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Record W4388287112 · doi:10.1136/jnis-2023-020899

Association between intraprocedural drops in blood pressure and infarct growth rate patterns after acute large-vessel occlusions

2023· article· en· W4388287112 on OpenAlexaboutno aff
Milagros Galecio‐Castillo, Darko Quispe‐Orozco, Mudassir Farooqui, Andres Dajles, Juan Vivanco‐Suarez, Aarón Rodríguez-Calienes, Ayush Prasad, Yelyzaveta Begunova, Nils Petersen, Santiago Ortega‐Gutiérrez

Bibliographic record

VenueJournal of NeuroInterventional Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeYale University
KeywordsMedicineThrombolysisModified Rankin ScaleCardiologyCerebral blood flowStroke (engine)Blood pressureInternal medicineInfarctionCerebral perfusion pressureCerebral infarctionPerfusion scanningMagnetic resonance imagingMean arterial pressurePerfusionRadiologyNuclear medicineIschemic strokeIschemiaMyocardial infarctionHeart rate

Abstract

fetched live from OpenAlex

Background Infarct growth rate (IGR) differs among patients with acute ischemic stroke due to large vessel occlusion (LVO-AIS), and this variability has critical clinical repercussions. We explored IGR patterns and their association with blood pressure during endovascular therapy (EVT). Methods This is a two-center cohort observational study that included consecutive anterior circulation LVO-AIS patients who underwent EVT and achieved modified Thrombolysis in Cerebral Infarction (mTICI) 2 c-3. Initial and final infarct volumes (FIV) were defined using admission computed tomography perfusion (CTP) defined as relative cerebral blood flow (rCBF) <30%, and diffusion-weighted imaging-magnetic resonance imaging (DWI-MRI) at 24 hours post-EVT. We categorized IGR patterns as exponential (ExpIGR) and Non-exponential (NonExp) based on their growth curves. We then dichotomized ExpIGR clinical significance based on the association of infarct growth with 90-day Modified Rankin Score (mRS) as ExpIGR-A ( > 13 mL) and ExpIGR-B (<13 mL). Intraprocedural blood pressure (BP) drops were calculated as the difference between median arterial pressure (MAP) at admission and the lowest intraprocedural MAP reading before recanalization, and the area between admission MAP threshold and all lower measurements of intraprocedural MAP. Logistic and linear regression were used to investigate associations between variables of interest. Results Of 159 modified Thrombolysis in Cerebral Infarction (mTICI) 2 c-3 patients, we found that 36% demonstrated ExpIGR-A, 31% ExpIGR-B, and 32.7% NonExp patterns. The Exp-A and Exp-B groups differed significantly in National Institutes of Health Stroke Scale (NIHSS) score, Alberta Stroke Program Early CT Score (ASPECTS), glucose, and FIV. The Exp-A and NonExp groups differed in rCBF <30% vol, and time of stroke onset (SO) to admission CTP; and the Exp-B and NonExp groups in NIHSS, rCBF <30%, Tmax <6 s volume, collateral flow measured by hypoperfusion intensity ratio (HIR), and FIV. Hypotensive MAP area (HMA) was independently associated with an ExpIGR-A pattern. Infarct volume increased by 1 mL per 100 units of hypotensive area and 4.2 mL per 0.1 units of HIR, with a significant interaction between both variables. Conclusion After an LVO-AIS, the IGR can be differentiated into two distinct exponential and non-exponential patterns. A subgroup of patients with the exponential pattern experienced clinically meaningful infarct growth rates between CTP acquisition and reperfusion and seem to be highly vulnerable to episodes of sustained intraprocedural BP drops during EVT.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.032
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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.

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

Citations6
Published2023
Admission routes1
Has abstractyes

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