Safety and Efficacy of Metformin for Idiopathic Intracranial Hypertension: A U.S.-Based Real-World Data Retrospective Multicenter Cohort Study
Bibliographic record
Abstract
Introduction: Managing idiopathic intracranial hypertension (IIH) is challenging due to limited treatment options. This study evaluates metformin as a potential therapy for IIH, examining its impact on disease outcomes and safety. Methods: We performed a retrospective cohort study using the TriNetX database, covering data from 2009 to August 2024. The study included IIH patients, excluding those with other causes of raised intracranial pressure or pre-existing diabetes. Propensity score matching adjusted for age, sex, race, ethnicity, Hemoglobin A1C, and baseline BMI at metformin initiation. We assessed outcomes up to 24 months. Results: Initially, 1,268 patients received metformin and 49,262 served as controls, showing disparities in various parameters. After matching, both groups consisted of 1,267 patients each. Metformin users had significantly lower risks of papilledema, headache, and refractory IIH at all follow-ups (p<0.0001). They also had fewer spinal punctures and reduced acetazolamide use. BMI reductions were more significant in the metformin group from 6 months onward (p<0.0001), with benefits persisting regardless of BMI changes. Metformin's safety profile was comparable to the control group. Conclusions: The study indicates metformin's potential as a disease-modifying treatment in IIH, with improvements across multiple outcomes independent of weight loss. This suggests complex mechanisms at play, supporting further research through prospective clinical trials to confirm metformin's role in IIH management and its mechanisms of action.
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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 | 0.005 |
| 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 | 0.000 |
| 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".