Evidence map›Paper›PMID 28778187›Full record

ArticleBMC infectious diseases2017

Risk factors associated with loss to follow-up from tuberculosis treatment in Tajikistan: a case-control study.

Jessica Wohlleben, Mavluda Makhmudova, Firuza Saidova, Shahnoza Azamova, Christina Mergenthaler, Suzanne Verver

Abstract read
In one paragraph

Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 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.

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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Ultrasononography in Managing Extrapulmonary Tuberculosis: A Randomized, Controlled, Parallel, Superiority, Open-Label Trial.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Low BMI increases all-cause mortality rates in patients with drug-resistant TB.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
    Article
  13. Observational
  14. Digital technologies and loss to follow-up for TB patients.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2021
    Article
  15. Geographic mobility and time to seeking care among people with TB in Limpopo, South Africa.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2021
    Article
  16. Factors associated with loss to follow-up among people with tuberculosis in the country of Georgia: a cohort study.Monaldi archives for chest disease = Archivio Monaldi per le malattie del torace · 2021
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

6 authors.

Jessica WohllebenKNCV Tuberculosis Foundation, Evidence team, The Hague, The Netherlands.
Mavluda MakhmudovaKNCV TB Foundation, country office Tajikistan, Dushanbe, Tajikistan.
Firuza SaidovaKNCV TB Foundation, country office Tajikistan, Dushanbe, Tajikistan.
Shahnoza AzamovaRepublican Center for protection of population from TB, Dushanbe, Tajikistan.
Christina MergenthalerKNCV Tuberculosis Foundation, Evidence team, The Hague, The Netherlands.
Suzanne VerverKNCV Tuberculosis Foundation, Evidence team, The Hague, The Netherlands. s.verver@erasmusmc.nl.ORCID 0000-0001-9088-7247

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are very few studies on reasons for loss to follow-up from TB treatment in Central Asia. This study assessed risk factors for LTFU and compared their occurrence with successfully treated (ST) patients in Tajikistan.

methodsThis study took place in all TB facilities in the 19 districts with at least 5 TB patients registered as loss to follow-up (LTFU) from treatment. With a matched case control design we included all LTFU patients registered in the selected districts in 2011 and 2012 as cases, with ST patients from the same districts being controls. Data were copied from patient records and registers. Conditional logistic regressions were run to analyse associations between collected variables and LTFU as dependent variable.

resultsThree hundred cases were compared to 592 controls. Half of the cases had migrated or moved. In multivariate analysis, risk factors associated with increased LTFU were migration to another country (OR 10.6, 95% CI 6.12-18.4), moving within country (OR 11.0, 95% CI 3.50-34.9), having side effects of treatment (OR 3.67, 95% CI 1.68-8.00) and being previously treated for TB (OR 2.03, 95% CI 1.05-3.93). Medical staff also mentioned patient refusal, stigma and family problems as risk factors.

conclusionsLTFU of TB patients in Tajikistan is largely a result of migration, and to a lesser extent associated with side-effects and previous treatment. There is a need to strengthen referral between health facilities within Tajikistan and with neighbouring countries and support patients with side effects and/or previous TB to prevent loss to follow-up from treatment.

Indexed as

AdolescentAdultAgedAntitubercular AgentsCase-Control StudiesChildChild, PreschoolFemaleFollow-Up StudiesHealth FacilitiesHumansInfantInfant, NewbornLogistic ModelsMaleMiddle AgedAntitubercular AgentsCase-control studyDefaultMigration

Identifiers

PMID28778187
PMCPMC5545046

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.