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Record W4361292160 · doi:10.1016/j.wnsx.2023.100189

Clinical efficacy of endovascular treatment approach in patients with carotid cavernous fistula: A systematic review and meta-analysis

2023· review· en· W4361292160 on OpenAlexaff
Aryoobarzan Rahmatian, Shirin Yaghoobpoor, Arian Tavasol, Komeil Aghazadeh-Habashi, Zahra Hasanabadi, Matin Bidares, Borna Safari‐Kish, Robert M. Starke, Evan Luther, Mohammadreza Hajiesmaeili, Fatemeh Sodeifian, Tara Fazel, Mina Dehghani, Reza Ramezan, Masood Zangi, Niloofar Deravi, Reza Goharani, Mobina Fathi

Bibliographic record

VenueWorld Neurosurgery X · 2023
Typereview
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsUniversity of Waterloo
FundersShahid Beheshti University of Medical SciencesCotton Research and Development Corporation
KeywordsMedicineChemosisCarotid-cavernous fistulaMeta-analysisCavernous sinusSurgeryPresentation (obstetrics)CohortInternal medicine

Abstract

fetched live from OpenAlex

Carotid-cavernous fistulas (CCFs) represent a group of rare, abnormal arteriovenous communications between the carotid arterial system and the cavernous sinuses (CS). CCFs often produce ophthalmologic symptoms related to increased CS pressures and retrograde venous drainage of the eye. Although endovascular occlusion remains the preferred treatment for symptomatic or high-risk CCFs, most of the data for these lesions is limited to small, single-center series. As such, we performed a systematic review and meta-analysis evaluating endovascular occlusions of CCFs to determine any differences in clinical outcomes based on presentation, fistula type, and treatment paradigm. A retrospective review of all studies discussing the endovascular treatment of CCFs published through March 2023 was conducted using PubMed, Scopus, Web of Science, and Embase databases. A total of 36 studies were included in the meta-analysis. Data from the selected articles were extracted and analyzed using Stata software version 14. 1494 patients were included. 55.08% were female and the mean age of the cohort was 48.10 years. A total number of 1516 fistulas underwent endovascular treatment, 48.05% of which were direct and 51.95% of which were indirect. 87.17% of CCFs were secondary to a known trauma while 10.18% were spontaneous. The most common presenting symptoms were 89% exophthalmos (95% CI: 78.0–100.0; I2 = 75.7%), 84% chemosis (95% CI: 79.0–88.0; I2 = 91.6%), 79% proptosis (95% CI: 72.0–86.0; I2 = 91.8%), 75.0% bruits (95% CI: 67.0–82.0; I2 = 90.7%), 56% diplopia (95% CI: 42.0–71.0; I2 = 92.3%), 49% cranial nerve palsy (95% CI: 32.0–66.0; I2 = 95.1%), 39% visual decline (95% CI: 32.0–45.0; I2 = 71.4%), 32% tinnitus (95% CI: 6.0–58.0; I2 = 96.7%), 29% elevated intraocular pain (95% CI: 22.0–36.0; I2 = 0.0%), 31% orbital or pre-orbital pain (95% CI: 14.0–48.0; I2 = 89.9%) and 24% headache (95% CI: 13.0–34.0; I2 = 74.98%). Coils, balloons, and stents were the three most used embolization methods respectively. Immediate complete occlusion of the fistula was seen in 68% of cases and complete remission was seen in 82%. Recurrence of CCF occurred in only 35% of the patients. Cranial nerve paralysis after treatment was observed in 7% of the cases. Exophthalmos, Chemosis, proptosis, bruits, cranial nerve palsy, diplopia, orbital and periorbital pain, tinnitus, elevated intraocular pressure, visual decline and headache are the most common clinical manifestations of CCFs. The majority of endovascular treatments involved coiling, balloons and onyx and a high percentage of CCF patients experienced complete remission with the improvement of their clinical symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.030
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.130
GPT teacher head0.354
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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