Diagnostic yield of screening for SARS-CoV-2 among patients admitted to hospital for alternate diagnoses: an observational cohort study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".