Identification and validation of objective triggers for initiation of resuscitation management of acutely ill non-trauma patients: the INITIATE IRON MAN study

Abstract Background While there are clear national resuscitation room admission guidelines for major trauma patients, there are no comparable alarm criteria for critically ill nontrauma (CINT) patients in the emergency department (ED). The aim of this study was to define and validate specific trigger factor cut-offs for identification of CINT patients in need of a structured resuscitation management protocol. Methods All CINT patients at a German university hospital ED for whom structured resuscitation management would have been deemed desirable were prospectively enrolled over a 6-week period (derivation cohort, n = 108). The performance of different thresholds and/or combinations of trigger factors immediately available during triage were compared with the National Early Warning Score (NEWS) and Quick Sequential Organ Failure Assessment (qSOFA) score. Identified combinations were then tested in a retrospective sample of consecutive nontrauma patients presenting at the ED during a 4-week period (n = 996), and two large external datasets of CINT patients treated in two German university hospital EDs (validation cohorts 1 [n = 357] and 2 [n = 187]). Results The any-of-the-following trigger factor iteration with the best performance in the derivation cohort included: systolic blood pressure < 90 mmHg, oxygen saturation < 90%, and Glasgow Coma Scale score < 15 points. This set of triggers identified > 80% of patients in the derivation cohort and performed better than NEWS and qSOFA scores in the internal validation cohort (sensitivity = 98.5%, specificity = 98.6%). When applied to the external validation cohorts, need for advanced resuscitation measures and hospital mortality (6.7 vs. 28.6%, p < 0.0001 and 2.7 vs. 20.0%, p < 0.012) were significantly lower in trigger factor-negative patients. Conclusion Our simple, any-of-the-following decision rule can serve as an objective trigger for initiating resuscitation room management of CINT patients in the ED.

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Predictive value of qSOFA score for death in emergency department resuscitation room among adult trauma patients:a retrospective study

BMC Emergency Medicine ◽

10.1186/s12873-021-00498-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Wenjuan Huang ◽

Peng Yang ◽

Feng Xu ◽

Du Chen

Keyword(s):

Emergency Department ◽

Predictive Value ◽

Univariate Analysis ◽

Area Under The Curve ◽

Study Endpoint ◽

Trauma Patients ◽

Roc Curve Analysis ◽

Resuscitation Room ◽

Failure Assessment ◽

Qsofa Score

Abstract Background To explore the predictive value of the quick Sequential Organ Failure Assessment (qSOFA) score for death in the emergency department (ED) resuscitation room among adult trauma patients. Methods During the period November 1, 2016 to November 30, 2019, data was retrospectively collected of adult trauma patients triaged to the ED resuscitation room in the First Affiliated Hospital of Soochow University. Death occurring in the ED resuscitation room was the study endpoint. Univariate and multivariate analyses were performed to explore the association between qSOFA score and death. Receiver operating characteristic (ROC) curve analysis was also performed for death. Results A total of 1739 trauma victims were admitted, including 1695 survivors and 44 non-survivors. The death proportion raised with qSOFA score: 0.60% for qSOFA = 0, 3.28% for qSOFA = 1, 12.06% for qSOFA = 2, and 15.38% for qSOFA = 3, p < 0.001. Subgroup of qSOFA = 0 was used as a reference. In univariate analysis, crude OR for death with qSOFA = 1 was 5.65 [95% CI 2.25 to 14.24, p < 0.001], qSOFA = 2 was 22.85 [95% CI 8.84 to 59.04, p < 0.001], and qSOFA = 3 was 30.30 [95% CI 5.50 to 167.05, p < 0.001]. In multivariate analysis, with an adjusted OR (aOR) of 2.87 (95% CI 0.84 to 9.87, p = 0.094) for qSOFA = 1, aOR 6.80 (95% CI 1.79 to 25.90, p = 0.005) for qSOFA = 2, and aOR 24.42 (95% CI 3.67 to 162.27, p = 0.001) for qSOFA = 3. The Area Under the Curve (AUC) for predicting death in the ED resuscitation room among trauma patients was 0.78 [95% CI, 0.72–0.85]. Conclusions The qSOFA score can assess the severity of emergency trauma patients and has good predictive value for death in the ED resuscitation room.

