Evidence map›Paper›PMID 41194161›Full record

ArticleFluids and barriers of the CNS2025

A retrospective longitudinal analysis of risk factors, treatment outcomes and imaging parameters of ventricular collapse in idiopathic intracranial hypertension.

Riccardo Serra, Smruti Mahapatra, Sakibul Huq, Michael Meggyesy, Noah Leviton Gorelick, Lacie Manthripragada, Abhay Moghekar, Mark Gregory Luciano

Abstract read
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In one paragraph

Article in Fluids and barriers of the CNS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Riccardo SerraDepartment of Neurosurgery, University of Maryland School of Medicine, 22 St Greene Street, Baltimore, 21201, MD, USA. rserra@som.umaryland.edu.
Smruti MahapatraDepartment of Biomedical Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA.
Sakibul HuqDepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Michael MeggyesyDepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Noah Leviton GorelickDepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Lacie ManthripragadaDepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abhay MoghekarDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Mark Gregory LucianoDepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveVentricular collapse is a prevalent yet poorly understood complication of ventriculo-peritoneal shunting (VPS) in idiopathic intracranial hypertension (IIH). By identifying the risk factors of ventricular collapse (VC), this study aims to characterize the clinical progression and treatment of IIH and its complications. The relationships between ventricular area, symptoms and treatments were assessed longitudinally with ventricular segmentation on MRI/CT imaging, and correlated with other risk factors of IIH and VC.

methodsWe retrospectively reviewed 147 patients who underwent VPS for IIH at our Institution, and identified 73 shunt-naïve subjects. Manual segmentation of CT/MRI scans was performed at each clinical stage (baseline, post-shunting, post-collapse and after each intervention). Variables collected included valve type and opening-pressure, shunt revisions, use of anti-siphoning devices (ASD), comorbidities, venous sinus hypoplasia/stenosis, stenting, general demographics. Linear univariate regression models were used to determine the association between individual risk factors and VC, and quantitatively assess the effect of treatment. Two multivariate models were tested, including Pre-Shunting and Post-Shunting variables, to quantify their association with VC.

resultsOf 73 IIH patients with new shunts, 32 experienced collapse (uni- or bilateral, 26.5% of the total). In shunt-naïve patients, collapse was associated with pre-shunting (rho = −0.36; p = 0.001) and post-shunting ventricular area (rho = 0.62; p = 0.0002). Both collapse and ventricular area were correlated with shunt-related symptoms at 6 months (rho = −0.29; p = 0.01). Shunt adjustment, addition of ASDs, valve replacement proved to be effective strategies to re-expand the ventricles and reduce symptoms. Nonetheless, a significant fraction of patients remained symptomatic after multiple treatments, suggesting a complex etiology for VC. On univariate analysis, catheter revisions were more common in the VC group, while the multivariate model with Post-Shunting factors was significantly associated with VC.

conclusionsIn newly VP-shunted IIH patients, small ventricular area predisposes to collapse and headaches, while higher valve settings and ASDs may reduce the risk of collapse and promote symptomatic improvement. Within the restraints of a retrospective analysis, this study is the first to analyze the risk factors of VC in IIH patients, longitudinally integrating the clinical progression with ventricular imaging. Further studies are warranted to better understand the clinical progression of collapse.

Indexed as

Cerebral VentriclesPostoperative ComplicationsPseudotumor CerebriVentriculoperitoneal ShuntAdolescentAdultFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesRisk FactorsTomography, X-Ray ComputedTreatment OutcomeIdiopathic intracranial hypertensionPseudotumor cerebriSlit-ventricle syndromeVentricular collapse

Identifiers

PMID41194161
PMCPMC12587583

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.