Risk Factors and Viruses Associated With Hospitalization Due to Lower Respiratory Tract Infections in Canadian Inuit Children
Bibliographic record
Abstract
OBJECTIVES: To examine risk factors for lower respiratory tract infections (LRTI) hospital admission in the Canadian Arctic. METHODS: This was a case-control study during a 14-month period among children less than 2 years of age. Cases were admitted to the Baffin Regional Hospital in Iqaluit, Nunavut with LRTI. Controls were age matched and came from Iqaluit and 2 communities. Odds ratios (ORs) of hospital admission for LRTI were estimated through multivariate conditional logistic regression modeling for following risk factors: smoking in pregnancy, Inuit race, prematurity, adoption status, breast-feeding, overcrowding, and residing outside of Iqaluit. Viruses in nasophayngeal aspirates were sought at the time of each hospital admission. RESULTS: There were 101 age-matched cases and controls. The following risk factors were significantly associated with an increased risk of admission for LRTI (adjusted OR): smoking in pregnancy (OR = 4.0; 95% CI: 1.1-14.6), residence outside of Iqaluit (OR = 2.7; 95% CI: 1.0 -7.2), full Inuit race (OR = 3.8; 95% CI: 1.1-12.8), and overcrowding (OR = 2.5, 95% CI: 1.1- 6.1). Non-breast-fed children had a 3.6-fold risk of being admitted for LRTI (95% CI: 1.2-11.5) and non-breast-fed adopted children had a 4.4-fold increased risk (95% CI: 1.1-17.6) when compared with breast-fed, nonadopted children. Prematurity was not associated with an increased risk of admission. Viruses were identified in 88 (72.7%) of admissions, with respiratory syncytial virus being identified in the majority of admissions, 62 (51.2%). Multiple viruses were isolated in 19 (15.7%) admissions. CONCLUSIONS: Smoking during pregnancy, place of residence, Inuit race, lack of breast-feeding, and overcrowding were all independently associated with increased risk of hospital admission for LRTI among Inuit children less than 2 years of age. Future research on the role of adoption and genetics on the health of Inuit children are required.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".