Novel screening tools for latent tuberculosis: time to leave an old friend?

PURPOSE OF REVIEW: Therapeutic inhibition of tumour necrosis factor-alpha strongly increases the risk of reactivation in latent tuberculosis infection. Recent blood tests based on antigen-specific T cell response and measuring production of interferon-gamma, so called interferon-gamma release assays (IGRAs), are promising novel tools to identify infected patients. The performance of diagnostic testing for latent tuberculosis infection in patients with rheumatic diseases will be discussed. RECENT FINDINGS: In patients with rheumatoid arthritis, IGRAs are more sensitive and more specific than traditional tuberculin skin testing. They are unaffected by Bacillus-Calmette-Guérin vaccination and most nontuberculous mycobacteria. Most comparative studies show a better performance of the IGRAs than tuberculin skin testing in terms of a higher specificity. The rate of indeterminate results may be affected by glucocorticoids and the underlying disease but appears independent of disease-modifying antirheumatic drugs. Despite using identical Mycobacterium tuberculosis antigens, the two commercially available tests show differences in clinical performance. SUMMARY: The current information about the performance of the tuberculin skin testing and the IGRAs in the detection of latent tuberculosis infection in patients with rheumatic diseases strongly suggest a clinically relevant advantage of the IGRAs. Their use will help to reduce overuse and underuse of preventive treatment in tumour necrosis factor inhibition.

Organized inpatient (stroke unit) care in very old patients

BACKGROUND AND PURPOSE: It is unclear whether very old patients benefit from organized inpatient (stroke unit) care. The aim of this work was to compare the clinical outcome of patients with first-ever ischemic stroke aged either >or=80 or <80 years who were treated conservatively (without cerebral revascularization) in a university-based stroke unit. PATIENTS AND METHODS: We included 147 (11%) patients >or=80 years and 1241 (89%) patients, <80 years. All patients underwent clinical examination, blood tests, electrocardiography (ECG), brain imaging and cerebrovascular ultrasound. Additional investigations were done at the discretion of the treating physician. The modified Rankin scale (mRS) score was used to assess the 3-month outcome (favorable: mRS, 0-1; poor: mRS, 2-6; death of any cause). RESULTS: Stroke severity did not differ between both groups [median National Institutes of Health Stroke Scale (NIHSS) score, 4]. Younger patients underwent magnetic resonance (MR) imaging of the brain, MR and catheter angiography and echocardiography (p<0.001) more frequently, whereas older patients underwent computed tomography of the brain and 24-hour ECG (p<0.001) more frequently. Stroke prevention included clopidogrel (p<0.001) and heparin (p=0.047) more often in older patients and aspirin (p=0.016) in younger patients. Recurrent ischemic events were similarly frequent in old (7%) and young (5%) patients. Favorable outcome was equally prevalent in old (71%) and young (76%) patients, whereas mortality was higher in older patients (7 and 3%, p=0.007). Admission NIHSS score >or=12 was the only independent predictor of unfavorable outcome (odds ratio, 19.6; 95% confidence interval, 9.7-39.6; p<0.001). CONCLUSION: Our work provides further evidence that also the oldest patients may benefit from conservative stroke unit care.

On the use of textural features for writer identification in old handwritten music scores

Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates.