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  • Meeting abstract
  • Open Access

Strategies for prevention of prolonged intensive care unit stay following cardiac surgery by identifying the determinants

  • 1,
  • 1,
  • 1,
  • 1 and
  • 2
Journal of Cardiothoracic Surgery201510 (Suppl 1) :A165

https://doi.org/10.1186/1749-8090-10-S1-A165

  • Published:

Keywords

  • Intensive Care Unit Stay
  • NYHA Class
  • Logistic Probability
  • Positive Test Result
  • Score Model

Background/Introduction

Cardiac surgery service is dependent on the availability of cardiac intensive care facility. some patients are eligible for fast-track protocol. We investigate the factors determining prolonged intensive care stay following cardiac surgery, with the view to developing a model that predicts prolonged stay.

Aims/Objectives

Develop a scoring model that predicts prolonged intensive care stay following cardiac surgery

Method

Retrospective data analysis on 1592 consecutive patients admitted to intensive care following cardiac surgery (2011-2014). Dichotomous and categorical data were compared using Chi-square or Fisher's Exact tests. P- value of < 0.05 was significant. Univariate and Multivariate Regression identified predictors of prolonged intensive care stay.

A score model for prolonged intensive care stay was developed as a logistic probability unit (z=logit (p)= log e (p/1-p); The area under the receiver curve (AUC) generated. The best cut-off point of the scoring model was identified, the likelihood ratio of a positive test result calculated.

Results

Logistic regression showed predictors of prolonged intensive care unit stay as ; NYHA class 3-4 (OR,1.5; p = 0.0029), FEV1 (OR, 0.76; p = 0.0026), emergency operation (OR,8.75; p = 0.0022), age (OR,1.02; p = 0.00007), LVEF<50% (OR,2.21; p = 0.00001), creatinine (OR,1.01; p = 0.000001), bypass time (OR, 1.01; p = 0.000001).

Intensive care unit stay score was determined by logistic probability (AUC=0.76, 95% CI, 0.73;0.78, p = 0.00001) suggesting that a cut-off score of 35 predicts prolonged intensive care stay with a sensitivity of 0.66, specificity of 0.72 and accuracy of 0.70. The likelihood ratio of a positive test was 2.34.

Discussion/Conclusion

Preoperative optimisation of the predictors of prolong intensive care stay, could reduce length of stay following cardiac-surgery.

Authors’ Affiliations

(1)
Department of Cardiothoracic Surgery, St George's University Hospital NHS Foundation Trust, London, SW17 0QT, UK
(2)
Department of Cardiorespiratory Medicine and Intensive Care, St George's University Hospital NHS Foundation Trust, London, SW17 0QT, UK

Copyright

© Gukop et al. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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