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Les données révèlent que les personnes âgées fragiles profitent de tout un spectre de soins plutô t que du modèle admission/sortie d'hô pital de notre système de santé. Cette étude se concentre sur l'évolution de l'état de santé des patients après leur sortie d'un hô pital gériatrique de jour (HGJ) afin de déterminer quelle proportion de ces gens continue de bien aller et quelle proportion connaît un déclin, quelles sont les différences entre ces deux groupes et si l'on peut déceler des facteurs qui permettraient de prédire la détérioration de l'état de santé. Au moyen d'un sondage téléphonique et de méthodes d'évaluation de l'atteinte des objectifs, les objectifs de 151 patients ayant obtenu leur sortie d'un HGJ il y a plus de six mois et moins de 18 mois ont été étudiés afin de déterminer si les objectifs atteints à l'HGJ se sont maintenus ou non. Tous les patients sauf cinq ont vu une amélioration de leur état entre leur admission et leur sortie de l'HGJ; après leur sortie, 39 p. 100 des patients ont vu leur état se détériorer. Le besoin d'un soutien accru au sein de la communauté constituait un élément permettant de prédire la détérioration, ce qui témoignait probablement de la fragilité du patient. Bon nombre de diagnostics médicaux et de traitements ne constituaient pas des éléments de prédiction. Les personnes âgées fragiles tendent à ne pas conserver les niveaux atteints dans un HGJ après leur sortie et elles pourraient tirer profit de services continus. ABSTRACTEvidence suggests that frailer older patients benefit from a continuum of care rather than the admit/discharge model of our health system. This study examined patient outcomes after discharge from a geriatric day hospital (GDH) to determine what proportion continues to do well, what proportion declines, how the two groups differ, and if factors predictive of deterioration can be identified. Using telephone survey and Goal Attainment Scaling methodologies, the goals of 151 patients discharged from a GDH between 6 and 18 months previously were examined to determine whether GDH achievements were maintained or lost. All but 5 patients improved between GDH admission and discharge; after discharge, 39 per cent deteriorated. The need for more support in the community was predictive of deterioration, probably reflecting patient frailty. Number of medical diagnoses or medications were not predictive. Frailer older patients tend not to maintain goals achieved in a GDH after discharge and may benefit from ongoing maintenance.

Significant microstructural anisotropy is known to develop during shearing flow of attractive particle suspensions. These suspensions, and their capacity to form conductive networks, play a key role in flow-battery technology, among other applications. Herein, we present and test an analytical model for the tensorial conductivity of attractive particle suspensions. The model utilizes the mean fabric of the network to characterize the structure, and the relationship to the conductivity is inspired by a lattice argument. We test the accuracy of our model against a large number of computer-generated suspension networks, based on multiple in-house generation protocols, giving rise to particle networks that emulate the physical system. The model is shown to adequately capture the tensorial conductivity, both in terms of its invariants and its mean directionality.

We propose a model for the evolution of the conductivity tensor for a flowing suspension of electrically conductive particles. We use discrete particle numerical simulations together with a continuum physical framework to construct an evolution law for the suspension microstructure during flow. This model is then coupled with a relationship between the microstructure and the electrical conductivity tensor. Certain parameters of the joint model are fit experimentally using rheo-electrical conductivity measurements of carbon black suspensions under flow over a range of shear rates. The model is applied to the case of steady shearing as well as time-varying conductivity of unsteady flow experiments. We find that the model prediction agrees closely with the measured experimental data in all cases.