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A Prediction Model for Severe AKI in Critically Ill Adults That Incorporates Clinical and Biomarker Data

Clinical Journal of the American Society of Nephrology ◽

10.2215/cjn.04100318 ◽

2019 ◽

Vol 14 (4) ◽

pp. 506-514 ◽

Cited By ~ 7

Author(s):

Pavan Kumar Bhatraju ◽

Leila R. Zelnick ◽

Ronit Katz ◽

Carmen Mikacenic ◽

Susanna Kosamo ◽

...

Keyword(s):

Critically Ill ◽

Critically Ill Patients ◽

Prediction Models ◽

Risk Model ◽

External Validation ◽

Variable Model ◽

Internal Validation ◽

Predictive Values ◽

Derivation Cohort ◽

C Statistic

Background and objectivesCritically ill patients with worsening AKI are at high risk for poor outcomes. Predicting which patients will experience progression of AKI remains elusive. We sought to develop and validate a risk model for predicting severe AKI within 72 hours after intensive care unit admission.Design, setting, participants, & measurementsWe applied least absolute shrinkage and selection operator regression methodology to two prospectively enrolled, critically ill cohorts of patients who met criteria for the systemic inflammatory response syndrome, enrolled within 24–48 hours after hospital admission. The risk models were derived and internally validated in 1075 patients and externally validated in 262 patients. Demographics and laboratory and plasma biomarkers of inflammation or endothelial dysfunction were used in the prediction models. Severe AKI was defined as Kidney Disease Improving Global Outcomes (KDIGO) stage 2 or 3.ResultsSevere AKI developed in 62 (8%) patients in the derivation, 26 (8%) patients in the internal validation, and 15 (6%) patients in the external validation cohorts. In the derivation cohort, a three-variable model (age, cirrhosis, and soluble TNF receptor-1 concentrations [ACT]) had a c-statistic of 0.95 (95% confidence interval [95% CI], 0.91 to 0.97). The ACT model performed well in the internal (c-statistic, 0.90; 95% CI, 0.82 to 0.96) and external (c-statistic, 0.93; 95% CI, 0.89 to 0.97) validation cohorts. The ACT model had moderate positive predictive values (0.50–0.95) and high negative predictive values (0.94–0.95) for severe AKI in all three cohorts.ConclusionsACT is a simple, robust model that could be applied to improve risk prognostication and better target clinical trial enrollment in critically ill patients with AKI.

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Development and Validation of a Prognostic Model for Transplant-Associated Thrombotic Microangiopathy Following Allogeneic Hematopoietic Stem Cell Transplantation

Blood ◽

10.1182/blood-2020-138408 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 16-17

Author(s):

Peng Zhao ◽

Ye-Jun Wu ◽

Qing-Yuan Qu ◽

Shan Chong ◽

Xiao-Wan Sun ◽

...

Keyword(s):

