Diabetes Screening Among Immigrants: A population-based urban cohort study
Why this work is in the frame
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Bibliographic record
Abstract
To examine diabetes screening, predictors of screening, and the burden of undiagnosed diabetes in the immigrant population and whether these estimates differ by ethnicity. A population-based retrospective cohort linking administrative health data to immigration files was used to follow the entire diabetes-free population aged 40 years and up in Ontario, Canada (N = 3,484,222) for 3 years (2004-2007) to determine whether individuals were screened for diabetes. Multivariate regression was used to determine predictors of having a diabetes test. Screening rates were slightly higher in the immigrant versus the general population (76.0 and 74.4%, respectively; P < 0.001), with the highest rates in people born in South Asia, Mexico, Latin America, and the Caribbean. Immigrant seniors (age =65 years) were screened less than nonimmigrant seniors. Percent yield of new diabetes subjects among those screened was high for certain countries of birth (South Asia, 13.0%; Mexico and Latin America, 12.1%; Caribbean, 9.5%) and low among others (Europe, Central Asia, U.S., 5.1-5.2%). The number of physician visits was the single most important predictor of screening, and many high-risk ethnic groups required numerous visits before a test was administered. The proportion of diabetes that remained undiagnosed was estimated to be 9.7% in the general population and 9.0% in immigrants. Overall diabetes-screening rates are high in Canada's universal health care setting, including among high-risk ethnic groups. Despite this finding, disparities in screening rates between immigrant subgroups persist and multiple physician visits are often required to achieve recommended screening levels.
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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) | 0.061 | 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