Cardiometabolic Outcomes in Idiopathic Intracranial Hypertension: An International Matched-Cohort Study
Bibliographic record
Abstract
Introduction: Idiopathic intracranial hypertension (IIH) has been traditionally viewed as a neuro-ophthalmic disorder, yet emerging evidence suggests broader systemic implications. Our study investigates the cardiometabolic outcomes associated with IIH through a comprehensive matched-cohort analysis. Methods: We conducted a retrospective analysis of electronic health records from 2009 to 2024. We compared IIH patients with matched controls using propensity score matching based on age, sex, race, ethnicity, and baseline BMI. Cardiovascular and metabolic outcomes were assessed over a ten-year follow-up period, with additional stratified analyses comparing obese and non-obese subgroups. Results: IIH patients demonstrated significantly increased risks of ischemic stroke/TIA (RR 2.515, 95% CI 2.250-2.812) and non-traumatic hemorrhagic stroke (RR 7.744, 95% CI 6.118-9.801). Notable metabolic findings included elevated risks of insulin resistance (RR 1.470, 95% CI 1.258-1.717) and type 2 diabetes mellitus (RR 1.210, 95% CI 1.171-1.250). These associations persisted in non-obese IIH patients, suggesting pathogenic mechanisms independent of adiposity. Additionally, IIH patients showed increased prevalence of polycystic ovarian syndrome (RR 1.470, 95% CI 1.258-1.717) and metabolic syndrome (RR 1.125, 95% CI 1.045-1.205). Conclusions: Our findings highlight IIH as a complex multisystem disorder with significant cardiometabolic implications beyond its traditional neuro-ophthalmic presentation. The findings suggest the need for comprehensive cardiovascular and metabolic screening in IIH patients, regardless of BMI status, and indicate potential novel therapeutic targets for investigation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".