Final implementation of SEACON: new scope and new open system platform.

SEACON is a hybrid (heuristic & algorithmic) expert system for contingency analysis and preventive or corrective control of the transmission network, that has been recently redesigned to implement new end user requirements and to increase its performance. This paper describes the main results and the operational experience from the development and implementation of a new system based on the initial idea. Software reuse strategies became capital in this project. The new design includes advanced functionalities demanded by the practical use of the former system. Because of the high performance of the new system (up to fifteen times faster than the original) and its friendly user interface, SEACON has become a very valuable tool among dispatchers. SEACON is in operation in the Red Electrica’s National Control Centre and in Iberdrola’s Central and Regional Control Centres, dealing with transmission and subtransmission networks (ranging between 4OOkV and 66kV), attached to the on-line state estimators and screening over 2000 possible contingencies. Results are presented using natural language, and a client-server scheme provided for corporate access. KeywOrdr - Expert system, security assessment, contingency analysis, power systems, real-time system

Phase angle by electrical bioimpedance is a predictive factor of hospitalisation, falls and mortality in patients with cirrhosis

The phase angle is a versatile measurement to assess body composition, frailty and prognosis in patients with chronic diseases. In cirrhosis, patients often present alterations in body composition that are related to adverse outcomes. The phase angle could be useful to evaluate prognosis in these patients, but data are scarce. The aim was to analyse the prognostic value of the phase angle to predict clinically relevant events such as hospitalisation, falls, and mortality in patients with cirrhosis. Outpatients with cirrhosis were consecutively included and the phase angle was determined by electrical bioimpedance. Patients were prospectively followed to determine the incidence of hospitalisations, falls, and mortality. One hundred patients were included. Patients with phase angle ≤ 4.6° (n = 31) showed a higher probability of hospitalisation (35% vs 11%, p = 0.003), falls (41% vs 11%, p = 0.001) and mortality (26% vs 3%, p = 0.001) at 2-year follow-up than patients with PA > 4.6° (n = 69). In the multivariable analysis, the phase angle and MELD-Na were independent predictive factors of hospitalisation and mortality. Phase angle was the only predictive factor for falls. In conclusion, the phase angle showed to be a predictive marker for hospitalisation, falls, and mortality in outpatients with cirrhosis

Impact of diabetes on the predictive value of heart failure biomarkers

Altres ajuts: This study was funded by the Redes Temáticas de Investigación Cooperativa en Salud (RETICS); Red Cardiovascular (RD12/0042/0047) as part of the Plan Nacional de I+D+I.Patients with diabetes mellitus (DM) have an increased risk of developing heart failure (HF). Further, DM is associated with poor prognosis in patients with HF. Our aim was to determine whether DM has any impact on the predictive value of a multi-biomarker panel in patients with HF. We included 1069 consecutive ambulatory HF patients in the study: age 66.2 ± 12.8 years, 33.5 ± 13.3 left ventricular ejection fraction, 36% diabetic patients. We measured serum concentrations of N-terminal pro-brain natriuretic peptide (NT-proBNP), high-sensitivity troponin T (hs-TnT), ST2, galectin-3, high-sensitivity C reactive protein (hs-CRP), cystatin-C, soluble transferrin receptor (sTfR), and neprilysin and followed patients for 4.9 ± 2.8 years. Primary endpoints were all-cause and cardiovascular death. During follow-up, 534 patients died; 283 died of cardiovascular causes. Diabetic subjects had higher mortality (57.7 vs. 45.6%, p < 0.001). NTproBNP (p = 0.07), hs-TnT (p < 0.001), galectin-3 (p < 0.001), and cystatin-C (p = 0.001) concentrations were higher in diabetic patients, whereas sTfR levels were lower (p = 0.005). There were no interactions between DM and NTproBNP, hs-TnT, galectin-3, hs-CRP, cystatin-C, sTfR, and neprilysin relative to risk prediction for all-cause or cardiovascular death. By contrast, ST2 significantly interacted with DM for all-cause (p = 0.02) and cardiovascular (p = 0.03) death. In diabetic patients, HRs for ST2 were 1.27 (95% CI 1.16-1.40, p < 0.001) and 1.23 (95% CI 1.09-1.39, p = 0.001) for all-cause and cardiovascular death, respectively. In nondiabetic patients, HRs for ST2 were 1.53 (95% CI 1.35-1.73, p < 0.001) and 1.64 (95% CI 1.31-2.05, p < 0.001) for all-cause and cardiovascular death, respectively. The multivariable Cox regression analysis showed that hs-TnT and ST2 were the only markers that were independently associated with both all-cause and cardiovascular mortality in patients with HF and diabetes. Moreover, in these patients, the combination of these two markers significantly increased discrimination as assessed by the area under the curve. Biomarkers used in the general population to predict the clinical course of heart failure are also useful in patients with diabetes. In these patients, among all the biomarkers analysed only hs-TnT and ST2 were independently associated with both all-cause and cardiovascular mortality

An Expert System for Cardiopulmonary Diseases in Primary Health Care

This paper shows the steps we have taken in order to define and design a first prototype of an expert system aimed at the general practitioner. The first part is devoted to analyze the systemic approach we gave to the definition problem. Also are given the results we reached from a delphi analysis which we accomplished in order to get the medical aspects and specifications that defined the system. The second part shows how the above conclusions drove to the definition of the first prototype: The knowledge acquisition process was accomplished by means of an especially designed tool, the medical knowledge considered was limited to those common aspects of the interaction of the basic entities in which the knowledge is organized. The knowledge is represented as a net where the vertices are diseases and manifestations and the arcs represent different types of relations. The tool provides the user with functions as the include or delete function of objects or vertices to the net or with the modification function of the values given to the arcs. The reasoning mechanism evaluates each diagnostic hypothesis (disease) by (1), how the disease explains the symptoms found in the patient and (2) by the symptoms that are usually found with the disease but are not prevalent in the patient. The system is in the validation phase

Final implementation of SEACON: new scope and new open system platform.

SEACON is a hybrid (heuristic & algorithmic)expert system for contingency analysis and preventive or corrective control of the transmission network, that has been recently redesigned to implement new end user requirements and to increase its performance. This paper describes the main results and the operational experience from the development and implementation of a new system based on the initial idea. Software reuse strategies became capital in this project. The new design includes advanced functionalities demanded by the practical use of the former system. Because of the high performance of the new system (up to fifteen times faster than the original) and its friendly user interface, SEACON has become a very valuable tool among dispatchers. SEACON is in operation in the Red Electrica’s National Control Centre and in Iberdrola’s Central and Regional Control Centres, dealing with transmission and subtransmission networks (ranging between 4OOkV and 66kV), attached to the on-line state estimators and screening over 2000 possible contingencies. Results are presented using natural language, and a client-server scheme provided for corporate access