Clinical decision-making and myocardial viability: current perspectives

Not all myocardium involved in a myocardial infarction is dead or irreversibly damaged. The balance between the amount of scar and live tissue, and the nature of the live tissue, determine the likelihood that contractile function will improve after revascularisation. This improvement (which defines viability) may be predicted with about 80% accuracy using several techniques. This review examines the determinants of functional recovery and how they may be integrated in making decisions regarding revascularisation. (Intern Med J 2005; 35: 118–125)

Achieving better in-hospital and after-hospital care of patients with acute cardiac disease

In patients hospitalised with acute coronary syndromes (ACS) and congestive heart failure (CHF), evidence suggests opportunities for improving in-hospital and after hospital care, patient self-care, and hospital-community integration. A multidisciplinary quality improvement program was designed and instigated in Brisbane in October 2000 involving 250 clinicians at three teaching hospitals, 1080 general practitioners (GPs) from five Divisions of General Practice, 1594 patients with ACS and 904 patients with CHF. Quality improvement interventions were implemented over 17 months after a 6-month baseline period and included: clinical decision support (clinical practice guidelines, reminders, checklists, clinical pathways); educational interventions (seminars, academic detailing); regular performance feedback; patient self-management strategies; and hospital-community integration (discharge referral summaries; community pharmacist liaison; patient prompts to attend GPs). Using a before-after study design to assess program impact, significantly more program patients compared with historical controls received: ACS: Angiotensin-converting enzyme (ACE) inhibitors and lipid-lowering agents at discharge, aspirin and beta-blockers at 3 months after discharge, inpatient cardiac counselling, and referral to outpatient cardiac rehabilitation. CHF. Assessment for reversible precipitants, use of prophylaxis for deep-venous thrombosis, beta-blockers at discharge, ACE inhibitors at 6 months after discharge, imaging of left ventricular function, and optimal management of blood pressure levels. Risk-adjusted mortality rates at 6 and 12 months decreased, respectively, from 9.8% to 7.4% (P=0.06) and from 13.4% to 10.1% (P= 0.06) for patients with ACS and from 22.8% to 15.2% (P < 0.001) and from 32.8% to 22.4% (P= 0.005) for patients with CHF. Quality improvement programs that feature multifaceted interventions across the continuum of care can change clinical culture, optimise care and improve clinical outcomes.

Participatory approach for the identification of dairy industry needs in the design of research, development and extension actions: Australian and Brazilian case studies

In both Australia and Brazil there are rapid changes occurring in the macroenvironment of the dairy industry. These changes are sometimes not noticed in the microenvironment of the farm, due to the labour-intensive nature of family farms, and the traditionally weak links between production and marketing. Trends in the external environment need to be discussed in a cooperative framework, to plan integrated actions for the dairy community as a whole and to demand actions from research, development and extension (R, D & E). This paper reviews the evolution of R, D & E in terms of paradigms and approaches, the present strategies used to identify dairy industry needs in Australia and Brazil, and presents a participatory strategy to design R, D & E actions for both countries. The strategy incorporates an integration of the opinions of key industry actors ( defined as members of the dairy and associated communities), especially farm suppliers ( input market), farmers, R, D & E people, milk processors and credit providers. The strategy also uses case studies with farm stays, purposive sampling, snowball interviewing techniques, semi-structured interviews, content analysis, focus group meetings, and feedback analysis, to refine the priorities for R, D & E actions in the region.

A cognitive genetic algorithm for power distribution system planning

Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.