Overall Survival ◽

Prognostic Model ◽

Validation Cohort ◽

Risk Group ◽

External Validation ◽

Internal Validation ◽

Hematopoietic Stem ◽

Derivation Cohort ◽

Peking University ◽

Score Model

Introduction Transplant-associated thrombotic microangiopathy (TA-TMA) is a potentially life-threatening complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT), which can result in multiorgan injury and increased risk for mortality. Renewed interest has emerged in the prognostication of TA-TMA with the development of novel diagnostic and management algorithms. Our previous study reported an adverse outcome in patients with TA-TMA and concomitant acute graft-versus-host disease (Eur J Haematol, 2018). However, information on markers for the early identification of severe cases remains limited. Therefore, this study is concentrated on the development and validation of a prognostic model for TA-TMA, which might facilitate risk stratification and contribute to individualized management. Methods Patients receiving allo-HSCT in Peking University People's Hospital with 1) a diagnosis of microangiopathic hemolytic anemia (MAHA) or 2) evidence of microangiopathy were retrospectively identified from 2010 to 2018. The diagnosis of TA-TMA was reviewed according to the Overall-TMA criteria (Transplantation, 2010). Patients without fulfillment of the diagnostic criteria or complicated with other causes of MAHA were excluded from analysis. Prognostic factors for TA-TMA were determined among patients receiving HSCT between 2010 and 2014 (derivation cohort). Candidate predictors (univariate P < 0.1) were included in the multivariate analysis using a backward stepwise logistic regression model. A risk score model was then established according to the regression coefficient of each independent prognostic factor. The performance of this predictive model was evaluated through internal validation (bootstrap method with 1000 repetitions) and external temporal validation performed on data from those who received HSCT between 2015 and 2018 (validation cohort). Results 5337 patients underwent allo-HSCT at Peking University Institute of Hematology from 2010 to 2018. A total of 1255 patients with a diagnosis of MAHA and/or evidence of microangiopathy were retrospectively identified, among whom 493 patients met the inclusion criteria for this analysis (269 in the derivation cohort and 224 in the validation cohort). The median age at the time of TA-TMA diagnosis was 28 (IQR: 17-41) years. The median duration from the time of transplantation to the diagnosis of TA-TMA was 63 (IQR: 38-121) days. The 6-month overall survival rate was 42.2% (208/493), and the 1-year overall survival rate was 45.0% (222/493). In the derivation cohort, patient age (≥35 years), anemia (hemoglobin <70 g/L), severe thrombocytopenia (platelet count <15,000/μL), elevated lactic dehydrogenase (serum LDH >800 U/L) and elevated total bilirubin (TBIL >1.5*ULN) were identified by multivariate analysis as independent prognostic factors for the 6-month outcome of TA-TMA. A risk score model was constructed according to the regression coefficients (Table 1), and patients were stratified into a low-risk group (0-1 points), an intermediate-risk group (2-4 points) and a high-risk group (5-6 points). The Kaplan-Meier estimations of overall survival separated well between these risk groups (Figure 1). The prognostic model showed significant discriminatory capacity, with a cross-validated c-index of 0.770 (95%CI, 0.714-0.826) in the internal validation and 0.768 (95%CI, 0.707-0.829) in the external validation cohort. The calibration plots also indicated a good correlation between model-predicted and observed probabilities. Conclusions A prognostic model for TA-TMA incorporating several baseline laboratory factors was developed and evaluated, which demonstrated significant predictive capacity through internal and external validation. This predictive model might facilitate prognostication of TA-TMA and contribute to early identification of patients at higher risk for adverse outcomes. Further study may focus on whether these high-risk patients could benefit from early application of specific management. Disclosures No relevant conflicts of interest to declare.

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Abstract 197: The TeleStroke Mimic (TM) Score: A Prediction Rule for Identifying Stroke Mimics Evaluated in a Telestroke Network

Stroke ◽

10.1161/str.45.suppl_1.197 ◽

2014 ◽

Vol 45 (suppl_1) ◽

Author(s):

Syed F Ali ◽

Aneesh B Singhal ◽

Steven K Feske ◽

Lawrence W Davis ◽

Pamela G Forducey ◽

...

