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Record W3163768363 · doi:10.21037/qims-20-1267

Analysis of right ventricular flow with 4-dimensional flow cardiovascular magnetic resonance imaging in patients with pulmonary arterial hypertension

2021· article· en· W3163768363 on OpenAlexfundno aff
Lei Wang, Min Liu, Pei Yao Zhang, Jin Zhu Dai, Hai Yi, Xin Tao, W M Xie, Jun Wan, Jing An

Bibliographic record

VenueQuantitative Imaging in Medicine and Surgery · 2021
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsnot available
FundersCircle Cardiovascular ImagingNational Natural Science Foundation of China
KeywordsCardiologyMedicineInternal medicineMagnetic resonance imagingHemodynamicsEjection fractionCardiac indexCardiac magnetic resonance imagingPulmonary hypertensionVascular resistanceStroke volumeCardiac outputHeart failureRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiac flow closely interact with function, however, the correlation of right ventricular (RV) flow and function remains unknown, thus our objective is to observe right ventricular flow with four-dimensional phase-contrast cardiovascular magnetic resonance imaging (4D flow CMR) in patients with pulmonary arterial hypertension (PAH) and to analyze flow components with RV function and hemodynamics. METHODS: This study retrospectively enrolled 30 patients with PAH (mean age: 49±13 years, 16 females) and 14 age- and sex-matched healthy volunteers as controls (mean age: 44±12 years, 9 females). All patients who underwent CMR and right heart catheterization (RHC) within 1 week between January 2019 and July 2020 were included. Hemodynamics were measured with RHC. RV flow components, including the percentages of direct flow (RVPDF), retained inflow (RVPRI), delayed ejection flow (RVPDEF) and residual volume (RVPRVo) were quantified using 4D flow CMR. The associations between RV flow components and other CMR metrics, clinical data, and hemodynamics were analyzed by Spearman's correlation analysis. RESULTS: In patients with PAH, RVPDF was decreased and RVPRVo was increased compared with the normal control group. The sum of RVPDF and RVPDEF RV was significantly correlated with RV ejection fraction (RVEF) (r=0.802, P<0.001), and there was no notable difference between RVEF and the sum of RVPDF and RVPDEF (t=0.251, P=0.831). Both RVPDF and RVPRVo were correlated (in opposite directions) with the RV end-diastolic volume index, RV end-systolic volume index, RV global longitudinal strain, and RVEF. RVPDF was negatively correlated with pulmonary vascular resistance (PVR), and positively correlated with cardiac output and cardiac index. RVPRVo was positively correlated with PVR and negatively correlated with cardiac output and cardiac index. CONCLUSIONS: RV blood flow components qualified with 4D flow CMR is a valuable noninvasive method for the assessment of RV function and hemodynamics in patients with PAH.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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

Citations17
Published2021
Admission routes1
Has abstractyes

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