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Record W4294335507 · doi:10.1212/wnl.0000000000200978

Development of the SAFETEA Scores for Predicting Risks of Complications of Preventive Endovascular or Microneurosurgical Intracranial Aneurysm Occlusion

2022· article· en· W4294335507 on OpenAlexaff
A. Algra, Jacoba P. Greving, Jordi de Winkel, Arttu Kurtelius, Kamil G. Laban, Dagmar Verbaan, René van den Berg, W. Peter Vandertop, Antti Lindgren, Timo Krings, Peter Y. M. Woo, George Kwok Chu Wong, Bob Roozenbeek, Adriaan C.G.M. van Es, Rúben Dammers, Nima Etminan, Hieronymus D. Boogaarts, Tristan P. C. van Doormaal, Albert van der Zwan, Irene C. van der Schaaf, Gabriël J.E. Rinkel, Mervyn D. I. Vergouwen

Bibliographic record

VenueNeurology · 2022
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineAneurysmSubarachnoid hemorrhageClipping (morphology)Endovascular coilingSurgeryOcclusionAsymptomaticStentConcordanceEndovascular treatmentRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Background and Objectives Preventive unruptured intracranial aneurysm (UIA) occlusion can reduce the risk of subarachnoid hemorrhage, but both endovascular and microneurosurgical treatment carry a risk of serious complications. To improve individualized management decisions, we developed risk scores for complications of endovascular and microneurosurgical treatment based on easily retrievable patient, aneurysm, and treatment characteristics. Methods For this multicenter cohort study, we combined individual patient data from patients with UIA aged 18 years or older undergoing preventive endovascular treatment (standard, balloon-assisted or stent-assisted coiling, Woven EndoBridge-device, or flow-diverting stent) or microneurosurgical clipping at one of the 10 participating centers from 3 continents between 2000 and 2018. The primary outcome was death from any cause or clinical deterioration from neurologic complications ≤30 days. We selected predictors based on previous knowledge about relevant risk factors and predictor performance and studied the association between predictors and complications with logistic regression. We assessed model performance with calibration plots and concordance (c) statistics. Results Of the 1,282 included patients, 94 (7.3%) had neurologic symptoms that resolved <30 days, 140 (10.9%) had persisting neurologic symptoms, and 6 died (0.5%). At 30 days, 52 patients (4.1%) were dead or dependent. Predictors of procedural complications were size of aneurysm, aneurysm location, familial subarachnoid hemorrhage, earlier atherosclerotic disease, treatment volume, endovascular modality (for endovascular treatment) or extra aneurysm configuration factors (for microneurosurgical treatment, branching artery from aneurysm neck or unfavorable dome-to-neck ratio), and age (acronym: SAFETEA). For endovascular treatment (n = 752), the c-statistic was 0.72 (95% CI 0.67–0.77) and the absolute complication risk ranged from 3.2% (95% CI 1.6%–14.9%; ≤1 point) to 33.1% (95% CI 25.4%–41.5%; ≥6 points). For microneurosurgical treatment (n = 530), the c-statistic was 0.72 (95% CI 0.67–0.77) and the complication risk ranged from 4.9% (95% CI 1.5%–14.9%; ≤1 point) to 49.9% (95% CI 39.4%–60.6%; ≥6 points). Discussion The SAFETEA risk scores for endovascular and microneurosurgical treatment are based on 7 easily retrievable risk factors to predict the absolute risk of procedural complications in patients with UIAs. The scores need external validation before the predicted risks can be properly used to support decision-making in clinical practice. Classification of Evidence This study provides Class III evidence that SAFETEA scores predict the risk of procedural complications after endovascular and microneurosurgical treatment of unruptured intracranial aneurysms.

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)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.297
Teacher spread0.259 · 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 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

Citations12
Published2022
Admission routes1
Has abstractyes

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