Venous sinus stenting for idiopathic intracranial hypertension: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Stenting of the intracranial venous sinuses is used as a treatment in certain cases of idiopathic intracranial hypertension (IIH). Interest in, and experience of, this technique is growing, particularly in recent years. We sought to provide an updated systematic review and meta-analysis of the use of venous stenting in these patients, examining clinical outcomes. METHODS: A literature search of venous stenting in IIH patients was performed. Using random-effects meta-analysis, we evaluated the following outcomes: clinical resolution of papilledema; headaches and pulsatile tinnitus; recurrence of symptoms after stenting; and complications. RESULTS: . Median follow-up was 18 months. The overall rate of improvement in papilloedema was 93.7% (95% CI 90.5% to 96.9%), while the overall rate of improvement or resolution of headache was 79.6% (95% CI 73.3% to 85.9%). Pulsatile tinnitus resolved in 90.3% (95% CI 83.8% to 96.70%), while the overall rate of recurrence of IIH symptoms after stenting was 9.8% (95% CI 6.7% to 13%). The rate of major complications was 1.9% (95% CI 0.07% to 3.1%). CONCLUSIONS: Venous sinus stenting in patients with IIH who are refractory to medical therapy appears to have an excellent safety profile and is associated with significant improvements in headaches, pulsatile tinnitus, and papilledema.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.028 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".