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O-025 Geographical influence on aneurysm treatment outcomes and retreatment rates

2012· article· en· W2315885196 on OpenAlexaff
Charles J. Prestigiacomo, J Mocco, Steven W. Hetts, Gary M. Nesbit, Yuichi Murayama, Carolyn E MacDougall, S. Claiborne Johnston, Guojun Ge, Simon Jung, A. Gholkar, Demetrius K. Lopes, John Perl, Donatella Tampieri, Aquilla S Turk

Bibliographic record

VenueJournal of NeuroInterventional Surgery · 2012
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMedicineDemographicsAneurysmClinical trialPost-hoc analysisSurgeryInternal medicineRadiologyDemography

Abstract

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Background and Purpose Recent data from HELPS, Cerecyte and MAPS trials demonstrate that aneurysms can be safely and effectively treated using various coils. Comparing outcomes between trials can be difficult due to different trial designs. The very low bleeding or rebleeding rates of treated aneurysms has led most investigators to use angiographic outcomes to compare devices. Angiographic assessments are operator-dependent, potentially affecting trial results. We sought to understand the impact of geography on aneurysm retreatment in patients enrolled in the Matrix and Platinum Science (MAPS) Trial. Materials and Methods Post hoc analysis was performed on MAPS trial data. Patients were stratified into two groups based on treating center location. Centers were categorized as being in North America (NA) or International (INTL). Baseline patient demographics, comorbidities, and aneurysms characteristics that could impact treatment outcomes were analyzed. Procedural complications and clinical and angiographic outcomes were compared. Results 407 patients (115 ruptured, 292 elective) from 28 NA sites and 219 patients (113 ruptured, 140 elective) from 15 INTL sites were evaluated. Patient demographics differed between NA and INTL, with the most significant (p<0.0001) differences being the proportion of female patients (76% vs 60%), ruptured aneurysms (28% vs 52%), Caucasians (86% vs 72%) and two or more Cardiovascular Risk Factors (31% vs 15%). A H&H score of III or IV was more prevalent in the NA ruptured patients (33% vs 21% p=0.0452). NA treated more posterior circulation aneurysms (16% vs 8% p=0.0064), more aneurysms with neck ≥4 mm (39% vs 31%, p=0.0353) and more patients >55 years old (54% vs 40%, p=0.0014). The angiographic core lab found 56.2% of NA aneurysms were completely or nearly completely occluded post-procedure vs 73.5% in INTL (p=0.0002). Packing density of >25% was similar in NA (41.3%) and INTL (37.4%) groups. Stents were used more frequently in unruptured aneurysms treated in NA than INTL (44% vs 19%, respectively, p<0.0001). At 30 days, NA ruptured patients were more likely to have been discharged than INTL patients (85.2% vs 66.4%, p=0.0101). At 1 year, there was no difference in the proportion of patients alive and free of disability (>90% of ruptured and >96% of unruptured), and no difference in the proportion of residual aneurysms (36.6% vs 28.7%, p=0.082). Ruptured aneurysms were more likely to have been retreated in NA vs INTL (21.7% vs 4.4%, p=0.0001); there was no significant difference in retreatment rates among unruptured aneurysms. NA sites retreated 49.2% of aneurysms that were operator-assessed as having residuals at 1 year, while INTL sites retreated 19.0% (p=0.0156). This difference in retreatment resolved at 2 years, with residual aneurysm retreatment rates being nearly equivalent on preliminary 2-year follow-up data. Conclusion Endovascular treatment practices for intracranial aneurysms are very different between NA and INTL sites, likely reflecting practice variation rather than individual patient differences. Retreatment of partially occluded aneurysms tends to occur more frequently in the first year in NA but later elsewhere. This trend has critical value when interpreting trials results that report short-term outcomes. Competing interests C Prestigiacomo: Thermopeutix, Edge Therapeutics, Stryker. J Mocco: None. S Hetts: None. G Nesbit: None. Y Murayama: None. C Macdougall: None. S Johnston: None. G Ge: Stryker Neurovascular. S Jung: Stryker Neurovascular. A Gholkar: None. D Lopes: None. J Perl: None. D Tampieri: None. A Turk: None.

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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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0000.000

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 head0.040
GPT teacher head0.312
Teacher spread0.272 · 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.

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".

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Published2012
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