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Record W3215200044 · doi:10.1016/j.jacep.2021.09.015

Temporal Association of Atrial Fibrillation With Cardiac Implanted Electronic Device Detected Heart Failure Status

2021· article· en· W3215200044 on OpenAlexaff
Alessandro Capucci, Jorge Wong, Michael R. Gold, John Boehmer, Rezwan Ahmed, Brian Kwan, Pramodsingh H. Thakur, Yi Zhang, Paul W. Jones, Jeff S. Healey

Bibliographic record

VenueJACC. Clinical electrophysiology · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsPopulation Health Research InstituteMcMaster University
FundersServierBoston Scientific CorporationMedtronicPfizer
KeywordsMedicineAtrial fibrillationInternal medicineHeart failureCardiologyCardiac resynchronization therapyAmbulatoryNatriuretic peptideImplantable loop recorderComorbidityEjection fraction

Abstract

fetched live from OpenAlex

OBJECTIVES: This study sought to investigate the temporal association between changes in physiologic heart failure (HF) sensors, atrial fibrillation (AF) progression, and clinical HF in patients with cardiac resynchronization therapy implantable defibrillators (CRT-D) designed to monitor AF and HF daily. BACKGROUND: AF is a common comorbidity in HF; however, it is unclear if HF triggers AF, or vice-versa. Current implantable cardiac devices have sensors capable of quantifying HF status, which permits a greater understanding of the impact of AF on HF status and may help guide treatment. METHODS: The MultiSENSE (Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients) study collected multiple sensor data indicative of HF status in patients with CRT-D followed for up to 12 months. Patients were grouped according to their longest daily AF burden: 1) at least 24 hours of AF (HIGH AF); 2) between 6 minutes and 24 hours (MID AF); and 3) <6 minutes (NO AF). Sensor data were aligned to the first qualifying AF event or a randomly selected day for patients in the NO AF group. RESULTS: Among 869 patients with daily AF data available, 98 patients had HIGH AF, 141 patients MID AF, and 630 patients NO AF. At baseline, history of AF, N-terminal pro hormone B-type natriuretic peptide and device-measured S3 were associated with development of AF. HeartLogic index increased before AF onset (Δ HeartLogic = 9.83 ± 2.49; P < 0.001). Multivariable time-dependent Cox regression showed an increased risk for HF events following a 24-hour AF episode compared with no 24-hour AF (hazard ratio: 1.96; 95% confidence interval: 1.03-3.74). CONCLUSIONS: Device-measured HF indicators worsened before AF onset, whereas clinical HF deterioration only became apparent after AF occurred. Thus, the sensitivity of methods to ascertain AF and HF status appear to influence the direction of perceived causality. (Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients [MultiSENSE]; NCT01128166).

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)0.002
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 score0.134
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.015
GPT teacher head0.325
Teacher spread0.310 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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