Evidence map›Paper›PMID 42876460›Full record

ArticleFrontiers in neurology2026

Multimodal evaluation and etiology-oriented management of chronic intracranial venous hypertension.

Jie Shen, Huabin Wang, Long Wang, Yifan Zhang, Sunhong Yan, Jia Wang

Abstract read
In one paragraph

Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jie ShenDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Huabin WangAnhui Provincial International Joint Research Center for Advanced Technology in Medical Imaging, School of Computer Science and Technology, Anhui University, Hefei, Anhui, China.
Long WangDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Yifan ZhangThe Second Clinical Medical College, Anhui Medical University, Hefei, Anhui, China.
Sunhong Yan *Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Jia Wang *Department of Nephropathy, The Third Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic intracranial venous hypertension (CIVHS) comprises a heterogeneous group of disorders characterized by impaired cerebral venous outflow and symptoms related to elevated intracranial pressure. Although venous sinus stenting is increasingly used for venous sinus stenosis with elevated trans-stenotic pressure gradients, venous sinus stenosis is an imaging phenotype rather than a single diagnosis. We retrospectively reviewed 13 consecutive patients with CIVHS who underwent clinical, imaging, and hemodynamic evaluation, including conventional neuroimaging, MR or CT venography, digital subtraction angiography, venous manometry when indicated, and selective high-resolution MRI. All patients initially presented to ophthalmology and had papilledema. Patients were classified according to presumed mechanisms of venous outflow impairment, and treatment was tailored to the anatomical substrate, hemodynamic findings, and clinical context. Six etiological categories were identified: intrinsic transverse sinus stenosis, extrinsic transverse-sigmoid sinus compression, shunt dependency syndrome, jugular foramen stenosis related to chronic organized thrombus, JAK2 V617F mutation-positive essential thrombocythemia with suspected microvascular venous congestion, and dialysis catheter-related central venous stenosis. An additional chronic cerebral venous sinus thrombosis case was included as an illustrative secondary comparator but was not classified as idiopathic intracranial hypertension. Treatments included venous sinus stenting, shunt-related management, hematologic-directed therapy, anticoagulation, acetazolamide, weight control, and conservative management. Among the 13 cohort patients with available follow-up, symptoms improved or remained clinically stable; Case 14 was lost to follow-up. No stent failure was documented during short-term follow-up, but long-term surveillance data were unavailable. These findings support an etiology-oriented, multimodal approach to chronic intracranial venous hypertension.

Indexed as

Disease ManagementIntracranial HypertensionAdultAngiography, Digital SubtractionChronic DiseaseConstriction, PathologicCranial SinusesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMultimodal ImagingPhlebographyRetrospective StudiesStentschronic intracranial venous hypertensionhigh-resolution MRImultimodal imagingvenous manometryvenous sinus stenosisvenous sinus stenting

Identifiers

PMID42876460
PMCPMC13661318

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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.