Bibliographic record
Abstract
Severe acute respiratory syndrome (SARS) is a highly contagious and predominantly pneumonic illness caused by a novel coronavirus now commonly known as SARS-CoV (1, 2). Since its recognition in February 2003, SARS has spread to 30 countries and has affected over 8,000 people, resulting in almost 700 deaths worldwide (3). In Hong Kong, over 25% of the victims are health care workers, and the fear of this disease has created devastating socioeconomic effects in Hong Kong and worldwide. SARS is a severe and potentially progressive disease, and many patients progress to severe pneumonia and some even die with diffuse alveolar damage (4). Although it is increasingly being recognized that the mode of transmission is predominantly via droplets, it is now suspected that SARS could also be transmitted via fomites and contaminated sewage systems (5). Although the outbreak of SARS has triggered tremendous international research collaboration, which has enabled rapid dissemination of newly found knowledge to combat this frightening condition, there is very little published literature illustrating the experience of clinicians in the management of these patients. As the vast majority of cases occurred in Hong Kong, Singapore, Taiwan, the mainland of China, and Toronto, physicians outside these areas have seldom had the opportunity to manage these patients (4, 6, 7). Although it is commonly agreed that SARS-CoV infection, being a viral illness, does not respond to antibiotic therapy, other treatment modalities are controversial (6, 8–11). In Hong Kong, a combination of corticosteroid and ribavirin, a broad-spectrum antiviral agent, is routinely used. The use of ribavirin has attracted considerable skepticism because it exhibits no in vitro efficacy against SARS-CoV and it is associated with considerable toxicities, including hemolytic anemia (10, 12, 13). Until we have an efficacious vaccine and implementation of effective epidemiologic infection control measures, and in the absence of effective anti-SARS-CoV agents in sight, SARS is likely to remain a major health threat to the world. In this article, we attempt to address the diagnostic and therapeutic experience regarding this new condition, and in doing so we hope our experience will assist clinicians in their encounter with this potentially devastating, poorly understood new disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".