Effects of an exercise training program in physical condition after liver transplantation in familial amyloidotic polyneuropathy: a case report

Introduction: Familial amyloidotic polyneuropathy (FAP) is a neurodegenerative disease that leads to sensory and motor polyneuropathies as well as functional limitations. So far, liver transplantation is the only treatment for FAP because the mutated protein causing the disease is mainly produced in the liver. With the increasing survival of transplant recipients, functional and cardiovascular problems as consequences of immunosuppressant side effects are increasing associated with sedentary lifestyles and/or retransplantation status. We sought to analyze the impact of exercise training programs on 1 FAP patient’s course long-term after liver transplantation. Methodology. A FAP patient (female; 49 years of age; body mass index 18.8 kg/m2) underwent a liver transplantation 133 months before assessment. She was assessed for body composition, isometric quadriceps muscle strength, functional capacity, fatigue, and levels of physical activity before and after a 6-month period of combined exercise training. Results: After the exercise training program, almost all variables were improved, namely, total body skeletal muscle mass, proximal femoral bone mineral density, quadriceps strength, maximal oxygen consumption on 6 minutes walk test (6mwt) or VO2peak, total ventilation on 6mwt, and fatigue. The improvement in distance on 6mwt (69.2 m) was clinically significant. Preintervention the levels of physical activity were below international recommendations for health; after the program they achieved the recommendations. Conclusion: The results showed an improvement in functional capacity with a decrease in future disability risk associated with a better lifestyle with respect to physical activity levels in 1 patient.

Decisions with multiple simultaneous goals and uncertain causal effects

A key aspect of decision-making in a disaster response scenario is the capability to evaluate multiple and simultaneously perceived goals. Current competing approaches to build decision-making agents are either mental-state based as BDI, or founded on decision-theoretic models as MDP. The BDI chooses heuristically among several goals and the MDP searches for a policy to achieve a specific goal. In this paper we develop a preferences model to decide among multiple simultaneous goals. We propose a pattern, which follows a decision-theoretic approach, to evaluate the expected causal effects of the observable and non-observable aspects that inform each decision. We focus on yes-or-no (i.e., pursue or ignore a goal) decisions and illustrate the proposal using the RoboCupRescue simulation environment.