Pavel S Roshanov1, John W Eikelboom2, Daniel I Sessler3, Clive Kearon4, Gordon H Guyatt5, Mark Crowther6, Vikas Tandon6, Flavia Kessler Borges2, Andre Lamy7, Richard Whitlock8, Bruce M Biccard9, Wojciech Szczeklik10, Mohamed Panju6, Jessica Spence11, Amit X Garg12, Michael McGillion13, Tomas VanHelder14, Peter A Kavsak15, Justin de Beer16, Mitchell Winemaker16, Yannick Le Manach17, Tej Sheth6, Jehonathan H Pinthus16, Deborah Siegal6, Lehana Thabane18, Marko R I Simunovic7, Ryszard Mizera6, Sebastian Ribas6, Philip J Devereaux19. 1. Division of Nephrology, London Health Science Centre, London, ON, Canada. Electronic address: pavel.roshanov@lhsc.on.ca. 2. Department of Medicine, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada. 3. Department of Outcomes Research, Anesthesiology Institute, Cleveland Clinic, Cleveland, OH, USA. 4. Department of Medicine, McMaster University, Hamilton, ON, Canada; Thrombosis and Atherosclerosis Research Institute, Canada. 5. Department of Medicine, McMaster University, Hamilton, ON, Canada; Department of Health Research Methods, Evidence, and Impact, Canada. 6. Department of Medicine, McMaster University, Hamilton, ON, Canada. 7. Department of Health Research Methods, Evidence, and Impact, Canada; Department of Surgery, McMaster University, Hamilton, ON, Canada. 8. Population Health Research Institute, Hamilton, ON, Canada; Department of Health Research Methods, Evidence, and Impact, Canada; Department of Surgery, McMaster University, Hamilton, ON, Canada. 9. Department of Anaesthesia and Perioperative Medicine, Groote Schuur Hospital, Observatory, Cape Town, Western Cape, South Africa; University of Cape Town, Rondebosch, Cape Town, Western Cape, South Africa. 10. Department of Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland. 11. Population Health Research Institute, Hamilton, ON, Canada. 12. Division of Nephrology, London Health Science Centre, London, ON, Canada; Institute for Clinical Evaluative Sciences at Western, London, ON, Canada. 13. Population Health Research Institute, Hamilton, ON, Canada; School of Nursing, Faculty of Health Sciences, Canada. 14. Department of Anesthesia, Canada. 15. Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada. 16. Department of Surgery, McMaster University, Hamilton, ON, Canada. 17. Population Health Research Institute, Hamilton, ON, Canada; Department of Health Research Methods, Evidence, and Impact, Canada; Department of Anesthesia, Canada. 18. Population Health Research Institute, Hamilton, ON, Canada; Department of Health Research Methods, Evidence, and Impact, Canada; Biostatistics Unit, St Joseph's Healthcare, Hamilton, ON, Canada. 19. Department of Medicine, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada; Department of Health Research Methods, Evidence, and Impact, Canada.
Abstract
BACKGROUND: We aimed to establish diagnostic criteria for bleeding independently associated with mortality after noncardiac surgery (BIMS) defined as bleeding during or within 30 days after noncardiac surgery that is independently associated with mortality within 30 days of surgery, and to estimate the proportion of 30-day postoperative mortality potentially attributable to BIMS. METHODS: This was a prospective cohort study of participants ≥45 yr old having inpatient noncardiac surgery at 12 academic hospitals in eight countries between 2007 and 2011. Cox proportional hazards models evaluated the adjusted relationship between candidate diagnostic criteria for BIMS and all-cause mortality within 30 days of surgery. RESULTS: Of 16 079 participants, 2.0% (315) died and 36.1% (5810) met predefined screening criteria for bleeding. Based on independent association with 30-day mortality, BIMS was identified as bleeding leading to a postoperative haemoglobin <70 g L-1, transfusion of ≥1 unit of red blood cells, or that was judged to be the cause of death. Bleeding independently associated with mortality after noncardiac surgery occurred in 17.3% of patients (2782). Death occurred in 5.8% of patients with BIMS (161/2782), 1.3% (39/3028) who met bleeding screening criteria but not BIMS criteria, and 1.1% (115/10 269) without bleeding. BIMS was associated with mortality (adjusted hazard ratio: 1.87; 95% confidence interval: 1.42-2.47). We estimated the proportion of 30-day postoperative deaths potentially attributable to BIMS to be 20.1-31.9%. CONCLUSIONS: Bleeding independently associated with mortality after noncardiac surgery (BIMS), defined as bleeding that leads to a postoperative haemoglobin <70 g L-1, blood transfusion, or that is judged to be the cause of death, is common and may account for a quarter of deaths after noncardiac surgery. CLINICAL TRIAL REGISTRATION: NCT00512109.
