Risk of Ruling out Severe Acute Respiratory Syndrome by Ruling in another Diagnosis: Variable Incidence of Atypical Bacteria Coinfection Based on Diagnostic Assays
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Severe acute respiratory syndrome (SARS) caused the first epidemic of the 21st century and continues to threaten the global community. OBJECTIVE: To assess the incidence of coinfection in patients confirmed to have SARS-associated coronavirus (SARS-CoV) infection, and thus, to determine the risk of ruling out SARS by ruling in another diagnosis. METHODS: The present report is a retrospective study evaluating the incidence and impact of laboratory-confirmed SARS-CoV and other pulmonary pathogens in 117 patients. These patients were evaluated in a Toronto, Ontario, community hospital identified as the epicentre for the second SARS outbreak. RESULTS: Coinfection with other pulmonary pathogens occurred in patients with SARS. Seventy-three per cent of the patient population evaluated had laboratory-confirmed SARS-CoV infection. Serology showing acute or recent Chlamydophila pneumoniae or Mycoplasma pneumoniae infection revealed an incidence of 30% and 9%, respectively, in those with SARS. These rates are similar to previously published studies on coinfection in pneumonia. All nucleic acid diagnostic assays were negative for C pneumoniae and M pneumoniae in respiratory samples from patients with SARS having serological evidence for these atypical pathogens. CONCLUSIONS: Diagnostic assays for well-recognized pulmonary pathogens have limitations, and ruling out SARS-CoV by ruling in another pulmonary pathogen carries significant risk. Despite positive serology for atypical pathogens, in a setting where clinical suspicion for SARS is high, specific tests for SARS should be performed to confirm or exclude a diagnosis.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it