The Role of Torovirus in Nosocomial Viral Gastroenteritis at a Large Tertiary Pediatric Centre
Bibliographic record
Abstract
OBJECTIVE: To describe the viral etiology and epidemiology of nosocomial viral gastroenteritis (NVG) at a tertiary care pediatric hospital and identify any changes over the past two decades. METHODS: Retrospective review of all patients with laboratory-confirmed NVG at The Hospital for Sick Children (Toronto, Ontario), from January 1, 2004, to December 31, 2005. RESULTS: One hundred forty-two episodes of NVG were found among 133 patients, occurring in 0.48 of 100 admissions. The median age was two years; 42% were <1 year of age and 41% were immunocompromised. The most commonly detected pathogen was torovirus (67% of episodes), followed by rotavirus (19%) and adenovirus (9%). Seventy-five cases (53%) were epidemiologically linked in 32 separate clusters (median cluster size two, range two to four). The NVG rate fell from 0.63 of 100 to 0.22 of 100 admissions after March 2005 (P<0.001) when enhanced infection control precautions were instituted in response to an outbreak of vancomycin-resistant Enterococcus. CONCLUSIONS: Torovirus remains the most commonly identified cause of NVG at The Hospital for Sick Children. Most NVG cases were epidemiologically linked, and a significant reduction in cases occurred after the institution of enhanced infection control practices following an outbreak of vancomycin-resistant Enterococcus. Improved education and surveillance for NVG should lead to further reduction in this problem.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".