Socioeconomic status and risk of hospitalization among individuals with cystic fibrosis in Ontario, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Socioeconomic status (SES) is a strong predictor of outcomes in cystic fibrosis (CF); however, there are no published studies evaluating this relationship in Canadians with CF. The objective of this study was to assess the effect of SES on annual hospitalization rates in a large cohort of pediatric and adult CF subjects under a universal health care system. METHODS: A population-based longitudinal study was completed in Ontario from 1993 to 2002 using a comprehensive CF registry containing patient-level data, linked to provincial health care administrative databases. Income quintiles were derived at the neighborhood level using postal code information and Statistics Canada census data. The effect of income quintile on the annual hospitalization rate for respiratory-related illness was estimated by Poisson regression using generalized estimating equations, and was expressed as a rate ratio (RR) and 95% confidence interval (CI). The analysis was adjusted for age, sex, lung function, nutritional status, the presence of diabetes, area of residence, and distance between the subject's residence and the reporting CF centre. RESULTS: A total of 1,174 participants over the age of 6 years contributed 8,444 patient-years of data. No statistically significant differences in annual hospitalization rates for respiratory-related causes were found between the lowest and highest income quintiles (adjusted RR 1.17 [95% CI 0.96-1.43]). The effect of income quintile remained non-significant across a majority of markers of CF disease severity and across a range of subgroups. CONCLUSIONS: After adjusting for important covariates, no SES-disparities in hospitalization rates were found in a large Canadian pediatric and adult CF cohort. It may be the distinctive combination of universal health care, a national network of specialty CF clinics, and drug and travel coverage available in Ontario that results in similar hospitalization rates regardless of SES.
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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) | 0.000 | 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 it