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      Association between emergency department disposition and mortality in patients with COVID‐19 acute respiratory distress syndrome

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          Abstract

          Objectives

          Patients hospitalized for COVID‐19 frequently develop hypoxemia and acute respiratory distress syndrome (ARDS) after admission. In non‐COVID‐19 ARDS studies, admission to hospital wards with subsequent transfer to intensive care unit (ICU) is associated with worse outcomes. We hypothesized that initial admission to the ward may affect outcomes in patient with COVID‐19 ARDS.

          Methods

          This was a retrospective study of consecutive adults admitted for COVID‐19 ARDS between March 2020 and March 2021 at Stanford Health Care. Mortality scores at hospital admission (Coronavirus Clinical Characterization Consortium Mortality Score [4C score]) and ICU admission (Simplified Acute Physiology Score III [SAPS‐III]) were calculated, as well as ROX index for patients on high flow nasal oxygen. Patients were classified by emergency department (ED) disposition (ward‐first vs. ICU‐direct), and 28‐ and 60‐day mortality and highest level of respiratory support within 1 day of ICU admission were compared. A second cohort (April 2021‒July 2022, n = 129) was phenotyped to validate mortality outcome.

          Results

          A total of 157 patients were included, 48% of whom were first admitted to the ward ( n = 75). Ward‐first patients had more comorbidities, including lung disease. Ward‐first patients had lower 4C and similar SAPS‐III score, yet increased mortality at 28 days (32% vs. 17%, hazard ratio [HR] 2.0, 95% confidence interval [95% CI] 1.0‒3.7, p = 0.039) and 60 days (39% vs. 23%, HR 1.83, 95% CI 1.04‒3.22, p = 0.037) compared to ICU‐direct patients. More ward‐first patients escalated to mechanical ventilation on day 1 of ICU admission (36% vs. 14%, p = 0.002) despite similar ROX index. Ward‐first patients who upgraded to ICU within 48 h of ED presentation had the highest mortality. Mortality findings were replicated in a sensitivity analysis.

          Conclusion

          Despite similar baseline risk scores, ward‐first patients with COVID‐19 ARDS had increased mortality and escalation to mechanical ventilation compared to ICU‐direct patients. Ward‐first patients requiring ICU upgrade within 48 h were at highest risk, highlighting a need for improved identification of this group at ED admission.

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          Most cited references25

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          Acute respiratory distress syndrome: the Berlin Definition.

          V Ranieri, Gordon D Rubenfeld, B Taylor Thompson … (2012)
          The acute respiratory distress syndrome (ARDS) was defined in 1994 by the American-European Consensus Conference (AECC); since then, issues regarding the reliability and validity of this definition have emerged. Using a consensus process, a panel of experts convened in 2011 (an initiative of the European Society of Intensive Care Medicine endorsed by the American Thoracic Society and the Society of Critical Care Medicine) developed the Berlin Definition, focusing on feasibility, reliability, validity, and objective evaluation of its performance. A draft definition proposed 3 mutually exclusive categories of ARDS based on degree of hypoxemia: mild (200 mm Hg < PaO2/FIO2 ≤ 300 mm Hg), moderate (100 mm Hg < PaO2/FIO2 ≤ 200 mm Hg), and severe (PaO2/FIO2 ≤ 100 mm Hg) and 4 ancillary variables for severe ARDS: radiographic severity, respiratory system compliance (≤40 mL/cm H2O), positive end-expiratory pressure (≥10 cm H2O), and corrected expired volume per minute (≥10 L/min). The draft Berlin Definition was empirically evaluated using patient-level meta-analysis of 4188 patients with ARDS from 4 multicenter clinical data sets and 269 patients with ARDS from 3 single-center data sets containing physiologic information. The 4 ancillary variables did not contribute to the predictive validity of severe ARDS for mortality and were removed from the definition. Using the Berlin Definition, stages of mild, moderate, and severe ARDS were associated with increased mortality (27%; 95% CI, 24%-30%; 32%; 95% CI, 29%-34%; and 45%; 95% CI, 42%-48%, respectively; P < .001) and increased median duration of mechanical ventilation in survivors (5 days; interquartile [IQR], 2-11; 7 days; IQR, 4-14; and 9 days; IQR, 5-17, respectively; P < .001). Compared with the AECC definition, the final Berlin Definition had better predictive validity for mortality, with an area under the receiver operating curve of 0.577 (95% CI, 0.561-0.593) vs 0.536 (95% CI, 0.520-0.553; P < .001). This updated and revised Berlin Definition for ARDS addresses a number of the limitations of the AECC definition. The approach of combining consensus discussions with empirical evaluation may serve as a model to create more accurate, evidence-based, critical illness syndrome definitions and to better inform clinical care, research, and health services planning.
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            Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score

