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Record W3198925346 · doi:10.1101/2021.09.11.21263431

A protocol for the multi-method evaluation of novel externally applied suction-based airway clearance devices in the treatment of foreign body airway obstructions

2021· preprint· en· W3198925346 on OpenAlexaff
Cody Dunne, Ana Catarina Queiroga, David Szpilman, Kayla Viguers, Selena Osman, Amy E. Peden

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsMemorial University of NewfoundlandUniversity of Calgary
Fundersnot available
KeywordsChokingMedicinePsychological interventionAirwayProtocol (science)Research ethicsAdverse effectIntensive care medicineMedical emergencyNursingSurgeryAlternative medicinePsychiatryInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background Foreign body airway obstructions (FBAO, choking) are a significant cause of preventable mortality. Abdominal thrusts, back blows, and chest compressions are traditional interventions; however, suction-based airway clearance devices (anti-choking devices, ACDs) have recently been marketed as an alternative. Of note, there is limited published evidence regarding their efficacy and safety. Our research has two aims: 1) To investigate what situational and patient factors are frequently identified, and which are associated with relief of the FBAO, and survival, in individuals with a FBAO treated with an ACD; and 2) To describe the experience of individuals who have used ACDs in response to a FBAO and identify facilitators and barriers to the use of ACDs compared to traditional interventions. Methods and analysis All ACD case reports collected a priori by manufacturers will be analyzed up to July 1st, 2021. Following, a prospective database will be developed using an online reporting system to capture future ACD use from July 1st, 2021 to Dec 31st, 2023. Descriptive statistics will be used to summarize cases, 58 outcomes, and adverse events. Where possible, bivariable and multivariable analysis will be employed to assess for predictors of outcomes (relief of FBAO, survival, and survival with good neurological function). Semi-structured interviews will be conducted with a subset of ACD users to describe in detail their experience using the device. Themes from these interviews will be assessed using the Theoretical Domains Framework. Ethics and dissemination This study has ethics approval from the University of New South Wales Human Research Ethics Committee (HC210242). Findings from this multi-year, multi-method study will be published in peer reviewed literature, presented at conferences and contribute to informing future resuscitation guidelines. Data on ACDs are urgently needed as these devices are already being used by parents, caregivers, lay rescuers, and healthcare professionals to respond to choking emergencies. Strengths and limitations of the study ∘ Foreign body airway obstruction (FBAO) intervention is an area with limited data, largely based on retrospective case series for traditional techniques (e.g., abdominal thrusts, back blows and chest thrusts) ∘ A multi-phase, multi-year study will be conducted to evaluate a novel intervention (suction-based airway clearance devices, ACDs) that have the potential to improve pre-hospital response to foreign body airway obstructions and survival ∘ Utilization of retrospective and prospective data, as well as evaluation of the users’ experience, will help determine the role for airway clearance devices in resuscitation algorithms and future guidelines ∘ Data will be reliant on self-reporting from users due to the infrequent occurrence of FBAO and few ACDs available to general public ∘ Previous studies have relied on data collected by manufacturers, which will be improved here by providing users with an independent reporting method

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)0.098
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.102
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0980.090
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0060.004
Science and technology studies0.0060.003
Scholarly communication0.0040.003
Open science0.0050.004
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.1020.033

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 head0.087
GPT teacher head0.403
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations1
Published2021
Admission routes1
Has abstractyes

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