Evidence map›Paper›PMID 23951346›Full record

ArticlePloS one2013

Predictors of death during tuberculosis treatment in TB/HIV co-infected patients in Malaysia.

Ismawati Ismail, Awang Bulgiba

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 6 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

35 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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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

2 authors.

Ismawati IsmailJulius Centre University of Malaya, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. drismawati@gmail.com
Awang Bulgiba

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMortality among TB/HIV co-infected patients is still high particularly in developing countries. This study aimed to determine the predictors of death in TB/HIV co-infected patients during TB treatment.

methodsWe reviewed medical records at the time of TB diagnosis and subsequent follow-up of all newly registered TB patients with HIV co-infection at TB clinics in the Institute of Respiratory Medicine and three public hospitals in the Klang Valley between January 2010 and September 2010. We reviewed these medical records again twelve months after their initial diagnosis to determine treatment outcomes and survival. We analysed using Kaplan-Meier and conducted multivariate Cox proportional hazards analysis to identify predictors of death during TB treatment in TB/HIV co-infected patients.

resultsOf the 227 patients studied, 53 (23.3%) had died at the end of the study with 40% of deaths within two months of TB diagnosis. Survival at 2, 6 and 12 months after initiating TB treatment were 90.7%, 82.8% and 78.8% respectively. After adjusting for other factors, death in TB/HIV co-infected patients was associated with being Malay (aHR 4.48; 95%CI 1.73-11.64), CD4 T-lymphocytes count < 200 cells/µl (aHR 3.89; 95% CI 1.20-12.63), three or more opportunistic infections (aHR 3.61; 95% CI 1.04-12.55), not receiving antiretroviral therapy (aHR 3.21; 95% CI 1.76-5.85) and increase per 10(3) total white blood cell count per microliter (aHR 1.12; 95% CI 1.05-1.20).

conclusionTB/HIV co-infected patients had a high case fatality rate during TB treatment. Initiation of antiretroviral therapy in these patients can improve survival by restoring immune function and preventing opportunistic infections.

Indexed as

CoinfectionAdolescentAdultAntitubercular AgentsFemaleHIV InfectionsHumansMalaysiaMaleMiddle AgedPrognosisSocioeconomic FactorsSurvival AnalysisTreatment OutcomeTuberculosisYoung AdultAntitubercular Agents

Identifiers

PMID23951346
PMCPMC3741191

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Registered trials

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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.