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Record W7056445344

Evidence summary: Is the use of warm humidified ‘wet’ circuit for mechanical ventilation recommended in ventilating patients with COVID-19?

2020· other· en· W7056445344 on OpenAlexaboutno aff

Bibliographic record

VenueLenus, The Irish Health Repository (Dr Steevens Hospital Library) · 2020
Typeother
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsExhalationMechanical ventilationFilter (signal processing)BreathingHeat exchangerVentilation (architecture)OcclusionAirwayTube (container)
DOInot available

Abstract

fetched live from OpenAlex

Based on the results of our search, ‘dry’ or hydrophobic systems are preferred from a HCW safety perspective. Cook7 recommends that “Actively heated and humidified ‘wet circuits’ may be avoided after tracheal intubation to avoid viral load being present in the ventilator circuit. This will theoretically reduce risks of contamination of the room if there is an unexpected circuit disconnection” ; Scott13 concludes that “potentially pathogenic organisms can pass through wet anaesthetic breathing filters, and found that they do so very easily. Further studies are required to investigate the potential for cross-contamination between patients if filters are used as the sole method of infection control in breathing systems for anaesthesia and intensive care.” UpToDate5 : “Other infection precautions include use of dual limb ventilator circuitry with filters placed at the exhalation outlets as well as heat moisture exchange (HME) systems rather than heated humification of single limb circuits.” Sundaram14 states: “Hydrophobic viral filter in the ventilator circuit minimizes chances of transmission of virus.” Hydrophobic filters are also recommended in the Canadian Anesthsiologists’ Society Guidelines4 : “Use of hydrophobic/HEPA filter between the ET tube and ventilator/Laerdal bag” and “Consider taping the filter to the ET tube to reduce the risk of accidental disconnection.” In terms of efficacy for the patient, Furyk10 when comparing HME with heated humidifiers, found that for people who are mechanically ventilated, randomized controlled trials have reported no clear differences overall between heat and moisture exchangers (HMEs) and heated humidifiers 2 (HHs) in terms of artificial airway occlusion [low‐quality evidence], all‐cause mortality [low‐quality evidence], pneumonia-related mortality, pneumonia [low‐quality evidence], and partial pressure of arterial carbon dioxide, duration of intensive care stay, or respiratory complications. “[Due to] potential for bias and often low event rates and/or small participant numbers, none of the analyses can be considered sufficiently robust to draw conclusions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.007
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.001
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0270.004

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 head0.083
GPT teacher head0.286
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations0
Published2020
Admission routes1
Has abstractyes

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