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Record W2147379905 · doi:10.1183/09031936.00075110

Idiopathic pulmonary arteriovenous malformations: clinical and imaging characteristics

2010· article· en· W2147379905 on OpenAlexaff
H. Wong, R Chan, Regan Klatt, Marie E. Faughnan

Bibliographic record

VenueEuropean Respiratory Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicVascular Anomalies and Treatments
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineRadiologyTelangiectasiaStroke (engine)Brain abscessAbscessSurgery

Abstract

fetched live from OpenAlex

Pulmonary arteriovenous malformations (PAVMs) can cause stroke, brain abscess or life-threatening haemorrhage. Most PAVMs are associated with hereditary haemorrhagic telangiectasia (HHT). The aim of the present study was to describe the clinical presentation and treatment outcomes of those with idiopathic PAVMs, which has not previously been described in the literature. Patients with idiopathic PAVMs were identified at our HHT centre. Retrospective review of charts and imaging were performed. 20 patients were identified with idiopathic PAVMs. The most common symptoms reported were dyspnoea and migraines (50 and 30% of patients, respectively). Previous complications of PAVMs included haemoptysis (20%), stroke (20%) and brain abscess (5%). A total of 28 focal PAVMs were identified. Most patients (80%) had a solitary PAVM. 13 out of 28 PAVMs (46%) were located in the lower lobes. Most were simple and fistulous rather than complex and plexiform. Transcatheter embolotherapy was performed in 17 patients and was successful in improving oxygenation in all cases. The clinical manifestations and complications of idiopathic PAVMs are similar to those associated with HHT. Idiopathic PAVMs are anatomically similar to HHT-related PAVMs except for a greater number of solitary PAVMs and a lack of lower lobe predominance. Transcatheter embolotherapy is a safe and effective method for treating idiopathic PAVMs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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

Citations86
Published2010
Admission routes1
Has abstractyes

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