CCEDRRN COVID-19 Infection Score (CCIS): development and validation in a Canadian cohort of a clinical risk score to predict SARS-CoV-2 infection in patients presenting to the emergency department with suspected COVID-19

The response of Canada's clinical health research ecosystem to the COVID-19 pandemic

BACKGROUND

The response of Canada's research community to the COVID-19 pandemic provides a unique opportunity to examine the country's clinical health research ecosystem. We sought to describe patterns of enrolment across Canadian Institutes of Health Research (CIHR)-funded studies on COVID-19.

METHODS

We identified COVID-19 studies funded by the CIHR and that enrolled participants from Canadian acute care hospitals between January 2020 and April 2023. We collected information on study-and site-level variables from study leads, site investigators, and public domain sources. We described and evaluated factors associated with cumulative enrolment.

RESULTS

We obtained information for 23 out of 26 (88%) eligible CIHR-funded studies (16 randomized controlled trials [RCTs] and 7 cohort studies). The 23 studies were managed by 12 Canadian and 3 international coordinating centres. Of 419 Canadian hospitals, 97 (23%) enrolled a total of 28 973 participants - 3876 in RCTs across 78 hospitals (median cumulative enrolment per hospital 30, interquartile range [IQR] 10-61), and 25 097 in cohort studies across 62 hospitals (median cumulative enrolment per hospital 158, IQR 6-348). Of 78 hospitals recruiting participants in RCTs, 13 (17%) enrolled 50% of all RCT participants, whereas 6 of 62 hospitals (9.7%) recruited 54% of participants in cohort studies.

INTERPRETATION

A minority of Canadian hospitals enrolled the majority of participants in CIHR-funded studies on COVID-19. This analysis sheds light on the Canadian health research ecosystem and provides information for multiple key partners to consider ways to realize the full research potential of Canada's health systems.

Administrative data ICD-10 diagnostic codes identifies most lab-confirmed SARS-CoV-2 admissions but misses many discharged from the Emergency Department

We estimated the operating characteristics of ICD-10 code U07.1, introduced by the World Health Organization in 2020, to identify lab-confirmed SARS-CoV-2. CCEDRRN is a national research registry of adults (March 2020-August 2021) with suspected/confirmed SARS-CoV-2 identified in Canadian emergency departments (EDs) using chart review (symptoms, clinical information, and lab test results including SARS-CoV-2 polymerase chain reaction, PCR results). CCEDRRN data were linked to administrative hospitalization discharge and ED ICD-10 diagnostic codes (accessed centrally via the Canadian Institute for Health Information). We identified ICD-10 diagnostic codes in CCEDRRN participants. We defined lab-confirmed SARS-CoV-2 based on at least one positive PCR in the 0-14 days before the ED presentation and/or during hospitalization (in those admitted from ED). We performed separate analyses for CCEDRRN participants discharged from ED and those hospitalized from the ED. Additional analyses were stratified by province, sex, age, and (for hospitalized patients) timing of the first PCR test. The sensitivity of ICD-10 code U07.1 for a positive SARS-CoV-2 test was 93.6% (95% CI 93.0-94.1%) in those hospitalized from ED and 83.0% (95% CI 82.1-83.9%) in those discharged from the ED. Sensitivity was similar across provinces and demographics, but in each stratified analysis, values were higher in those hospitalized versus those discharged from ED. The ICD-10 diagnostic code for U07.1 within administrative data identified most lab-confirmed SARS-CoV-2 within persons hospitalized from ED, although a significant number of cases discharged from ED were missed. This should be considered when using administrative data for research and public health planning.

Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study

INTRODUCTION

Not all patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop symptomatic coronavirus disease 2019 (COVID-19), making it challenging to assess the burden of COVID-19-related hospitalizations and mortality. We aimed to determine the proportion, resource utilization, and outcomes of SARS-CoV-2 positive patients admitted for COVID-19, and assess the impact of using the Center for Disease Control's (CDC) discharge diagnosis-based algorithm and the Massachusetts state department's drug administration-based classification system on identifying admissions for COVID-19.

