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Record W4282565066 · doi:10.1001/jamaneurol.2022.1413

Outcomes After Endovascular Thrombectomy With or Without Alteplase in Routine Clinical Practice

2022· article· en· W4282565066 on OpenAlexaff
Eric E. Smith, Charlotte Zerna, Nicole Solomon, Roland Matsouaka, Brian Mac Grory, Jeffrey L. Saver, Michael D. Hill, Gregg C. Fonarow, Lee H. Schwamm, Steven R. Messé, Ying Xian

Bibliographic record

VenueJAMA Neurology · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineThrombolysisStroke (engine)Atrial fibrillationEmergency medicineIntracerebral hemorrhageObservational studyModified Rankin ScaleCohortFibrinolytic agentCerebral infarctionClinical trialRandomized controlled trialInternal medicineMyocardial infarctionIschemic strokeTissue plasminogen activatorSubarachnoid hemorrhageIschemia

Abstract

fetched live from OpenAlex

Importance: The effectiveness and safety of intravenous alteplase given before or concurrently with endovascular thrombectomy (EVT) is uncertain. Randomized clinical trials suggest there is little difference in outcomes but with only modest precision and insufficient power to analyze uncommon outcomes including symptomatic intracranial hemorrhage (sICH). Objective: To determine whether 8 prespecified outcomes are different in patients with acute ischemic stroke treated in routine clinical practice with EVT with alteplase compared with patients treated with EVT alone without alteplase. It was hypothesized that alteplase would be associated with higher risk of sICH. Design, Setting, and Participants: This was an observational cohort study conducted from February 1, 2019, to June 30, 2020, that included adult patients with acute ischemic stroke treated with EVT within 6 hours of time last known well, after excluding patients without information on discharge destination and patients with in-hospital stroke. Participants were recruited from Get With The Guidelines-Stroke, a large nationwide registry of patients with acute ischemic stroke from 555 hospitals in the US. Exposures: Intravenous alteplase or no alteplase. Main Outcomes and Measures: Prespecified outcomes were discharge destination, independent ambulation at discharge, modified Rankin score at discharge, discharge mortality, cerebral reperfusion according to modified Thrombolysis in Cerebral Infarction grade, and sICH. Results: There were 15 832 patients treated with EVT (median [IQR] age, 72.0 [61.0-82.0] years; 7932 women [50.1%]); 10 548 (66.7%) received alteplase and 5284 (33.4%) did not. Patients treated with alteplase were younger, arrived via Emergency Medical Services sooner, were less likely to have certain comorbidities, including atrial fibrillation, hypertension, and diabetes, but had similar National Institutes of Health Stroke Severity (NIHSS) scores. Compared with patients who did not receive alteplase treatment, patients treated with alteplase were less likely to die (11.1% [1173 of 10 548 patients] vs 13.9% [734 of 5284 patients]; adjusted odds ratio [aOR] 0.83; 95% CI, 0.77-0.89; P < .001), more likely to have no major disability based on modified Rankin scale of 2 or less at discharge (28.5% [2415 of 8490 patients] vs 20.7% [894 of 4322 patients]; aOR, 1.36; 95% CI, 1.28-1.45; P < .001), and to have better reperfusion based on modified Thrombolysis in Cerebral Infarction grade 2b or greater (90.9% [8474 of 9318 patients] vs 88.0% [4140 of 4705 patients]; aOR, 1.39; 95% CI, 1.28-1.50; P < .001). However, alteplase treatment was associated with higher risk of sICH (6.5% [685 of 10 530 patients] vs 5.3% [279 of 5249 patients]; OR, 1.28; 95% CI, 1.16-1.42; P < .001). Conclusions and Relevance: In this observational cohort study of patients treated with EVT, intravenous alteplase treatment was associated with better in-hospital survival and functional outcomes but higher sICH risk after adjusting for other covariates.

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)0.002
metaresearch head score (Gemma)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.021
GPT teacher head0.330
Teacher spread0.308 · 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".

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Citations31
Published2022
Admission routes1
Has abstractyes

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