/L) with 52.4%, 83.9%, 46.2%, and 65.2%, respectively. Patients with chronic diseases were more likely to be classified as qSOFA ≥2 vs. qSOFA <2 if they had chronic obstructive pulmonary disease (COPD) (17.7% vs. 12.7%, P=0.017) or congestive heart failure [CHF New York Heart Association (NYHA) Class IV] (7.3% vs. 4.3%, P=0.03). Those with immunosuppression were more likely to meet SIRS ≥2 vs. SIRS <2, (17% vs. 8.8%, P=0.006) as were patients with cirrhosis (3.5% vs. 0%, P=0.005). On the other hand, patients were less likely to have a history of diabetes mellitus if they met SIRS ≥2 vs. SIRS <2 criteria (29.0% vs. 38.2%, P=0.017). Compared to patients with qSOFA <2, those with qSOFA ≥2 were more likely to have been diagnosed with shock (28.0% vs. 3.0%, P=0.001) and higher median Acute Physiology and Chronic Health Evaluation (APACHE) II score (16 vs. 10, P<0.001).

Overall, 14.2% (239/1,689) of patients had GCS <15 (P<0.001). As expected, variables inherent to the definitions were different. The clinical characteristics of the cohort are summarized in Table 1.

Outcomes

Overall hospital mortality rate was 5.2% (88/1,689). OR of qSOFA ≥2 compared to qSOFA <2 for death was 4.61 (95% CI: 2.96–7.19, P=0.001) and was highest for vasopressor use at 6.92 (95% CI: 4.70–10.19) followed by composite outcome of death and ICU LOS ≥3 at 5.31 (95% CI: 4.01–7.02). Significant ORs for all other outcomes were higher for qSOFA ≥2 compared to SIRS ≥2 (Tables 2,3).

Table 2

Frequency of outcomes investigated for qSOFA and SIRS criteria

Outcomes, n (%) All (n=1,689) qSOFA SIRS
qSOFA ≥2 (n=372) qSOFA <2 (n=1,317) P value SIRS ≥2 (n=1,519) SIRS <2 (n=170) P value
Death 88 (5.2) 48 (12.9) 40 (3.0) <0.001 84 (5.5) 4 (2.4) 0.099
Death/ICU LOS ≥3 days 370 (21.9) 180 (48.4) 190 (14.4) <0.001 351 (23.1) 19 (11.2) 0.002
ICU LOS ≥3 days 338 (20.0) 163 (43.8) 175 (13.3) <0.001 321 (21.1) 17 (10.0) 0.004
ICU utilization 474 (28.1) 211 (56.7) 263 (20.0) <0.001 452 (29.8) 22 (12.9) <0.001
Invasive ventilation 242 (14.3) 107 (28.8) 135 (10.3) <0.001 230 (15.1) 12 (7.1) 0.004
Non-invasive ventilation 124 (7.4) 44 (11.8) 80 (6.1) 0.004 114 (7.5) 10 (5.9) 0.536
Vasopressor use 139 (8.2) 83 (22.3) 56 (4.3) <0.001 133 (8.8) 6 (3.5) 0.018
Hemodialysis 86 (5.1) 29 (7.8) 57 (4.3) 0.011 82 (5.4) 4 (2.4) 0.098

ICU, intensive care unit; LOS, length of stay; qSOFA, quick Sequential Organ Failure Assessment; SIRS, Systemic Inflammatory Response Syndrome.

