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Record W1845910220 · doi:10.1177/159101990000600302

Palliative Embolisation of Brain Arteriovenous Malformations Presenting with Progressive Neurological Deficit

2000· article· en· W1845910220 on OpenAlexaff
Mahmoud AlYamany, Karel G. terBrugge, Robert A. Willinsky, Walter Montanera, Michael Tymianski, M. Christopher Wallace

Bibliographic record

VenueInterventional Neuroradiology · 2000
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineNeurological deficitPalliative careArteriovenous malformationPalliative treatmentEmbolizationSurgeryPediatrics

Abstract

fetched live from OpenAlex

SUMMARY: Large arteriovenous malformations (AVMs) located in eloquent areas of the brain are generally considered incurable because of the high morbidity and mortality associated with their treatment. When these patients develop a progressive neurological deficit they in time often become severely disabled. This report presents the results of palliative embolisation in this subgroup of patients. Analysis of our data-base of 714 patients with known brain AVMs revealed 17 patients who presented with progressive neurological deficit and who underwent palliative embolisation as the therapeutic modality of choice for management of their AVM. One patient was excluded due to lack of follow-up and two were excluded because they later received radiation therapy. Following embolisation 43% had improvement of their neurological deficit, 50% stabilized and 7% continued to deteriorate and these clinical results persisted for an average of more than 2 years follow-up. Transient neurological morbidity associated with embolisation treatment was 7% and there was no permanent morbidity and no mortality. Palliative embolisation of brain AVMs presenting with progressive neurological deficits arrested deterioration in more than 90% of patients and was associated with low morbidity and no mortality.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.290
Teacher spread0.267 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations14
Published2000
Admission routes1
Has abstractyes

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