MétaCan
Menu
Back to cohort
Record W2997175756 · doi:10.1002/ehf2.12582

Gender and Age Normalization and Ventilation Efficiency During Exercise in Heart Failure with Reduced Ejection Fraction

2020· article· en· W2997175756 on OpenAlexaff
Elisabetta Salvioni, Ugo Corrà, Massimo Piepoli, Sara Rovai, Michele Correale, Stefania Paolillo, Mario Pasquali, Damiano Magrì, Giuseppe Vitale, Laura Fusini, Massimo Mapelli, Carlo Vignati, Rocco Lagioia, Rosa Raimondo, Gianfranco Sinagra, Federico Boggio, Lorenzo Cangiano, Giovanna Gallo, Alessandra Magini, Mauro Contini, Pietro Palermo, Anna Apostolo, Beatrice Pezzuto, Alice Bonomi, Angela Beatrice Scardovi, Pasquale Perrone Filardi, Giuseppe Limongelli, Marco Metra, Domenico Scrutinio, Michele Emdin, Lucrezia Piccioli, Carlo Lombardi, Gaia Cattadori, Gianfranco Parati, Sergio Caravita, Federica Re, Mariantonietta Cicoira, Maria Frigerio, Francesco Clemenza, Maurizio Bussotti, Elisa Battaia, Marco Guazzi, Francesco Bandera, Roberto Badagliacca, Andrea Di Lenarda, Giuseppe Pacileo, Claudio Passino, Susanna Sciomer, Giuseppe Ambrosio, Piergiuseppe Agostoni

Bibliographic record

VenueESC Heart Failure · 2020
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSurgical Specialties (Canada)
FundersMinistero della Salute
KeywordsEjection fractionMedicineHeart failureCardiologyInternal medicinePopulationRespiratory minute volumeRespiratory system

Abstract

fetched live from OpenAlex

Abstract Aims Ventilation vs. carbon dioxide production (VE/VCO2) is among the strongest cardiopulmonary exercise testing prognostic parameters in heart failure (HF). It is usually reported as an absolute value. The current definition of normal VE/VCO2 slope values is inadequate, since it was built from small groups of subjects with a particularly limited number of women and elderly. We aimed to define VE/VCO2 slope prediction formulas in a sizable population and to test whether the prognostic power of VE/VCO2 slope in HF was different if expressed as a percentage of the predicted value or as an absolute value. Methods and results We calculated the linear regressions between age and VE/VCO2 slope in 1136 healthy subjects (68% male, age 44.9 ± 14.5, range 13–83 years). We then applied age-adjusted and sex-adjusted formulas to predict VE/VCO2 slope to HF patients included in the metabolic exercise test data combined with cardiac and kidney indexes score database, which counts 6112 patients (82% male, age 61.4 ± 12.8, left ventricular ejection fraction 33.2 ± 10.5%, peakVO2 14.8 ± 4.9, mL/min/kg, VE/VCO2 slope 32.7 ± 7.7) from 24 HF centres. Finally, we evaluated whether the use of absolute values vs. percentages of predicted VE/VCO2 affected HF prognosis prediction (composite of cardiovascular mortality + urgent transplant or left ventricular assist device). We did so in the entire cardiac and kidney indexes score population and separately in HF patients with severe (peakVO2 < 14 mL/min/kg, n = 2919, 61.1 events/1000 pts/year) or moderate (peakVO2 ≥ 14 mL/min/kg, n = 3183, 19.9 events/1000 pts/year) HF. In the healthy population, we obtained the following equations: female, VE/VCO2 = 0.052 × Age + 23.808 (r = 0.192); male, VE/VCO2 = 0.095 × Age + 20.227 (r = 0.371) (P = 0.007). We applied these formulas to calculate the percentages of predicted VE/VCO2 values. The 2-year survival prognostic power of VE/VCO2 slope was strong, and it was similar if expressed as absolute value or as a percentage of predicted value (AUCs 0.686 and 0.690, respectively). In contrast, in severe HF patients, AUCs significantly differed between absolute values (0.637) and percentages of predicted values (0.650, P = 0.0026). Moreover, VE/VCO2 slope expressed as a percentage of predicted value allowed to reclassify 6.6% of peakVO2 < 14 mL/min/kg patients (net reclassification improvement = 0.066, P = 0.0015). Conclusions The percentage of predicted VE/VCO2 slope value strengthens the prognostic power of VE/VCO2 in severe HF patients, and it should be preferred over the absolute value for HF prognostication. Furthermore, the widespread use of VE/VCO2 slope expressed as percentage of predicted value can improve our ability to identify HF patients at high risk, which is a goal of utmost clinical relevance.

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)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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

Citations44
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueESC Heart FailureSame topicHeart Failure Treatment and ManagementFrench-language works237,207