dc.contributor.author | Berg, Kristin Sandal | |
dc.date.accessioned | 2015-10-01T07:53:22Z | |
dc.date.available | 2015-10-01T07:53:22Z | |
dc.date.issued | 2015 | |
dc.identifier.isbn | 978-82-326-1105-8 | |
dc.identifier.issn | 1503-8181 | |
dc.identifier.uri | http://hdl.handle.net/11250/1537372 | |
dc.description.abstract | Background
In cardiac surgery improvements in quality of care have been a major focus for several
decades. Statistical models for predicting the risk of operative mortality and other
adverse outcomes have been an important part of this work. Risk prediction models may
be used to inform patients of the risk of the planned operation, to adjust complication
rates to enable a valid comparison between institutions or surgeons, and to identify
potential fields of improvement. Risk prediction models were often less accurate when
applied to other patient populations than the one they were derived from. No risk
prediction models for mortality or acute kidney injury following cardiac surgery had
been developed using data from Norwegian patients.
The surgical trauma and the artificial surfaces in the cardiopulmonary bypass circuit
evoke a systemic inflammatory response. The inflammatory response includes
activation of leukocytes, endothelium, and plasma cascade systems including the
complement system, coagulation and fibrinolysis. Inflammation is thought to play a
pivotal role in the development of major complications following cardiac surgery.
Cardiac dysfunction following open-heart surgery is a clinical syndrome where reduced
cardiac output results in insufficient oxygen delivery to the tissues. It is thought to be
induced by ischaemia and reperfusion, as well as inflammation, increasing the
myocardial oxidative stress. Several inflammatory biomarkers, including C-reactive
protein (general marker of inflammation), lactoferrin (neutrophil activation marker),
neopterin (monocyte/macrophage activation marker) and the terminal complement
complex (complement activation marker), had previously been associated with adverse
cardiac outcomes in ischaemic heart disease.
Aims
One aim was to develop local risk prediction models for operative mortality and acute
kidney injury following cardiac surgery. Another aim was to investigate whether
increased preoperative inflammation was associated with the development of cardiac
dysfunction following open-heart surgery.
Methods
For developing the risk prediction models for mortality and acute kidney injury we
included all 5029 adult patients who underwent open-heart surgery at St. Olavs
University Hospital, Trondheim from 2000 through 2007. We applied multivariable
logistic regression for model development, and the models were internally validated
using bootstrapping methods. For investigating whether increased preoperative
inflammation was associated with cardiac dysfunction following open-heart surgery we
included 1018 consecutive patients who underwent open-heart surgery at St. Olavs
University Hospital, Trondheim, Norway from 1 April 2008 to 19 April 2010. We
applied enzyme immunoassay to measure the preoperative concentration of C-reactive
protein, lactoferrin, neopterin and the terminal complement complex in plasma. Logistic
regression was used for the statistical analysis, and we adjusted for clinical variables
previously associated with postoperative cardiac dysfunction.
Results and discussion
The mortality risk prediction model consisted of eight preoperative variables easily
obtainable in clinical practice: Age, degree of urgency for surgery, female gender,
serum creatinine concentration, chronic pulmonary disease, chronic cardiac
insufficiency, previous cardiac surgery, and type of operation. The acute kidney injury
risk model included eleven easily available preoperative variables: age, body mass
index, lipid lowering treatment (protective effect), hypertension, peripheral vascular
disease, chronic pulmonary disease, haemoglobin concentration, serum creatinine
concentration, previous cardiac surgery, emergency operation, and operation type. Both
the mortality and the acute kidney injury risk models displayed good discrimination and
calibration in our population.
We found that neopterin was associated with cardiac dysfunction after cardiac surgery,
and this association remained significant also after adjustment for clinical variables
associated with postoperative cardiac dysfunction.
Conclusions
Our local preoperative risk models predicted mortality and acute kidney injury
accurately, and were generally robust. Our findings regarding neopterin and cardiac
dysfunction support the hypothesis of the role of inflammation and oxidative stress in
the development of postoperative cardiac dysfunction. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | NTNU | nb_NO |
dc.relation.ispartofseries | Doctoral thesis at NTNU;2015:224 | |
dc.relation.haspart | Paper 1: Berg, Kristin Sandal; Stenseth, Roar; Pleym, Hilde; Wahba, Alexander; Videm, Vibeke. Mortality risk prediction in cardiac surgery: comparing a novel model with the EuroSCORE. Acta Anaesthesiologica Scandinavica 2011 ;Volum 55.(3) s. 313-321
<a href="http://dx.doi.org/10.1111/j.1399-6576.2010.02393.x" target="_blank"> http://dx.doi.org/10.1111/j.1399-6576.2010.02393.x</a>
(c)2011 The Authors
Acta Anaesthesiologica Scandinavica
r 2011 The Acta Anaesthesiologica Scandinavica Foundation | nb_NO |
dc.relation.haspart | Paper 2: Berg, Kristin Sandal; Stenseth, Roar; Wahba, Alexander; Pleym, Hilde; Videm, Vibeke. How can we best predict acute kidney injury following cardiac surgery? A prospective observational study. European Journal of Anaesthesiology 2013 ;Volum 30.(11) s. 704-712 Is not included due to copyright available at
<a href="http://dx.doi.org/10.1097/EJA.0b013e328365ae64" target="_blank"> http://dx.doi.org/10.1097/EJA.0b013e328365ae64</a> | nb_NO |
dc.relation.haspart | Paper 3: Berg KS, Stenseth R, Pleym H, Wahba A, Videm V. Neopterin predicts cardiac dysfunction following cardiac surgery.
This is a pre-copyedited, author-produced PDF of an article accepted for publication in Interactive Cardiovascular and Thoracic Surgery following peer review. The version of record is available online at:
<a href="http://dx.doi.org/10.1093/icvts/ivv219" target="_blank"> http://dx.doi.org/10.1093/icvts/ivv219</a>
© The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved. | nb_NO |
dc.title | Inflammation and Risk Prediction of Major Complications Following Cardiac Surgery | nb_NO |
dc.type | Doctoral thesis | nb_NO |
dc.subject.nsi | VDP::Medical disciplines: 700 | nb_NO |