Evidence map›Paper›PMID 30818352›Full record

ArticlePloS one2019

Evaluation of Xpert MTB-RIF guided diagnosis and treatment of rifampicin-resistant tuberculosis in Indonesia: A retrospective cohort study.

Arto Yuwono Soeroto, Bony Wiem Lestari, Prayudi Santoso, Lidya Chaidir, Basti Andriyoko, Bachti Alisjahbana, Reinout van Crevel, Philip C Hill

Registry-linked trialAbstract readEvaluation Study
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04208789 (Artificial Neural Network as Diagnostic Tools For Rifampicin-Resistant Tuberculosis In Indonesia), which is not on this map. Cited by 23 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

NCT04208789 completednot on this mapstarted 2020, after this paper: background citation

Artificial Neural Network as Diagnostic Tools For Rifampicin-Resistant Tuberculosis In Indonesia: A Predictive Model Study and Economic Evaluation

TypeobservationalSponsorHasanuddin UniversityRan2020 to 2020Enrolled524ConditionsMDR Tuberculosis, Resistance to Tuberculostatic DrugsArmsRapid Molecular Drug-Resistant Tuberculosis Test, Artificial Intelligent Model, Drug Susceptibility Test
3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  11. Prevalence ofJournal of clinical tuberculosis and other mycobacterial diseases · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Arto Yuwono SoerotoDepartment of Internal Medicine, Respirology and Critical Illness Division, Faculty of Medicine Universitas Padjadjaran, Hasan Sadikin General Hospital, Bandung, Indonesia.
Bony Wiem LestariDepartment of Public Health, Faculty of Medicine Universitas Padjadjaran, Bandung, Indonesia.ORCID 0000-0002-6476-2034
Prayudi SantosoDepartment of Internal Medicine, Respirology and Critical Illness Division, Faculty of Medicine Universitas Padjadjaran, Hasan Sadikin General Hospital, Bandung, Indonesia.ORCID 0000-0002-7182-386X
Lidya ChaidirTB-HIV Research Center, Faculty of Medicine Universitas Padjadjaran, Bandung, Indonesia.
Basti AndriyokoDepartment of Clinical Pathology, Faculty of Medicine Universitas Padjadjaran, Hasan Sadikin General Hospital, Bandung, Indonesia.
Bachti AlisjahbanaTB-HIV Research Center, Faculty of Medicine Universitas Padjadjaran, Bandung, Indonesia.
Reinout van CrevelDepartment of Internal Medicine, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Philip C HillCenter for International Health, University of Otago, Dunedin, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRifampicin-resistant tuberculosis (RR-TB) is largely underdetected in Indonesia. Xpert MTB/RIF (Xpert) has recently been introduced, prioritizing patients at risk of RR-TB, followed by phenotypic drug-susceptibility (DST) if rifampicin resistance is detected.

objectiveThis study investigated Xpert-based management of presumptive RR-TB cases under routine practice in West Java, Indonesia.

methodsWe examined all records of patients tested with Xpert in the referral hospital for West Java in 2015-2016. We measured loss across a limited cascade of care, time to Xpert diagnosis and the commencement of initial second-line treatment, and identified factors associated with diagnostic and treatment delay. Additionally, we analyzed the appropriateness of treatment according to DST results.

resultsOf 3415 patients with presumptive RR-TB, 3215 (94%) were tested by Xpert, of whom 339 (10.5%) were diagnosed as RR-TB. 288 (85%) of 339 RR-TB patients started initial second-line TB treatment, with 48 (14%) patients being lost between diagnosis and pre-treatment assessment. Second-line treatment was commenced at a median of 41 days (IQR 29-70) after RR-TB diagnosis. Delays in both diagnosis and treatment initiation were observed in 104 (52%) of 201 RR-TB patients with identifiable referral date. Rural residence was associated with delay to diagnosis (adjusted OR 2.7; 95%CI 1.5-5.2) and treatment initiation (adjusted OR 2.0; 1.2-3.4). Of 162 patients with available DST result, 107 (66%) had multidrug-resistant tuberculosis (MDR-TB) and 32 (20%) had either pre-extensively drug resistant (pre-XDR) or extensively drug resistant tuberculosis (XDR-TB). We estimated that with the current algorithm 41% of pre-XDR or XDR-TB patients are diagnosed, and 33% of them started on an appropriate treatment regimen.

conclusionsMany patients with Xpert-diagnosed RR-TB either do not start MDR-TB treatment or encountered diagnostic and treatment delays under programmatic conditions in Indonesia, and most pre-XDR and XDR-TB cases remain undiagnosed. Further expansion and ongoing quality improvement of RR-TB services are urgently needed.

Indexed as

AdultAntibiotics, AntitubercularCohort StudiesDrug Resistance, BacterialExpert SystemsFemaleHumansIndonesiaMaleMicrobial Sensitivity TestsMiddle AgedMycobacterium tuberculosisRetrospective StudiesRifampinTime-to-TreatmentTuberculosis, Multidrug-ResistantAntibiotics, AntitubercularRifampin

Identifiers

PMID30818352
PMCPMC6394995

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LicenceCC BY
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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.