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Record W2913979854 · doi:10.1161/str.50.suppl_1.tp24

Abstract TP24: Impact of Pretreatment With Intravenous Thrombolysis on Reperfusion Status in Emergent Large Vessel Occlusion (ELVO) Patients Treated With Mechanical Thrombectomy (MT)

2019· article· en· W2913979854 on OpenAlexaff
Nitin Goyal, Georgios Tsivgoulis, Abhi Pandhi, Rashi Krishnan, Konark Malhotra, Muhammad Ishfaq, Balaji Krishnaiah, Christopher Nickele, Violiza Inoa, Daniel Hoit, Lucas Elijovich, Anne W. Alexandrov, Andrei V. Alexandrov, Adam S Arthur

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsNickel Institute
Fundersnot available
KeywordsMedicineThrombolysisModified Rankin ScaleStroke (engine)OcclusionCerebral infarctionInternal medicineReperfusion therapyCardiologyAnesthesiaSurgeryIschemic strokeIschemiaMyocardial infarction

Abstract

fetched live from OpenAlex

Introduction: It currently remains unclear whether pre-treatment with intravenous thrombolysis (IVT) provides any additional benefits to emergent large vessel occlusion (ELVO) patients undergoing mechanical thrombectomy (MT). We sought to evaluate the impact of pretreatment with IVT on the rate and the speed of complete reperfusion (CR) in LVO patients treated with MT in a high-volume tertiary care stroke center. Methods: Consecutive ELVO patients treated with MT during a five-year period were evaluated. Baseline stroke severity was assessed by NIHSS-score. Standard safety [symptomatic Intracranial Hemorrhage (sICH) by SITS-MOST definition] and efficacy outcomes [CR (modified Thrombolysis in Cerebral Infarction IIb/III), 3-month functional independence (FI; modified Rankin Scale scores of 0-2)] were compared between patients who underwent combined IVT and MT (IVT+MT) vs. direct MT (dMT). The elapsed time between groin puncture to beginning of reperfusion (GPTBRT) and the numbers of device passes (DP) required to achieve CR were also documented. Results: A total of 287 and 132 patients were treated with IVT+MT and dMT respectively. The IVT+MT group had higher CR (74% vs. 63%; p=0.023) and FI (52% vs.38%; p=0.008) rates and shorter median GPTBRT (48 vs. 70 min; p<0.001). The two groups did not differ in sICH rates (7% vs. 9%; p=0.368). Among patients who achieved CR, the median number of required DP was lower in the IVT+MT subgroup (1 vs. 2; p<0.001) and the rate of patients requiring ≤2 DP was higher (98% vs. 77%; p<0.001). IVT+MT was independently related to higher odds of CR (OR:1.64; 95%:1.03-2.61; p=0.036) and shorter GPTBRT (unstandardized linear regression coefficient: -20; 95%CI: -12, -27; p<0.001) on multivariable analyses adjusting for potential confounders including demographics, vascular risk factors, collateral status, stroke severity, location of occlusion and onset to groin puncture time. Among patients with CR, IVT+MT was independently associated with higher likelihood of ≤2 DP (OR:14.75; 95%:4.72-46.04; p<0.001). Conclusions: IVT pretreatment increases the rates of CR and shortens the duration of endovascular procedure by requiring fewer DP in ELVO patients treated with MT.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.007
GPT teacher head0.253
Teacher spread0.247 · 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
Published2019
Admission routes1
Has abstractyes

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