Semaglutide as an Adjunctive Therapy to Standard Management for Idiopathic Intracranial Hypertension: A Real-World Data-Based Retrospective Analysis
Bibliographic record
Abstract
Abstract Background Idiopathic intracranial hypertension (IIH) is a neurological disorder characterized by elevated intracranial pressure, predominantly affecting young women with obesity. This study evaluates the effectiveness of semaglutide as an adjunctive therapy to standard IIH management using real-world data. Methods We conducted a retrospective cohort analysis comparing IIH patients receiving semaglutide plus standard therapy versus standard therapy alone. After propensity score matching, we analyzed 635 patients in each cohort. Primary outcomes included papilledema, headache manifestations, visual disturbances, and refractory disease status at 3-months, 6-months, 12-months, and 24-months. Secondary outcomes included BMI changes. Result Semaglutide demonstrated significant improvements across all outcomes. At three months, the treatment group showed reduced risks of visual disturbances (RR 0.28, 95% CI 0.179-0.440, p=0.0001), papilledema (RR 0.366, 95% CI 0.260-0.515, p=0.0001), and headache (RR 0.578, 95% CI 0.502-0.665, p=0.0001). These benefits persisted through 24 months. Refractory disease risk was reduced by 40% at three months (RR 0.6, 95% CI 0.520-0.692, p=0.0001). The semaglutide group showed progressive BMI reduction, with a baseline-adjusted difference of -1.38 kg/m 2 (95% CI [-1.671, -1.089], p<0.0001) at 24 months. Conclusions Semaglutide as an adjunctive therapy demonstrates significant and sustained improvements in IIH-related outcomes, including visual disturbances, papilledema, and headache symptoms. These findings suggest semaglutide may be a valuable addition to standard IIH management protocols, particularly for patients with refractory disease.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".