Capturing Scientific Knowledge on Medical Risk Factors

In this paper, we describe a model for representing scientific knowledge of risk factors in medicine in an explicit format which enables its use for automated reasoning. The resulting model supports linking the conclusions of up-to-date clinical research with data relating to individual patients. This model, which we have implemented as an ontology-based system using Linked Data, enables the capture of risk factor knowledge and serves as a translational research tool to apply that knowledge to assist with patient treatment, lifestyle, and education. Knowledge captured using this model can be disseminated for other intelligent systems to use for a variety of purposes, for example, to explore the state of the available medical knowledge

Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria

Background: The urinary proteomic classifier CKD273 has shown promise for prediction of progressive diabetic nephropathy (DN). Whether it is also a determinant of mortality and cardiovascular disease in patients with microalbuminuria (MA) is unknown. Methods: Urine samples were obtained from 155 patients with type 2 diabetes and confirmed microalbuminuria. Proteomic analysis was undertaken using capillary electrophoresis coupled to mass spectrometry to determine the CKD273 classifier score. A previously defined CKD273 threshold of 0.343 for identification of DN was used to categorise the cohort in Kaplan–Meier and Cox regression models with all-cause mortality as the primary endpoint. Outcomes were traced through national health registers after 6 years. Results: CKD273 correlated with urine albumin excretion rate (UAER) (r = 0.481, p = <0.001), age (r = 0.238, p = 0.003), coronary artery calcium (CAC) score (r = 0.236, p = 0.003), N-terminal pro-brain natriuretic peptide (NT-proBNP) (r = 0.190, p = 0.018) and estimated glomerular filtration rate (eGFR) (r = 0.265, p = 0.001). On multivariate analysis only UAER (β = 0.402, p < 0.001) and eGFR (β = − 0.184, p = 0.039) were statistically significant determinants of CKD273. Twenty participants died during follow-up. CKD273 was a determinant of mortality (log rank [Mantel-Cox] p = 0.004), and retained significance (p = 0.048) after adjustment for age, sex, blood pressure, NT-proBNP and CAC score in a Cox regression model. Conclusion: A multidimensional biomarker can provide information on outcomes associated with its primary diagnostic purpose. Here we demonstrate that the urinary proteomic classifier CKD273 is associated with mortality in individuals with type 2 diabetes and MA even when adjusted for other established cardiovascular and renal biomarkers

Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria

Background: The urinary proteomic classifier CKD273 has shown promise for prediction of progressive diabetic nephropathy (DN). Whether it is also a determinant of mortality and cardiovascular disease in patients with microalbuminuria (MA) is unknown. Methods: Urine samples were obtained from 155 patients with type 2 diabetes and confirmed microalbuminuria. Proteomic analysis was undertaken using capillary electrophoresis coupled to mass spectrometry to determine the CKD273 classifier score. A previously defined CKD273 threshold of 0.343 for identification of DN was used to categorise the cohort in Kaplan–Meier and Cox regression models with all-cause mortality as the primary endpoint. Outcomes were traced through national health registers after 6 years. Results: CKD273 correlated with urine albumin excretion rate (UAER) (r = 0.481, p = <0.001), age (r = 0.238, p = 0.003), coronary artery calcium (CAC) score (r = 0.236, p = 0.003), N-terminal pro-brain natriuretic peptide (NT-proBNP) (r = 0.190, p = 0.018) and estimated glomerular filtration rate (eGFR) (r = 0.265, p = 0.001). On multivariate analysis only UAER (β = 0.402, p < 0.001) and eGFR (β = − 0.184, p = 0.039) were statistically significant determinants of CKD273. Twenty participants died during follow-up. CKD273 was a determinant of mortality (log rank [Mantel-Cox] p = 0.004), and retained significance (p = 0.048) after adjustment for age, sex, blood pressure, NT-proBNP and CAC score in a Cox regression model. Conclusion: A multidimensional biomarker can provide information on outcomes associated with its primary diagnostic purpose. Here we demonstrate that the urinary proteomic classifier CKD273 is associated with mortality in individuals with type 2 diabetes and MA even when adjusted for other established cardiovascular and renal biomarkers

Associations of inflammatory and hemostatic variables with the risk of recurrent stroke

<p><b>Background and Purpose:</b> Several prospective studies have shown significant associations between plasma fibrinogen, viscosity, C-reactive protein (CRP), fibrin D-dimer, or tissue plasminogen activator (tPA) antigen and the risk of primary cardiovascular events. Little has been published on the associations of these variables with recurrent stroke. We studied such associations in a nested case-control study derived from the Perindopril Protection Against Recurrent Stroke Study (PROGRESS).</p> <p><b>Methods:</b> Nested case-control study of ischemic (n=472) and hemorrhagic (n=83) strokes occurring during a randomized, placebo-controlled multicenter trial of perindopril-based therapy in 6105 patients with a history of stroke or transient ischemic attack. Controls were matched for age, treatment group, sex, region, and most recent qualifying event at entry to the parent trial.</p> <p><b>Results:</b> Fibrinogen and CRP were associated with an increased risk of recurrent ischemic stroke after accounting for the matching variables and adjusting for systolic blood pressure, smoking, peripheral vascular disease, and statin and antiplatelet therapy. The odds ratio for the last compared with the first third of fibrinogen was 1.34 (95% CI, 1.01 to 1.78) and for CRP was 1.39 (95% CI, 1.05 to 1.85). After additional adjustment for each other, these 2 odds ratios stayed virtually unchanged. Plasma viscosity, tPA, and D-dimer showed no relationship with recurrent ischemic stroke, although tPA was significant for lacunar and large artery subtypes. Although each of these variables showed a negative relationship with recurrent hemorrhagic stroke, none of these relationships achieved statistical significance.</p> <p><b>Conclusions:</b> Fibrinogen and CRP are risk predictors for ischemic but not hemorrhagic stroke, independent of potential confounders.</p&gt

Risk factors for deterioration of renal function after coronary artery bypass grafting

Abstract Objective: Various definitions of impairment of renal function after coronary artery bypass grafting (CABG) are used in the literature. Depending on the definition, several risk factors are identified. We analysed our data to determine the risk factors for postoperative deterioration of the creatinine clearance of 10% or more. Methods: All patients undergoing isolated coronary surgery in a single centre between January 1998 and December 2007 are included. Clinical data, including demographics and renal risk factors, were prospectively collected in our database. The most recent preoperative serum creatinine level and the maximum serum creatinine level within the first week postoperatively were used to calculate the creatinine clearance. A deterioration of 10% or more was considered to be an endpoint for this study. Results: In 10 098 out of a total of 10 626 patients, the preoperative as well as the postoperative creatinine clearance could be calculated. In 1053 patients, the deterioration of the creatinine clearance was 10% or more. We could identify the following risk factors: advanced age, diabetes, chronic obstructive pulmonary disease, peripheral vascular disease, emergency operation, previous cardiac surgery, low preoperative haemoglobin level, high preoperative C-reactive protein level, perioperative myocardial infarction, re-exploration and the number of blood transfusions. Conclusions: Risk factors for the deterioration of renal function after revascularisation have been confirmed in this study. In addition, we found peripheral vascular disease, previous cardiac surgery, low preoperative haemoglobin, increased preoperative C-reactive protein level, perioperative myocardial infarction and the number of blood transfusions to be risk factors that have not been described earlier

Clinical applications of personalized medicine: a new paradigm and challenge

The personalized medicine is an emergent and rapidly developing method of clinical practice that uses new technologies to provide decisions in regard to the prediction, prevention, diagnosis and treatment of disease. The continue evolution of technology and the developments in molecular diagnostics and genomic analysis increased the possibility of an even more understanding and interpretation of the human genome and exome, allowing a "personalized" approach to clinical care, so that the concepts of "Systems Medicine" and "System Biology" are increasingly actual. The purpose of this study is to evaluate the personalized medicine about its indications and benefits, actual clinical applications and future perspectives as well as its issues and health care implications. It was made a careful review of the scientific literature on this field that highlighted the applicability and usefulness of this new medical approach as well as the fact that personalized medicine strategy is even more increasing in numerous fields of applications

Resonance-thrombography indices of the haemostatic process in relation to risk of incident coronary heart disease: 9 years follow-up in the Caerphilly Prospective Heart Disease Study

Global assays, such as resonance-thrombography (RTG), which measure the interaction between platelets, coagulation and fibrinolysis have been used as summary measures of risk for over two decades but have not been evaluated in epidemiological studies. We examined whether RTG indices are risk indicators for incident coronary heart disease (CHD). RTG indices, related haematological variables and other risk factors were measured between 1984 and 1988 in a cohort of 2398 British men. Reaction time (r) and amplitude of fibrin leg (AF) were associated with lifestyle risk factors. During 9 years of follow-up, 282 (12%) men developed a major new CHD event, as classified by World Health Organization criteria. On adjustment for age, only r and AF measured at baseline were related to risk of incident CHD. On multivariate adjustment in a multiple logistic regression model that included age, diastolic blood pressure, body mass index, total and high-density lipoprotein cholesterol, lifestyle risk factors and use of prescribed medicine, these associations weakened but remained significant. Additional adjustment for fibrinogen, viscosity, white cell count and fibrin D-dimer either reduced these associations to non- significance (AF) or to borderline significance(r)

Should socioeconomic factors be considered as traditional risk factors for cardiovascular disease, as confounders, or as risk modifiers?

A large number of studies show that cardiovascular disease and its traditional risk factors are associated with socioeconomic conditions. However, their etiological role in the development of cardiovascular outcomes is not always well understood. In particular, it is unclear whether socioeconomic factors should be considered as traditional risk factors for CVD, as confounders, or as risk modifiers. In this article, after examining whether socioeconomic conditions meet the criteria for the three definitions, we argue that none of them fully captures the complexity of their contribution in shaping the epidemic of heart disease across and within societies. We argue instead that socioeconomic factors are the “causes of the causes” of heart disease. Implications for research and interventions to reduce heart disease are discussed