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The frequency of relapse-free cure from multidrug-resistant tuberculosis is higher than previously anticipated

Relapse-Free Cure From MDR-TB Higher Than Anticipated

Per simplified outcome definition, frequency similar in low-, intermediate-, high-incidence countries
In pretreatment isolates of Mycobacterium tuberculosis

MICs of Isoniazid, Rifampin May Predict Tuberculosis Relapse

Higher MIC in pretreatment M. tuberculosis isolates linked to relapse risk
In children with latent tuberculosis

Rifampin Effective for Latent Tuberculosis in Children

Rifampin has advantage of being a shorter, single-drug regimen that is palatable for children
A four-month regimen of rifampin is similar to a nine-month regimen of isoniazid for the prevention of active tuberculosis

Rifampin Similar to Isoniazid for Preventing Active Tuberculosis

Rifampin has significantly higher rate of treatment completion, fewer drug-related adverse events
Most people complete treatment for latent tuberculosis without direct observation

Completion Likely With Self-Administration of TB Treatment

Self-administration without reminders is noninferior to direct observation in patients with latent TB
An automated molecular assay can detect Mycobacterium tuberculosis with resistance to drugs directly from sputum specimens

Assay Can ID M. tuberculosis Resistance Mutations

Assay detects mutations associated with resistance to isoniazid, fluoroquinolones, aminoglycosides

Change in Conversion Definition May Improve TB Detection

Increase from IFNγ <0.2 to >0.7 IU/mL would improve identification of those at risk of tuberculosis
Isoniazid monotherapy

Meta-Analysis Compares Efficacy of Therapies for Preventing TB

Isoniazid, rifampicin monotherapy, combination therapies can prevent active TB in latent TB infection
Multidrug-resistant and extensively drug-resistant tuberculosis are expected to increase through 2040

Multidrug-Resistant TB Set to Increase Through 2040

Increase in percentage of MDR tuberculosis, XDR tuberculosis in India, Philippines, Russia, S. Africa
Deep learning with deep convolutional neural networks can result in accurate detection of tuberculosis on chest radiographs

Deep Convolutional Neural Networks Accurately Detect TB

Ensemble of AlexNet and GoogLeNet was best-performing classifier, with AUC of 0.99