METHODS

In this retrospective cohort study, we enrolled consecutive SARS-CoV-2 positive patients admitted to one of five hospitals in British Columbia between December 19, 2021 and May 31,2022. We completed medical record reviews, and classified hospitalizations as being primarily for COVID-19 or with incidental SARS-CoV-2 infection. We applied the CDC algorithm and the Massachusetts classification to estimate the difference in hospital days, intensive care unit (ICU) days and in-hospital mortality and calculated sensitivity and specificity.

RESULTS

Of 42,505 Emergency Department patients, 1,651 were admitted and tested positive for SARS-CoV-2, with 858 (52.0%, 95% CI 49.6-54.4) admitted for COVID-19. Patients hospitalized for COVID-19 required ICU admission (14.0% versus 8.2%, p<0.001) and died (12.6% versus 6.4%, p<0.001) more frequently compared with patients with incidental SARS-CoV-2. Compared to case classification by clinicians, the CDC algorithm had a sensitivity of 82.9% (711/858, 95% CI 80.3%, 85.4%) and specificity of 98.1% (778/793, 95% CI 97.2%, 99.1%) for COVID-19-related admissions and underestimated COVID-19 attributable hospital days. The Massachusetts classification had a sensitivity of 60.5% (519/858, 95% CI 57.2%, 63.8%) and specificity of 78.6% (623/793, 95% CI 75.7%, 81.4%) for COVID-19-related admissions, underestimating total number of hospital and ICU bed days while overestimating COVID-19-related intubations, ICU admissions, and deaths.

CONCLUSION

Half of SARS-CoV-2 hospitalizations were for COVID-19 during the Omicron wave. The CDC algorithm was more specific and sensitive than the Massachusetts classification, but underestimated the burden of COVID-19 admissions.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT04702945.

Intubation practices and outcomes for patients with suspected or confirmed COVID-19: a national observational study by the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN)

OBJECTIVE

Intubation practices changed during the COVID-19 pandemic to protect healthcare workers from transmission of disease. Our objectives were to describe intubation characteristics and outcomes for patients tested for SARS CoV-2 infection. We compared outcomes between patients testing SARS COV-2 positive with those testing negative.

METHODS

We conducted a health records review using the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) registry. We included consecutive eligible patients who presented to one of 47 EDs across Canada between March 1, 2020 and June 20, 2021, were tested for SARS-CoV-2 and intubated in the ED. The primary outcome was the proportion of patients experiencing a post-intubation adverse event during the ED stay. Secondary outcomes included first-pass success, intubation practices, and hospital mortality. We used descriptive statistics to summarize variables with subgroup differences examined using t tests, z tests, or chi-squared tests where appropriate with 95% CIs.

RESULTS

Of 1720 patients with suspected COVID-19 who were intubated in the ED during the study period, 337 (19.6%) tested SARS-CoV-2 positive and 1383 (80.4%) SARS-CoV-2 negative. SARS-CoV-2 positive patients presented to hospital with lower oxygen levels than SARS-CoV-2 negative patients (mean pulse oximeter SaO2 86 vs 94%, p < 0.001). In total, 8.5% of patients experienced an adverse event post-intubation. More patients in the SARS-CoV-2 positive subgroup experienced post-intubation hypoxemia (4.5 vs 2.2%, p = 0.019). In-hospital mortality was greater for patients who experienced intubation-related adverse events (43.2 vs 33.2%, p = 0.018). There was no significant difference in adverse event-associated mortality by SARS-CoV-2 status. First-pass success was achieved in 92.4% of all intubations, with no difference by SARS-CoV-2 status.

CONCLUSIONS

During the COVID-19 pandemic, we observed a low risk of adverse events associated with intubation, even though hypoxemia was common in patients with confirmed SARS-CoV-2. We observed high rates of first-pass success and low rates of inability to intubate. The limited number of adverse events precluded multivariate adjustments. Study findings should reassure emergency medicine practitioners that system modifications made to intubation processes in response to the COVID-19 pandemic do not appear to be associated with worse outcomes compared to pre-COVID-19 practices.

