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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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.815

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 head0.024
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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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