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Massive Cerebral Infarction

2005· review· en· W1963611672 on OpenAlex

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

VenueThe Neurologist · 2005
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCerebral edemaComa (optics)Cerebral infarctionIntensive care medicineDecompressionHyperventilationMortality rateStroke (engine)Glasgow Coma ScaleDecompressive craniectomySurgeryAnesthesiaTraumatic brain injuryIschemiaCardiology

Abstract

fetched live from OpenAlex

BACKGROUND: Massive cerebral infarcts cause brain edema with midline shifts and impingement on vital structures producing coma and death. The mortality rate is estimated at 80% with standard medical treatment. Surgical decompression with hemicraniectomy has proved to be life saving, but the impact on functional outcomes is largely unknown. The focus of this review is to discuss the treatment options for massive cerebral infarcts. REVIEW SUMMARY: Neurologic deterioration following massive cerebral infarct needs to be recognized early enough for medical and surgical interventions. Medical management includes monitoring in a neurologic intensive care unit, hyperosmolar agents, and hyperventilation. Surgical management includes decompressive hemicraniectomy and duraplasty with resection of infarcted tissue in some instances. CONCLUSION: Hemicraniectomy is emerging as a promising treatment of patients with massive cerebral infarcts, but only select patients benefit from this procedure. Further information from randomized controlled trials is required to elucidate the best treatment options for this kind of stroke.

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 categoriesInsufficient 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 score0.892
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0000.001

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 head0.059
GPT teacher head0.345
Teacher spread0.286 · 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