ArticleJournal of tropical medicine2015
A prospective study of tuberculosis drug susceptibility in sabah, malaysia, and an algorithm for management of isoniazid resistance.
Article in Journal of tropical medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 25 citations in OpenAlex.
- The Effort to Rationalize Antibiotic Use in Indonesian Hospitals: Practice and Its Implication.Journal of tropical medicine · 2023Article
- Whole-Genome Sequencing of Streptomycin-Resistant Mycobacterium tuberculosis Strain SBH145 from Sabah, Malaysia.Microbiology resource announcements · 2022Article
- Genomic epidemiology of tuberculosis in eastern Malaysia: insights for strengthening public health responses.Microbial genomics · 2021Article
- Epidemiology of tuberculosis in Sabah, Malaysia, 2012-2018.Infectious diseases of poverty · 2020Article
- Vitamin D and activated vitamin D in tuberculosis in equatorial Malaysia: a prospective clinical study.BMC infectious diseases · 2017Observational
- Tuberculous meningitis is a major cause of mortality and morbidity in adults with central nervous system infections in Kota Kinabalu, Sabah, Malaysia: an observational study.BMC infectious diseases · 2016Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction. The burden of tuberculosis is high in eastern Malaysia, and rates of Mycobacterium tuberculosis drug resistance are poorly defined. Our objectives were to determine M. tuberculosis susceptibility and document management after receipt of susceptibility results. Methods. Prospective study of adult outpatients with smear-positive pulmonary tuberculosis (PTB) in Sabah, Malaysia. Additionally, hospital clinicians accessed the reference laboratory for clinical purposes during the study. Results. 176 outpatients were enrolled; 173 provided sputum samples. Mycobacterial culture yielded M. tuberculosis in 159 (91.9%) and nontuberculous Mycobacterium (NTM) in three (1.7%). Among outpatients there were no instances of multidrug resistant M. tuberculosis (MDR-TB). Seven people (4.5%) had isoniazid resistance (INH-R); all were switched to an appropriate second-line regimen for varying durations (4.5-9 months). Median delay to commencement of the second-line regimen was 13 weeks. Among 15 inpatients with suspected TB, 2 had multidrug resistant TB (one extensively drug resistant), 2 had INH-R, and 4 had NTM. Conclusions. Current community rates of MDR-TB in Sabah are low. However, INH-resistance poses challenges, and NTM is an important differential diagnosis in this setting, where smear microscopy is the usual diagnostic modality. To address INH-R management issues in our setting, we propose an algorithm for the treatment of isoniazid-resistant PTB.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.