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Record W7117108160 · doi:10.1016/j.jacadv.2025.102507

Prognostic Value of CMR-Derived Left Ventricular Filling Pressure in Broad Referral Populations

2025· article· en· W7117108160 on OpenAlexaff
Ahsan A. Khan, Steven Dykstra, Jacqueline Flewitt, Sandra Rivest, Yuanchao Feng, Augustine Amakiri, Melanie King, Andrew G. Howarth, Carmen Lydell, Michael Bristow, Louis Kolman, Jonathan G. Howlett, Robert J.H. Miller, Nowell M. Fine, Dina Labib, James A. White

Bibliographic record

VenueJACC Advances · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of CalgaryLibin Cardiovascular Institute of Alberta
Fundersnot available
KeywordsVentricular fillingReferralValue (mathematics)Heart failureBlood pressureTertiary referral centre

Abstract

fetched live from OpenAlex

BACKGROUND: ) has shown strong correlation with invasively measured values and early promise as a prognostic marker in defined patient populations. OBJECTIVES: with future heart failure (HF) outcomes in a large, diverse CMR referral population with stratified analyses by left ventricular (LV) ejection fraction (LVEF) subgroups. METHODS: was calculated. RESULTS: ≥18 mm Hg remained independently associated with the outcome in the overall cohort, as well as LVEF subgroups. Respective adjusted HR for patients with LVEF <40%, 40 to 50% and >50% were 1.510 (1.216-1.876), 1.582 (1.153-2.171), and 2.865 (2.307-3.559). The latter group demonstrated similar value in patients with vs without coronary disease. CONCLUSIONS: is a powerful predictor of future HF outcomes in broad referral populations inclusive of patients with reduced, mildly reduced, and preserved LV function.

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)0.005
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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 science0.0000.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.302
Teacher spread0.283 · 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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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