BACKGROUND: We aimed to establish diagnostic criteria for bleeding independently associated with mortality after noncardiac surgery (BIMS) defined as bleeding during or within 30 days after noncardiac surgery that is independently associated with mortality within 30 days of surgery, and to estimate the proportion of 30-day postoperative mortality potentially attributable to BIMS. METHODS: This was a prospective cohort study of participants ≥45 yr old having inpatient noncardiac surgery at 12 academic hospitals in eight countries between 2007 and 2011. Cox proportional hazards models evaluated the adjusted relationship between candidate diagnostic criteria for BIMS and all-cause mortality within 30 days of surgery. RESULTS: Of 16 079 participants, 2.0% (315) died and 36.1% (5810) met predefined screening criteria for bleeding. Based on independent association with 30-day mortality, BIMS was identified as bleeding leading to a postoperative haemoglobin <70 g L-1, transfusion of ≥1 unit of red blood cells, or that was judged to be the cause of death. Bleeding independently associated with mortality after noncardiac surgery occurred in 17.3% of patients (2782). Death occurred in 5.8% of patients with BIMS (161/2782), 1.3% (39/3028) who met bleeding screening criteria but not BIMS criteria, and 1.1% (115/10 269) without bleeding. BIMS was associated with mortality (adjusted hazard ratio: 1.87; 95% confidence interval: 1.42-2.47). We estimated the proportion of 30-day postoperative deaths potentially attributable to BIMS to be 20.1-31.9%. CONCLUSIONS:Bleeding independently associated with mortality after noncardiac surgery (BIMS), defined as bleeding that leads to a postoperative haemoglobin <70 g L-1, blood transfusion, or that is judged to be the cause of death, is common and may account for a quarter of deaths after noncardiac surgery. CLINICAL TRIAL REGISTRATION: NCT00512109.
Authors: Maura Marcucci; Thomas W Painter; David Conen; Kate Leslie; Vladimir V Lomivorotov; Daniel Sessler; Matthew T V Chan; Flavia K Borges; Maria J Martínez Zapata; C Y Wang; Denis Xavier; Sandra N Ofori; Giovanni Landoni; Sergey Efremov; Ydo V Kleinlugtenbelt; Wojciech Szczeklik; Denis Schmartz; Amit X Garg; Timothy G Short; Maria Wittmann; Christian S Meyhoff; Mohammed Amir; David Torres; Ameen Patel; Emmanuelle Duceppe; Kurtz Ruetzler; Joel L Parlow; Vikas Tandon; Michael K Wang; Edith Fleischmann; Carisi A Polanczyk; Raja Jayaram; Sergey V Astrakov; Mangala Rao; Tomas VanHelder; William K K Wu; Chao Chia Cheong; Sabry Ayad; Marat Abubakirov; Mikhail Kirov; Keyur Bhatt; Miriam de Nadal; Valery Likhvantsev; Pilar Paniagua Iglesisas; Hector J Aguado; Michael McGillion; Andre Lamy; Richard P Whitlock; Pavel Roshanov; David Stillo; Ingrid Copland; Jessica Vincent; Kumar Balasubramanian; Shrikant I Bangdiwala; Bruce Biccard; Andrea Kurz; Sadeesh Srinathan; Shirley Petit; John Eikelboom; Toby Richards; Peter L Gross; Pascal Alfonsi; Gordon Guyatt; Emily Belley-Cote; Jessica Spence; William McIntyre; Salim Yusuf; P J Devereaux Journal: Trials Date: 2022-01-31 Impact factor: 2.279