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Record W2027431924 · doi:10.4021//jmc.v4i3.478

Endovascular Revascularization in Secondary Raynaud's Phenomenon

2013· article· en· W2027431924 on OpenAlexvenueno aff
Pim W. van Egmond, Peter M. T. Pattynama, P.M. Schlejen

Bibliographic record

VenueJournal of Medical Cases · 2013
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSclerodactylyThrombolysisTelangiectasiaDigital subtraction angiographyUrokinaseAngioplastyRadiologyOcclusionRevascularizationBalloonCalcinosisSurgeryAngiographyCardiologyMyocardial infarctionCalcification

Abstract

fetched live from OpenAlex

Endovascular intervention is not previously described in patients with exacerbated Raynaud ’ s phenomenon (RP). A 45-year-old male with secondary RP and CREST (Calcinosis cutis, Raynaud’s phenomenon, Esophageal dysmotility, Sclerodactyly and Telangiectasia) with a smoking history, who was noncompliant in the non-interventional treatment, presented with necrosis of the right hand in exacerbated RP. An intra-arterial digital subtraction angiography (DSA) showed occlusion of the right distal ulnar and radial arteries. Initial pharmacological therapy showed no improvement. Thrombolysis with Urokinase therapy had a beneficial, but not optimal, effect on perfusion. This was probably due to an atherosclerotic component. An endovascular intervention, 2 mm balloon dilatation, in the right radial artery; improved this significantly. The clinical situation proved stable and no expansion of necrosis was seen. An endovascular procedure, not previously described in RP management, can be helpful in the treatment of exacerbated RP; especially when an atherosclerotic component is present. doi: http://dx.doi.org/10.4021/jmc478 w

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical Cases→Same topicSystemic Sclerosis and Related Diseases→French-language works237,207→