Patient-reported health outcomes of SARS-CoV-2-tested patients presenting to emergency departments: a propensity score-matched prospective cohort study

OBJECTIVE

This study aimed to compare the long-term physical and mental health outcomes of matched severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive and SARS-CoV-2-negative patients controlling for seasonal effects.

STUDY DESIGN

This was a retrospective cohort study.

METHODS

This study enrolled patients presenting to emergency departments participating in the Canadian COVID-19 Emergency Department Rapid Response Network. We enrolled consecutive eligible consenting patients who presented between March 1, 2020, and July 14, 2021, and were tested for SARS-CoV-2. Research assistants randomly selected four site and date-matched SARS-CoV-2-negative controls for every SARS-CoV-2-positive patient and interviewed them at least 30 days after discharge. We used propensity scores to match patients by baseline characteristics and used linear regression to compare Veterans RAND 12-item physical health component score (PCS) and mental health component scores (MCS), with higher scores indicating better self-reported health.

RESULTS

We included 1170 SARS-CoV-2-positive patients and 3716 test-negative controls. The adjusted mean difference for PCS was 0.50 (95% confidence interval [CI]: -0.36, 1.36) and -1.01 (95% CI: -1.91, -0.11) for MCS. Severe disease was strongly associated with worse PCS (β = -7.4; 95% CI: -9.8, -5.1), whereas prior mental health illness was strongly associated with worse MCS (β = -5.4; 95% CI: -6.3, -4.5).

CONCLUSION

Physical health, assessed by PCS, was similar between matched SARS-CoV-2-positive and SARS-CoV-2-negative patients, whereas mental health, assessed by MCS, was worse during a time when the public experienced barriers to care. These results may inform the development and prioritization of support programs for patients.

Prognostic association between d-dimer thresholds and 30-day pulmonary embolism diagnosis among emergency department patients with suspected SARS-CoV-2 infection: a Canadian COVID-19 Emergency Department Rapid Response Network study

OBJECTIVE

The primary objective was to quantify the prognostic association between various D-dimer thresholds and 30-day PE diagnosis among emergency department (ED) patients with suspected SARS-CoV-2 infection.

METHODS

This was a retrospective study of patients enrolled in the Canadian COVID-19 ED Rapid Response Network (CCEDRRN) registry from March 1, 2020 to July 2, 2021. We included consecutive adults (≥ 18 years) presenting to 49 EDs with chest pain, shortness of breath, hypoxia, syncope, presyncope, or hemoptysis who were tested for both SARS-CoV-2 and D-dimer at index ED visit. The primary outcome measure was the sensitivity, specificity, and negative predictive value of D-dimer test thresholds for the outcome of 30-day PE diagnosis.

RESULTS

Among 10,837 patients included in our study, 404 (3.7%) were diagnosed with PE at 30-days. A standard D-Dimer threshold of 500 ng/mL had a sensitivity of 97.8% (95% confidence interval [CI] 95.8-99.0%), specificity of 40.9% (95% CI 39.9-41.8%), and negative predictive value of 99.8% (95% CI 99.6-99.9%). An age-adjusted D-dimer threshold had a sensitivity of 96.0% (95% CI 93.6-97.7%), specificity of 48.5% (95% CI 47.5-49.4%), and negative predictive value of 99.7% (95% CI 99.5-99.8%). D-dimer testing had slightly lower prognostic performance among SARS-CoV-2 positive compared to SARS-CoV-2 negative patients in predicting 30-day PE diagnosis.

CONCLUSIONS

Among ED patients with suspected SARS-CoV-2, the standard 500 ng/mL and age-adjusted D-dimer thresholds were comparable for the prediction of PE at 30-days. The prognostic performance of D-dimer was lower among SARS-CoV-2 positive patients.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT04702945.

Sensitivity and Diagnostic Yield of the First SARS-CoV-2 Nucleic Acid Amplification Test Performed for Patients Presenting to the Hospital

IMPORTANCE

Early and accurate diagnostic testing for SARS-CoV-2 is essential to initiate appropriate treatment and infection control and prevention measures among patients presenting to the hospital.

