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Record W2087425763 · doi:10.1111/jsap.12267

Use of silicone tracheal stoma stents for temporary tracheostomy in dogs with upper airway obstruction

2014· article· en· W2087425763 on OpenAlexaff
Tonje Trinterud, Pieter Nelissen, R. A. S. White

Bibliographic record

VenueJournal of Small Animal Practice · 2014
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsPeace Arch Hospital
Fundersnot available
KeywordsMedicineStoma (medicine)StentGranulation tissueSurgeryAirwayAirway obstructionSiliconeForcepsWound healing

Abstract

fetched live from OpenAlex

OBJECTIVES: To report the use of silicone tracheal stoma stents for temporary tracheostomy in dogs with upper airway obstruction. METHODS: Retrospective review of medical records for dogs in which silicone tracheal stoma stents were placed. RESULTS: Eighteen dogs had a silicone tracheal stoma stent placed for maintenance of a tracheostomy stoma for periods ranging from three hours to eight months. No intra-operative or immediate postoperative complications were recorded. In 11 dogs the stent was removed by simple traction after a period ranging from 36 hours to 6 weeks, and the tracheal stoma was left to heal by second intention. Five of the 18 dogs were determined as being tracheostomy dependent and underwent conversion to permanent tracheostomy after a period ranging from five days to eight months following stent placement. One dog was euthanased after three months, with the stent still in place, because of poor respiratory function, and one dog died of unrelated reasons. In 6 of 10 dogs (60%) where the stent was in place for five days or more, granulation tissue formation caused dislodgement of the stent. CLINICAL SIGNIFICANCE: Silicone tracheal stoma stents may be used as an alternative to conventional tracheostomy tubes in selected dogs with upper airway obstruction. Long-term use of the stent beyond five days is not recommended because of granulation tissue formation. The long-term consequences of partial tracheal ring resection are unknown.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.398
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.093
GPT teacher head0.356
Teacher spread0.263 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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