MétaCan
Menu
Back to cohort
Record W3027129568 · doi:10.1002/hed.26278

Is the ultrasonic scalpel recommended in head and neck surgery during the <scp>COVID</scp>‐19 pandemic? <scp>State‐of‐the‐</scp>art review

2020· review· en· W3027129568 on OpenAlexaff
Miguel Mayo‐Yáñez, Christian Calvo‐Henríquez, Jérôme R. Lechien, Nicolas Fakhry, Tareck Ayad, Carlos M. Chiesa‐Estomba

Bibliographic record

VenueHead & Neck · 2020
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsRespiratorCoronavirus disease 2019 (COVID-19)PandemicPersonal protective equipmentUltrasonic sensorMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Airway managementSurgeryAirwayIntensive care medicineInfectious disease (medical specialty)PathologyChemistryRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Guidelines for ultrasonic devices use are imperative because infectious aerosols arising from airway procedures were a key etiologic factor in prior coronavirus outbreaks. This manuscript aims to summarize the available recommendations and the most relevant concepts about the use of ultrasonic scalpel during the SARS-CoV-2 pandemic. METHODS: Literature review of manuscripts with patients, animal models, or in vitro studies where the ultrasonic scalpel was used and the plume produced was analyzed in a quantitative and/ or qualitative way. DISCUSSION: Activated devices with tissue produce a biphasic bioaerosol composed (size 68.3-994 nm) of tissue particles, blood, intact and no viable cells, and carcinogenic or irritant hydrocarbons (benzene, ethylbenzene, styrene, toluene, heptene, and methylpropene). CONCLUSION: It is imperative to use an active smoke evacuator, to avoid ultrasonic scalpel use in COVID-19 positive patients and in upper airway surgery, as well as to follow the protection recommendations of the guidelines for management this type of patients.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.814
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.064
GPT teacher head0.339
Teacher spread0.275 · 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
GenreReview

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

Citations12
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueHead & NeckSame topicInfection Control and VentilationFrench-language works237,207