Seasonal variations in healthcare-associated infection in neonates in Canada
Bibliographic record
Abstract
OBJECTIVE: To assess the seasonal pattern of healthcare-associated infections (HCAI) among neonates and to describe the trend of HCAI. DESIGN: Secondary analyses of database. SETTING: The Canadian Neonatal Network database (2003-2009). PARTICIPANTS: Neonates with HCAI defined as blood/cerebrospinal fluid positive with pathogenic organism in a symptomatic infant after 2 days of age. MAIN OUTCOME MEASURE: The incidence rate for HCAI per 1000 days with a 95% CI, for the 4 warmest months (June-September) was compared with the remaining 8 months, to calculate the incidence rate ratio (IRR). RESULTS: Of 75 629 total infants, 4305 (5.7%) had HCAI (3367 had 1 and 938 had >1 episodes). Infants who had HCAI were of lower gestation, birth weight and Apgar score; but had higher severity of illness scores and clinical chorioamnionitis. There was a borderline increase in all HCAI (IRR 1.05, 95% CI 1.00 to 1.11) and a significant increase in Gram-negative HCAI (IRR 1.20, 95% CI 1.04 to 1.39) during the summer months. Overall, there was a 20% reduction in HCAI from 4.45/1000 days in January 2003 to 3.54/1000 days in December 2009 (mean difference 0.91/1000 days (95% CI 0.89 to 0.92). CONCLUSIONS: Gram-negative infections were significantly increased during the summer months of the year compared with the rest of the year among neonates. Overall, there was a significant temporal reduction in HCAI rates over the study period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".