Obesity and Weight Loss in Idiopathic Intracranial Hypertension: A Narrative Review
Bibliographic record
Abstract
BACKGROUND: Most patients with idiopathic intracranial hypertension (IIH) are obese. Weight loss is felt to be an important factor in improving IIH. The mechanism by which weight loss leads to a reduction in elevated intracranial pressure is unclear. Evidence from prospective studies evaluating the role of weight loss in IIH is lacking. EVIDENCE ACQUISITION: We performed a detailed review of the published literature regarding the association of IIH and obesity, including proposed pathogenetic mechanisms, and the effect of weight loss and weight-loss interventions in IIH. References were identified by searching PubMed with the terms idiopathic intracranial hypertension and weight loss. Additional citations were found in the identified references. RESULTS: Over 90% of IIH patients are obese or overweight. The risk of IIH increases as a function of body mass index (BMI) and weight gain over the preceding year. The risk of IIH-induced vision loss also increases with increasing BMI, especially with BMI >40 kg/m. Several mechanisms have been proposed linking obesity to the development of IIH but the pathophysiology remains unknown. Published studies and clinical observations strongly support weight loss as an effective treatment, although there are no prospective controlled trials. Weight loss in the range of 6%-10% often leads to IIH remission. Weight loss of ≥5% at 1 year is achieved in roughly 50%-70% of patients if they are enrolled in a high-intensity lifestyle modification program and in 20%-35% of patients if they direct their own weight loss. Weight is typically regained over 1-3 years but about a third of patients maintain ≥5% weight loss over the long term. Patients treated initially with lifestyle modification therapy show a modest persisting benefit over self-directed patients. Selected commercial weight loss programs also may improve long-term maintenance of weight loss. New antiobesity drugs significantly improve the proportion of obese patients who have ≥5% loss of weight at 1 year. CONCLUSIONS: Obesity is an important contributing factor for the development of IIH, although the pathophysiological mechanism linking obesity to IIH is unknown. The risk of developing IIH and associated visual loss increases with increasing BMI. Weight loss is an effective treatment for IIH. Long-term maintenance of initial weight loss is helped modestly by lifestyle modification programs and possibly by selected commercial weight loss programs. New antiobesity drugs may provide further options for IIH therapy in the future.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".