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Record W3158426153 · doi:10.1161/circ.138.suppl_2.31

Abstract 31: "Cold" Debriefing After Pediatric In-Hospital Cardiac Arrests

2018· article· en· W3158426153 on OpenAlexaffabout
Heather Wolfe, Jesse Wenger, Robert M Sutton, Dana Niles, Vinay Nakdarni, Jordan Duval‐Arnould, Anita Sen, Adam Cheng

Bibliographic record

VenueCirculation · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsDebriefingMedicinePatient safetyEmergency medicineMedical emergencyFamily medicineNursingMedical educationHealth care

Abstract

fetched live from OpenAlex

Background: Cold debriefing(CD) is defined as occurring after at least 1 day to several weeks after a cardiac arrest event. CD has been reported to improve patient survival when implemented in a single institution, however little is known about the nature of cold debriefings across multiple pediatric centers. Methods: Retrospective review of prospectively collected data from the Pediatric Resuscitation Quality Collaborative (pediResQ). The collaborative is comprised of 18 institutions in the US and Canada, reporting 283 cardiac arrest events at the time of analysis. We analyzed CD data from in-hospital cardiac arrest (IHCA) events between Feb 2016 and April 2018. Debriefing content was collected with a Plus/Delta framework and qualitative analysis of debriefing comments was performed utilizing a modified Team Emergency Assessment Measurement (TEAM) Framework. The TEAM framework consists of ten categories: leadership, communication, cooperation, team climate, adaptability, situational awareness (SA), prioritization, clinical standards(CS) (e.g. CPR quality), and other. Univariate and regression models were applied accounting for clustering by site. Results: CD occurred in 33% (93/283) of IHCA events. Median time to debriefing was 25.5 days [IQR 11, 41] with a duration of 60 minutes [20,60]. Median number of facilitators per event was 1 (IQR 1, 1; range 0, 3). Facilitation and/or co-facilitation was performed by physicians 94%(87/93), nurses 18%(17/93) nurse practitioners 9%(8/93) and other 8%(7/93). Attendance was varied across sites (profession, number per debriefing): physicians 12 [IQR 4, 20], nurses 1 [1, 6], RT 0 [0, 1], administrators 1 [0, 1]. Plus comments were most commonly CS 35%(44/127) of comments, cooperation 21%(27/127) and communication 13%(16/127); Delta comments were CS 31%(41/134), cooperation 18%(24/134) communication 10%(13/134) and SA 9%(12/134). There was no difference in age, sex, race, illness category or survival outcome between events that were debriefed vs. not. Conclusions: In a multicenter pediatric IHCA collaborative, cold debriefings were performed after 33% of cardiac arrests. The majority of plus and delta comments could be categorized as clinical standards, followed by cooperation and communication.

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)0.011
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.062
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.252
Teacher spread0.244 · 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 designQualitative
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

Citations0
Published2018
Admission routes2
Has abstractyes

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