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Record W3109217075 · doi:10.1093/ehjci/ehaa946.2345

Role of estimated aortic pulse wave velocity in the prediction of future thoracic aortic aneurysm expansion

2020· article· en· W3109217075 on OpenAlexaffabout
Kevin E. Boczar, Munir Boodhwani, Luc Beauchesne, Carole Dennie, Kwan‐Leung Chan, George A. Wells, Thais Coutinho

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsPulse wave velocityMedicineCardiologyInternal medicineArterial stiffnessPulse pressureLinear regressionBlood pressureThoracic aortic aneurysmStepwise regressionAortaAortic aneurysm

Abstract

fetched live from OpenAlex

Abstract Background Thoracic aortic aneurysm (TAA) is a deadly disease in critical need of novel strategies for risk assessment and medical management. To address this need, we have previously shown that directly measured carotid-femoral pulse wave velocity (cfPWV), a marker of aortic stiffness and health, independently predicts future TAA expansion. Since aortic pulse wave velocity can be estimated from age and mean arterial pressure (MAP), in the present study we sought to determine whether estimated aortic pulse wave velocity (e-aPWV) also predicts TAA expansion. Methods One hundred and five consecutive, unoperated subjects with TAA were recruited. e-aPWV was estimated from validated equations based on age and MAP. cfPWV was measured with arterial tonometry according to guidelines. TAA size was measured at baseline and at the latest follow-up using available imaging modalities according to guidelines. Stepwise multivariable linear regression (P≤0.25 to enter, P≤0.10 to stay in the model) assessed independent associations of e-aPWV and cfPWV with future TAA growth. Variables considered in the models were: age, sex, BSA, MAP, TAA etiology and location, baseline TAA size, follow-up time, imaging modality, history of hypertension, diabetes and smoking. Results Seventy eight percent of subjects were men. Mean±SD age, baseline aneurysm size and follow-up time were 62.6±11.4 years, 46.2±3.8 mm and 3.0±1.0 years, respectively. e-aPWV and cfPWV were moderately correlated (Pearson's correlation coefficient = 0.61). Results of the linear regression analyses showed that both measured (cfPWV) and estimated (e-aPWV) independently predicted future TAA expansion (β±SE: 0.032±0.011, P=0.048 and 0.240±0.085, P=0.006, respectively). The base model's R-squared value of 0.39 was increased to 0.44 with addition of either cfPWV or e-aPWV to the model, confirming that each parameter of aortic stiffness enhances prediction of TAA growth. Conclusion Aortic stiffness is relevant for assessment of TAA disease activity. Similar to cfPWV, e-aPWV is also independently associated with future TAA expansion. Thus, e-aPWV represents a tool to improve TAA risk stratification that is simple, free of cost, and obviates the need for specialized equipment or dedicating training, which leads to excellent potential for widespread incorporation into clinical practice. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Canadian Institutes of Health Research

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)0.002
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.303
Teacher spread0.234 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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