Interpretation of diagnostic laboratory tests for severe acute respiratory syndrome: the Toronto experience.
Bibliographic record
Abstract
BACKGROUND: An outbreak of severe acute respiratory syndrome (SARS) began in Canada in February 2003. The initial diagnosis of SARS was based on clinical and epidemiological criteria. During the outbreak, molecular and serologic tests for the SARS-associated coronavirus (SARS-CoV) became available. However, without a "gold standard," it was impossible to determine the usefulness of these tests. We describe how these tests were used during the first phase of the SARS outbreak in Toronto and offer some recommendations that may be useful if SARS returns. METHODS: We examined the results of all diagnostic laboratory tests used in 117 patients admitted to hospitals in Toronto who met the Health Canada criteria for suspect or probable SARS. Focusing on tests for SARS-CoV, we attempted to determine the optimal specimen types and timing of specimen collection. RESULTS: Diagnostic test results for SARS-CoV were available for 110 of the 117 patients. SARS-CoV was detected by means of reverse-transcriptase polymerase chain reaction (RT-PCR) in at least one specimen in 59 (54.1%) of 109 patients. Serologic test results of convalescent samples were positive in 50 (96.2%) of 52 patients for whom paired serum samples were collected during the acute and convalescent phases of the illness. Of the 110 patients, 78 (70.9%) had specimens that tested positive by means of RT-PCR, serologic testing or both methods. The proportion of RT-PCR test results that were positive was similar between patients who met the criteria for suspect SARS (50.8%, 95% confidence interval [CI] 38.4%-63.2%) and those who met the criteria for probable SARS (58.0%, 95% CI 44.2%-70.7%). SARS-CoV was detected in nasopharyngeal swabs in 33 (32.4%) of 102 patients, in stool specimens in 19 (63.3%) of 30 patients, and in specimens from the lower respiratory tract in 10 (58.8%) of 17 patients. INTERPRETATION: These findings suggest that the rapid diagnostic tests in use at the time of the initial outbreak lack sufficient sensitivity to be used clinically to rule out SARS. As tests for SARS-CoV continue to be optimized, evaluation of the clinical presentation and elucidation of a contact history must remain the cornerstone of SARS diagnosis. In patients with SARS, specimens taken from the lower respiratory tract and stool samples test positive by means of RT-PCR more often than do samples taken from other areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".