The Role of Nurse Understaffing in Nosocomial Viral Gastrointestinal Infections on a General Pediatrics Ward
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between nurse staffing levels and the rate of nosocomial viral gastrointestinal infections (NVGIs) in a general pediatrics population. DESIGN: Retrospective descriptive study. SETTING: A general pediatrics ward at The Hospital for Sick Children in Toronto, Ontario, Canada, a 320-bed, tertiary-care pediatric institution. RESULTS: Forty-three NVGIs were detected in 37 patients of 2,929 admissions (1.3%). The monthly NVGI rate correlated significantly with the monthly night patient-to-nurse ratio (r = 0.56) and the monthly day patient-to-nurse ratio (r = 0.50). The nursing hours per patient-day during the preinfection period (PIP) were significantly lower than those during the nonpreinfection period (NPIP; 12.5 vs 13.0). There was no difference between the PIP and the NPIP day patient-to-nurse ratios (3.31 vs 3.32), but there was a significant difference between the PIP and the NPIP night patient-to-nurse ratios (3.26 vs 3.16). The incidence of NVGIs in the 72-hour period after any day when the nursing hours per patient-day were less than 10.5 was 6.39 infections per 1,000 patient-days, compared with 2.17 infections per 1,000 patient-days in periods with more than 10.5 nursing hours per patient-day (rate ratio, 2.94; 95% confidence interval, 2.16 to 4.01). CONCLUSION: Nurse understaffing contributed to an increased NVGI rate in our general pediatrics population, and should be assessed as a risk factor in outbreak investigations.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".