Investigation and Control of a Large Outbreak of Multi-Drug Resistant Tuberculosis at a Central Lisbon Hospital

An increase in the number of new cases of tuberculosis (TB) combined with poor clinical outcome was identified among HIV-infected injecting drug users attending a large HIV unit in central Lisbon. A retrospective epidemiological and laboratory study was conducted to review all newly diagnosed cases of TB from 1995 to 1996 in the HIV unit. Results showed that from 1995 to 1996, 63% (109/173) of the Mycobacterium tuberculosis isolates from HIV-infected patients were resistant to one or more anti-tuberculosis drugs; 89% (95) of these were multidrug-resistant, i.e., resistant to at least isoniazid and rifampicin. Eighty percent of the multidrug-resistant strains (MDR) available for restriction fragment length polymorphism (RFLP) DNA fingerprinting clustered into one of two large clusters. Epidemiological data support the conclusion that the transmission of MDR-TB occurred among HIV-infected injecting drug users exposed to infectious TB cases on open wards in the HIV unit. Improved infection control measures on the HIV unit and the use of empirical therapy with six drugs once patients were suspected to have TB, reduced the incidence of MDR-TB from 42% of TB cases in 1996 to 11% in 1999.

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.