Keyword(s):

Roc Curve ◽

External Validation ◽

Prediction Rule ◽

Curve Analysis ◽

Vascular Risk ◽

Roc Curve Analysis ◽

Internal Validation ◽

Derivation Cohort ◽

Presenting Symptoms ◽

Stroke Mimics

Intro: Up to 30% of acute stroke evaluations are deemed stroke mimics (SM). SMs are likely common in telestroke as well, and a model to help a priori identify these patients might be clinically useful. Methods: We used 829 consecutive patients from 01/04 to 04/13 in our internal New England based Partners TeleStroke Network for a derivation cohort and 332 cases for internal validation. External validation was performed on 226 cases from 01/08-08/12 in our Partners National TeleStroke Network. Performance of a prediction rule developed with stepwise logistic regression was characterized by ROC curve analysis. Result: There were 23% SM in the derivation, 24% in the internal and 22% in external validation cohorts based on final clinical diagnosis. Compared to those with ischemic cerebrovascular disease (CVD), SM had lower mean age, fewer vascular risk factors, more often prior seizure and a different profile of presenting symptoms (Table 1). The TM-Score (Figure 1) was based on factors independently associated with SM status including age, medical history (atrial fibrillation, hypertension, seizures), facial weakness and NIHSS >14. The TM-Score performed well on ROC curve analysis (derivation cohort AUC=0.753, internal validation AUC=0.710, external validation AUC=0.770). Conclusion: As telestroke consultation expands, increasing numbers of SM patients are being evaluated. These patients differ substantially from their ischemic CVD counterparts in their vascular risk profiles and other characteristics. Decision-support tools based on predictive models, like the one we propose, may help highlight these differences during complex, time-critical telestroke evaluations.

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False-negative RT-PCR for COVID-19 and a diagnostic risk score: a retrospective cohort study among patients admitted to hospital

BMJ Open ◽

10.1136/bmjopen-2020-047110 ◽

2021 ◽

Vol 11 (2) ◽

pp. e047110 ◽

Cited By ~ 2

Author(s):

Ankur Gupta-Wright ◽

Colin Kenneth Macleod ◽

Jessica Barrett ◽

Sarah Ann Filson ◽

Tumena Corrah ◽

...

Keyword(s):

Cohort Study ◽

Risk Score ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

External Validation ◽

False Negative ◽

Early Warning Score ◽

Risk Scores ◽

Rt Pcr ◽

Internal Validation

ObjectiveTo describe the characteristics and outcomes of patients with a clinical diagnosis of COVID-19 and false-negative SARS-CoV-2 reverse transcription-PCR (RT-PCR), and develop and internally validate a diagnostic risk score to predict risk of COVID-19 (including RT-PCR-negative COVID-19) among medical admissions.DesignRetrospective cohort study.SettingTwo hospitals within an acute NHS Trust in London, UK.ParticipantsAll patients admitted to medical wards between 2 March and 3 May 2020.OutcomesMain outcomes were diagnosis of COVID-19, SARS-CoV-2 RT-PCR results, sensitivity of SARS-CoV-2 RT-PCR and mortality during hospital admission. For the diagnostic risk score, we report discrimination, calibration and diagnostic accuracy of the model and simplified risk score and internal validation.Results4008 patients were admitted between 2 March and 3 May 2020. 1792 patients (44.8%) were diagnosed with COVID-19, of whom 1391 were SARS-CoV-2 RT-PCR positive and 283 had only negative RT-PCRs. Compared with a clinical reference standard, sensitivity of RT-PCR in hospital patients was 83.1% (95% CI 81.2%–84.8%). Broadly, patients with false-negative RT-PCR COVID-19 and those confirmed by positive PCR had similar demographic and clinical characteristics but lower risk of intensive care unit admission and lower in-hospital mortality (adjusted OR 0.41, 95% CI 0.27–0.61). A simple diagnostic risk score comprising of age, sex, ethnicity, cough, fever or shortness of breath, National Early Warning Score 2, C reactive protein and chest radiograph appearance had moderate discrimination (area under the receiver–operator curve 0.83, 95% CI 0.82 to 0.85), good calibration and was internally validated.ConclusionRT-PCR-negative COVID-19 is common and is associated with lower mortality despite similar presentation. Diagnostic risk scores could potentially help triage patients requiring admission but need external validation.

