Metastasis of nasopharyngeal carcinoma (NPC) to the dura, an extremely rare condition, can be symptomatically silent and mistaken for a benign entity radiographically. Missed diagnosis can lead to serious consequences or prove immediately fatal. We report a woman with dural metastasis of NPC that mimicked a meningioma on radiography. Craniectomy with tumour resection was performed due to rapid progression from the onset of symptoms to disability. The patient was still alive two years after surgery. This case emphasises the need to keep in mind the possibility of dural metastasis of NPC in patients with abnormal imaging features. This would not only avoid wrong and optimistic diagnosis, but also allow for appropriate treatment in a timely manner. To our knowledge, this is the first report of metastasis of NPC to the dura. We provide detailed information on the neoplastic lesion, which masqueraded as a benign entity and caused potentially fatal consequences.
Adult ; Brain Neoplasms ; diagnosis ; secondary ; surgery ; Carcinoma ; Diagnosis, Differential ; Disease Progression ; Dura Mater ; pathology ; Female ; Humans ; Magnetic Resonance Imaging ; Meningioma ; diagnosis ; pathology ; Nasopharyngeal Neoplasms ; diagnosis ; pathology ; Neoplasm Metastasis

No abstract available.
Hemangioendothelioma* ; Neck*

OBJECTIVES: The aims of this study were to compare the performance of machine learning methods for the prediction of the medical costs associated with spinal fusion in terms of profit or loss in Taiwan Diagnosis-Related Groups (Tw-DRGs) and to apply these methods to explore the important factors associated with the medical costs of spinal fusion. METHODS: A data set was obtained from a regional hospital in Taoyuan city in Taiwan, which contained data from 2010 to 2013 on patients of Tw-DRG49702 (posterior and other spinal fusion without complications or comorbidities). Naïve-Bayesian, support vector machines, logistic regression, C4.5 decision tree, and random forest methods were employed for prediction using WEKA 3.8.1. RESULTS: Five hundred thirty-two cases were categorized as belonging to the Tw-DRG49702 group. The mean medical cost was US $4,549.7, and the mean age of the patients was 62.4 years. The mean length of stay was 9.3 days. The length of stay was an important variable in terms of determining medical costs for patients undergoing spinal fusion. The random forest method had the best predictive performance in comparison to the other methods, achieving an accuracy of 84.30%, a sensitivity of 71.4%, a specificity of 92.2%, and an AUC of 0.904. CONCLUSIONS: Our study demonstrated that the random forest model can be employed to predict the medical costs of Tw-DRG49702, and could inform hospital strategy in terms of increasing the financial management efficiency of this operation.
Area Under Curve ; Costs and Cost Analysis ; Dataset ; Decision Trees ; Diagnosis-Related Groups ; Financial Management ; Forests ; Humans ; Length of Stay ; Logistic Models ; Machine Learning ; Methods ; Sensitivity and Specificity ; Spinal Fusion ; Support Vector Machine ; Taiwan