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Real‐Time Hemodynamic Assessment of Intracranial Stenosis in a Patient with Orthostatic Aphasia: Potential Applications of Transcranial Doppler

2009· article· en· W1994805092 on OpenAlexaff
Yasser Aladdin, Muhammad Shazam Hussain, Maher Saqqur

Bibliographic record

VenueJournal of Neuroimaging · 2009
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineTranscranial DopplerOrthostatic vital signsCardiologyMiddle cerebral arteryInternal medicineStenosisRadiologyBasilar arteryHemodynamicsIschemiaBlood pressure

Abstract

fetched live from OpenAlex

BACKGROUND: Intracranial atherosclerotic stenosis is thought to be responsible for 8% of all ischemic stroke subtypes. Transcranial Doppler (TCD) ultrasonography allows for noninvasive and dynamic evaluation of the cerebral circulation within the circle of Willis. We present a case of recurrent, orthostatic transient ischemic attacks in which, using TCD, we were able to correlate dynamically between the orthostatic symptomatology and a significant drop in the mean flow velocity (MFV) across the stenotic middle cerebral artery (MCA) segment. METHODS: A 56-year-old male presented with recurrent episodes of orthostatic right-sided weakness and expressive aphasia. Diagnostic TCD revealed a stenotic signal in the left internal carotid artery (ICA) siphon. Subsequent TCD monitoring of both MCAs demonstrated a significant orthostatic drop in MFV of the left MCA, which closely correlated with his symptoms. The cerebral angiogram confirmed a high-grade stenosis at the supraclinoid segment of the left ICA. CONCLUSION: TCD is a useful, noninvasive, and dynamic tool for assessment of the intracranial circulation, and should be considered in the workup of patients with hypoperfusion cerebrovascular events.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.251
Teacher spread0.247 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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