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Abstract 126: Derivation and Validation of a Proposed Long Length of Stay (≥ 7 days) Score in Patients Hospitalized for Acute Ischemic Stroke

Stroke ◽

10.1161/str.46.suppl_1.126 ◽

2015 ◽

Vol 46 (suppl_1) ◽

Author(s):

Syed F Ali ◽

Nabeel Chauhan ◽

Nicolas Bianchi ◽

Aneesh B Singhal ◽

Lee H Schwamm

Keyword(s):

Atrial Fibrillation ◽

Ischemic Stroke ◽

Length Of Stay ◽

Carotid Stenosis ◽

External Validation ◽

Predictive Score ◽

Internal Validation ◽

Altered Level ◽

Derivation Cohort ◽

Previous Stroke

Introduction: Long length of stay (LLOS) is one of the main factors in the determination of high cost in hospitalized stroke patients. Our aim was to prospectively predict patients more likely to have a long length of stay using our hospitals Get with the guidelines (GWTG) ischemic stroke registry. Methods: We selected 5,400 patients from our database of which 3,400 (~70%) were used for the derivation cohort and 2,000 (~30%) were used for internal validation. For external validation, 730 patients were included from the University of Arkansas. Long length of stay was defined ≥ 7 days. A predictive score was developed using stepwise logistic regression, and its performance assessed using ROC curve analysis. Result: Patients with LLOS in the derivation cohort were more likely to female, self-pay, more often have diabetes mellitus, atrial fibrillation, heart failure, previous stroke and carotid stenosis, and more often presented with weakness. They were more likely to have received IV or IA thrombolysis and early antithrombotics, and had higher rates of pneumonia (18.8% vs. 2.6%) and UTI (16.7% vs. 5.3%). Independent predictors of LLOS were Medicare/Medicaid insurance, self pay, history of atrial fibrillation, CAD, previous stroke, carotid stenosis, higher NIHSS and altered level of consciousness at presentation. The LLOS score (Table 2) performed well on ROC analysis (Derivation cohort AUC=0.72, Internal validation AUC=0.73 and External validation AUC=0.77). Conclusion: Many factors play a role in determining the length of stay for AIS patients. Our study provides a scoring system that may help physicians predict which patients are more likely to have a prolonged hospital stay.

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Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19 in Wuhan, China: the PLANS (platelet lymphocyte age neutrophil sex) model

BMC Infectious Diseases ◽

10.1186/s12879-020-05688-y ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Jiong Li ◽

Yuntao Chen ◽

Shujing Chen ◽

Sihua Wang ◽

Dingyu Zhang ◽

...

Keyword(s):

Hospital Mortality ◽

Cumulative Incidence ◽

Prognostic Model ◽

External Validation ◽

Predictive Performance ◽

Prognostic Models ◽

Internal Validation ◽

Derivation Cohort ◽

Proposed Model ◽

Bootstrap Approach

Abstract Background Previous published prognostic models for COVID-19 patients have been suggested to be prone to bias due to unrepresentativeness of patient population, lack of external validation, inappropriate statistical analyses, or poor reporting. A high-quality and easy-to-use prognostic model to predict in-hospital mortality for COVID-19 patients could support physicians to make better clinical decisions. Methods Fine-Gray models were used to derive a prognostic model to predict in-hospital mortality (treating discharged alive from hospital as the competing event) in COVID-19 patients using two retrospective cohorts (n = 1008) in Wuhan, China from January 1 to February 10, 2020. The proposed model was internally evaluated by bootstrap approach and externally evaluated in an external cohort (n = 1031). Results The derivation cohort was a case-mix of mild-to-severe hospitalized COVID-19 patients (43.6% females, median age 55). The final model (PLANS), including five predictor variables of platelet count, lymphocyte count, age, neutrophil count, and sex, had an excellent predictive performance (optimism-adjusted C-index: 0.85, 95% CI: 0.83 to 0.87; averaged calibration slope: 0.95, 95% CI: 0.82 to 1.08). Internal validation showed little overfitting. External validation using an independent cohort (47.8% female, median age 63) demonstrated excellent predictive performance (C-index: 0.87, 95% CI: 0.85 to 0.89; calibration slope: 1.02, 95% CI: 0.92 to 1.12). The averaged predicted cumulative incidence curves were close to the observed cumulative incidence curves in patients with different risk profiles. Conclusions The PLANS model based on five routinely collected predictors would assist clinicians in better triaging patients and allocating healthcare resources to reduce COVID-19 fatality.

