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Record W4380763463 · doi:10.1161/circ.146.suppl_1.200

Abstract 200: Left-ventricular Outflow Compression During Cardiopulmonary Resuscitation Is Associated With Lower Return Of Spontaneous Circulation In Out-of-hospital Cardiac Arrest

2022· article· en· W4380763463 on OpenAlexaff
Felipe Teran, Nathaniel Sands, Trenton Wray, Wendy Hanna, Erik Kraai, Jenna White, Ranjani Venkataramani, John E Hipskind, Jonathan Nogueira, Michelle Clinton, Michael Jones, Daniella Rodriguez, Peiman Nazerian, Eleonora Villa, Justine Lessard, William Bédard Michel, Chantal Lanthier, Lawrence Haines, Leily Naraghi, Harpriya Singh, Antonios Likourezos, Michael Y. Woo, Paul Pageau, Rajiv Thavanathan, Michael Secko, Daniel E. Singer, Brian Buchanan, Nadia Baig, Korbin Haycock, Ramiz Fargo, Lauren D Sutherland, Harry Wanar, James L. J. Coleman, Zan M Jafry, John Joyce, Aaron Hittson, Lindsay Taylor, Michael J. Vitto, Stephanie C. DeMasi, Katharine Burns, Pedro D. Salinas, Matthew D. Tyler, Frank Myslik, Robert Arntfield, Branka Vujčić, Clark G. Owyang, Tomislav Jelić, Benjamin S. Abella

Bibliographic record

VenueCirculation · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of ManitobaLondon Health Sciences CentreUniversity of OttawaUniversity of AlbertaHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicineReturn of spontaneous circulationCardiopulmonary resuscitationCardiologyVentricular outflow tractInternal medicineResuscitationUnivariate analysisProspective cohort studyRetrospective cohort studyMultivariate analysisEmergency medicine

Abstract

fetched live from OpenAlex

Introduction: Transesophageal echocardiography (TEE) has been proposed as a tool ideally suited for imaging patients during cardiac arrest (CA) resuscitation, allowing for the evaluation of the area of maximal compression (AMC) during CPR. Previous work has shown that compression of the left-ventricular outflow tract (LVOT) or the aortic root during CPR (AMC-LVOT/Ao) occurs in over 50% of patients; animal trials and small single-center retrospective clinical study have linked this finding to lower rates of ROSC. We aimed to prospectively investigate the AMC and its association with ROSC. We hypothesized that patients who have AMC-LVOT/Ao have lower likelihood of ROSC. Methods: A prospective, observational, multicenter cohort study involving patients with out-of-hospital CA (OHCA) in whom TEE was performed during CPR. The study aimed to compare patients with AMC over the LV (AMC-LV) vs AMC-LVOT/Ao and was conducted through a collaborative research network involving 16 hospitals (NCT04972526). Data was collected on clinical and TEE characteristics and findings. Primary outcome was ROSC. We performed univariate analysis followed by multivariate regression model evaluating variables known to impact resuscitation outcomes. Results: Eighty-four patients were included in the analysis. Mean age 62 (46-72), 28% female, 71% had witnessed arrest, 60% had bystander CPR, 47% had mechanical CPR. Overall 26 patients (32%) had ROSC. Initial AMC during CPR was determined in 55/84 (65%) patients, of whom 33 (60%) had AMC-LV, 18 (33%) had AMC-LVOT/Ao, and 4 (7%) had other locations. There was no significant difference in AMC when analyzed by demographic characteristics, height, weight or between patients who received manual vs mechanical CPR. In multivariate regression controlling for age, race, gender, initial rhythm of arrest, level of TEE operator, doses of epinephrine, now-flow time, and total time of arrest, AMC-LVOT/Ao was significantly associated with lower ROSC probability (OR 0.06, 95% CI 0.01-0.4; p=0.009). Conclusion: In this multicenter, prospective study of patients with OHCA, TEE-guided resuscitation showed a strong association between the AMC and ROSC.

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)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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