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Record W2099349385 · doi:10.1016/j.euje.2005.09.007

Hazards of percutaneous PFO closure

2005· letter· en· W2099349385 on OpenAlexaff
Markus Schwerzmann, Omid Salehian

Bibliographic record

VenueEuropean Journal of Echocardiography · 2005
Typeletter
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsMedicinePercutaneousClosure (psychology)CardiologyInternal medicine

Abstract

fetched live from OpenAlex

Please see the article by Christen et al. (doi: 10.1016/j.euje.2005.08.002 ) to which this editorial pertains. In 2004, an estimated 2000–3000 patients underwent percutaneous closure of a patent foramen ovale (PFO). Given the range of potential indications (such as prevention of cryptogenic stroke, decompression illness in divers, platypnea–orthodeoxia syndrome, and migraine headaches) and the perception of PFO closure being an easy and safe procedure,1 the number of patients with percutaneously implanted PFO closure devices will continue to grow. The first attempt to percutaneously close an interatrial defect was undertaken in 1974 and reported by King and colleagues in 1976.2 In the following years, several different devices were developed and re-modified to facilitate this technique. It began with the Clamshell occluder from Rashkind,3 later modified into the CardioSEAL and then the StarFLEX device. Other models soon followed including the Buttoned device,4 the ASDOS device,5 the Monodisk,6 the Angel-Wings device,7 the Amplatzer ASD occluder8 and the Helex device.9 Although these devices were initially intended for atrial septal defect closure, they could also be used for closure of PFO, an idea first evoked by Bridges in 1992.10 Soon thereafter, devices dedicated exclusively for percutaneous PFO closure entered the market, namely the Amplatzer PFO occluder and the PFOStar (now Cardiastar) device. Part of the reasoning to favour percutaneous PFO closure over open heart surgery promises a safer and of course, less …

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.706
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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.

Study designNot applicable
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

Citations24
Published2005
Admission routes1
Has abstractyes

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