Dataset Information

Derivation and validation of a clinical decision rule to risk-stratify COVID-19 patients discharged from the emergency department: The CCEDRRN COVID discharge score.

ABSTRACT:

Objective

To risk-stratify COVID-19 patients being considered for discharge from the emergency department (ED).

Methods

We conducted an observational study to derive and validate a clinical decision rule to identify COVID-19 patients at risk for hospital admission or death within 72 hours of ED discharge. We used data from 49 sites in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) between March 1, 2020, and September 8, 2021. We randomly assigned hospitals to derivation or validation and prespecified clinical variables as candidate predictors. We used logistic regression to develop the score in a derivation cohort and examined its performance in predicting short-term adverse outcomes in a validation cohort.

Results

Of 15,305 eligible patient visits, 535 (3.6%) experienced the outcome. The score included age, sex, pregnancy status, temperature, arrival mode, respiratory rate, and respiratory distress. The area under the curve was 0.70 (95% confidence interval [CI] 0.68-0.73) in derivation and 0.71 (95% CI 0.68-0.73) in combined derivation and validation cohorts. Among those with a score of 3 or less, the risk for the primary outcome was 1.9% or less, and the sensitivity of using 3 as a rule-out score was 89.3% (95% CI 82.7-94.0). Among those with a score of ≥9, the risk for the primary outcome was as high as 12.2% and the specificity of using 9 as a rule-in score was 95.6% (95% CI 94.9-96.2).

Conclusion

The CCEDRRN COVID discharge score can identify patients at risk of short-term adverse outcomes after ED discharge with variables that are readily available on patient arrival.

SUBMITTER: Brooks SC

PROVIDER: S-EPMC9780419 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Derivation and validation of a clinical decision rule to risk-stratify COVID-19 patients discharged from the emergency department: The CCEDRRN COVID discharge score.

Brooks Steven C SC Rosychuk Rhonda J RJ Perry Jeffrey J JJ Morrison Laurie J LJ Wiemer Hana H Fok Patrick P Rowe Brian H BH Daoust Raoul R Vatanpour Shabnam S Turner Joel J Landes Megan M Ohle Robert R Hayward Jake J Scheuermeyer Frank F Welsford Michelle M Hohl Corinne C

Journal of the American College of Emergency Physicians open 20221222 6

<h4>Objective</h4>To risk-stratify COVID-19 patients being considered for discharge from the emergency department (ED).<h4>Methods</h4>We conducted an observational study to derive and validate a clinical decision rule to identify COVID-19 patients at risk for hospital admission or death within 72 hours of ED discharge. We used data from 49 sites in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) between March 1, 2020, and September 8, 2021. We randomly assigned hospi ...[more]

PMID: 36579029

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Project description:ObjectiveTo derive and validate a new clinical prediction rule to risk-stratify emergency department (ED) patients admitted with suspected sepsis.DesignRetrospective prognostic study of prospectively collected data.SettingED.ParticipantsPatients aged ≥18 years who met two Systemic Inflammatory Response Syndrome criteria or one Red Flag sepsis criteria on arrival, received intravenous antibiotics for a suspected infection and admitted.Primary outcome measureIn-hospital all-cause mortality.MethodThe data were divided into derivation and validation cohorts. The simplified-Mortality in Severe Sepsis in the ED score and quick-SOFA scores, refractory hypotension and lactate were collectively termed 'component scores' and cumulatively termed the 'Risk-stratification of ED suspected Sepsis (REDS) score'. Each patient in the derivation cohort received a score (0-3) for each component score. The REDS score ranged from 0 to 12. The component scores were subject to univariate and multivariate logistic regression analyses. The receiver operator characteristic (ROC) curves for the REDS and the components scores were constructed and their cut-off points identified. Scores above the cut-off points were deemed high-risk. The area under the ROC (AUROC) curves and sensitivity for mortality of the high-risk category of the REDS score and component scores were compared. The REDS score was internally validated.Results2115 patients of whom 282 (13.3%) died in hospital. Derivation cohort: 1078 patients with 140 deaths (13%). The AUROC curve with 95% CI, cut-off point and sensitivity for mortality (95% CI) of the high-risk category of the REDS score were: derivation: 0.78 (0.75 to 0.80); ≥3; 85.0 (78 to 90.5).Validation0.74 (0.71 to 0.76); ≥3; 84.5 (77.5 to 90.0). The AUROC curve and the sensitivity for mortality of the REDS score was better than that of the component scores. Specificity and mortality rates for REDS scores of ≥3, ≥5 and ≥7 were 54.8%, 88.8% and 96.9% and 21.8%, 36.0% and 49.1%, respectively.ConclusionThe REDS score is a simple and objective score to risk-stratify ED patients with suspected sepsis.

