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Patients With Transient Ischemic Attack or Minor Stroke Should Be Admitted to Hospital

2006· review· en· W2149338612 on OpenAlexaff
Geoffrey A. Donnan, Stephen M. Davis, Michael D. Hill, David J. Gladstone

Bibliographic record

VenueStroke · 2006
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of CalgarySunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineMinor strokeStroke (engine)Ischemic strokeEmergency medicineTransient (computer programming)CardiologyInternal medicineIschemiaStenosis

Abstract

fetched live from OpenAlex

Transient ischemic attacks (TIAs), like other vasculardiseases, whether acute limb ischemia or acute coro-nary syndromes, are high-risk, unstable conditions. TIA heralds a relatively high risk of stroke, variably esti-mated to range between 10 % and 20 % in the ensuing 90 days.1–4 This has been known for several decades.5–8 What is new are reports that show that at least half of the risk of early stroke accrues in the first 2 days after TIA. Necessarily then, any protective strategy needs to be implemented rapidly. It is surprising that for a condition as common and serious as TIA, there remains so much variability in acute manage-ment. Whereas in some institutions, TIA patients are admitted routinely, in other jurisdictions, TIA patients are frequently discharged from the emergency department with suboptimal management, and many discharged TIA patients are unlikely to obtain adequate evaluation or treatment on an outpatient basis within 30 days.4 What Are the Potential Benefits of Hospitalization? Although the value of inpatient stroke units is well estab-lished, little is known about the value of acute observation and investigation units for patients with TIA or minor stroke. Some potential benefits of a short-stay hospital admission include: (1) expedited diagnostic evaluation; (2) monitoring of fluctuating patients with ready access to thrombolysis if they deteriorate; (3) facilitation of early carotid revascularization; and (4) greater opportunity for risk factor modification.9

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.319
Teacher spread0.276 · 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; both teacher heads agree on what is shown here.

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

Citations48
Published2006
Admission routes1
Has abstractyes

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