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Professor Malin Malmsjö, MD, PhD. Photo.

Malin Malmsjö

Professor

Professor Malin Malmsjö, MD, PhD. Photo.

Vacuum-assisted closure therapy for deep sternal wound infections: the impact of learning curve on survival and predictors for late mortality.

Author

  • Johan Sjögren
  • Arash Mokhtari
  • Ronny Gustafsson
  • Malin Malmsjö
  • Johan Nilsson
  • Richard Ingemansson

Summary, in English

The aim of this study was to evaluate the possible learning curve effects on survival during the introduction of vacuum-assisted closure (VAC) therapy in patients with deep sternal wound infection (DSWI). Furthermore, predictors of late mortality were analysed and causes of late death were examined. Fifty-three patients (early Group, n = 26, January 1999 to July 2001 versus late group, n = 27, August 2001 to March 2003) were all treated with VAC for DSWI. A follow-up was carried out in September 2006. Multivariate analyses were used to evaluate the predictors of late mortality. The 90-day mortality was 0% in both groups. The survival rates at 5 years were 69.2 +/- 9.1% (early group) versus 58.5 +/- 11.7% (late group), P = ns (non significant). The time interval from cardiac surgery to diagnosis of DSWI and prolonged VAC therapy were identified as independent predictors of late mortality. Our concept for VAC therapy in DSWI seems to be readily introduced in clinical practice. There was no difference in survival between our initial cases and later cases. Late diagnosis and prolonged wound therapy were identified as predictors for late mortality.

Department/s

  • Section II
  • Medicine, Lund
  • Ophthalmology, Lund
  • Thoracic Surgery
  • Artificial Intelligence and Bioinformatics in Cardiothoracic Sciences (AIBCTS)
  • Heart and Lung transplantation
  • Artificial Intelligence in CardioThoracic Sciences (AICTS)

Publishing year

2008

Language

English

Pages

216-223

Publication/Series

International Wound Journal

Volume

5

Issue

2

Document type

Journal article

Publisher

Wiley-Blackwell

Topic

  • Other Clinical Medicine
  • Ophthalmology

Status

Published

Research group

  • Artificial Intelligence and Bioinformatics in Cardiothoracic Sciences (AIBCTS)
  • Heart and Lung transplantation
  • Artificial Intelligence in CardioThoracic Sciences (AICTS)

ISBN/ISSN/Other

  • ISSN: 1742-481X