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Record W3047735891 · doi:10.14740/cr1134

Catheter Reprocessing for Coronary Angiography: It is Not Safe

2020· article· en· W3047735891 on OpenAlexvenueno aff
Dinaldo Cavalcanti de Oliveira, Flávia Gaze Bonfim, Maria Vinhas, Ivan Nunes da Silva, Magno Felipe Holanda Barboza Inácio Teixeira, André Galembeck

Bibliographic record

VenueCardiology Research · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMedical Device Sterilization and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCatheterThermogravimetric analysisCoronary angiographyLumen (anatomy)Percutaneous coronary interventionAngiographyPercutaneousRadiologyCardiologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Coronary angiography and percutaneous coronary intervention are frequently and increasingly performed worldwide. Although catheters for coronary angiography are considered as single-use devices, some people still question this decision. This study evaluated the structural characteristics and thermal stability of new and reprocessed catheters. METHODS: Five catheters (Judkins left) of the same brand and manufacturer were selected for each analysis. We evaluated: new catheters, catheters reprocessed once (first), twice (second), thrice (third), and seven times (seventh). The optical analyses of the proximal, middle and distal parts of the catheters were performed by magnifying glass. Besides, thermogravimetric analyses were done. RESULTS: After reprocessing, the crushing, color changes, folds, dents, deformations, and lumen narrowing were observed; the stainless-steel framework, the external tortuosity, the interlaced mesh of stainless-steel wires and loss of polymeric material were visualized. Thermogravimetric analysis showed lost of mass of the catheters. CONCLUSIONS: This study demonstrated that the structural integrity and mass of catheters are lost with reprocessing. These findings may be caused by several steps of reprocessing; however, regardless of which step or steps were responsible, the presence of structural integrity loss leads to the recommendation of not reusing this type of device.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.951

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.175
GPT teacher head0.401
Teacher spread0.226 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

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