Literature DB >> 23235520

Preoperative identification of patients with increased risk for perioperative bleeding.

Hans Gombotz1, Hans Knotzer.   

Abstract

PURPOSE OF REVIEW: Although the overall complication rate in cardiac surgery has been decreased, perioperative bleeding increasing morbidity and mortality is still frequent. Furthermore, the widespread use of new antithrombotic and antiplatelet agents presents an additional challenge in daily practice. Therefore, identifying patients with increased bleeding risk would be advantageous to optimize perioperative management. RECENT
FINDINGS: Bleeding classifications are frequently discussed, but are of little relevance for the perioperative setting. In the nonsurgical setting the most relevant risk factors in bleeding prediction are age, renal disease, sex, pre-existing anemia, and the administration of antithrombotic/antiplatelet drugs. In cardiac surgery, the Papworth Bleeding Risk Stratification Score identifies mainly procedure-linked risk factors and might be one of the most suitable scores to be used. Routine laboratory screening appears to have limited utility.
SUMMARY: Apart from precise bleeding history only insufficient data exist in cardiac surgery to exactly predict bleeding complications. Therefore, there is urgent need for further studies to improve perioperative bleeding management.

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Year:  2013        PMID: 23235520     DOI: 10.1097/ACO.0b013e32835b9a23

Source DB:  PubMed          Journal:  Curr Opin Anaesthesiol        ISSN: 0952-7907            Impact factor:   2.706


  5 in total

Review 1.  [Patient Blood Management : three pillar strategy to improve outcome through avoidance of allogeneic blood products].

Authors:  H Gombotz; A Hofmann
Journal:  Anaesthesist       Date:  2013-07       Impact factor: 1.041

2.  Comparison of the Utilization of Tranexamic Acid and Tourniquet Use in Total Knee Arthroplasty: A Retrospective Case Series.

Authors:  Promil Kukreja; Brittany M Johnson; Corey Traylor; Kevin J O'Keefe; Sameer Naranje; Jason McKeown; Christopher A Paul; Brooke Bell
Journal:  Cureus       Date:  2022-05-09

3.  Detection of Surgical Site Infection Utilizing Automated Feature Generation in Clinical Notes.

Authors:  Feichen Shen; David W Larson; James M Naessens; Elizabeth B Habermann; Hongfang Liu; Sunghwan Sohn
Journal:  J Healthc Inform Res       Date:  2018-11-06

Review 4.  Management of non-vitamin K antagonist oral anticoagulants in the perioperative setting.

Authors:  Anne-Sophie Dincq; Sarah Lessire; Jonathan Douxfils; Jean-Michel Dogné; Maximilien Gourdin; François Mullier
Journal:  Biomed Res Int       Date:  2014-09-03       Impact factor: 3.411

5.  Machine learning-based prediction of transfusion.

Authors:  Andreas Mitterecker; Axel Hofmann; Kevin M Trentino; Adam Lloyd; Michael F Leahy; Karin Schwarzbauer; Thomas Tschoellitsch; Carl Böck; Sepp Hochreiter; Jens Meier
Journal:  Transfusion       Date:  2020-06-28       Impact factor: 3.157

  5 in total

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