RESUMO
Functional impairment is of major importance in the evaluation of assault victims. French law assesses the seriousness of the violence in terms of the functional impairment experienced by the victims, quantified by the duration of the victims' inability to fulfill their usual daily activities, measured in days of "total incapacity to work" (TIW). Significant variations in the duration of TIW have been reported depending on the examination centers or physician. To date, few studies, all monocentric, have focused on the determinants of this variability. We aimed to study the functional impairment of assault victims by searching for determinants of TIW. We conducted a retrospective multicenter study, including assault victims from seven forensic medicine units. The data were automatically extracted from the medical certificates drawn up and gathered within the ORFéAD database. Thirty-eight variables were studied, relating to the victim's characteristics, the circumstances of the examination and the assault, the physical and psychological symptoms, and the duration of TIW. A total of 5,663 victims were included, including 2,438 (43%) women. The median age was 32 years (min; max [10; 98]). The median duration of TIW was 2 days (min; max [0; 182]). Male gender, age, time to examination, examination center, traumatic injuries (ecchymosis, hematoma, wound, bone fracture), use of a weapon, and functional limitation were associated with the duration of TIW (p < .05). The associations formerly identified in a monocentric setting were confirmed and new determinants were identified. This study has allowed a better understanding of the factors influencing the evaluation of functional impairment and determination of the TIW of assault victims. This first study using ORféAD is intended to be supplemented by the participation of other forensic units, and the inclusion of other variables, such as violence type, victim categories, or the examining physician.
RESUMO
Diagnosis and management of bone and joint infections (BJI) is a challenging task. The high intra and inter patient's variability in terms of clinical presentation makes it impossible to rely on a systematic description or classical statistical analysis for its diagnosis. Advances can be achieved through a better understanding of the system behavior that results from the interactions between the components at a micro-scale level, which is difficult to mastered using traditional methods. Multiple studies from the literature report factors and interactions that affect the dynamics of the BJI system. The objectives of this study were (i) to perform a systematic review to identify relevant interactions between agents (cells, pathogens) and parameters values that characterize agents and interactions, and (ii) to develop a two dimensional computational model of the BJI system based on the results of the systematic review. The model would simulate the behavior resulting from the interactions on the cellular and molecular levels to explore the BJI dynamics, using an agent-based modeling approach. The BJI system's response to different microbial inoculum levels was simulated. The model succeeded in mimicking the dynamics of bacteria, the innate immune cells, and the bone mass during the first stage of infection and for different inoculum levels in a consistent manner. The simulation displayed the destruction in bone tissue as a result of the alteration in bone remodeling process during the infection. The model was used to generate different patterns of system behaviors that could be analyzed in further steps. Simulations results suggested evidence for the existence of latent infections. Finally, we presented a way to analyze and synthesize massive simulated data in a concise and comprehensive manner based on the semi-supervised identification of ordinary differential equations (ODE) systems. It allows to use the known framework for temporal and structural ODE analyses and therefore summarize the whole simulated system dynamical behavior. This first model is intended to be validated by in vivo or in vitro data and expected to generate hypotheses to be challenged by real data. Step by step, it can be modified and complexified based on the test/validation iteration cycles.