The revised Tokuhashi score; analysis of parameters and assessment of its accuracy in determining survival in patients afflicted with spinal metastasis.

PURPOSE: To determine the significance of each parameter of the revised Tokuhashi score and identify which is associated with survival. BACKGROUND: Spinal metastases are common and can be a challenging medical issue. Treatment options depend on patients' prognosis. Many scoring systems in the literature help estimate prognosis, such as the Tokuhashi, revised Tokuhashi, and Tomita scoring systems. METHODS: A retrospective review of all patients from 2003 to 2012 treated for spinal metastases in one center was conducted. Imaging, pathology, and charts were reviewed to determine the modified Tokuhashi scores. Scores were then compared to the actual documented survival. Univariate and multiple regression analyses were used to assess the importance of each individual parameter and survival time. Linear regression was used to determine the relationship between the Tokuhashi score and weighted Tokuhashi score with survival time. RESULTS: A total of 126 patients were reviewed. All parameters in the revised Tokuhashi score were significantly associated with survival time except for primary site using univariate analysis. Only the number of spinal metastases and metastasis to major organs showed statistical significance when multiple variable analysis was used. CONCLUSION: A number of spinal metastases and metastasis to major organs were the most important predictors of actual survival. Modification to the score based on population characteristics would help better identify patients with spinal metastases that can benefit from surgery.

Power-based segmentation of respiratory signals using forward-backward bank filtering.

We present an automated method for the segmentation of ribcage and abdominal signals measured by noninvasive respiratory inductance plethysmography (RIP) into quiet breathing and artifact-corrupted segments. This procedure, which involves forward-backward filtering, is applicable to the automated off-line analysis of long records of respiratory signals. Examples of applications include home and sleep laboratory studies of cardiorespiratory data. The new procedure was successfully applied to the segmentation of cardiorespiratory signals acquired post-operatively from infants in the recovery room of the Montreal Children's Hospital (MCH).