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Record W4321018683 · doi:10.1101/2023.02.15.23285974

Classification and Predictors of Right Ventricular Functional Recovery in Pulmonary Arterial Hypertension

2023· preprint· en· W4321018683 on OpenAlexaff
Franz Rischard, Roberto J. Bernardo, Rebecca Vanderpool, Deborah Kwon, Tushar Acharya, Margaret Park, Austin Katrynuik, Michael Insel, Saad Kubba, Roberto Badagliacca, A. Brett Larive, Robert Naeije, Joe G. N. Garcia, Gerald J. Beck, Serpil C. Erzurum, Robert P. Frantz, Paul M. Hassoun, Anna R. Hemnes, Nicholas S. Hill, Evelyn M. Horn, Jane A. Leopold, Erika B. Rosenzweig, W.H. Wilson Tang, Jennifer Wilcox

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsColumbia College
FundersUniversity of ArizonaPulmonary Hypertension Association
KeywordsMedicineCardiologyInternal medicinePreloadAfterloadContext (archaeology)Pulmonary arteryStroke volumeReceiver operating characteristicArea under the curveHeart failureHemodynamicsEjection fraction

Abstract

fetched live from OpenAlex

Abstract Background Normative changes in right ventricular (RV) structure and function have not been characterized in the context of treatment-associated functional recovery (RVFnRec). The aim of this study is to assess the clinical relevance of a proposed RVFnRec definition. Methods We evaluated 63 incident patients with PAH by right heart catheterization and cardiac MRI (CMR) at diagnosis and CMR and invasive cardiopulmonary exercise (CPET) following treatment (∼11 months). Sex, age, race/ethnicity matched healthy control subjects (n=62) with one-time CMR and non-invasive CPET were recruited from the PVDOMICS project. We examined therapeutic CMR changes relative to the evidence-based peak oxygen consumption (VO2 peak )>15mL/kg/min to define RVFnRec by receiver operating curve analysis. Afterload was measured in the as mean pulmonary artery pressure, resistance, compliance, and elastance. Results A drop in RV end-diastolic volume of -15 mL best defined RVFnRec (AUC 0.87, P=0.0001) and neared upper 95% CI RVEDV of controls. 22/63 (35%) of subjects met this cutoff which was reinforced by freedom from clinical worsening, RVFnRec 1/21 (5%) versus no RVFnRec 17/42, 40%, (log rank P=0.006). A therapy-associated increase of 0.8 mL/mmHg in compliance had the best predictive value of RVFnRec (AUC 0.76, CI 0.64-0.88, P=0.001). RVFnRec subjects had greater increases in stroke volume, and cardiac output at exercise. Conclusions RVFnRec defined by RVEDV therapeutic decrease of -15mL predicts exercise capacity, freedom from clinical worsening, and nears normalization. A therapeutic improvement of compliance is superior to other measures of afterload in predicting RVFnRec. RVFnRec is also associated with increased RV output reserve at exercise. Clinical Perspective What is new? Right ventricular functional recovery (RVFnRec) represents a novel endpoint of therapeutic success in PAH. We define RVFnRec as treatment associated normative RV changes related to function (peak oxygen consumption). Normative RV imaging changes are compared to a well phenotyped age, sex, and race/ethnicity matched healthy control cohort from the PVDOMICS project. Previous studies have focused on RV ejection fraction improvements. However, we show that changes in RVEDV are perhaps more important in that improvements in LV function also occur. Lastly, RVFnRec is best predicted by improvements in pulmonary artery compliance versus pulmonary vascular resistance, a more often cited metric of RV afterload. What are the clinical implications? RVFnRec represents a potential non-invasive assessment of clinical improvement and therapeutic response. Clinicians with access to cardiac MRI can obtain a limited scan (i.e., ventricular volumes) before and after treatment. Future study should examine echocardiographic correlates of RVFnRec.

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)0.003
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0010.001
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 head0.054
GPT teacher head0.272
Teacher spread0.218 · 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
Published2023
Admission routes1
Has abstractyes

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