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Record W1479890193 · doi:10.5772/27044

Understanding and Augmenting Collateral Blood Flow During Ischemic Stroke

2012· book-chapter· en· W1479890193 on OpenAlex
Gomathi Ramakrishnan, Andrea J. Glenn, Ian R.

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineStroke (engine)CardiologyInternal medicineEmbolusCerebral blood flowCollateral circulationIschemiaIschemic strokeDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

Stroke refers to brain damage and dysfunction that occurs due to the obstruction of blood flow to brain tissue. Stroke is one of the leading causes of death and disability worldwide, accounting for 10% of all deaths (Grysiewicz et al., 2008; Donnan et al., 2008). Risk of stroke is affected by a number of modifiable and non-modifiable risk factors. Age is the primary non-modifiable risk factor, while modifiable risk factors include chronic hypertension, diabetes, smoking, cholesterol and lack of exercise (Simons et al., 1998; Knuiman & Vu, 1996; Iso et al., 1989; Wadley et al., 2007). Ischemic stroke, the rapid development of a neurological deficit due to the disruption of blood supply to a specific region of the brain, is the most common cause of stroke. Usually caused by the blockage of an artery or vein by an embolus or blood clot, an ischemic stroke is a major cerebrovascular trauma with a mortality rate of 25% after one month (Donnan et al., 2008; Hossmann, 2006). Ischemic strokes are differentiated from transient ischemic attacks by neurological symptoms lasting for more than 24 hours (Albers et al., 2002). Death and extent of disability due to ischemic stroke is largely defined by location of the occlusion and corresponding size and location of the infarct. Brain injury following ischemic stroke results from an “ischemic cascade” of pathological events triggered by reduced blood flow. Disturbed ion homeostasis, excitotoxity, elevation of intracellular calcium concentrations, peri-infarct depolarisations, free radical generation, lipid peroxidation and protein synthesis dysfunction are all triggered by reduced blood flow and contribute to necrotic and apoptotic processes in ischemic tissue and expansion of the infarct (Dirnagl et al., 1999 and Hossmann et al., 2006). Notably, necrotic cell death tends to be fast and irreversible in the core or infarct of the stroke area, where blood flow falls below ~20% of baseline perfusion and results in energy failure in resident neurons (Hossman, 2006). However, in “penumbral” regions surrounding the core, partial blood flow is maintained and tissue is considered functionally silent but structurally intact. Importantly, damage in the penumbra is reversible, though this reversibility is time-limited (Hakim, 1987). Because pathophysiology in the penumbra evolves over hours and days after ischemic onset, it is believed that early treatments that restore blood flow or reduce brain damage can reduce damage and improve outcome (Green, 2008). Although hundreds to thousands of prospective treatments to salvage ischemic tissue or halt the pathological ischemic cascade have been identified, few have successfully been translated to clinical practice (Ginsberg , 2008; Wahlgren & Ahmed, 2005). In fact, only thrombolytic drugs have thus far produced significant positive

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.422
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.240
Teacher spread0.197 · 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