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Record W4414083237 · doi:10.1007/s00701-025-06658-6

Ultrasonographic assessment of bypass capacity after revascularization surgery in moyamoya disease: a systematic review and single-arm meta-analysis

2025· review· en· W4414083237 on OpenAlexaboutno aff
Nedret Koç, Maurycy Rakowski, Samuel D. Pettersson, Paulina Skrzypkowska, Tomasz Szmuda, Piotr Zieliński

Bibliographic record

VenueActa Neurochirurgica · 2025
Typereview
Languageen
FieldMedicine
TopicMoyamoya disease diagnosis and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsRevascularizationNeuroradiologyUltrasoundInterventional radiologyBypass surgerySurgical anastomosisDerivation

Abstract

fetched live from OpenAlex

PURPOSE: Moyamoya disease (MMD) is a chronic cerebrovascular disorder characterized by progressive arterial stenosis and fragile collateral formation, elevating stroke risk. Revascularization is the standard treatment, yet up to 27% of patients experience ischemic events within a year due to bypass insufficiency. While digital subtraction angiography (DSA) remains the gold standard for assessing bypass function, it is invasive and time-consuming. This study evaluates ultrasonography (US) as a noninvasive, cost-effective tool to assess bypass capacity post-revascularization in MMD. METHODS: A systematic search was conducted following PRISMA guidelines. PubMed, Web of Science, and Scopus were searched for studies reporting US parameters with control imaging confirming bypass capacity. Study quality was assessed using the Newcastle-Ottawa Scale. Mean difference (MD) values were calculated using random-effects models. High bypass capacity was defined as good patency or favorable collateral development. RESULTS: Eight cohort studies comprising 264 MMD patients and 301 operated hemispheres were included, with 180 demonstrating high bypass capacity. Within two weeks post-surgery, increased superficial temporal artery (STA) peak systolic velocity (PSV, MD = 28.26, p < 0.0001), mean flow velocity (MFV, MD = 22.97, p = 0.03), end-diastolic velocity (EDV, MD = 33.45, p < 0.0001), and decreased resistance index (RI, MD = -0.09, p = 0.006) were predictive. External carotid artery (ECA) EDV (MD = 13.92, p = 0.04) was also significant. At 3-6 months, elevated EDV in both STA (MD = 8.13, p = 0.006) and ECA (MD = 8.71, p = 0.0002) remained predictive. In the indirect subgroup, lower anterior cerebral artery (ACA) MFV within 0-3 months predicted favorable outcomes (MD = -64.98, p = 0.001). CONCLUSIONS: Changes in STA and ECA US parameters measured following revascularization surgery predict high bypass capacity. Decreased ACA MFV suggests effective revascularization after indirect surgery. Ultrasound modality offers a valuable, noninvasive tool for postoperative assessment in MMD.

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)0.009
metaresearch head score (Gemma)0.023
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.024
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.071
GPT teacher head0.336
Teacher spread0.265 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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