Idiopathic Intracranial Hypertension and Socioeconomic Status in the Greater Toronto Area, Canada
Bibliographic record
Abstract
BACKGROUND: Previous studies have identified an association between obesity and socioeconomic variables such as poverty, minority status, and a low level of education. Because obesity is a major risk factor for the development of idiopathic intracranial hypertension (IIH), this study aims to identify and assess relationships between socioeconomic and geographic variables in patients with IIH in Canada. METHODS: A retrospective chart review was performed to identify female patients with IIH presenting to 2 neuro-ophthalmology clinics in Toronto between 2014 and 2022. Consecutive female patients younger than 50 years who did not have IIH were identified as controls. Patient age, body mass index (BMI), and postal code were obtained from electronic medical records. Patient postal codes were then converted to geographic dissemination areas based on the 2016 Canadian census, and data on socioeconomic outcomes were collected from Statistics Canada. RESULTS: Three hundred twenty-two female patients with IIH (mean age: 32.3 ± 10) and 400 female controls (mean age: 33.9 ± 9) were included. The mean BMI was 35.0 ± 8 for patients with IIH and 26.7 ± 7 for control patients ( P < 0.00001). There was a significant difference between dissemination areas resided by patients with IIH and control patients for median income ($34640 vs $36685 CAD, P = 0.02) and rate of postsecondary degree attainment (57.7% vs 60.5%, P = 0.01). There were no significant differences in the percentage of visible minorities, percentage of immigrants, knowledge of official languages, percentage of married individuals, average household size, or unemployment rate. There was a weak but significant inverse relationship between the rate of postsecondary degree attainment in dissemination areas resided by patients with IIH and their BMI ( P = 0.01, R 2 = 0.02). CONCLUSION: Patients with IIH reside in geographic areas with lower average levels of income and education than control patients. Patients with lower levels of education may be at higher risk of elevated BMI and therefore disease incidence and progression.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".