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Record W4295270937 · doi:10.1080/17434440.2022.2124109

Efficacy and safety of mechanical thrombectomy in acute stroke patients with pre-morbid disability

2022· review· en· W4295270937 on OpenAlexaff
Aravind Ganesh, Joachim Fladt, Nishita Singh, Mayank Goyal

Bibliographic record

VenueExpert Review of Medical Devices · 2022
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineObservational studyThrombolysisStroke (engine)Intracerebral hemorrhageRandomized controlled trialAdverse effectEpidemiologyClinical trialPhysical therapyEmergency medicineIntensive care medicineSurgeryInternal medicineSubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

INTRODUCTION: Patients with pre-morbid disability have been generally excluded from randomized controlled trials of mechanical thrombectomy for acute ischemic stroke. However, stroke physicians commonly encounter such patients in practice, and face challenging treatment decisions when caring for them. AREAS COVERED: We review the literature on the safety and efficacy of thrombectomy in patients with pre-morbid disability. Recent clinical-epidemiological studies have highlighted the adverse outcomes that come with each increment of additional post-stroke disability in these patients. Several observational studies - both case series and registry-based studies - have helped demonstrate the comparable safety of thrombectomy in patients with pre-morbid disability as in those without, complementing similar data on thrombolysis. These data also suggest similar rates of successful recanalization, symptomatic intracerebral hemorrhage, and return to pre-stroke level of disability when treated with mechanical thrombectomy, although they have higher mortality. EXPERT OPINION: In the absence of high-quality evidence, we recommend pursuing shared decision-making with patients or family members and being upfront about the uncertain evidence. Available observational data underline the potential for a substantial proportion of these patients to return to their pre-morbid state, do not indicate a greater rate of treatment-related complications, and do not support routinely excluding these patients from thrombectomy.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.368
Teacher spread0.345 · 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
GenreReview

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

Citations5
Published2022
Admission routes1
Has abstractyes

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