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Record W2760513219 · doi:10.1161/str.48.suppl_1.29

Abstract 29: The Association Between General Anesthesia and Outcome of Endovascular Thrombectomy in Pooled Data From Five Randomized Trials

2017· article· en· W2760513219 on OpenAlexaff
Bruce Campbell, Wim H. van Zwam, Mayank Goyal, Bijoy K. Menon, Diederik W.J. Dippel, Andrew M. Demchuk, Antoni Dávalos, Charles B.L.M. Majoie, Scott Brown, Jeffrey L. Saver, Tudor G. Jovin, Michael D. Hill, Peter Mitchell

Bibliographic record

VenueStroke · 2017
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineRandomized controlled trialModified Rankin ScaleStroke (engine)Odds ratioObservational studyClinical trialSurgeryInternal medicineAnesthesiaIschemic stroke

Abstract

fetched live from OpenAlex

Background and purpose: General anesthesia (GA) during endovascular thrombectomy has been associated with worse patient outcomes in observational studies. We examined the association between GA and thrombectomy outcomes in pooled data from five randomized trials. Methods: Patient-level data were pooled from trials comparing endovascular thrombectomy (predominantly using stent retrievers) with standard care in anterior circulation ischemic stroke patients (HERMES Collaboration): MR CLEAN, ESCAPE, REVASCAT, SWIFT PRIME, and EXTEND IA. The primary outcome was ordinal analysis of modified Rankin scale (mRS) at 90 days in the GA and non-GA subgroups, adjusted for baseline prognostic variables. To account for between-trial variance we used mixed-effects modeling with a random effect for trial incorporated in all models. Results: Of 1287 patients, 634 were allocated to endovascular thrombectomy and general anesthesia was used in 153/609 (25%) of endovascular-treated patients with anesthesia information available. Although dysphasic patients are sometimes felt to be less co-operative and require GA, the rate of GA was 25% in both right and left hemisphere patients. At baseline, GA and non-GA patients had similar age, NIHSS and time to randomization. Endovascular thrombectomy was associated with increased odds of improved functional outcome at 3 months, regardless of whether GA (cOR 1.73 95%CI 1.10-2.72, p=0.02) or non-GA (cOR 2.61 95%CI 2.01-3.40, p<0.001) was used. The odds of improved outcome were, however, significantly greater for those treated under non-GA (OR 1.59 95%CI 1.12-2.26, p=0.01). Pneumonia was more common in the GA group (16% vs 9% p=0.03). Rates of vessel perforation were similar in GA (0.7%) vs non-GA patients (1.8%, p=0.52). Delay between randomization and reperfusion was greater in GA versus non-GA patients (median 98 vs 75 min, p<0.001). Conclusions: Worse outcomes after endovascular thrombectomy were associated with GA, after adjustment for baseline prognostic variables. These data support avoidance of GA whenever possible. The procedure did, however, remain effective versus standard care in patients treated under GA, indicating that treatment is still worthwhile in those who require anesthesia for medical reasons.

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)0.124
metaresearch head score (Gemma)0.181
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.654

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1240.181
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0170.047
Bibliometrics0.0090.008
Science and technology studies0.0010.002
Scholarly communication0.0060.003
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.066
GPT teacher head0.343
Teacher spread0.278 · 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 designMeta-analysis
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
Published2017
Admission routes1
Has abstractyes

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