Incidence of Lower Respiratory Tract Infections and Atopic Conditions in Boys and Young Male Adults: Royal College of General Practitioners Research and Surveillance Centre Annual Report 2015-2016
Bibliographic record
Abstract
BACKGROUND: The Royal College of General Practitioners Research and Surveillance Centre comprises more than 150 general practices, with a combined population of more than 1.5 million, contributing to UK and European public health surveillance and research. OBJECTIVE: The aim of this paper was to report gender differences in the presentation of infectious and respiratory conditions in children and young adults. METHODS: Disease incidence data were used to test the hypothesis that boys up to puberty present more with lower respiratory tract infection (LRTI) and asthma. Incidence rates were reported for infectious conditions in children and young adults by gender. We controlled for ethnicity, deprivation, and consultation rates. We report odds ratios (OR) with 95% CI, P values, and probability of presenting. RESULTS: Boys presented more with LRTI, largely due to acute bronchitis. The OR of males consulting was greater across the youngest 3 age bands (OR 1.59, 95% CI 1.35-1.87; OR 1.13, 95% CI 1.05-1.21; OR 1.20, 95% CI 1.09-1.32). Allergic rhinitis and asthma had a higher OR of presenting in boys aged 5 to 14 years (OR 1.52, 95% CI 1.37-1.68; OR 1.31, 95% CI 1.17-1.48). Upper respiratory tract infection (URTI) and urinary tract infection (UTI) had lower odds of presenting in boys, especially those older than 15 years. The probability of presenting showed different patterns for LRTI, URTI, and atopic conditions. CONCLUSIONS: Boys younger than 15 years have greater odds of presenting with LRTI and atopic conditions, whereas girls may present more with URTI and UTI. These differences may provide insights into disease mechanisms and for health service planning.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".