Hospital admission rates for lower respiratory tract infections in infants in the Northwest Territories and the Kitikmeot region of Nunavut between 2000 and 2004
Bibliographic record
Abstract
BACKGROUND: Health care workers have long observed increased rates of hospital admissions for respiratory illness in infants from the northern regions of Canada. Particularly high rates have been reported in the Inuit population. The purpose of the present study was to compare rates of hospital admission in Inuit versus non-Inuit infants from the perspective of a single northern health region. METHODS: A retrospective review of all hospital admissions for lower respiratory tract infections (LRTIs) in infants from the Northwest Territories and the Kitikmeot region of Nunavut between 2000 and 2004 was completed and admission rates were compared by health region. RESULTS: Hospital admission rates for LRTIs in infants were above the Canadian rate for all regions. The rate of hospital admission for LRTIs in infants from the Kitikmeot region of Nunavut was dramatically high at 590 hospital admissions/1000 live births in the first 12 months of life. The majority of hospitalized infants were previously healthy, non-breastfed term infants with no underlying disease. INTERPRETATION: The rate of hospital admission in the Kitikmeot region of Nunavut is the highest reported in the current literature. The reason for such significant morbidity is difficult to explain and raises the question of an underlying predisposition to severe disease in this infant population. The question warrants further study to gain a better understanding of risk factors as well as the role of prevention.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".