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Record W1932162856 · doi:10.1177/159101991301900113

The Cost of Materials for Intra-Arterial Thrombectomy

2013· article· en· W1932162856 on OpenAlexaff
F. Bing, Grégory Jacquin, Alex Poppe, Daniel Roy, Jean Raymond, Alain Weill

Bibliographic record

VenueInterventional Neuroradiology · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsHôpital Notre-Dame
Fundersnot available
KeywordsTIMIMedicineThrombolysisModified Rankin ScaleStroke (engine)Myocardial infarctionOcclusionRadiologyCardiologyInternal medicineSurgeryIschemic strokeIschemia

Abstract

fetched live from OpenAlex

This paper reports the cost of endovascular materials used for the treatment of large-vessel ischemic stroke in the anterior circulation according to the angiographic score and clinical results at three months. From November 2009 to July 2011, 57 ischemic patients (mean age, 64.6 ±13.8 years) with anterior large vessel occlusion were included. Mean National Institutes of Health Stroke Scale (NIHSS) on admission was 18.4 ± 4.9. Mean duration of symptoms until the arterial puncture was 207±67 minutes. Recanalization was assessed using the Thrombolysis In Myocardial Infarction (TIMI) score. Patient selection was performed on a non-enhanced CT scanner. According to the TIMI final angiographic score and the modified Rankin score (mRS) at three months, we determined the cost of the material used. Complete (n=12, TIMI grade 3) or partial perfusion (n=35, TIMI grade 2) was achieved in 47 (82.5%) lesions. At three months, 33.3% (n=19) had a mRS score ≤ 2. The mean cost of the material used in the operative room was 5018±2402 euro. Intra-arterial thrombolysis presents a substantial initial cost and the long-term economic impact has to be evaluated. Our health system has to take the price of these new technologies into account for future medical choices and urgently evaluate them in randomized controlled trials.

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)0.001
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.024
GPT teacher head0.300
Teacher spread0.276 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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