A Prospective Study of Agents Associated With Acute Respiratory Infection Among Young American Indian Children
Bibliographic record
Abstract
BACKGROUND: Native American children have higher rates of morbidity associated with acute respiratory infection than children in the general US population, yet detailed information is lacking regarding their principal clinical presentations and infectious etiologies. METHODS: We pursued a comprehensive molecular survey of bacteria and viruses in nasal wash specimens from children with acute respiratory disease collected prospectively over 1 year (January 1 through December 31, 2009) from 915 Navajo and White Mountain Apache children in their second or third year of life who had been enrolled in an efficacy study of a respiratory syncytial virus monoclonal antibody in the first year of life. RESULTS: During the surveillance period, 1476 episodes of disease were detected in 669 children. Rates of outpatient and inpatient lower respiratory tract illness were 391 and 79 per 1000 child-years, respectively, and were most commonly diagnosed as pneumonia. Potential pathogens were detected in 88% of specimens. Viruses most commonly detected were respiratory syncytial virus and human rhinovirus; the 2009 pandemic influenza A (H1N1) illnesses primarily occurred in the fall. Streptococcus pneumoniae was detected in 60% of subjects; only human rhinovirus was significantly associated with S. pneumoniae carriage. The presence of influenza virus, human rhinovirus or S. pneumoniae was not associated with increased risk for lower respiratory tract involvement or hospitalization. CONCLUSIONS: Acute lower respiratory illnesses occur at disproportionately high rates among young American Indian children and are associated with a range of common pathogens. This study provides critical evidence to support reducing the disproportionate burden of acute respiratory disease among young Native Americans.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".