Background: Gṛdhrasī correlates with "Lumbago with Sciatica. " Disease complexity suggests that integrative whole-system Āyurvēda treatment combining external and internal therapies will optimize patient care. Objectives: The aim was to evaluate the effectiveness of an integrative whole-system Āyurvēda treatment approach to the management of pain and disability in Gṛdhrasī patients. Study Design: An observational study using standard monitoring procedures. Materials and Methods: Fifty-four Gṛdhrasī patients (age range 41.53 ± 1.71 years, M: F 27:27, mean duration of illness 18.51 ± 4.36 months) receiving individualized treatments at the Integrative Healthcare Center were recruited. Subjects were assessed at the outset, and after each period of treatment using visual analog scale (VAS), straight leg-raising test (SLR), and Roland Morris disability questionnaire (RMDQ). Statistical analysis used Microsoft Excel and SPSS 16.0. Results: Following initial consultations, 16 subjects dropped out. Of the 38 remaining, 68.4% showed significant improvements in pain and disability, 18.4% were borderline non-responders, and 13.2% failed to respond to treatment. There was a statistically significant reduction in the pain (VAS) (F = 62.53, P < 0.0001) and measures of disability (RMDQ) (F = 17.14, P = 0.018). Leg-raising as assessed by SLR also improved significantly for both the legs (P < 0.001). Conclusion: The results of the current observational study are encouraging despite the small size of the group; further clinical trials using a similar integrative whole-system approach for the management of Gṛdhrasī are warranted.
Abstract:Encryption is used to secure data before it is sent to cloud storage. It is done by data owner in order to protect data from misuse. However, there are issues when the encrypted data needs to accessed or searched for. The traditional search operation is not suitable for searching encrypted cloud data. Many researchers contributed towards providing search mechanisms on encrypted and outsourced cloud data. Xia et al. focused on secure multi-keyword ranked search on the encrypted and outsourced data to public cloud. They supported search operations and data dynamics as well. In this paper we proposed a methodology for performing flexible multi-keyword based optimized search scheme for encrypted cloud storage with user revocation feature. Users who are no longer supported by the system are revoked in order to ensure that the system remains secure. A model is built in order to have dynamic queries possible. Towards this end TF/IDF measure is used for flexible search operations on outsourced cloud data. We built a prototype application that shows multi-keyword ranked search with user revocation feature. The results revealed that the proposed system is flexible, secure and supporting optimized search over encrypted cloud data.
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