Table 3

Association between qSOFA and SIRS criteria and outcomes

Outcomes qSOFA ≥2 vs. qSOFA <2, odds ratio (95% confidence interval) (P value) SIRS ≥2 vs. SIRS<2, odds ratio (95% confidence interval) (P value)
Death 4.61 (2.96–7.19) (0.001) 1.74 (0.62–4.90) (0.30)
Death/ICU LOS ≥3 days 5.31 (4.01–7.02) (0.001) 1.88 (1.10–3.21) (0.02)
ICU LOS ≥3 days 4.78 (3.57–6.34) (0.001) 1.92 (1.09–3.36) (0.02)
ICU utilization 5.05 (3.84–6.63) (0.001) 2.60 (1.53–4.43) (0.004)
Invasive ventilation 3.73 (2.73–5.11) (0.001) 1.70 (0.91–3.20) (0.09)
Non-invasive ventilation 1.63 (1.06–2.51) (0.025) 1.11 (0.55–2.22) (0.779)
Vasopressor use 6.92 (4.70–10.19) (<0.001) 1.95 (0.82–4.63) (0.129)
Hemodialysis 1.80 (1.10–2.90) (0.02) 1.94 (0.69–5.45) (0.21)

ICU, intensive care unit; LOS, length of stay; qSOFA, quick Sequential Organ Failure Assessment; SIRS, Systemic Inflammatory Response Syndrome.

We further analyzed the demographic, clinical characteristics, vital signs, and laboratory values of all patients who had either qSOFA ≥2 or SIRS ≥2 and died. Interestingly, patients with qSOFA ≥2 had higher alcohol consumption (21% vs. 3%, P=0.002), lower median diastolic blood pressure (49.5 vs. 64.5 mmHg, P=0.002) and lower HCO3 (20.5 vs. 24.7 mEq/L, P=0.01) as compared to patients with SIRS ≥2. Those who had SIRS ≥2 and died were more likely to have CHF NYHA Class IV (7% vs. 1%, P=0.04) or been exposed to systemic steroids (14% vs. 6%, P=0.03) (Tables S1,S2).

Predictive performance

Overall, the AUROC for qSOFA ≥2 was greater than SIRS ≥2. AUROC for death was higher for qSOFA ≥2 (0.66, 95% CI: 0.60–0.73) vs. SIRS ≥2 (0.55, 95% CI: 0.49–0.61).

qSOFA ≥2 had the strongest predictability for both vasopressor use and composite outcome of death and ICU LOS ≥3 days, with an adequate AUROC of 0.77 (95% CI: 0.73–0.81) and 0.77 (95% CI: 0.74–0.80) respectively. qSOFA ≥2 consistently demonstrated significantly better predictive performance than SIRS ≥2 for all outcomes, except for non-invasive ventilation and hemodialysis. When combining the two criteria, SIRS ≥2 did not significantly improve the performance of qSOFA ≥2 in predicting outcomes (Table 4, Figure 1, Figures S2,S3).

Table 4

Discrimination of different models using qSOFA and/or SIRS for predicting in-hospital outcomes

Outcome AUROC (95% confidence interval) P value
Model 1: model with qSOFA indicator Model 2: model with SIRS indicator Model 3: model with qSOFA & SIRS indicators Model 1 vs. Model 2 Model 1 vs. Model 3 Model 2 vs. Model 3
Death 0.66 (0.60–0.73) 0.55 (0.49–0.61) 0.67 (0.61–0.73) <0.001 0.552 <0.001
Death/ICU LOS ≥3 days 0.77 (0.74–0.80) 0.68 (0.65–0.71) 0.77 (0.75–0.80) <0.001 0.235 <0.001
ICU LOS ≥3 days 0.77 (0.75–0.80) 0.70 (0.66–0.73) 0.78 (0.75–0.81) <0.001 0.352 <0.001
ICU utilization 0.76 (0.73–0.79) 0.70 (0.67–0.73) 0.77 (0.74–0.79) <0.001 0.013 <0.001
Invasive ventilation 0.70 (0.66–0.74) 0.62 (0.58–0.66) 0.70 (0.66–0.74) <0.001 0.810 <0.001
Non-invasive ventilation 0.69 (0.63–0.74) 0.67 (0.61–0.72) 0.68 (0.63–0.74) 0.287 0.665 0.301
Vasopressor use 0.77 (0.73–0.81) 0.64 (0.60–0.69) 0.78 (0.74–0.82) <0.001 0.329 <0.001
Hemodialysis 0.57 (0.50–0.65) 0.60 (0.52–0.66) 0.58 (0.51–0.65) 0.344 0.072 0.598

qSOFA indicator is the binary variable which indicates whether qSOFA criteria was met or not; that is whether qSOFA ≥2 or qSOFA <2. SIRS indicator is the binary variable which indicates whether SIRS criteria was met or not; that is whether SIRS ≥2 or SIRS <2. AUROC, area under the receiver operating characteristic curve; ICU, intensive care unit; LOS, length of stay; qSOFA, quick Sequential Organ Failure Assessment; SIRS, Systemic Inflammatory Response Syndrome.

