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Association of preoperative anaemia with cardiopulmonary exercise capacity and postoperative outcomes in noncardiac surgery: a substudy of the Measurement of Exercise Tolerance before Surgery (METS) Study
Justyna Bartoszko, Kevin E. Thorpe, Andreas Laupacis, Duminda N. Wijeysundera, Paul S. Myles, Mark Shulman, Sophie Wallace, Paddy Farrington, Bruce Thompson, Mathew J. Ellis, Brigitte M. Borg, Ross Kerridge, J. Douglas, John D. Brannan, Jeffrey J. Pretto, M.G. Godsall, N. Beauchamp, Sandra L. Allen, A. Kennedy, E. Wright, J. Malherbe, Hilmy Ismail, Bernhard Riedel, Andrew Melville, H. 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, Jason M. Samuels, C. Wilde, Kate Leslie, Andrew MacCormick, David E. Bramley, Anne Marie Southcott, Jonathan 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, Stephen Choi, Priya Somascanthan, K. Flores, W. Scott Beattie, Keyvan Karkouti, Hance Clarke, Angela Jerath, Stuart A. McCluskey, Marcin Wąsowicz, Lauren Day, Janneth Pazmino‐Canizares, Paul Oh, R. Belliard, Lawrence Lee, K. 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, M Ali, Jonathan Kumar, Ellen Waymouth, C. 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, N. McMillan, G. Back, Bernard Croal, M. Lum, Daniel Martín, S. James, Helder Filipe, M. Pinto, S. Kynaston, Rupert M. Pearse, Tom Abbott, M. Phull, Christian M. Beilstein, Phoebe Bodger, Kirsty Everingham, Ya‐Han Hu, Edyta Niebrzegowska, C. Corriea, Thais Creary, Marta Januszewska, Tahania Ahmad, J. 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, B. Tyrell, N. Tantony, Kim Golder, Gareth L. Ackland, L. Gallego-Paredes, Anna Reyes, Ana Gutierrez del Arroyo, Ashok Raj, Rhiannon Lifford, Brian H. Cuthbertson, Elizabeth Torres, A. Ambosta, Magda Melo, Muhammad Mamdani, Michael P. W. Grocott, Graham S. Hillis, Harindra C. Wijeysundera
Bibliographic record
VenueBritish Journal of Anaesthesia · 2019
Typeletter
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsSt. Michael's HospitalPublic Health OntarioToronto Rehabilitation InstituteUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of TorontoUnited Kingdom Clinical Research CollaborationMonash UniversityOntario Ministry of Research, Innovation and ScienceCanada Research ChairsGovernment of OntarioNational Institute of Academic AnaesthesiaOntario Ministry of Health and Long-Term CareGovernment of CanadaAustralian and New Zealand College of AnaesthetistsHeart and Stroke Foundation of Canada
KeywordsMedicineAnaerobic exerciseOdds ratioConfidence intervalConfoundingVO2 maxInternal medicineClinical endpointLogistic regressionCohort studyProspective cohort studySurgeryCardiologyAnesthesiaPhysical therapyBlood pressureRandomized controlled trialHeart 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.016
GPT teacher head0.223
Teacher spread0.207 · 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 teacher head, not a consensus.
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
Citations23
Published2019
Admission routes2
Has abstractno