MétaCan
Menu
Back to cohort
Record W2606023343 · doi:10.1164/rccm.201701-0150ws

Enhancing Insights into Pulmonary Vascular Disease Through a Precision Medicine Approach. A Joint NHLBI–Cardiovascular Medical Research and Education Fund Workshop Report

2017· article· en· W2606023343 on OpenAlexaff
John H. Newman, Stuart Rich, Steven H. Abman, John H. Alexander, John Barnard, Gerald J. Beck, Raymond L. Benza, Todd M. Bull, Stephen Y. Chan, Hyung J. Chun, Declan Doogan, Jocelyn Dupuis, Serpil C. Erzurum, Robert P. Frantz, Mark W. Geraci, Hunter Gillies, Mark T. Gladwin, Michael P. Gray, Anna R. Hemnes, Roy S. Herbst, Adrian F. Hernandez, Nicholas S. Hill, Evelyn M. Horn, Kendall S. Hunter, Zhi‐Cheng Jing, Roger A. Johns, Sanjay Kaul, Steven M. Kawut, Tim Lahm, Jane A. Leopold, Greg Lewis, Stephen C. Mathai, Vallerie V. McLaughlin, Evangelos D. Michelakis, Steven D. Nathan, William C. Nichols, Grier P. Page, Marlene Rabinovitch, Jonathan D. Rich, Franz Rischard, Sharon Rounds, Sanjiv J. Shah, Victor F. Tapson, Naomi Lowy, Norman Stockbridge, Gail Weinmann, Lei Xiao

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of AlbertaUniversité de Montréal
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood InstituteNational Institutes of HealthCardiovascular Medical Research and Education Fund
KeywordsMedicineClinical trialPrecision medicinePulmonary hypertensionProtocol (science)DiseaseTranslational researchIntensive care medicineMedical educationFamily medicineAlternative medicinePathologyInternal medicine

Abstract

fetched live from OpenAlex

The Division of Lung Diseases of the NHLBI and the Cardiovascular Medical Education and Research Fund held a workshop to discuss how to leverage the anticipated scientific output from the recently launched "Redefining Pulmonary Hypertension through Pulmonary Vascular Disease Phenomics" (PVDOMICS) program to develop newer approaches to pulmonary vascular disease. PVDOMICS is a collaborative, protocol-driven network to analyze all patient populations with pulmonary hypertension to define novel pulmonary vascular disease (PVD) phenotypes. Stakeholders, including basic, translational, and clinical investigators; clinicians; patient advocacy organizations; regulatory agencies; and pharmaceutical industry experts, joined to discuss the application of precision medicine to PVD clinical trials. Recommendations were generated for discussion of research priorities in line with NHLBI Strategic Vision Goals that include: (1) A national effort, involving all the stakeholders, should seek to coordinate biosamples and biodata from all funded programs to a web-based repository so that information can be shared and correlated with other research projects. Example programs sponsored by NHLBI include PVDOMICS, Pulmonary Hypertension Breakthrough Initiative, the National Biological Sample and Data Repository for PAH, and the National Precision Medicine Initiative. (2) A task force to develop a master clinical trials protocol for PVD to apply precision medicine principles to future clinical trials. Specific features include: (a) adoption of smaller clinical trials that incorporate biomarker-guided enrichment strategies, using adaptive and innovative statistical designs; and (b) development of newer endpoints that reflect well-defined and clinically meaningful changes. (3) Development of updated and systematic variables in imaging, hemodynamic, cellular, genomic, and metabolic tests that will help precisely identify individual and shared features of PVD and serve as the basis of novel phenotypes for therapeutic interventions.

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)0.107
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.107
Threshold uncertainty score0.567

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1070.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0020.003
Scholarly communication0.0080.006
Open science0.0020.006
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0050.001

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 head0.089
GPT teacher head0.408
Teacher spread0.319 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations79
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Respiratory and Critical Care MedicineSame topicPulmonary Hypertension Research and TreatmentsFrench-language works237,207