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Abstract 241: Amplitude Spectrum Area as a Tool to Identify the Circulatory Phase of Ventricular Fibrillation

2013· article· en· W204257880 on OpenAlexaff
Giuseppe Ristagno, Weilun Quan, Annemarie Silver, Ulrich Herken, Bentley J. Bobrow

Bibliographic record

VenueCirculation · 2013
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsBentley (Canada)
Fundersnot available
KeywordsMedicineVentricular fibrillationCirculatory systemCardiologyInternal medicinePhase (matter)

Abstract

fetched live from OpenAlex

Background: Ventricular fibrillation (VF) cardiac arrest (CA) is characterized by 3 time dependent phases: electrical (shorter than 4min), circulatory (4-10min), and metabolic (longer than 10min). These phases reflect the progressive increase of myocardial ischemia and suggest the potentially optimal treatment. During the electrical phase, immediate defibrillation is likely to be successful, while during the circulatory phase, the success of defibrillation diminishes without CPR. In the metabolic phase, there is low likelihood of successful resuscitation and probably a longer CPR interval prior to defibrillation is necessary. In the out-of-hospital (OH) setting, most patients may have passed the electrical phase when EMS arrives. Identification of the VF phase may therefore facilitate the proper CPR treatment. We used AMSA to determine if patients were in circulatory or in metabolic phase at EMS arrival. Methods: Data from an Utstein-compliant registry along with electronic ECG records were collected on consecutive adult OHCA patients treated by 2 EMS agencies over a 2 year period. Patients with bystander witnessed CA and with VF as initial CA rhythm were included (n=41). AMSA was calculated in earliest pause without compression artifacts, using a 2 sec ECG with a Tukey (0.2) FFT window. VF duration was calculated as the sum of the time interval from collapse to defibrillator on and the time interval from defibrillator on to first CPR interruption for defibrillation delivery. Results: VF duration ranged between 6.5 and 29.6 min (11.3+4.1 min), with a corresponding AMSA between 2.1 and 16.4 mV-Hz (9.4+4.2 mV-Hz). AMSA measured in the circulatory phase (N=19) was significantly higher than that in the metabolic phase (N=22) (8.14+3.17 vs. 5.98+2.88, p=0.03). Linear regression revealed that AMSA decreases by 0.22 mV-Hz for every min of VF. AMSA was able to predict circulatory phase with an accuracy of 0.7 in ROC area. An AMSA threshold of 10 mV-Hz was able to predict the circulatory phase with sensitivity of 32%, specificity of 95%, PPV of 86%, NPV of 62% and overall accuracy of 66%. Conclusions: AMSA is a good indicator of downtime in OHCA with initial rhythm of VF. AMSA could be used to identify VF phase and thereby suggest for the proper CPR intervention.

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)0.004
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.033
GPT teacher head0.353
Teacher spread0.320 · 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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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