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Record W3095060600 · doi:10.1097/cce.0000000000000214

Rationale and Strategies for Development of an Optimal Bundle of Management for Cardiac Arrest

2020· article· en· W3095060600 on OpenAlex
Paul E. Pepe, Tom P. Aufderheide, Lionel Lamhaut, Daniel P. Davis, Charles Lick, Kees H. Polderman, Kenneth Scheppke, Charles D. Deakin, Brian J. O’Neil, Hans van Schuppen, Michael K. Levy, Marvin A. Wayne, Scott T. Youngquist, Johanna Moore, Keith G. Lurie, Jason A. Bartos, Kerry Bachista, Michael Jacobs, Carolina Rojas-Salvador, Sean Grayson, James E. Manning, Michael C. Kurz, Guillaume Debaty, Nicolas Segal, Peter Antevy, David Miramontes, Sheldon Cheskes, Joe Holley, Ralph J. Frascone, Raymond L. Fowler, Demetris Yannopoulos

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Care Explorations · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCardiopulmonary resuscitationMedicineReturn of spontaneous circulationExtracorporeal membrane oxygenationResuscitationEmergency medical servicesEmergency medicineAdvanced life supportPopulationSudden cardiac arrestMedical emergencyInternal medicine

Abstract

fetched live from OpenAlex

Objectives: To construct a highly detailed yet practical, attainable roadmap for enhancing the likelihood of neurologically intact survival following sudden cardiac arrest. Design, Setting, and Patients: Population-based outcomes following out-of-hospital cardiac arrest were collated for 10 U.S. counties in Alaska, California, Florida, Ohio, Minnesota, Utah, and Washington. The 10 identified emergency medical services systems were those that had recently reported significant improvements in neurologically intact survival after introducing a more comprehensive approach involving citizens, hospitals, and evolving strategies for incorporating technology-based, highly choreographed care and training. Detailed inventories of in-common elements were collated from the ten 9-1-1 agencies and assimilated. For reference, combined averaged outcomes for out-of-hospital cardiac arrest occurring January 1, 2017, to February 28, 2018, were compared with concurrent U.S. outcomes reported by the well-established Cardiac Arrest Registry to Enhance Survival. Interventions: Most commonly, interventions and components from the ten 9-1-1 systems consistently included extensive public cardiopulmonary resuscitation training, 9-1-1 system-connected smart phone applications, expedited dispatcher procedures, cardiopulmonary resuscitation quality monitoring, mechanical cardiopulmonary resuscitation, devices for enhancing negative intrathoracic pressure regulation, extracorporeal membrane oxygenation protocols, body temperature management procedures, rapid cardiac angiography, and intensive involvement of medical directors, operational and quality assurance officers, and training staff. Measurements and Main Results: Compared with Cardiac Arrest Registry to Enhance Survival ( n = 78,704), the cohorts from the 10 emergency medical services agencies examined ( n = 2,911) demonstrated significantly increased likelihoods of return of spontaneous circulation (mean 37.4% vs 31.5%; p < 0.001) and neurologically favorable hospital discharge, particularly after witnessed collapses involving bystander cardiopulmonary resuscitation and shockable cardiac rhythms (mean 10.7% vs 8.4%; p < 0.001; and 41.6% vs 29.2%; p < 0.001, respectively). Conclusions: The likelihood of neurologically favorable survival following out-of-hospital cardiac arrest can improve substantially in communities that conscientiously and meticulously introduce a well-sequenced, highly choreographed, system-wide portfolio of both traditional and nonconventional approaches to training, technologies, and physiologic management. The commonalities found in the analyzed systems create a compelling case that other communities can also improve out-of-hospital cardiac arrest outcomes significantly by conscientiously exploring and adopting similar bundles of system organization and care.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.812
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.066
GPT teacher head0.347
Teacher spread0.281 · 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