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Preoperative prediction of Bleeding Independently associated with Mortality after noncardiac Surgery (BIMS): an international prospective cohort study.
Roshanov, Pavel S; Guyatt, Gordon H; Tandon, Vikas; Borges, Flavia K; Lamy, Andre; Whitlock, Richard; Biccard, Bruce M; Szczeklik, Wojciech; Panju, Mohamed; Spence, Jessica; Garg, Amit X; McGillion, Michael; Eikelboom, John W; Sessler, Daniel I; Kearon, Clive; Crowther, Mark; VanHelder, Tomas; Kavsak, Peter A; de Beer, Justin; Winemaker, Mitchell; Le Manach, Yannick; Sheth, Tej; Pinthus, Jehonathan H; Siegal, Deborah; Thabane, Lehana; Simunovic, Marko R I; Mizera, Ryszard; Ribas, Sebastian; Devereaux, Philip J.
Afiliação
  • Roshanov PS; Division of Nephrology, London Health Science Centre, London, ON, Canada. Electronic address: pavel.roshanov@lhsc.on.ca.
  • Guyatt GH; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Tandon V; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Borges FK; Department of Medicine, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada.
  • Lamy A; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; Department of Surgery, McMaster University, Hamilton, ON, Canada.
  • Whitlock R; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada; Department of Surgery, McMaster University, Hamilton, ON, Canada.
  • Biccard BM; 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.
  • Szczeklik W; Department of Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland.
  • Panju M; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Spence J; Population Health Research Institute, Hamilton, ON, Canada.
  • Garg AX; Division of Nephrology, London Health Science Centre, London, ON, Canada; Institute for Clinical Evaluative Sciences at Western, London, ON, Canada.
  • McGillion M; Population Health Research Institute, Hamilton, ON, Canada; School of Nursing, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
  • Eikelboom JW; Department of Medicine, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada.
  • Sessler DI; Department of Outcomes Research, Anesthesiology Institute, Cleveland Clinic, Cleveland, OH, USA.
  • Kearon C; Department of Medicine, McMaster University, Hamilton, ON, Canada; Thrombosis and Atherosclerosis Research Institute, McMaster University, Hamilton, ON, Canada.
  • Crowther M; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • VanHelder T; Department of Anesthesia, McMaster University, Hamilton, ON, Canada.
  • Kavsak PA; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada.
  • de Beer J; Department of Surgery, McMaster University, Hamilton, ON, Canada.
  • Winemaker M; Department of Surgery, McMaster University, Hamilton, ON, Canada.
  • Le Manach Y; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada; Department of Anesthesia, McMaster University, Hamilton, ON, Canada.
  • Sheth T; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Pinthus JH; Department of Surgery, McMaster University, Hamilton, ON, Canada.
  • Siegal D; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Thabane L; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada; Biostatistics Unit, St. Joseph's Healthcare, Hamilton, ON, Canada.
  • Simunovic MRI; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; Department of Surgery, McMaster University, Hamilton, ON, Canada.
  • Mizera R; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Ribas S; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Devereaux PJ; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; Department of Medicine, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada.
Br J Anaesth ; 126(1): 172-180, 2021 01.
Article em En | MEDLINE | ID: mdl-32718723
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transfusão de Sangue / Hemorragia Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transfusão de Sangue / Hemorragia Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article