Risk scores to facilitate preoperative prediction of transfusion and large volume blood transfusion associated with adult cardiac surgery

R. Goudie; J. A C Sterne; V. Verheyden; M. Bhabra; M. Ranucci; G. J. Murphy

doi:10.1093/bja/aeu483

Risk scores to facilitate preoperative prediction of transfusion and large volume blood transfusion associated with adult cardiac surgery

R. Goudie, J. A C Sterne, V. Verheyden, M. Bhabra, M. Ranucci, G. J. Murphy

IRCCS Policlinico San Donato

Research output: Contribution to journal › Article › peer-review

Abstract

Background: The aim of this study was to develop two novel risk prediction scores for transfusion and bleeding that would be used to inform treatment decisions, quality assurance, and clinical trial design in cardiac surgery. Methods: Clinical data prospectively collected from 26 UK cardiac surgical centres and a single European centre were used to develop two risk prediction models: one for any red blood cell (RBC) transfusion, and the other for large volume blood transfusion (≥4 RBC units; LVBT), an index of severe blood loss. 'Complete case' data were available for 24 749 patients. Multiple imputation was used for missing covariate data (typically

Original language	English
Pages (from-to)	757-766
Number of pages	10
Journal	British Journal of Anaesthesia
Volume	114
Issue number	5
DOIs	https://doi.org/10.1093/bja/aeu483
Publication status	Published - May 1 2015

Keywords

blood transfusion
cardiac anaesthesia

ASJC Scopus subject areas

Anesthesiology and Pain Medicine
Medicine(all)

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10.1093/bja/aeu483

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AU - Goudie, R.

AU - Sterne, J. A C

AU - Verheyden, V.

AU - Bhabra, M.

AU - Ranucci, M.

AU - Murphy, G. J.

PY - 2015/5/1

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AB - Background: The aim of this study was to develop two novel risk prediction scores for transfusion and bleeding that would be used to inform treatment decisions, quality assurance, and clinical trial design in cardiac surgery. Methods: Clinical data prospectively collected from 26 UK cardiac surgical centres and a single European centre were used to develop two risk prediction models: one for any red blood cell (RBC) transfusion, and the other for large volume blood transfusion (≥4 RBC units; LVBT), an index of severe blood loss. 'Complete case' data were available for 24 749 patients. Multiple imputation was used for missing covariate data (typically

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Risk scores to facilitate preoperative prediction of transfusion and large volume blood transfusion associated with adult cardiac surgery

Abstract

Keywords

ASJC Scopus subject areas

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