J Trauma
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Comparative Study
Variations in bone mineral density of proximal femora of elderly people with hip fractures: a case-control analysis.
Bone mass as represented by bone mineral density (BMD) is the most important factor determining bone strength. Elderly people with and without hip fractures were compared with the BMD of the proximal femora. The correlation between hip fractures in elderly patients and osteoporosis was investigated. ⋯ The severity of osteoporosis may affect the risk of hip fractures in elderly people. The risk of intertrochanteric fractures may be determined simply by BMD, but the risk of femoral neck fractures may be determined by multiple factors. Intertrochanteric fractures may start at the greater trochanter due to its low BMD.
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Comparative Study
Accidental and intentional perpetration of serious injury or death: correlates and relationship to trauma exposure.
The pernicious individual and societal effects of exposure to violence highlight the importance of understanding factors related to trauma perpetration. Little research has investigated the phenomenon of accidental perpetration of serious injury and death, or considered the relationship between perpetration and trauma exposure. ⋯ Findings suggest that accidental, as well as intentional, perpetration of serious injury or death frequently occurs in the context of trauma and violence. Both types of perpetration are related to psychopathology. Potential mechanisms underlying the relationship between trauma exposure, psychopathology, and perpetration are discussed. Further research is needed to elucidate pathways from trauma exposure to perpetration and mental disorder.
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Comparative Study
Using principal component analysis to aid bayesian network development for prediction of critical care patient outcomes.
Predicting an intensive care unit patient's outcome is highly desirable. An end goal is for computational techniques to provide updated, accurate predictions about changing patient condition using a manageable number of physiologic parameters. ⋯ Outcome prediction for critical care patients is possible. Future work should explore model development using additional temporal data and should include prospective validation. Such technology could serve as the basis of real-time intelligent monitoring systems for critical patients.