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P3‐171: Moderate‐to‐severe cognitive impairment is common in patients with moderate chronic kidney disease
Author(s) -
Murray Anne M.,
Kolste Ali,
Pederson Sarah,
Zaun David
Publication year - 2009
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2009.04.1045
Subject(s) - dementia , medicine , cognition , kidney disease , stroke (engine) , renal function , cognitive impairment , population , neuropsychology , physical therapy , disease , psychiatry , mechanical engineering , environmental health , engineering
Background: Cognitive disorders are clinically heterogeneous and multifactorially caused aging phenomena. Although a number of subtle biomarkers have been identified, based on advances in high-throughput technicques, it has not been decided which of them are valuable to be monitored for practical purposes. A diagnosis is still largerly made by using clinical criteria. For substantial diagnostic and therapeutic progress, better understanding of the relevant mechanisms involved in the pathogenesis of these disorders should be achieved. Efforts are focused on systems biology approach and computerbased modeling. Methods: Many clinical and biochemical data (54 parameters in a total) were used to describe many aspects of the health status of a group of 93 persons, 50-89 years old (median 69), characterized by multiple medical conditions. MMSE was used to differentiate them according to if they have cognitive impairments or not. Multivariate regression and Machine Learning (ML) technicques were applied to compute the data. Results: There were 13 out of 54 parameters selected in multivariate regression as to correlate with cognitive impairments. Those were mainly parameters indicating inflammation and chronic activation of the neuroendocrine stress axis. By applying ML algorithms, together with available knowledge, it was possible to recognize the main medical conditions associated with cognitive impairments. Data indicated chronic renal impairment, Helicobacter pylori positive gastritis and the thyroid gland hormone hypofunction as conditions which might influence the development of the brain disorders. Conclusions: In this way, by collecting medical data on-line in the form of a database and using systems biology approach, it could be possible to find patterns concerning many yet poorly defined aging phenomena. This approach might shed more light on the matter of how chronic aging disorders are linked, interracting with each other in the common network. This could also be a framework for risk prediction modeling. This aprroach is connected with the assumption that chronic aging disorders are highly integrated and stochastic in their nature.