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Record W3107323282 · doi:10.1093/ehjci/ehaa946.0383

Frequent premature atrial complexes and risk of concurrent atrial fibrillation

2020· article· en· W3107323282 on OpenAlexaff
Linda Johnson, Natan Napiórkowski, Marek Jacek Dziubinski, David Conen, Jeff S. Healey, Gunnar Engström

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsMedicineAtrial fibrillationAmbulatoryPremature atrial contractionAmbulatory ECGInternal medicineCardiologyReproducibilityPopulationElectrocardiography

Abstract

fetched live from OpenAlex

Abstract Background Premature atrial complexes (PACs) predict incident atrial fibrillation (AF) in long-term follow-up studies. It is unclear whether frequent PACs on ambulatory ECG recordings indicate a higher likelihood of concurrent, undiagnosed AF. Furthermore, the reproducibility of a 24 h PAC count is unclear. Objectives To determine if frequent PACs on 24 h ambulatory ECG monitoring predicts concurrent AF during subsequent, prolonged ECG monitoring and to assess the diagnostic reliability of PAC counts on a 24 hour ECG recording. Methods AF was defined as ≥30 seconds of irregular rhythm without P waves, which was detected by a proprietary algorithm and manually verified. The proportion of AF occurrence during the remainder of the monitoring period was calculated for pre-specified levels of PACs during the first 24 h, and a function describing the association was fitted. The diagnostic reproducibility of a 24 h PAC count was assessed by calculating the likelihood of a PAC count ≥1000/day during the entire monitoring duration for prespecified PAC count levels during the first 24h. Results The study population comprised 20,973 patients (41% men, mean age 69.5 years) who had recorded an ambulatory ECG with a monitoring duration of 4–30 days in the United States during the year 2017 (median monitoring duration 16 days). AF was detected in 2,029 (9.7%) of patients and the median time to first occurrence of AF was 5 days. PAC frequency during the first 24 h was associated with AF during the monitoring period beyond the first 24 h, increasing steadily from 4.2% among those with 0–5 PACs, to a plateau around 17% among those with 250–1000 PACs per day and above. (Fig. 1A). The reproducibility of low PAC counts was good. Only 5.5% of patients with 0–5 PACs during the first 24 h of monitoring (31.8% of the population), had ≥1000 PACs on an alternate monitoring day. In contrast, among subjects with 100 PACs the probability of a day with ≥1000 PACs was close to 50% (Fig. 1B). Conclusion In patients undergoing ambulatory ECG monitoring, frequent PACs during the first 24 h indicate a higher likelihood of AF occurrence during subsequent days of monitoring. Less than 5 PACs during the first 24 h indicate a low probability of AF or frequent PACs on a subsequent day of ECG monitoring. Figure 1 Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): The Swedish Heart and Lung Foundation; The Swedish Heart and Lung Association

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)0.006
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 science0.0000.000
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 head0.100
GPT teacher head0.340
Teacher spread0.240 · 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
Published2020
Admission routes1
Has abstractyes

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