Septic arthritis of the hip in children represents a serious disorder with unfavourable long-term sequelae. In neonates, a poor hip outcome is expected especially if the treatment was delayed. Late sequelae can lead to structural joint damage and instability, causing deformity and dislocations which ultimately may result in limb length discrepancy, early degenerative changes and limited range of motion. Surgery at the appropriate time can improve the hip condition and functional outcome. Previous classifications of post septic hip sequelae are useful guides for treatment, but did not discuss one particular group of patient. This group-septic hip dislocation with a preserved femoral head, has recently been described as a distinct entity. This report highlights an 11-year follow-up of a 2-year-old child who had a successful outcome following open reduction and varus derotation
osteotomy for a septic hip dislocation with a preserved femoral head.
Keywords: septic arthritis, hip dislocation, child, infection
Percutaneous pinning after closed reduction is commonly used to treat supracondylar fractures of the humerus in children. Minor pin tract infections frequently occur. The aim of this study was to prevent pin tract infections using a rubber stopper to reduce irritation of the skin against the Kirschner (K) wire following percutaneous pinning. Between July 2011 and June 2012, seventeen children with closed supracondylar fracture of the humerus of Gartland types 2 and 3 were treated with this technique. All patients were treated with closed reduction and percutaneous pinning and followed up prospectively. Only one patient, who was a hyperactive child, developed pin tract infection due to softening of the plaster slab. We found using the rubber stopper to be a simple and inexpensive method to reduce pin tract infections following percutaneous pinning.
Tuberculosis (TB) remains one of the most devastating infectious diseases and its treatment efficiency is majorly influenced by the stage at which infection with the TB bacterium is diagnosed. The available methods for TB diagnosis are either time consuming, costly or not efficient. This study employs a signal generation mechanism for biosensing, known as Plasmonic ELISA, and computational intelligence to facilitate automatic diagnosis of TB. Plasmonic ELISA enables the detection of a few molecules of analyte by the incorporation of smart nanomaterials for better sensitivity of the developed detection system. The computational system uses k-means clustering and thresholding for image segmentation. This paper presents the results of the classification performance of the Plasmonic ELISA imaging data by using various types of classifiers. The five-fold cross-validation results show high accuracy rate (>97%) in classifying TB images using the entire data set. Future work will focus on developing an intelligent mobile-enabled expert system to diagnose TB in real-time. The intelligent system will be clinically validated and tested in collaboration with healthcare providers in Malaysia.