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Record W4391048926 · doi:10.1093/ckj/sfae004

Cystatin C or creatinine for pre-operative assessment of kidney function and risk of post-operative acute kidney injury: a secondary analysis of the METS cohort study

2024· article· en· W4391048926 on OpenAlexafffund
John R. Prowle, Bernard Croal, Brian H. Cuthbertson, Duminda N. Wijeysundera, Paul S. Myles, M A Shulman, Sophie Wallace, Paddy Farrington, Bruce Thompson, Mathew J. Ellis, Brigitte M. Borg, Ross Kerridge, Janice G. Douglas, James R. Brannan, Jeffrey J. Pretto, M.G. Godsall, N.J. Beauchamp, Scott 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, Kimberley E. Steele, Oystein Tronstad, P. Masel, Annette Dent, Emma‐Jane Smith, A Bodger, M. Abolfathi, P Sivalingam, Alistair S. Hall, Thomas Painter, Sarah Macklin, Adrian D. Elliott, A M Carrera, N C S Terblanche, Susan C. Pitt, Jason M. Samuels, C. Wilde, Kate Leslie, Andrew MacCormick, David E. Bramley, Anne Marie Southcott, Jelani Grant, Hugh R. Taylor, Samantha Bates, Michael Towns, Anna Tippett, Fray F. Marshall, C. David Mazer, J. Kunasingam, Anmol Yagnik, C. Crescini, Suresh 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, L Lee, K. Dobson, Vincent Chan, Richard Brull, Noam Ami, M Stanbrook, Knut Hagen, Douglas Campbell, Timothy G. Short, Japie Van der Westhuizen, Kushlin Higgie, Helen Lindsay, R. Jang, Christopher Wong, Denise McAllister, M. Ben Ali, Jitendra Kumar, Ellen Waymouth, C Kim, J. Dimech, Michelle Lorimer, Jin Tai, Reuben Jonathan Miller, R. Sara, A. Collingwood, Sue Olliff, Stacey Gabriel, Helen Houston, Paul Dalley, Sally Hurford, Adam Hunt, Lynn Andrews, L Navarra, A. Jason-Smith, N. McMillan, Geum Mun Back, Mark Lum, Daniel Martín, S. James, Helder Filipe, M. Pinto, S. Kynaston, Rupert M. Pearse, Tom Abbott, Mandeep Phull, Christian M. Beilstein, Pheobe Bodger, Kirsty Everingham, Ya‐Han Hu, Edyta Niebrzegowska, C. Corriea, Thais Creary, Marta Januszewska, Tahania Ahmad, Justin P. Whalley, Richard Haslop, John J. McNeil, Allison C. Brown, Neil MacDonald, M. Pakats, Kim Greaves, Shaman Jhanji, R Raobaikady, E. G. Black, Martin Rooms, H. Lawrence, Maria Koutra, Katrina Pirie, M. Gertsman, Sandy Jack, Michael Celinski, Denny Levett, Mark Edwards, Karen Salmon, C. Bolger, Lisa Loughney, Leanne Seaward, Hannah Collins, B. Tyrell, N. Tantony, Kim Golder, Gareth L. Ackland, Robert Stephens, L. Gallego-Paredes, Anna Reyes, Ana Gutierrez del Arroyo, Ashok Raj, Rhiannon Lifford

Bibliographic record

VenueClinical Kidney Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsSt. Michael's HospitalHealth Sciences CentrePublic Health OntarioUniversity of TorontoSunnybrook Health Science Centre
FundersOntario Ministry of Research and InnovationMedical Research CouncilMonash UniversityCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchHeart and Stroke Foundation of CanadaAustralian and New Zealand College of AnaesthetistsOntario Ministry of Health and Long-Term CareNational Institute of Academic Anaesthesia
KeywordsCystatin CMedicineCreatinineRenal functionAcute kidney injuryCohortKidneyInternal medicineCohort study

Abstract

fetched live from OpenAlex

ABSTRACT Background Post-operative acute kidney injury (PO-AKI) is a common surgical complication consistently associated with subsequent morbidity and mortality. Prior kidney dysfunction is a major risk factor for PO-AKI, however it is unclear whether serum creatinine, the conventional kidney function marker, is optimal in this population. Serum cystatin C is a kidney function marker less affected by body composition and might provide better prognostic information in surgical patients. Methods This was a pre-defined, secondary analysis of a multi-centre prospective cohort study of pre-operative functional capacity. Participants were aged ≥40 years, undergoing non-cardiac surgery. We assessed the association of pre-operative estimated glomerular filtration rate (eGFR) calculated using both serum creatinine and serum cystatin C with PO-AKI within 3 days after surgery, defined by KDIGO creatinine changes. The adjusted analysis accounted for established AKI risk factors. Results A total of 1347 participants were included (median age 65 years, interquartile range 56–71), of whom 775 (58%) were male. A total of 82/1347 (6%) patients developed PO-AKI. These patients were older, had higher prevalence of cardiovascular disease and related medication, were more likely to have intra-abdominal procedures, had more intraoperative transfusion, and were more likely to be dead at 1 year after surgery 6/82 (7.3%) vs 33/1265 (2.7%) (P = .038). Pre-operative eGFR was lower in AKI than non-AKI patients using both creatinine and cystatin C. When both measurements were considered in a single age- and sex-adjusted model, eGFR-Cysc was strongly associated with PO-AKI, with increasing risk of AKI as eGFR-Cysc decreased below 90, while eGFR-Cr was no longer significantly associated. Conclusions Data from over 1000 prospectively recruited surgical patients confirms pre-operative kidney function as major risk factor for PO-AKI. Of the kidney function markers available, compared with creatinine, cystatin C had greater strength of association with PO-AKI and merits further assessment in pre-operative assessment of surgical risk.

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 distilled prediction

Teacher imitation

Not 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)0.007
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.473
Teacher spread0.437 · 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 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

Citations11
Published2024
Admission routes2
Has abstractyes

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