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Record W1595228630 · doi:10.1161/circ.130.suppl_2.86

Abstract 86: Association Between Hospital Postresuscitative Performance and Clinical Outcomes in Patients with Out-of-Hospital Cardiac Arrest

2014· article· en· W1595228630 on OpenAlexaff
Dion Stub, Robert H. Schmicker, Monique Anderson, Eric D. Peterson, Clifton W. Callaway, Mohamud Daya, Michael R. Sayre, Jonathan Elmer, Brian Grunau, Tom P. Aufderheide, Steve Lin, Jason E. Buick, Dana Zive, Graham Nichol

Bibliographic record

VenueCirculation · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of TorontoSt. Paul's Hospital
Fundersnot available
KeywordsMedicineQuartileResuscitationContext (archaeology)Observational studyCardiopulmonary resuscitationMyocardial infarctionTargeted temperature managementInternal medicineEmergency medicineHospital dischargeAdvanced life supportReturn of spontaneous circulationConfidence interval

Abstract

fetched live from OpenAlex

Context: Whilst performance measures have been extensively evaluated in conditions such as myocardial infarction, it remains unclear if adherence to post-resuscitation guidelines is associated with better outcome in patients hospitalized after out-of-hospital cardiac arrest (OHCA). Objectives: To assess whether survival and good functional status at discharge are associated with post-resuscitation performance score based on treatment guidelines for patients with OHCA, comprised of a) initiation of temperature management; b) target temperature 32 0 -34 0 C achieved; c) temperature management continued for more than 12 hours; d) coronary angiography performed within 24 hrs; e) life sustaining treatment not withdrawn prior to day 3. Methods: An observational analysis of hospital care in 111 North American hospitals, including 3252 patients enrolled in the Resuscitation Outcomes Consortium (ROC-PRIMED) study, between 2007 and 2009, following OHCA. Performance scores were calculated, utilizing opportunity based scoring, with each factor weighted equally and scaled from 0-1. Scores for individual patients were grouped at the hospital level, with hospitals divided for descriptive purposes into quartiles based on their median opportunity composite score. Results: Performance score varied widely (median [IQR] scores from lowest to highest hospital quartiles, 21% [20%-25%] vs 59% [55%-64%]. Adjusted survival to discharge increased with each quartile of performance score (lowest to highest: 16.2%, 20.8%, 28.5%, 34.8%, P <0.01). Similarly adjusted rates of good functional outcome improved (lowest quartile to highest: 8.3%, 13.8%, 22.2%, 25.9%, P<0.01). Hospital performance score were significantly associated with outcome after risk adjustment for established prehospital resuscitative factors (Highest versus lowest adherence quartile: adjusted OR of survival 1.64; 95% CI 1.13, 2.38) Conclusions: Increased survival and improved functional status at discharge are associated with greater adherence to recommended hospital based post-resuscitative care guidelines. Measuring, reporting and improving hospital adherence to guideline-based performance metrics could improve outcomes following OHCA.

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)0.003
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.009
GPT teacher head0.270
Teacher spread0.261 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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