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Early prediction of noninvasive ventilation failure in COPD patients: derivation, internal validation, and external validation of a simple risk score

Annals of Intensive Care ◽

10.1186/s13613-019-0585-9 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 7

Author(s):

Jun Duan ◽

Shengyu Wang ◽

Ping Liu ◽

Xiaoli Han ◽

Yao Tian ◽

...

Keyword(s):

Hospital Mortality ◽

Noninvasive Ventilation ◽

Scoring System ◽

External Validation ◽

Chronic Obstructive ◽

Internal Validation ◽

Obstructive Pulmonary Disease ◽

Derivation Cohort ◽

Copd Patients ◽

Early Intubation

Abstract Background Early identification of noninvasive ventilation (NIV) failure is a promising strategy for reducing mortality in chronic obstructive pulmonary disease (COPD) patients. However, a risk-scoring system is lacking. Methods To develop a scale to predict NIV failure, 500 COPD patients were enrolled in a derivation cohort. Heart rate, acidosis (assessed by pH), consciousness (assessed by Glasgow coma score), oxygenation, and respiratory rate (HACOR) were entered into the scoring system. Another two groups of 323 and 395 patients were enrolled to internally and externally validate the scale, respectively. NIV failure was defined as intubation or death during NIV. Results Using HACOR score collected at 1–2 h of NIV to predict NIV failure, the area under the receiver operating characteristic curves (AUC) was 0.90, 0.89, and 0.71 for the derivation, internal-validation, and external-validation cohorts, respectively. For the prediction of early NIV failure in these three cohorts, the AUC was 0.91, 0.96, and 0.83, respectively. In all patients with HACOR score > 5, the NIV failure rate was 50.2%. In these patients, early intubation (< 48 h) was associated with decreased hospital mortality (unadjusted odds ratio = 0.15, 95% confidence interval 0.05–0.39, p < 0.01). Conclusions HACOR scores exhibited good predictive power for NIV failure in COPD patients, particularly for the prediction of early NIV failure (< 48 h). In high-risk patients, early intubation was associated with decreased hospital mortality.

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External validation of predictive scores for mortality following Clostridium difficile infection

Open Forum Infectious Diseases ◽

10.1093/ofid/ofx163.1001 ◽

2017 ◽

Vol 4 (suppl_1) ◽

pp. S401-S401

Author(s):

Catherine Beauregard-Paultre ◽

Claire Nour Abou Chakra ◽

Allison Mcgeer ◽

Annie-Claude Labbé ◽

Andrew E Simor ◽

...

Keyword(s):

