MétaCan
Menu
← Back to cohort

O-002 Lifetime benefit and cost consequences of the achieved grade of reperfusion after thrombectomy for stroke based on hermes collaboration data

2018· article· en· W2907679006 on OpenAlexaffabout
Wolfgang G. Kunz, Mohammed Almekhlafi, Bijoy K. Menon, Jeffrey L. Saver, Diederik W.J. Dippel, Charles B.L.M. Majoie, David S. Liebeskind, Tudor G. Jovin, Antoni Dávalos, Serge Bracard, Françis Guillemin, Bruce Campbell, Peter Mitchell, Phil White, Keith W. Muir, Scott Brown, Andrew M. Demchuk, Michael D. Hill, Mayank Goyal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineThrombolysisStroke (engine)Quality-adjusted life yearWaiting listHealth careEconomic evaluationCost–benefit analysisEmergency medicineCost effectivenessMyocardial infarctionSurgeryCardiologyTransplantation

Abstract

fetched live from OpenAlex

Purpose The benefit that endovascular thrombectomy (EVT) offers to stroke patients with large vessel occlusions depends strongly on reperfusion grade as defined by the eTICI (extended Thrombolysis in Cerebral Infarction) scale. Our aim was to determine the lifetime quality of life and cost consequences of reperfusion for patients, healthcare systems, and society. Materials and methods A Markov model estimated lifetime quality-adjusted life years (QALY) of EVT-treated patients and associated costs based on eTICI grades. The analysis was performed from a United States perspective with two cost frameworks: 1) healthcare costs and 2) societal costs, which include productivity losses and costs of informal care given by family members. Input parameters were based on best available evidence, including patient data from the 7-trial HERMES collaboration (ESCAPE, EXTEND-IA, MR CLEAN, REVASCAT, SWIFT PRIME, PISTE, THRACE). The lead analysis was conducted for stroke onset at 65 years. Probabilistic sensitivity analysis was performed using Monte Carlo simulations. Results Lifetime QALYs increased for every grade of improved reperfusion (figure 1A). On average, eTICI 3 resulted in 6.50 QALYs over the patients‘ lifetimes, eTICI 2 c (90%–99%) in 5.89 QALYs, eTICI 2b (67%–89%) in 5.79 QALYs, eTICI 2b (50%–66%) in 4.80 QALYs, eTICI 2a in 3.55 QALYs, and eTICI 1 or 0 in 2.57 QALYs. In contrast, the healthcare and societal costs of each QALY yielded by EVT decreased for every grade of improved reperfusion (Figure 1B). The advantage of achieving eTICI 3 over eTICI 2b (50%–66%) reperfusion results in average cost-savings of about $15,000/QALY per patient incurred by the healthcare system and $20,000/QALY per patient incurred by the society. Conclusion Every grade of improved reperfusion grants stroke patients additional QALYs and substantially reduces healthcare and societal costs per QALY. The clinical benefit and cost-savings of eTICI 3 reperfusion support to assess procedural strategies aiming at complete reperfusion for safety and feasibility, even when initial reperfusion seems to be adequate (eTICI 2b). Disclosures W. Kunz: 1; C; The HERMES collaboration was supported by Medtronic through an unrestricted research grant to the University of Calgary. M. Almekhlafi: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. B. Menon:1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. J. Saver: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. D. Dippel: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. C. Majoie: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. D. Liebeskind: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. T. Jovin: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. A. Davalos: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. S. Bracard: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. F. Guillemin: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. B. Campbell: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. P. Mitchell: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. P. White: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. K. Muir: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. S. Brown: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. A. Demchuk: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. M. Hill: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary. M. Goyal: 1; C; The HERMES pooled analysis project is supported by an unrestricted grant from Medtronic to the University of Calgary.

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)0.016
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.002

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 head0.027
GPT teacher head0.301
Teacher spread0.274 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

Same topicAcute Ischemic Stroke Management→French-language works237,207→