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Record W2046830264 · doi:10.1002/ccd.22517

A biodegradable device (BioSTAR™) for atrial septal defect closure in children

2010· article· en· W2046830264 on OpenAlexaff
Gareth J. Morgan, Kyong‐Jin Lee, Rajiv Chaturvedi, Lee Benson

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicineFluoroscopyImplantPercutaneousSurgeryClosure (psychology)Retrospective cohort studyCohortBalloonInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Percutaneous closure of atrial defects (ASD) has evolved as the treatment of choice for the majority of defects and patent oval foramens. The BioSTAR biodegradable implant avoids many issues associated with devices containing substantial amounts of metal. METHODS: Reviewed was a consecutive series of 10 ASD occlusions in a pediatric population with the BioSTAR biodegradable device. All implantations were performed by one operator. The inclusion criterion was a balloon stretched ASD diameter of < or =16 mm. Procedural data and acute and early-term closure rates were retrospectively matched to a cohort of children having defect closure using the Amplatzer Septal Occluder (ASO). RESULTS: Acute and 6 month follow up closure rates for the BioSTAR were 90% and 100% vs. 100% and 100% closure with the ASO implants. There was a statistically significant difference in the median procedure time (52 min: BioSTAR; 39.5 min: ASO device, P < 0.05), with fluoroscopy times slightly longer for the BioSTAR group (6.7 min vs. 6.1 min, P = ns). There were no significant complications in either group. CONCLUSIONS: The BioSTAR implant can achieve comparable closure rates to the ASO in small- to moderate-atrial septal defects with only a minimal skeleton of foreign material remaining after 6 months. Longer fluoroscopy and procedure times were a drawback; however, these should improve with familiarity with the implant and deployment system.

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 score0.281
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.009
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 head0.020
GPT teacher head0.280
Teacher spread0.260 · 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

Citations39
Published2010
Admission routes1
Has abstractyes

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