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Record W3156114616 · doi:10.1016/j.ijcha.2021.100780

Rhythm monitoring strategies for atrial fibrillation detection in patients with cryptogenic stroke: A systematic review and meta-analysis

2021· review· en· W3156114616 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIJC Heart & Vasculature · 2021
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersAlberta InnovatesUniversity of AdelaideNational Health and Medical Research CouncilNational Heart Foundation of Australia
KeywordsMedicineAtrial fibrillationInternal medicineCardiologyStroke (engine)Meta-analysisConfidence intervalPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize data on atrial fibrillation (AF) detection rates and predictors across different rhythm monitoring strategies in patients with cryptogenic stroke (CS) or embolic stroke of undetermined source (ESUS). METHODS: MEDLINE, Embase, and Web of Science were searched to identify all published studies providing relevant data through July 6, 2020. Random-effects meta-analysis method was used to pool estimates. RESULTS: -VASc score, left atrial enlargement, P wave maximal duration and prolonged PR interval. CONCLUSION: The yield of ICM increases with the duration of monitoring. More than a quarter of patients with CS or ESUS will be diagnosed with AF during follow-up. About one in seven patients had AF detected within a month of MCOT, suggesting that a non-invasive rhythm monitoring strategy should be considered before invasive monitoring.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.005
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 head0.090
GPT teacher head0.371
Teacher spread0.281 · 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