Predictors of later COVID-19 test seeking
Bibliographic record
Abstract
Background: Delays in COVID-19 testing may increase the risk of secondary household and community transmission. Little is known about what patient characteristics and symptom profiles are associated with delays in test seeking. Methods: We conducted a retrospective cohort study of all symptomatic patients diagnosed with COVID-19 and assessed in a COVID Expansion to Outpatients (COVIDEO) virtual care program between March 2020 and June 2021. The primary outcome was later test seeking more than 3 days from symptom onset. Multivariable logistic regression was used to examine predictors of later testing including patient characteristics and symptoms (30 individual symptoms or 7 symptom clusters). Results: Of 5,363 COVIDEO patients, 4,607 were eligible and 2,155/4,607 (46.8%) underwent later testing. Older age was associated with increased odds of late testing (adjusted odds ratio [aOR] 1.007/year; 95% CI 1.00 to 1.01), as was history of recent travel (aOR 1.4; 95% CI 1.01 to 1.95). Health care workers had lower odds of late testing (aOR 0.50; 95% CI 0.39 to 0.62). Late testing was associated with symptoms in the cardiorespiratory (aOR 1.2; 95% CI 1.05, 1.36), gastrointestinal (aOR = 1.2; 95% CI 1.04, 1.4), neurological (aOR 1.1; 95% CI 1.003, 1.3) and psychiatric (aOR 1.3; 95% CI 1.1, 1.5) symptom clusters. Among individual symptoms, dyspnea, anosmia, dysgeusia, sputum, and anorexia were associated with late testing; pharyngitis, myalgia, and headache were associated with early testing. Conclusion: Certain patient characteristics and symptoms are associated with later testing, and warrant further efforts to encourage earlier testing to minimize transmission.
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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 | 0.016 |
| 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".