Project description:BackgroundPredicting mortality from COVID-19 using information available when patients present to the emergency department can inform goals-of-care decisions and assist with ethical allocation of critical care resources. The study objective was to develop and validate a clinical score to predict emergency department and in-hospital mortality among consecutive nonpalliative patients with COVID-19; in this study, we define palliative patients as those who do not want resuscitative measures, such as intubation, intensive care unit care or cardiopulmonary resuscitation.MethodsThis derivation and validation study used observational cohort data recruited from 46 hospitals in 8 Canadian provinces participating in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN). We included adult (age ≥ 18 yr) nonpalliative patients with confirmed COVID-19 who presented to the emergency department of a participating site between Mar. 1, 2020, and Jan. 31, 2021. We randomly assigned hospitals to derivation or validation, and prespecified clinical variables as candidate predictors. We used logistic regression to develop the score in a derivation cohort and examined its performance in predicting emergency department and in-hospital mortality in a validation cohort.ResultsOf 8761 eligible patients, 618 (7.0%) died. The CCEDRRN COVID-19 Mortality Score included age, sex, type of residence, arrival mode, chest pain, severe liver disease, respiratory rate and level of respiratory support. The area under the curve was 0.92 (95% confidence interval [CI] 0.90-0.93) in derivation and 0.92 (95% CI 0.90-0.93) in validation. The score had excellent calibration. These results suggest that scores of 6 or less would categorize patients as being at low risk for in-hospital death, with a negative predictive value of 99.9%. Patients in the low-risk group had an in-hospital mortality rate of 0.1%. Patients with a score of 15 or higher had an observed mortality rate of 81.0%.InterpretationThe CCEDRRN COVID-19 Mortality Score is a simple score that can be used for level-of-care discussions with patients and in situations of critical care resource constraints to accurately predict death using variables available on emergency department arrival. The score was derived and validated mostly in unvaccinated patients, and before variants of concern were circulating widely and newer treatment regimens implemented in Canada.Study registrationClinicalTrials.gov, no. NCT04702945.

Project description:IntroductionWhile emergency department (ED) crowding has deleterious effects on patient care outcomes and operational efficiency, impacts on the experience for patients discharged from the ED are unknown. We aimed to study how patient-reported experience is affected by ED crowding to characterize which factors most impact discharged patient experience.MethodsThis institutional review board-exempt, retrospective, cohort study included all discharged adult ED patients July 1, 2020-June 30, 2021 with at least some response data to the the National Research Corporation Health survey, sent to most patients discharged from our large, academic medical center ED. Our query yielded 9,401 unique encounters for 9,221 patients. Based on responses to the summary question of whether the patient was likely to recommend our ED, patients were categorized as "detractors" (scores 0-6) or "non-detractors" (scores 7-10). We assessed the relationship between census and patient experience by 1) computing percentage of detractors within each care area and assessing for differences in census and boarder burden between detractors and non-detractors, and 2) multivariable logistic regression assessing the relationship between likelihood of being a detractor in terms of the ED census and the patient's last ED care area. A second logistic regression controlled for additional patient- and encounter-specific covariates.ResultsSurvey response rate was 24.8%. Overall, 13.9% of responders were detractors. There was a significant difference in the average overall ED census for detractors (average 3.70 more patients physically present at the time of arrival, 95% CI 2.33-5.07). In unadjusted multivariable analyses, three lower acuity ED care areas showed statistically significant differences of detractor likelihood with changes in patient census. The overall area under the curve (AUC) for the unadjusted model was 0.594 (CI 0.577-0.610). The adjusted model had higher AUC (0.673, CI 0.657-.690]; P<0.001), with the same three care areas having significant differences in detractor likelihood based on patient census changes. Length of stay (OR 1.71, CI 1.50-1.95), leaving against medical advice/without being seen (OR 5.15, CI 3.84-6.89), and the number of ED care areas a patient visited (OR 1.16, CI 1.01-1.33) was associated with an increase in detractor likelihood.ConclusionPatients arriving to a crowded ED and ultimately discharged are more likely to have negative patient experience. Future studies should characterize which variables most impact patient experience of discharged ED patients.

Project description:ObjectiveThe risk of occupational exposure during endotracheal intubation has required the global Emergency Medicine (EM), Anesthesia, and Critical Care communities to institute new COVID- protected intubation guidelines, checklists, and protocols. This survey aimed to deepen the understanding of the changes in intubation practices across Canada by evaluating the pre-COVID-19, early-COVID-19, and present-day periods, elucidating facilitators and barriers to implementation, and understanding provider impressions of the effectiveness and safety of the changes made.MethodsWe conducted an electronic, self-administered, cross-sectional survey of EM physician site leads within the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) to characterize and compare airway management practices in the pre-COVID-19, early-COVID-19, and present-day periods. Ethics approval for this study was obtained from the University of Manitoba Health Research Ethics Board. The electronic platform SurveyMonkey ( www.surveymonkey.com ) was used to collect and store survey tool responses. Categorical item responses, including the primary outcome, are reported as numbers and proportions. Variations in intubation practices over time were evaluated through mixed-effects logistic regression models.ResultsInvitations were sent to 33 emergency department (ED) physician site leads in the CCEDRRN. We collected 27 survey responses, 4 were excluded, and 23 analysed. Responses were collected in English (87%) and French (13%), from across Canada and included mainly physicians practicing in mainly Academic and tertiary sites (83%). All respondents reported that the intubation protocols used in their EDs changed in response to the COVID-19 pandemic (100%, n = 23, 95% CI 0.86-1.00).ConclusionsThis study provides a novel summary of changes to airway management practices in response to the evolving COVID-19 pandemic in Canada. Information from this study could help inform a consensus on safe and effective emergent intubation of persons with communicable respiratory infections in the future.

Dataset Information

Derivation and validation of a clinical decision rule to risk-stratify COVID-19 patients discharged from the emergency department: The CCEDRRN COVID discharge score.

Objective

Methods

Results

Conclusion

Publications

Derivation and validation of a clinical decision rule to risk-stratify COVID-19 patients discharged from the emergency department: The CCEDRRN COVID discharge score.

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