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Meta-Analysis of Normal Reference Values for Right and Left Ventricular Quantification by Cardiovascular Magnetic Resonance

2024· article· en· W4391983004 on OpenAlexaff
Yang Zhan, Matthias G. Friedrich, Nandini Dendukuri, Lu Yang, Michael Chetrit, Ian Schiller, Lawrence Joseph, Jaime L. Shaw, Michael L. Chuang, Johannes Riffel, Warren J. Manning, Jonathan Afilalo

Bibliographic record

VenueCirculation Cardiovascular Imaging · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsMcGill UniversityMcGill University Health CentreRegina General HospitalJewish General Hospital
Fundersnot available
KeywordsReference valuesBody surface areaCardiologyMedicineMagnetic resonance imagingConfidence intervalEjection fractionInternal medicineMeta-analysisStroke volumeNuclear medicineRadiologyHeart failure

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiovascular magnetic resonance (CMR) reference values are relied upon to accurately diagnose left ventricular (LV) and right ventricular (RV) pathologies. To date, reference values have been derived from modest sample sizes with limited patient diversity and attention to 1 but not both commonly used tracing techniques for papillary muscles and trabeculations. We sought to overcome these limitations by meta-analyzing normal reference values for CMR parameters stemming from multiple countries, vendors, analysts, and patient populations. METHODS: We comprehensively extracted published and unpublished data from studies reporting CMR parameters in healthy adults. A steady-state free-precession short-axis stack at 1.5T or 3T was used to trace either counting the papillary muscles and trabeculations in the LV volume or mass. We used a novel Bayesian hierarchical meta-analysis model to derive the pooled lower and upper reference values for each CMR parameter. Our model accounted for the expected differences between tracing techniques by including informative prior distributions from a large external data set. RESULTS: A total of 254 studies from 25 different countries were systematically reviewed, representing 12 812 healthy adults, of which 52 were meta-analyzed. For LV parameters counting papillary muscles and trabeculations in the LV volume, pooled normative reference ranges in men and women, respectively, were as follows: LV ejection fraction of 52% to 73% and 54% to 75%, LV end-diastolic volume index of 60 to 109 and 56 to 96 mL/m 2 , LV end-systolic volume index of 18 to 45 and 16 to 38 mL/m 2 , and LV mass index of 41 to 76 and 33 to 57 g/m 2 . For LV parameters counting papillary muscles and trabeculations in the LV mass, pooled normative reference ranges in men and women, respectively, were as follows: LV ejection fraction of 57% to 74% and 57% to 75%, LV end-diastolic volume index of 60 to 97 and 55 to 88 mL/m 2 , LV end-systolic volume index of 18 to 37 and 15 to 34 mL/m 2 , and LV mass index of 50 to 83 and 38 to 65 g/m 2 . For RV parameters, pooled normative reference ranges in men and women, respectively, were as follows: RV ejection fraction of 47% to 68% and 49% to 71%, RV end-diastolic volume index of 64 to 115 and 57 to 99 mL/m 2 , RV end-systolic volume index of 23 to 52 and 18 to 42 mL/m 2 , and RV mass index of 14 to 29 and 13 to 25 g/m 2 . CONCLUSIONS: Our Bayesian hierarchical meta-analysis provides normative reference values for CMR parameters of LV and RV size, systolic function, and mass, encompassing both tracing techniques across a diverse multinational sample of healthy men and women.

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)0.000
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: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.006
Bibliometrics0.0010.001
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 head0.039
GPT teacher head0.278
Teacher spread0.239 · 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 designMeta-analysis
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

Citations22
Published2024
Admission routes1
Has abstractyes

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