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Record W2892184016 · doi:10.1161/strokeaha.118.022114

Endovascular Thrombectomy for Mild Strokes: How Low Should We Go?

2018· article· en· W2892184016 on OpenAlexaboutno aff
Amrou Sarraj, Ameer E Hassan, Sean I. Savitz, James C. Grotta, Chunyan Cai, Kaushik Parsha, Christine Farrell, Bita Imam, Clark Sitton, Sujan Reddy, Haris Kamal, Nitin Goyal, Lucas Elijovich, Katelin Reishus, Rashi Krishnan, Navdeep Sangha, Abel Wu, Renata Oliveira Costa, Ruqayyah Malik, Osman Mir, Rashedul Hasan, Lindsay Snodgrass, Manuel Requena, Dion Graybeal, Michael Abraham, Michael Chen, Louise D. McCullough, Marc Ribó

Bibliographic record

VenueStroke · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeNational Institutes of HealthStryker
KeywordsMedicineStroke (engine)Intracerebral hemorrhageThrombusOcclusionOdds ratioPropensity score matchingLogistic regressionComputed tomographicCohortRetrospective cohort studyCerebral infarctionThrombolysisSurgeryInternal medicineMyocardial infarctionComputed tomographyGlasgow Coma ScaleIschemia

Abstract

fetched live from OpenAlex

Background and Purpose- Endovascular thrombectomy (EVT) is effective for acute ischemic stroke with large vessel occlusion and National Institutes of Health Stroke Scale (NIHSS) ≥6. However, EVT benefit for mild deficits large vessel occlusions (NIHSS, <6) is uncertain. We evaluated EVT efficacy and safety in mild strokes with large vessel occlusion. Methods- A retrospective cohort of patients with anterior circulation large vessel occlusion and NIHSS <6 presenting within 24 hours from last seen normal were pooled. Patients were divided into 2 groups: EVT or medical management. Ninety-day mRS of 0 to 1 was the primary outcome, mRS of 0 to 2 was the secondary. Symptomatic intracerebral hemorrhage was the safety outcome. Clinical outcomes were compared through a multivariable logistic regression after adjusting for age, presentation NIHSS, time last seen normal to presentation, center, IV alteplase, Alberta Stroke Program early computed tomographic score, and thrombus location. We then performed propensity score matching as a sensitivity analysis. Results were also stratified by thrombus location. Results- Two hundred fourteen patients (EVT, 124; medical management, 90) were included from 8 US and Spain centers between January 2012 and March 2017. The groups were similar in age, Alberta Stroke Program early computed tomographic score, IV alteplase rate and time last seen normal to presentation. There was no difference in mRS of 0 to 1 between EVT and medical management (55.7% versus 54.4%, respectively; adjusted odds ratio, 1.3; 95% CI, 0.64-2.64; P=0.47). Similar results were seen for mRS of 0 to 2 (63.3% EVT versus 67.8% medical management; adjusted odds ratio, 0.9; 95% CI, 0.43-1.88; P=0.77). In a propensity matching analysis, there was no treatment effect in 62 matched pairs (53.5% EVT, 48.4% medical management; odds ratio, 1.17; 95% CI, 0.54-2.52; P=0.69). There was no statistically significant difference when stratified by any thrombus location; M1 approached significance ( P=0.07). Symptomatic intracerebral hemorrhage rates were higher with thrombectomy (5.8% EVT versus 0% medical management; P=0.02). Conclusions- Our retrospective multicenter cohort study showed no improvement in excellent and independent functional outcomes in mild strokes (NIHSS, <6) receiving thrombectomy irrespective of thrombus location, with increased symptomatic intracerebral hemorrhage rates, consistent with the guidelines recommending the treatment for NIHSS ≥6. There was a signal toward benefit with EVT only in M1 occlusions; however, this needs to be further evaluated in future randomized control 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.037
GPT teacher head0.295
Teacher spread0.257 · 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.

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

Citations123
Published2018
Admission routes1
Has abstractyes

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