Objective
Postoperative delirium (POD) is characterized by the progressive deterioration of sensory/cognitive function after surgery with incidences of up to 30-80%. It is frequently followed by postoperative cognitive dysfunction (POCD) which tends to persist over time. In elderly patients, POCD resembles chronic dementia and appears to accelerate the cognitive decline in Alzheimer dementia. POD is strongly associated with subsequent dementia after 3.2 and 5.0 years of follow-up: odds ratio = 12.52 [95% CI, 1.86-84.21] corrected for baseline dementia, severity of illness, age. In an aging society like the EU, the socioeconomic implications of POD/POCD are therefore profound. At present no treatment exists and there are no established molecular or imaging biomarkers that allow risk and clinical outcome prediction. We will establish valid biomarkers panels for risk and clinical outcome prediction of POD/POCD in N=1200 surgical patients according to the regulatory requirements of the European Medicines Agency. Thus, a valuable database will be created not yet existing worldwide. Neuroimaging investigations, which directly provide information on brain structure/function, will include structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), arterial spin labelling (ASL), functional magnetic resonance imaging with simultaneous electrophysiology (fMRI/EEG) and glutamate MR-spectroscopy (MRS). These investigations will be complemented by genetic/gene expression analyses (sequencing of cholinergic candidate genes/corresponding transcripts) and analyses of plasma and cerebrospinal fluid markers (inflammatory/metabolic). Supported by bioinformatics approaches, integration of neuroimaging data with knowledge from molecular biomarkers (multivariate expert system) is expected to allow patient stratification. This will greatly support decision-making before surgical intervention (balancing benefits and risks) as well as the development of novel therapies in POD/POCD.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesneurobiologycognitive neuroscience
- medical and health sciencesbasic medicineneurologydementiaalzheimer
- natural sciencescomputer and information sciencesartificial intelligenceexpert systems
- medical and health sciencesclinical medicinesurgerysurgical procedures
- engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imaging
Call for proposal
FP7-HEALTH-2013-INNOVATION-1
See other projects for this call
Funding Scheme
CP-FP - Small or medium-scale focused research projectCoordinator
10117 Berlin
Germany