MétaCan
Menu
Back to cohort
Record W3011053330 · doi:10.1177/2048872619891675

Improving bystander defibrillation in out-of-hospital cardiac arrests at home

2020· article· en· W3011053330 on OpenAlexaff
Lena Karlsson, Carolina Malta Hansen, Christina Vourakis, Christopher Sun, Shahzleen Rajan, Kathrine Bach Søndergaard, Linn Andelius, Freddy Lippert, Gunnar Gislason, Timothy CY Chan, Christian Torp‐Pedersen, Fredrik Folke

Bibliographic record

VenueEuropean Heart Journal Acute Cardiovascular Care · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of Toronto
FundersNovo Nordisk FondenTrygFonden
KeywordsMedicineBystander effectDefibrillationMedical emergencyEmergency medicineInternal medicineCardiology

Abstract

fetched live from OpenAlex

Aims: Most out-of-hospital cardiac arrests occur at home with dismal bystander defibrillation rates. We investigated automated external defibrillator coverage of home arrests, and the proportion potentially reachable with an automated external defibrillator before emergency medical service arrival according to different bystander activation strategies. Methods and results: Cardiac arrests in homes (private/nursing/senior homes) in Copenhagen, Denmark (2008–2016) and registered automated external defibrillators (2007–2016), were identified. Automated external defibrillator coverage (distance from arrest to automated external defibrillator) and accessibility at the time of arrest were examined according to route distance to nearest automated external defibrillator and emergency medical service response time. The proportion of arrests reachable with an automated external defibrillator by bystander was calculated using two-way (from patient to automated external defibrillator and back) and one-way (from automated external defibrillator to patient) potential activation strategies. Of 1879 home arrests, automated external defibrillator coverage ≤100 m was low (6.3%) and a two-way bystander could potentially only retrieve an accessible automated external defibrillator before emergency medical service in 31.1% (n=37) of cases. If a bystander only needed to travel one-way to bring an automated external defibrillator (≤100 m, ≤250 m and ≤500 m), 45.4% (n=54/119), 37.1% (n=196/529) and 29.8% (n=350/1174) could potentially be reached before the emergency medical service based on current automated external defibrillator accessibility. Conclusions: Few home arrests were reachable with an automated external defibrillator before emergency medical service if bystanders needed to travel from patient to automated external defibrillator and back. However, nearly one-third of arrests ≤500 m of an automated external defibrillator could be reached before emergency medical service arrival if the bystander only needed to travel one-way from the automated external defibrillator to the patient.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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 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

Citations20
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart Journal Acute Cardiovascular CareSame topicCardiac Arrest and ResuscitationFrench-language works237,207