Preoperative prediction of Bleeding Independently associated with Mortality after noncardiac Surgery (BIMS): an international prospective cohort study
Pavel S Roshanov, Gordon H Guyatt, Vikas Tandon, Flavia K Borges, Andre Lamy, Richard Whitlock, Bruce M Biccard, Wojciech Szczeklik, Mohamed Panju, Jessica Spence, Amit X Garg, Michael McGillion, John W Eikelboom, Daniel I Sessler, Clive Kearon, Mark Crowther, Tomas VanHelder, Peter A Kavsak, Justin de Beer, Mitchell Winemaker, Yannick Le Manach, Tej Sheth, Jehonathan H Pinthus, Deborah Siegal, Lehana Thabane, Marko R I Simunovic, Ryszard Mizera, Sebastian Ribas, Philip J Devereaux, Pavel S Roshanov, Gordon H Guyatt, Vikas Tandon, Flavia K Borges, Andre Lamy, Richard Whitlock, Bruce M Biccard, Wojciech Szczeklik, Mohamed Panju, Jessica Spence, Amit X Garg, Michael McGillion, John W Eikelboom, Daniel I Sessler, Clive Kearon, Mark Crowther, Tomas VanHelder, Peter A Kavsak, Justin de Beer, Mitchell Winemaker, Yannick Le Manach, Tej Sheth, Jehonathan H Pinthus, Deborah Siegal, Lehana Thabane, Marko R I Simunovic, Ryszard Mizera, Sebastian Ribas, Philip J Devereaux
Abstract
Background: Diagnostic criteria for Bleeding Independently associated with Mortality after noncardiac Surgery (BIMS) have been defined as bleeding that leads to a postoperative haemoglobin <70 g L-1, leads to blood transfusion, or is judged to be the direct cause of death. Preoperative prediction guides for BIMS can facilitate informed consent and planning of perioperative care.
Methods: In a prospective cohort study of 16 079 participants aged ≥45 yr having inpatient noncardiac surgery at 12 academic hospitals in eight countries between 2007 and 2011, 17.3% (2782) experienced BIMS. An electronic risk calculator for BIMS was developed and internally validated by logistic regression with bootstrapping, and further simplified to a risk index. Decision curve analysis assessed the potential utility of each prediction guide compared with a strategy of identifying risk of BIMS based on preoperative haemoglobin <120 g L-1.
Results: With information about the type of surgery, preoperative haemoglobin, age, sex, functional status, kidney function, history of high-risk coronary artery disease, and active cancer, the risk calculator accurately predicted BIMS (bias-corrected C-statistic, 0.84; 95% confidence interval, 0.837-0.852). A simplified index based on preoperative haemoglobin <120 g L-1, open surgery, and high-risk surgery also predicted BIMS, but less accurately (C-statistic, 0.787; 95% confidence interval, 0.779-0.796). Both prediction guides could improve decision making compared with knowledge of haemoglobin <120 g L-1 alone.
Conclusions: BIMS, defined as bleeding that leads to a postoperative haemoglobin <70 g L-1, leads to blood transfusion, or that is judged to be the direct cause of death, can be predicted by a simple risk index before surgery.
Clinical trial registration: NCT00512109.
Keywords: mortality; noncardiac surgery; perioperative bleeding; prediction; risk index; transfusion.
Copyright © 2020 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.
Source: PubMed