OBJECTIVE

To evaluate the diagnostic sensitivity of the SARS-CoV-2 nucleic acid amplification test (NAAT) performed within 24 hours of arrival to the emergency department among a nationally representative sample of patients.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study was conducted at 47 hospitals across 7 provinces in Canada participating in the Canadian COVID-19 Rapid Response Emergency Department Network among consecutive eligible patients presenting to a participating emergency department who were tested for SARS-CoV-2 from March 1, 2020, to December 31, 2021. Patients not tested within 24 hours of arrival and those presenting with a positive result from a test performed in the community were excluded.

MAIN OUTCOMES AND MEASURES

The primary outcome was a positive result from the SARS-CoV-2 NAAT. Outcome measures were the diagnostic sensitivity and yield of the SARS-CoV-2 NAAT.

RESULTS

Of 132 760 eligible patients (66 433 women [50.0%]; median age, 57 years [IQR, 37-74 years]), 17 174 (12.9%) tested positive for SARS-CoV-2 within 14 days of their first NAAT. The diagnostic sensitivity of the SARS-CoV-2 NAAT was 96.2% (17 070 of 17 740 [95% CI, 95.9%-96.4%]) among all of the tests performed. Estimates ranged from a high of 97.7% (1710 of 1751 [95% CI, 96.8%-98.3%]) on day 2 of symptoms to a low of 90.4% (170 of 188 [95% CI, 85.3%-94.2%]) on day 11 of symptoms among patients presenting with COVID-19 symptoms. Among patients reporting COVID-19 symptoms, the sensitivity of the SARS-CoV-2 NAAT was 97.1% (11 870 of 12 225 [95% CI, 96.7%-97.3%]) compared with 87.6% (812 of 927 [95% CI, 85.2%-89.6%]) among patients without COVID-19 symptoms. The diagnostic yield of the SARS-CoV-2 NAAT was 12.0% (18 985 of 158 004 [95% CI, 11.8%-12.2%]) and varied from a high of 20.0% (445 of 2229 [95% CI, 18.3%-21.6%]) among patients tested on day 10 after symptom onset to a low of 8.1% (1686 of 20 719 [95% CI, 7.7%-8.5%]) among patients presenting within the first 24 hours of symptom onset.

CONCLUSIONS AND RELEVANCE

This study suggests that the diagnostic sensitivity was high for the first SARS-CoV-2 NAAT performed in the hospital and did not vary significantly by symptom duration. Repeated testing of patients with negative test results should be avoided unless their pretest probability of disease is high.

Evaluation of Diagnostic Strategies for Identifying SARS-CoV-2 Infection in Clinical Practice: a Systematic Review and Compliance with the Standards for Reporting Diagnostic Accuracy Studies Guideline (STARD)

We aimed to review strategies for identifying SARS-CoV-2 infection before the availability of molecular test results, and to assess the reporting quality of the studies identified through the application of the STARD guideline. We screened 3,821 articles published until 30 April 2021, of which 23 met the inclusion criteria: including at least two diagnostic variables, being designed for use in clinical practice or in a public health context and providing diagnostic accuracy rates. Data extraction and application of STARD criteria were performed independently by two researchers and discrepancies were discussed with a third author. Most of the studies (16, 69.6%) included symptomatic patients with suspected infection, six studies (26.1%) included patients already diagnosed and one study (4.3%) included individuals with close contact to a COVID-positive patient. The main variables considered in the studies, which included symptomatic patients, were imaging and demographic characteristics, symptoms, and lymphocyte count. The values for area under the receiver operating characteristic curve (AUC)ranged from 53-97.4. Seven studies (30.4%) validated the diagnostic model in an independent sample. The average number of STARD criteria fulfilled was 17.6 (maximum, 27 and minimum, 5). High diagnostic accuracy values are shown when more than one diagnostic variable is considered, mainly imaging and demographic characteristics, symptoms, and lymphocyte count. This could offer the potential to identify individuals with SARS-CoV-2 infection with high accuracy when molecular testing is not available. However, external validation for developed models and evaluations in populations as similar as possible to those in which they will be applied is urgently needed. IMPORTANCE According to this review, the inclusion of more than one diagnostic test in the diagnostic process for COVID-19 infection shows high diagnostic accuracy values. Imaging characteristics, patients' symptoms, demographic characteristics, and lymphocyte count were the variables most frequently included in the diagnostic models. However, developed models should be externally validated before reaching conclusions on their utility in practice. In addition, it is important to bear in mind that the test should be evaluated in populations as similar as possible to those in which it will be applied in practice.

