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Record W4308060043 · doi:10.1002/jmri.28491

Cardiac <scp>MRI</scp> Left Atrial Strain Associated With <scp>New‐Onset</scp> Atrial Fibrillation in Patients With <scp>ST</scp>‐Segment Elevation Myocardial Infarction

2022· article· en· W4308060043 on OpenAlexaboutno aff
Lei Chen, Min Zhang, Wensu Chen, Zhi Li, Yiwen Wang, Dongchen Liu, Yang Duan, Chaoqun Zhang, Zhirong Wang, Yuan Lu

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtrial fibrillationInternal medicineCardiologyEjection fractionMagnetic resonance imagingMyocardial infarctionReceiver operating characteristicCardiac magnetic resonance imagingCoronary artery diseaseArea under the curveHeart failureRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Left atrial (LA) strain is associated with structural remodeling of the LA. Whether there is an association between LA strain obtained by cardiac magnetic resonance imaging (MRI) and new-onset atrial fibrillation (AF) after ST-segment elevation myocardial infarction (STEMI) is unclear. PURPOSE: To investigate the relationship between LA strain and new-onset AF after STEMI. STUDY TYPE: Retrospective. POPULATION: Three hundred and seventy-nine STEMI patients were enrolled, of which 26 had new-onset AF. FIELD STRENGTH/SEQUENCE: 3.0 T, balanced turbo field echo sequence. ASSESSMENT: Patients were divided into w/o AF group and new-onset AF group. Cardiac MRI images were analyzed using cardiovascular imaging software CVI 42 (Circle Cardiovascular Imaging, Canada). An automatic tracing algorithm was applied to obtain strain values. The reservoir strain, conduit strain, and booster strain were included in model 1, model 2, and model 3, respectively. STATISTICAL TESTS: Student's t-test, Mann-Whiney U test, and chi-square test were performed. Variables with a P ≤ 0.05 were incorporated into the logistic regression analysis. Area under curve of receiver operating characteristic was used to assess the ability of LA strain to identify new-onset AF. Bayesian information criterion, Akaike information criterion, and C-index were used to make comparisons between three models. P < 0.05 was considered statistically significant. RESULTS: Three models were used to assess LA strain identification ability for new-onset AF. After including multiple factors, right coronary artery (RCA), LVEF, and reservoir strain were still risk factors for new-onset AF in model 1. In model 2, age, RCA, LVEF, and conduit strain were still risk factors for new-onset AF. In model 3, RCA, LVEF, LVEDVi, and booster strain were still risk factors for new-onset AF. Model 2 has a stronger identification ability than others. DATA CONCLUSION: LA strain associated with new-onset AF after STEMI. The model including conduit strain was the best-fit one. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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.

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

Citations15
Published2022
Admission routes1
Has abstractyes

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