Evidence map›Paper›PMID 26511931›Full record

ArticleBMC health services research2015

Pathways to multidrug-resistant tuberculosis diagnosis and treatment initiation: a qualitative comparison of patients' experiences in the era of rapid molecular diagnostic tests.

Pren Naidoo, Margaret van Niekerk, Elizabeth du Toit, Nulda Beyers, Natalie Leon

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 4 pooled it
2.9field-weighted citation impact, top 9% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 4 syntheses or guidelines pooled it, 51 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Pren NaidooDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa. pnaidoo@icon.co.za.
Margaret van NiekerkDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa. mbunting@sun.ac.za.
Elizabeth du ToitDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa. ejodutoit@gmail.com.
Nulda BeyersDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa. nb@sun.ac.za.
Natalie LeonHealth Systems Research Unit, South African Medical Research Council, Cape Town, South Africa. Natalie.leon@mrc.ac.za.
Desmond Tutu HIV Foundation · ZASouth African Medical Research Council · ZAStellenbosch University · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough new molecular diagnostic tests such as GenoType MTBDRplus and Xpert® MTB/RIF have reduced multidrug-resistant tuberculosis (MDR-TB) treatment initiation times, patients' experiences of diagnosis and treatment initiation are not known. This study aimed to explore and compare MDR-TB patients' experiences of their diagnostic and treatment initiation pathway in GenoType MTBDRplus and Xpert® MTB/RIF-based diagnostic algorithms.

methodsThe study was undertaken in Cape Town, South Africa where primary health-care services provided free TB diagnosis and treatment. A smear, culture and GenoType MTBDRplus diagnostic algorithm was used in 2010, with Xpert® MTB/RIF phased in from 2011-2013. Participants diagnosed in each algorithm at four facilities were purposively sampled, stratifying by age, gender and MDR-TB risk profiles. We conducted in-depth qualitative interviews using a semi-structured interview guide. Through constant comparative analysis we induced common and divergent themes related to symptom recognition, health-care access, testing for MDR-TB and treatment initiation within and between groups. Data were triangulated with clinical information and health visit data from a structured questionnaire.

resultsWe identified both enablers and barriers to early MDR-TB diagnosis and treatment. Half the patients had previously been treated for TB; most recognised recurring symptoms and reported early health-seeking. Those who attributed symptoms to other causes delayed health-seeking. Perceptions of poor public sector services were prevalent and may have contributed both to deferred health-seeking and to patient's use of the private sector, contributing to delays. However, once on treatment, most patients expressed satisfaction with public sector care. Two patients in the Xpert® MTB/RIF-based algorithm exemplified its potential to reduce delays, commencing MDR-TB treatment within a week of their first health contact. However, most patients in both algorithms experienced substantial delays. Avoidable health system delays resulted from providers not testing for TB at initial health contact, non-adherence to testing algorithms, results not being available and failure to promptly recall patients with positive results.

conclusionWhilst the introduction of rapid tests such as Xpert® MTB/RIF can expedite MDR-TB diagnosis and treatment initiation, the full benefits are unlikely to be realised without reducing delays in health-seeking and addressing the structural barriers present in the health-care system.

Indexed as

Critical PathwaysAdultAlgorithmsFemaleGenotypeHumansInterviews as TopicMaleMedical AuditMiddle AgedMolecular Diagnostic TechniquesMycobacterium tuberculosisPathology, MolecularPrevalenceQualitative ResearchRifampinRifampin

Identifiers

PMID26511931
PMCPMC4624595
OpenAlexW2163916310

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.