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Record W2965734418 · doi:10.1161/circep.119.007171

Refining the World Health Organization Definition

2019· article· en· W2965734418 on OpenAlexaff
Zian H. Tseng, James W. Salazar, Jeffrey E. Olgin, Philip C. Ursell, Annie Bedigian, Joanne Probert, Amy P. Hart, Ellen Moffatt, Eric Vittinghoff

Bibliographic record

VenueCirculation Arrhythmia and Electrophysiology · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsOffice of the Chief Medical Examiner
FundersNational Institute of Biomedical Imaging and BioengineeringNational Heart, Lung, and Blood Institute
KeywordsMedicineRefining (metallurgy)Intensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Conventional definitions of sudden cardiac death (SCD) presume cardiac cause. We studied the World Health Organization-defined SCDs autopsied in the POST SCD study (Postmortem Systematic Investigation of SCD) to determine whether premortem characteristics could identify autopsy-defined sudden arrhythmic death (SAD) among presumed SCDs. METHODS: Between January 2, 2011, and January 4, 2016, we prospectively identified all 615 World Health Organization-defined SCDs (144 witnessed) 18 to 90 years in San Francisco County for medical record review and autopsy via medical examiner surveillance. Autopsy-defined SADs had no extracardiac or acute heart failure cause of death. We used 2 nested sets of premortem predictors-an emergency medical system set and a comprehensive set adding medical record data-to develop Least Absolute Selection and Shrinkage Operator models of SAD among witnessed and unwitnessed cohorts. RESULTS: Of 615 presumed SCDs, 348 (57%) were autopsy-defined SAD. For witnessed cases, the emergency medical system model (area under the receiver operator curve 0.75 [0.67-0.82]) included presenting rhythm of ventricular tachycardia/fibrillation and pulseless electrical activity, while the comprehensive (area under the receiver operator curve 0.78 [0.70-0.84]) added depression. If only ventricular tachycardia/fibrillation witnessed cases (n=48) were classified as SAD, sensitivity was 0.46 (0.36-0.57), and specificity was 0.90 (0.79-0.97). For unwitnessed cases, the emergency medical system model (area under the receiver operator curve 0.68 [0.64-0.73]) included black race, male sex, age, and time since last seen normal, while the comprehensive (area under the receiver operator curve 0.75 [0.71-0.79]) added use of β-blockers, antidepressants, QT-prolonging drugs, opiates, illicit drugs, and dyslipidemia. If only unwitnessed cases <1 hour (n=59) were classified as SAD, sensitivity was 0.18 (0.13-0.22) and specificity was 0.95 (0.90-0.97). CONCLUSIONS: Our models identify premortem characteristics that can better specify autopsy-defined SAD among presumed SCDs and suggest the World Health Organization definition can be improved by restricting witnessed SCDs to ventricular tachycardia/fibrillation or nonpulseless electrical activity rhythms and unwitnessed cases to <1 hour since last normal, at the cost of sensitivity.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.245
Teacher spread0.234 · 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 teacher head, 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

Citations27
Published2019
Admission routes1
Has abstractyes

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