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Record W1723310269

Inverse electrocardiographic imaging to assess electrical dyssynchrony in cardiac resynchronization therapy patients

2012· article· en· W1723310269 on OpenAlex

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

VenueComputing in Cardiology Conference · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCardiac resynchronization therapyCardiologyInternal medicineVentricular dyssynchronyMedicineElectrocardiographyHeart failureBiomedical engineeringEjection fraction
DOInot available

Abstract

fetched live from OpenAlex

Electrical dyssynchrony is postulated to be one of the main factors contributing to non-response of patients to cardiac resynchronization therapy (CRT). We applied inverse epicardial imaging computed from patient-specific geometry and body-surface potential recordings to assess global and regional electrical dyssynchrony. Patients were imaged pre- and post-device implantation, without and with pacing function (P-OFF and P-ON). The reconstructed maps of activation in the dyssynchronous pre-CRT rhythm agree with published contact mapping activation maps with earliest activation starting on the RV free wall and slowly spreading to the LV in a U-shaped pattern. The new ΔQRSi metric captures global pre-CRT dyssynchrony showing negative values (−0.32±0.10) with minimal variability beats (coefficient of variation 10±3.6%) while post-CRT pacing indicates positive values (0.18±0.11). The imaging method is well-suited to study electrical dyssynchrony and potentially guide CRT lead placement.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.043
GPT teacher head0.315
Teacher spread0.271 · 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