            Stephen R. Knight, Antonia Ho, Riinu Pius … (2020)
            Objective To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). Design Prospective observational cohort study. Setting International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020. Participants Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. Main Outcome Measure In-hospital mortality. Results 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). Conclusions An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. Study Registration ISRCTN66726260
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              SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission

              Rui P Moreno, Philipp G H Metnitz, Eduardo Almeida … (2005)
              Objective To develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data. Design Prospective multicentre, multinational cohort study. Patients and setting A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002. Measurements and results ICU admission data (recorded within ±1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test Ĥ=10.56, p=0.39, Ĉ=14.29, p=0.16). Customised equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit. Conclusions The SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels. Electronic Supplementary Material Electronic supplementary material is included in the online fulltext version of this article and accessible for authorised users: http://dx.doi.org/10.1007/s00134-005-2763-5
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                Author and article information

                Contributors
                Katie M. Lebold:
                ORCID: https://orcid.org/0000-0001-6913-3758
                lebold@stanford.edu
                Journal
                Journal ID (nlm-ta): J Am Coll Emerg Physicians Open
                Journal ID (iso-abbrev): J Am Coll Emerg Physicians Open
                Journal ID (doi): 10.1002/(ISSN)2688-1152
                Journal ID (publisher-id): EMP2
                Title: Journal of the American College of Emergency Physicians Open
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Electronic): 2688-1152
                Publication date (Electronic): 16 June 2024
                Publication date Collection: June 2024
                Volume: 5
                Issue: 3 ( doiID: 10.1002/emp2.v5.3 )
                Electronic Location Identifier: e13192
                Affiliations
                [ 1 ] Department of Emergency Medicine Stanford University School of Medicine Palo Alto California USA
                [ 2 ] Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine Stanford University School of Medicine Palo Alto California USA
                [ 3 ] Division of Cardiovascular Medicine, Department of Medicine Stanford University School of Medicine Palo Alto California USA
                [ 4 ] Divison of Hospital Medicine, Department of Medicine Stanford University School of Medicine Palo Alto California USA
                Author notes
                [*] [* ] Correspondence

                Katie M. Lebold, Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA, USA.

                Email: lebold@ 123456stanford.edu

                Author information
                https://orcid.org/0000-0001-6913-3758
                Article
                Publisher ID: EMP213192
                DOI: 10.1002/emp2.13192
                PMC ID: 11180691
                PubMed ID: 38887225
                SO-VID: 3f68ee36-722c-4998-a5c2-8f04c20a8c59
                Copyright © © 2024 The Author(s). Journal of the American College of Emergency Physicians Open published by Wiley Periodicals LLC on behalf of American College of Emergency Physicians.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                Date revision received : 28 April 2024
                Date received : 14 November 2023
                Date accepted : 03 May 2024
                Page count
                Figures: 5, Tables: 3, Pages: 10, Words: 5935
                Funding
                Funded by: Society for Academic Emergency Medicine Foundation
                Award ID: 2022–2023
                Categories
                Subject: Original Article
                Subject: Infectious Disease
                Custom metadata
                source-schema-version-number 2.0
                cover-date June 2024
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.4 mode:remove_FC converted:17.06.2024

                Keywords: acute respiratory distress syndrome,covid‐19,disposition,emergency department
                Data availability:
                Keywords: acute respiratory distress syndrome, covid‐19, disposition, emergency department

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