Diagnostic yield of screening for SARS-CoV-2 among patients admitted to hospital for alternate diagnoses: an observational cohort study

OBJECTIVES

To determine the diagnostic yield of screening patients for SARS-CoV-2 who were admitted with a diagnosis unrelated to COVID-19 and to identify risk factors for positive tests.

DESIGN

Cohort from the Canadian COVID-19 Emergency Department Rapid Response Network registry.

SETTING

30 acute care hospitals across Canada.

PARTICIPANTS

Patients hospitalised for non-COVID-19-related diagnoses who were tested for SARS-CoV-2 between 1 March and 29 December 2020.

MAIN OUTCOME

Positive nucleic acid amplification test for SARS-CoV-2.

OUTCOME MEASURE

Diagnostic yield.

RESULTS

We enrolled 15 690 consecutive eligible adults who were admitted to hospital without clinically suspected COVID-19. Among these patients, 122 tested positive for COVID-19, resulting in a diagnostic yield of 0.8% (95% CI 0.64% to 0.92%). Factors associated with a positive test included presence of fever, being a healthcare worker, having a positive household contact or institutional exposure, and living in an area with higher 7-day average incident COVID-19 cases.

CONCLUSIONS

Universal screening of hospitalised patients for COVID-19 across two pandemic waves had a low diagnostic yield and should be informed by individual-level risk assessment in addition to regional COVID-19 prevalence.

TRIAL REGISTRATION NUMBER

NCT04702945.

Treatments, resource utilization, and outcomes of COVID-19 patients presenting to emergency departments across pandemic waves: an observational study by the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN)

Background

Treatment for coronavirus disease 2019 (COVID-19) evolved between pandemic waves. Our objective was to compare treatments, acute care utilization, and outcomes of COVID-19 patients presenting to emergency departments (ED) across pandemic waves.

Methods

This observational study enrolled consecutive eligible COVID-19 patients presenting to 46 EDs participating in the Canadian COVID-19 ED Rapid Response Network (CCEDRRN) between March 1 and December 31, 2020. We collected data by retrospective chart review. Our primary outcome was in-hospital mortality. Secondary outcomes included treatments, hospital and ICU admissions, ED revisits and readmissions. Logistic regression modeling assessed the impact of pandemic wave on outcomes.

Results

We enrolled 9,967 patients in 8 provinces, 3,336 from the first and 6,631 from the second wave. Patients in the second wave were younger, fewer met criteria for severe COVID-19, and more were discharged from the ED. Adjusted for patient characteristics and disease severity, steroid use increased (odds ratio [OR] 7.4; 95% confidence interval [CI] 6.2–8.9), and invasive mechanical ventilation decreased (OR 0.5; 95% CI 0.4–0.7) in the second wave compared to the first. After adjusting for differences in patient characteristics and disease severity, the odds of hospitalization (OR 0.7; 95% CI 0.6–0.8) and critical care admission (OR 0.7; 95% CI 0.6–0.9) decreased, while mortality remained unchanged (OR 0.7; 95% CI 0.5–1.1).

Interpretation

In patients presenting to cute care facilities, we observed rapid uptake of evidence-based therapies and less use of experimental therapies in the second wave. We observed increased rates of ED discharges and lower hospital and critical care resource use over time. Substantial reductions in mechanical ventilation were not associated with increasing mortality. Advances in treatment strategies created health system efficiencies without compromising patient outcomes.

Trial registration

Clinicaltrials.gov, NCT04702945.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43678-022-00275-3.

The CCEDRRN COVID-19 Mortality Score to predict death among nonpalliative patients with COVID-19 presenting to emergency departments: a derivation and validation study

BACKGROUND

Predicting 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.

METHODS

This 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.

RESULTS

Of 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%.

INTERPRETATION

The 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 REGISTRATION

ClinicalTrials.gov, no. NCT04702945.