OBJECTIVE: To report on
the complication profile and clinical outcomes obtained with less invasive image-guided surgical correction of degenerative (de novo) scoliosis in a high-risk population.
METHODS: Thirty patients (age, 64-88 years) with progressive postural impairment, back pain, radiculopathy, and neurogenic claudication caused by degenerative scoliosis were treated by less invasive image-guided correction (3-8 segments) by multisegmental transforaminal lumbar interbody fusion and facet fusions. With a mean follow-up of 19.6 months, Panobinostat molecular weight intraoperative blood loss, curve correction, fusion and complication rates, duration of hospitalization, incidence of hardware-related problems, and clinical outcome parameters were assessed using multivariate analysis.
RESULTS: Satisfactory multiplanar correction was obtained in all patients. Mean intraoperative blood loss was
771.7 +/- 231.9 mL, time to full ambulation was 0.8 +/- 0.6 days, and length of stay was FAK inhibitor 8.2 6 +/- 2.9 days. After 12 months, preoperative SF12v2 physical component summary scores (20.2 +/- 2.6), visual analog scale scores (7.5 +/- 0.8), and Oswestry disability index (57.2 +/- 6.9) improved to 34.6 +/- 3.9, 2.63 +/- 0.6, and 24.8 +/- 7.1, respectively. The rate of major and minor complications was 23.4% and 59.9%, respectively. Ninety percent of patients rated treatment success as excellent, good, SB273005 chemical structure or fair.
CONCLUSION: Less invasive image-guided correction of degenerative scoliosis in elderly patients with significant comorbidity yields a favorable complication profile. Significant improvements in spinal balance, pain, and functional scores mirrored expedited ambulation and early resumption of daily activities. Less invasive techniques appear suitable to reduce periprocedural morbidity, especially in elderly patients and individuals with significant medical risk factors.”
“Nested
structure, which is non-random, controls cooperation dynamics and biodiversity in plant-animal mutualistic networks. This structural pattern has been explained in a static (non-growth) network models. However, evolutionary processes might also influence the formation of such a structural pattern. We thereby propose an evolving network model for plant-animal interactions and show that non-random patterns such as nested structure and heterogeneous connectivity are both qualitatively and quantitatively predicted through simple evolutionary processes. This finding implies that network models can be simplified by considering evolutionary processes, and also that another explanation exists for the emergence of non-random patterns and might provide more comprehensible insights into the formation of plant-animal mutualistic networks from the evolutionary perspective. (C) 2010 Elsevier Ltd. All rights reserved.