Severe acute respiratory syndrome and critical care medicine: The Toronto experience
Bibliographic record
Abstract
BACKGROUND: The 2003 global outbreak of severe acute respiratory syndrome (SARS) provided numerous challenges to the delivery of critical care. The Toronto critical care community has learned important lessons from SARS, which will help in preparation for future disease outbreaks. OBJECTIVES: The objectives of this study were to review the epidemiology and clinical characteristics of the Toronto SARS outbreak, the challenges SARS provided to the delivery of critical care, and how we would like to be better organized for a similar challenge in the future. FINDINGS: SARS manifests clinically as atypical pneumonia and ranges in severity from minor nonspecific symptoms to adult respiratory distress syndrome (ARDS). Approximately 20% of patients with SARS will become critically ill and require admission to the intensive care unit. ARDS develops in the majority of these patients. Mortality from ARDS in SARS is high, and outcome is associated with the presence of comorbid disease and the severity of illness at presentation. The influx of critically ill patients and the transmission of SARS to front line workers created a tremendous strain on Toronto's healthcare system. From a critical care perspective, the most important limitation in the response to SARS was the absence of a coordinated leadership and communication infrastructure. Other challenges encountered during SARS include the following: closure of intensive care unit beds and loss of staff through quarantine and illness, implementing novel infection control protocols, educating staff, conducting research to learn about SARS, system planning, and maintaining staff morale during this very difficult period. CONCLUSIONS: Communication and leadership strategies were key components in the critical care response to SARS. Ideally, centers should have systems in place to allow for the rapid expansion and modification of critical care services in the event of a disease outbreak. Other critical care communities should consider their crisis response strategies in advance of similar events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".