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Assessment of functional capacity before major non-cardiac surgery: an international, prospective cohort study
Duminda N. Wijeysundera, Rupert M. Pearse, Mark Shulman, Tom Abbott, Elizabeth Torres, A. Ambosta, Bernard Croal, Kevin E. Thorpe, Michael P. W. Grocott, Catherine Farrington, Paul S. Myles, Brian H. Cuthbertson, Sophie Wallace, Bruce Thompson, Mathew J. Ellis, B. Borg, Ross Kerridge, J. Douglas, John D. Brannan, Jeffrey J. Pretto, Guy Godsall, N. Beauchamp, Sandra L. Allen, A. Kennedy, E. Wright, J. Malherbe, Hilmy Ismail, Bernhard Riedel, Andrew Melville, Harry Sivakumar, A. Murmane, K. Kenchington, Y. Kirabiyik, Usha Gurunathan, C. Stonell, K. Brunello, Katherine T. Steele, Oystein Tronstad, P. Masel, Annette Dent, Emma Smith, A Bodger, M. Abolfathi, P Sivalingam, Adrian Hall, Thomas Painter, S. Macklin, Adrian D. Elliott, Anna María Claverol Carrera, N Terblanche, S. Pitt, J. Samuel, Chris Wilde, Kate Leslie, Andrew MacCormick, David E. Bramley, Anne Marie Southcott, J. C. Boileau Grant, H. Taylor, Samantha Bates, Miriam Towns, Anna Tippett, Fiona Marshall, C. David Mazer, J. Kunasingam, Anmol Yagnik, C. Crescini, S. Yagnik, Colin J. L. McCartney, Priya Somascanthan, Stephen Choi, K. Flores, Shelly Au, W. Scott Beattie, Keyvan Karkouti, Hance Clarke, Angela Jerath, Stuart A. McCluskey, Marcin Wąsowicz, Lauren Day, Janneth Pazmino‐Canizares, Paul Oh, Rene Belliard, Leanna Lee, Karen Dobson, Vincent Chan, Richard Brull, Noam Ami, Matthew B. Stanbrook, K. Hagen, Douglas Campbell, Timothy G. Short, J. Van Der Westhuizen, Kushlin Higgie, Helen Lindsay, R. Jang, Chris Ho Ming Wong, Davina McAllister, Marlynn Ali, Jonathan Kumar, Ellen Waymouth, Chang Joon Kim, J. Dimech, Michael Lorimer, Joyce Tai, R. Miller, Rachel Sara, A. Collingwood, Sue Olliff, S. Gabriel, Helen Houston, Paul Dalley, Sally Hurford, Anna Hunt, Lynn Andrews, Leanlove Navarra, A. Jason-Smith, Helen Thompson, N. McMillan, G. Back, Daniel Martín, Sarah James, Helder Filipe, Manuel Pinto, S. Kynaston, Mandeep Phull, Christian M. Beilstein, Pheobe Bodger, Kirsty Everingham, Ying Hu, Edyta Niebrzegowska, C. Corriea, Thais Creary, Marta Januszewska, Tahania Ahmad, Jan Whalley, Richard Haslop, Jane E. McNeil, A. Brown, Neil MacDonald, M. Pakats, Kathryn Greaves, Shaman Jhanji, R. Raobaikady, Ethel Black, Martin Rooms, H. Lawrence, Maria Koutra, Katrina Pirie, M. Gertsman, Sandy Jack, Michael Celinski, Denny Levett, Mark Edwards, Karen Salmon, Clare Bolger, Lisa Loughney, Leanne Seaward, Hannah Collins, Bryony Tyrell, N. Tantony, Kim Golder, Gareth L. Ackland, RCM Stephens, L. Gallego-Paredes, Anna Reyes, Ana Gutierrez del Arroyo, Ashok Raj, Rhiannon Lifford, Magda Melo, Muhammad Mamdani, Graham S. Hillis, Harindra C. Wijeysundera
Bibliographic record
VenueThe Lancet · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsHealth Sciences CentrePublic Health OntarioSunnybrook Health Science CentreSinai Health SystemToronto Rehabilitation InstituteUniversity of TorontoUniversity Health NetworkSt. Michael's Hospital
FundersMedical Research CouncilCanadian Institutes of Health ResearchOntario Ministry of Research, Innovation and ScienceUnited Kingdom Clinical Research CollaborationMonash UniversityUniversity of TorontoRoyal College of AnaesthetistsNational Institute for Health and Care ResearchOntario Ministry of Health and Long-Term CareNational Institute of Academic AnaesthesiaAustralian and New Zealand College of AnaesthetistsHeart and Stroke Foundation of CanadaPfizer
KeywordsMedicineProspective cohort studyMyocardial infarctionPhysical therapyInternal medicineCardiac surgeryCohortVO2 maxCoronary artery diseaseMetabolic equivalentCohort studyLogistic regressionCardiologySurgeryBlood pressureHeart rate
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)0.002
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 score0.014
Threshold uncertainty score0.029
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 head0.035
GPT teacher head0.322
Teacher spread0.287 · 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 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
Citations480
Published2018
Admission routes2
Has abstractno