Figure 1 AUROC for death. AUROC, area under the receiver operating characteristic curve; qSOFA, quick Sequential Organ Failure Assessment; SIRS, Systemic Inflammatory Response Syndrome.

qSOFA ≥2 was more specific for all outcomes measured, while SIRS ≥2 was more sensitive. Specificity for qSOFA ≥2 was four times greater than SIRS ≥2, ranging from 79% to 87% whereas sensitivity for SIRS ≥2 was twice that of qSOFA ≥2 at an average of 88%. PPVs for qSOFA ≥2 and SIRS ≥2 were highest for ICU utilization at 57% and 31%, respectively. NPVs ranged from 80% to 97% for both qSOFA ≥2 and SIRS ≥2 (Table S3).


Discussion

Advantages of the qSOFA score over the SIRS criteria include its simplicity and the ability to calculate the score without laboratory data. Despite these advantages, the value of the qSOFA score as a screening tool to identify patients presenting with sepsis in non-ICU settings was called into question (21,22). ED LOS is also known to play a role in the survival of patients with sepsis requiring ICU admission (23). In this study, we assessed the predictive ability of the qSOFA ≥2 criteria to identify ED patients with suspected infection at risk for poor outcomes. qSOFA ≥2 was better than SIRS ≥2 in predicting in-hospital death and the composite outcome of death or ICU LOS ≥3 days. qSOFA ≥2 was a significant predictor for ICU utilization, invasive and non-invasive ventilation vasopressor use, and hemodialysis as compared to SIRS ≥2. However, despite significant gains in accuracy, qSOFA ≥2 possessed a poor predictor for death with AUROC 0.66. In contrast, qSOFA ≥2 had an adequate AUROC of 0.77 for the composite outcome of death or ICU LOS ≥3 days.

In this ED cohort, SIRS ≥2 was found to have greater sensitivity for in-hospital mortality compared with qSOFA ≥2, potentially lending credence to doubts about qSOFA, though an inverse trend was noted regarding the specificity of the two tools, with qSOFA ≥2 outperforming SIRS ≥2. These trends have been noted in other ED cohorts, and together lend strong support and voiced by many in the emergency medicine community, that qSOFA ≥2 has inadequate sensitivity to be utilized in a screening capacity (21,22). For predicting poor outcomes of patients with sepsis in the ED, qSOFA may be superior to SIRS, but the sensitivity of qSOFA is of great concern (24,25). Adoption of qSOFA ≥2 as a triage screening tool for sepsis would likely expose EDs to miss many patients at risk for poor outcomes. Utilizing qSOFA ≥2 criteria as an initial screening tool for triggering ED diagnostic and treatment pathway in sepsis is not supported by our findings.

The qSOFA ≥2 vs. SIRS ≥2 controversy potentially represents a form of discord between construct validity and criterion/predictive validity. This is of significance because sepsis is a clinical syndrome versus a discrete disease with a singular pathology. Given that qSOFA was shown to be superior in predicting poor outcomes, applying the qSOFA score to ED patients with suspected infection who are more likely to develop sepsis and organ dysfunction may be valuable in determining floor vs. ICU admission (21,22). Similar to our findings, several studies documented a modest increase in accuracy of qSOFA vs. SIRS in terms of predicting mortality (21,22). Given the lack of sensitivity, yet adequate to good prediction of hospital death or ICU ≥3 days and ICU utilization, qSOFA ≥2 may be a useful tool for risk stratification of ED patients with sepsis at risk for deterioration. Whereby ICU resources are at a premium in institutions, qSOFA ≥2 may be used as a tool to standardize the most appropriate inpatient designation for the sepsis patient in the ED. In addition, qSOFA ≥2 could conceivably be used in the pre-hospital arena in austere or remote environments, and meeting qSOFA criteria could trigger the transportation of a suspected sepsis patient at risk of deterioration to a center with higher levels of care, capable of managing high risk sepsis patient (25).

