Meta-narrative review of molecular methods for diagnosis and monitoring of multidrug-resistant tuberculosis treatment in adults.
Clicks: 285
ID: 75577
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Steady Performance
69.1
/100
280 views
228 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
Early and accurate diagnosis and rigorous clinical and microbiological monitoring of multidrug-resistant tuberculosis (MDR-TB) treatment can curb morbidity and mortality. While others are still under evaluation, the World Health Organization has recommended few novel molecular methods for MDR-TB diagnosis only. We present current molecular methods for diagnosis and monitoring of MDR-TB treatment in TB-endemic settings. A systematic meta-narrative review was conducted according to the RAMESES recommendations. Electronic databases were searched for relevant articles published in English language from January 2013 to June 2018. Based on predefined criteria, two independent reviewers extracted the key messages from relevant articles. Disagreement between them was resolved through discussion and the involvement of a third reviewer, if needed. Key messages were synthesized to create the meta-narratives for method's accuracy, drug-susceptibility capability, and laboratory infrastructure required. We included 33 articles out of 1213 records retrieved, of which 16 (48%) and 12 (36%) were conducted in high- and low-TB-endemic settings, respectively. Xpert MTB/RIF, GenoType MTBDRplus, GenoType MTBDRsl, FlouroType™ MTBDR, TB TaqMan array card, and DNA sequencers can accurately guide effective treatment regimens. Molecular bacterial load assay quantifies mycobactericidal impact of these regimens. Although they present inherent advantages compared to the current standard of care, they carry important limitations to implementation and/or scale-up. Therefore, considerable effort must now be directed to implementation and health systems research to maximize these forecasted benefits for individual patient's health outcomes.
| Reference Key |
mbelelemetanarrativeinternational
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Mbelele, Peter M;Mohamed, Sagal Y;Sauli, Elingarami;Mpolya, Emmanuel A;Mfinanga, Sayoki G;Addo, Kennedy K;Heysell, Scott K;Mpagama, Stellah G; |
| Journal | International journal of mycobacteriology |
| Year | Year not found |
| DOI |
10.4103/ijmy.ijmy_135_18
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.