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Global Consensus Recommendations on Improving the Safety of Chronic Total Occlusion Interventions
Eugene B. Wu, Arun Kalyanasundaram, Emmanouil S Brilakis, Kambis Mashayekhi, Etsuo Tsuchikane, Nidal Abi Rafeh, Pierfrancesco Agostoni, Khaldoon Alaswad, Mario Araya, Alexandre Avran, Mohamed Ayoub, Lorenzo Azzalini, А. М. Бабунашвили, Baktash Bayani, Michael Behnes, Ravinay Bhindi, Nicolas Boudou, Marouane Boukhris, Nenad Božinović, Leszek Bryniarski, Alexander Bufe, Christopher E. Buller, M. Nicholas Burke, Heinz Joachim Buettner, Pedro Cardoso, Mauro Carlino, Chi Kin Chan, Jiyan Chen, Evald Høj Christiansen, Antonio Colombo, Kevin Croce, Félix Damas de los Santos, Tony De Martini, Joseph Dens, Carlo Di Mario, Darshan Doshi, Kefei Dou, Mohaned Egred, Basem Elbarouni, Ahmed ElGuindy, Javier Escaned, Sergey Furkalo, Andrea Gagnor, Alfredo R. Galassi, Roberto Garbo, Gabriele Gasparini, Junbo Ge, Lei Ge, Pravin K. Goel, Ömer Göktekín, Nieves Gonzalo, Şevket Görgülü, Luca Grancini, Allison B. Hall, Colm G. Hanratty, Stefan Harb, S. Harding, Raja Hatem, Farrel Hellig, Josè P.S. Henriques, David Hildick‐Smith, Jonathan Hill, Angela Hoye, Wissam Jaber, Farouc A. Jaffer, Yangsoo Jang, Risto Jussila, Artis Kalniņš, Sanjog Kalra, David E. Kandzari, Hsien‐Li Kao, Dimitri Karmpaliotis, Hussien Heshmat Kassem, Kathleen E. Kearney, Jimmy Kerrigan, Jaikirshan Khatri, Dmitri Khelimskii, Ajay J. Kirtane, Paul Knaapen, Ran Kornowski, Oleg Krestyaninov, Vinay Kumar, Prathap Kumar, Pablo Lamelas, Seung‐Whan Lee, Thierry Lefèvre, Gregor Leibundgut, Raymond Leung, Sum-Kin Leung, Yu Li, Yue Li, Soo-Teik Lim, S. Lo, William Lombardi, Anbukarasi Maran, Margaret McEntegart, Jeffrey W. Moses, Muhammad Munawar, Wataru Nagamatsu, Andrés Navarro, Hung Manh Ngo, William Nicholson, Anja Øksnes, Göran Olivecrona, Lucio Padilla, Mitul Patel, Ashish Pershad, Marin Postu, Stylianos A. Pyxaras, Jie Qian, Alexandre Schaan de Quadros, Franklin Leonardo Hanna Quesada, Truls Råmunddal, Vithala Suryaprakasa Rao, Sudhir Rathore, Nicolaus Reifart, Robert F. Riley, Stéphane Rinfret, Meruzhan Saghatelyan, Ricardo Santiago, Ashok Seth, Georgios Sianos, Elliot J. Smith, Anthony Spaedy, James Spratt, Gregg W. Stone, Julian Strange, Khalid Tammam, Craig A. Thompson, Aurel Toma, Jennifer A. Tremmel, Imre Ungi, Giuseppe Vadalà, Minh Vo, Vũ Hoàng Vũ, Simon Walsh, Daniel Weilenmann, Gerald S. Werner, Jarosław Wójcik, Jason Wollmuth, Chiung-Jen Wu, Bo Xu, Masahisa Yamane, Luiz F. Ybarra, Robert W. Yeh, Chris Zambakides, Qi Zhang
Bibliographic record
VenueHeart Lung and Circulation · 2024
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsRoyal Columbian HospitalMcGill University Health CentreRoyal Alexandra HospitalLondon Health Sciences CentreMcMaster UniversityMemorial University of NewfoundlandSt. Boniface HospitalToronto General HospitalWestern UniversityHôpital du Sacré-Cœur de MontréalSt. Michael's Hospital
FundersAbbott VascularSzegedi TudományegyetemHaukeland UniversitetssjukehusMedizinische Universität GrazHumanitas UniversitySchool of Medicine, University of California, San DiegoUniversity of Cape TownMedizinische Universität WienSahlgrenska UniversitetssjukhusetUniversité de MontréalUniversità degli Studi di PalermoLunds UniversitetFudan UniversityDaiichi-SankyoUniversity of California, San DiegoMemorial University of NewfoundlandUniversity of New South WalesUniversiteit van AmsterdamNewcastle UniversityUniversidad Complutense de MadridSanofiAbiomedUniversitas IndonesiaAmsterdam University Medical CentersAstraZenecaAmarin CorporationMcGill University Health CentreRegeneron PharmaceuticalsOsprey MedicalIrving Medical Center, Columbia UniversityUniversität WienEmory UniversityBoston Scientific CorporationUniversity of HullKarl-Franzens-Universität GrazMcGill UniversityAmerican Heart AssociationUniversity of WashingtonCardinal HealthAmgenEdwards LifesciencesFakultas Kedokteran, Universitas IndonesiaReCor MedicalMassachusetts General HospitalUniversidad San Francisco de QuitoUniversity of South CarolinaCardiovascular Systems
KeywordsMedicinePsychological interventionIntensive care medicineNursing
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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)0.103
metaresearch head score (Gemma)0.179
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 score0.103
Threshold uncertainty score0.544
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.103 | 0.179 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.012 | 0.007 |
| Research integrity | 0.020 | 0.023 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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 head0.018
GPT teacher head0.316
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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
Citations14
Published2024
Admission routes2
Has abstractno