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Record W3143707759 · doi:10.14740/jmc1786w

Simultaneous Thrombosis in a Normal Left Ventricle and Normal Carotid Artery in a Patient With a Stroke Secondary to Iron Deficiency Anemia

2014· article· en· W3143707759 on OpenAlexvenueno aff
Nakamizo

Bibliographic record

VenueJournal of Medical Cases · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac tumors and thrombi
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombusCardiologyInternal medicineThrombosisStroke (engine)VentricleCerebral infarctionEmbolismIschemia

Abstract

fetched live from OpenAlex

Iron deficiency anemia (IDA) is implicated as a cause of stroke, particularly in young patients without cardiovascular disease. In such patients, thrombi sometimes form in carotid arteries or the aorta. We report here a patient with a stroke secondary to IDA with thrombi in the normal left ventricle and normal carotid artery. The patient was a 45-year-old woman with severe IDA who developed cerebral infarction in the right middle cerebral artery. She had no other thrombophilia or cardiovascular diseases. Echocardiography showed a left ventricular thrombus without cardiac disease, and the carotid ultrasound showed a mobile thrombus attached to the right internal carotid artery without atherosclerosis. Antithrombotic therapy with iron supplementation removed both thrombi within 2 weeks. This is the first case of IDA with a ventricular thrombus in a normal heart. This case identifies a new site for thrombosis in IDA and shows that patients with IDA may present with simultaneous thrombosis at separate sites. IDA must therefore be recognized as a cause of stroke or systemic embolism, particularly in patients without detectable cardiovascular disease. In such patients, it is important to conduct careful investigations to detect thrombosis. J Med Cases. 2014;5(6):351-354 doi: http://dx.doi.org/ 10.14740 /jmc1786w

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 score0.089
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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
Published2014
Admission routes1
Has abstractyes

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