To the best of our knowledge, this study represents the largest US multi-center study to examine the performance of qSOFA ≥2 as compared to SIRS ≥2 among hospitalized ED patients with suspected infection. As there are more than 500,000 ED patients presenting with sepsis annually, emergency physicians need both good screening and prognosticating tools in order to deliver the most appropriate care to their patients in a timely fashion. Until then, the Surviving Sepsis Campaign (SSC) international guidelines for the management of sepsis and septic shock will continue to state, “we recommend that hospitals and hospital systems have a performance improvement program for sepsis, including sepsis screening for acutely ill, high-risk patients (17).”

Limitations

Our study has several limitations. First, the cohort did not include all-comers to the ED with suspected or diagnosed infection and was limited to those patients with either identified pneumonia or sepsis at the time of enrollment in the original LIPS 1 cohort. Sepsis was defined with clinical symptoms and SIRS ≥2 criteria, which could cause bias from not considering non-pneumonia patients with qSOFA ≥2. Also, the absence of data regarding time-to-onset of the SIRS and qSOFA criteria and the longitudinal characteristics of sepsis could affect criteria utility (26). For instance, it is plausible that tachycardia manifested earlier than altered mental status in sepsis, which may increase the utility of SIRS criteria over qSOFA criteria in terms of screening ED patients with suspected infection at risk for poor outcomes from sepsis. Lastly, with the SIRS criteria and consequent sepsis definition available at the time of the enrollment of these patients, it is difficult to establish whether clinical management was altered on the basis of that ascertainment conferring relatively better outcomes among patients with SIRS ≥2 compared to those with qSOFA ≥2.


Conclusions

Among this cohort of ED patients with suspected infection, qSOFA ≥2 was a better predictor compared to SIRS ≥2 for hospital mortality, composite outcome of death or ICU LOS ≥3 days, ICU utilization, invasive ventilation, and vasopressor use. However, the performance of qSOFA ≥2 by AUROC for hospital mortality was modest to adequate for the composite outcome of death or ICU LOS ≥3 days. Moreover, qSOFA ≥2 fell short in sensitivity compared to SIRS ≥2. Neither tool appears sufficient for independent use in the prognostication of hospitalized ED patients with suspected infection. The findings from this study suggest that further multicenter prospective trials are warranted to examine the utility of qSOFA as a screening tool.


Acknowledgments

This study was presented in part at the Society of Critical Care Medicines 46th Annual Conference in Hawaii, January 2017.

Funding: The efforts of this study were supported by the internal funding at the University of Florida Departments of Emergency Medicine and Medicine, Division of Nephrology to Marie-Carmelle Elie-Turenne.


Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://dx.doi.org/10.21037/jeccm-21-56

Data Sharing Statement: Available at https://dx.doi.org/10.21037/jeccm-21-56

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/jeccm-21-56). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Institutional Review Board of Mass General Brigham (NO. IRB00012706) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


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doi: 10.21037/jeccm-21-56
Cite this article as: Elie-Turenne MC, Seethala RR, Aisiku IP, Bihorac A, Ozrazgat-Baslanti T, Mark K, George NR, Allen BR, Bozorgmehri S, Meurer D, Rasheed H, Tzeng CF, Hou PC; the USCIITG-LIPS Investigators. A large multicenter evaluation of quick Sequential Organ Failure Assessment (qSOFA) and Systemic Inflammatory Response Syndrome (SIRS) performance among hospitalized US Emergency Department patients with suspected infection. J Emerg Crit Care Med 2021;5:32.

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