Clostridium Difficile ◽

Clostridium Difficile Infection ◽

External Validation ◽

Healthcare Facility ◽

Adverse Outcomes ◽

Predictive Tool ◽

Internal Validation ◽

Derivation Cohort ◽

Low Sensitivity ◽

Research Grant

Abstract Background The burden of Clostridium difficile infection (CDI) has increased in the last decade, with more adverse outcomes and related mortality. Although many predictive scores were developed, few were validated and their performances were sub-optimal. We conducted an external validation study of predictive scores or models for mortality in CDI. Methods Published predictive tools were identified through a systematic review. We included those reporting at least an internal validation approach. A multicenter prospective cohort of 1380 adults with confirmed CDI enrolled in two Canadian provinces was used for external validation. Most cases were elderly (median age 71), had a healthcare facility-associated CDI (90%), and 52% were infected by NAP1/BI/027 strains. All-cause 30-day death occurred in 12% of patients. The performance of each scoring system was analyzed using individual primary outcomes. Results We identified two scores which performances (95% CI) are shown in the table. Both had low sensitivity and PPV, moderate specificity and NPV, and similar AUC/ROC (0.66 vs. 0.77 in the derivation cohort, and 0.69 vs. 0.75 respectively). One predictive model for 30 days all-cause mortality (Archbald-Pannone 2015, including Charlson score, WBC, BUN, diagnosis in ICU, and delirium*) was associated with only 5% increase in odds of death (crude OR = 1.05 (1.03–1.06)) with an AUC of 0.74 (0.7–0.8). Conclusion The predictive models of CDI mortality evaluated in our study have limitations in their methods and showed moderate performances in a validation cohort consisting of a majority of CDI caused by NAP1 strains. An accurate predictive tool is needed to guide clinicians in the management of CDI to prevent adverse outcomes. Disclosures J. Powis, Merck: Grant Investigator, Research grant; GSK: Grant Investigator, Research grant; Roche: Grant Investigator, Research grant; Synthetic Biologicals: Investigator, Research grant

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Predictive value of qSOFA score for death in emergency department resuscitation room among adult trauma patients：a retrospective study

10.21203/rs.3.rs-147006/v1 ◽

2021 ◽

Author(s):

Wenjuan Huang ◽

Peng Yang ◽

Feng Xu ◽

Du Chen

Keyword(s):

Emergency Department ◽

Predictive Value ◽

Univariate Analysis ◽

Area Under The Curve ◽

Study Endpoint ◽

Trauma Patients ◽

Roc Curve Analysis ◽

Resuscitation Room ◽

Failure Assessment ◽

Qsofa Score

Abstract Background To explore the predictive value of quick Sequential Organ Failure Assessment (qSOFA) score for death in emergency department (ED) resuscitation room among adult trauma patients.Methods During the period November 1, 2016 to November 30, 2019, we retrospectively collected data of adult trauma patients triaged to ED resuscitation room of the First Affiliated Hospital of Soochow University. Take death occurred in ED resuscitation room as the study endpoint. Univariate and multivariate analyses were performed to explore the association between qSOFA score and death. Receiver operating characteristic (ROC) curve analysis was also performed for death.Results A total of 1739 trauma victims were admitted, including 1695 survivors and 44 non-survivors. The death proportion raised with qSOFA score: 0.60% for qSOFA=0, 3.28% for qSOFA༝1, 12.06% for qSOFA༝2, and 15.38% for qSOFA༝3, p < 0.001. Subgroup of qSOFA = 0 was used as a reference. In univariate analysis, crude OR for death with qSOFA = 1 was 5.65 [95% CI 2.25 to 14.24, p < 0.001], qSOFA = 2 was 22.85 [95% CI 8.84 to 59.04, p < 0.001], and qSOFA = 3 was 30.30 [95% CI 5.50 to 167.05, p < 0.001]. In multivariate analysis, with an adjusted OR (aOR) of 2.87 (95% CI 0.84 to 9.87, p༝0.094) for qSOFA༝1, aOR 6.80 (95% CI 1.79 to 25.90, p = 0.005) for qSOFA༝2, and aOR 24.42 (95% CI 3.67 to 162.27, p = 0.001) for qSOFA༝3. The Area Under the Curve (AUC) for predicting death in ED resuscitation room among trauma patients was 0.78 [95% CI, 0.72–0.85].Conclusions qSOFA score can assess the severity of emergency trauma patients and has good predictive value for death in ED resuscitation room.

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