Evidence map›Paper›PMID 38308252›Full record

ArticleBMC infectious diseases2024

Risk factors for diagnosis and treatment delay among patients with multidrug-resistant tuberculosis in Hunan Province, China.

Temesgen Yihunie Akalu, Archie C A Clements, Eyob Alemayehu Gebreyohannes, Zuhui Xu, Liqiong Bai, Kefyalew Addis Alene

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

12 citing papers in PubMed, 11 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

6 authors at 5 institutions in 4 countries.

Temesgen Yihunie AkaluSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, WA, 6102, Australia. t.akalu@postgrad.curtin.edu.au.
Archie C A ClementsGeospatial and Tuberculosis Research Team, Telethon Kids Institute, Perth, WA, Australia.
Eyob Alemayehu GebreyohannesGeospatial and Tuberculosis Research Team, Telethon Kids Institute, Perth, WA, Australia.
Zuhui XuXiangya School of Public Health, Central South University, Changsha, China.
Liqiong BaiTB Control Institute of Hunan Province, Changsha, China.
Kefyalew Addis AleneSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, WA, 6102, Australia.
The Kids Research Institute Australia · AUCentral South University · CNCurtin University · AUHunan Provincial Center for Disease Control and Prevention · CNUniversity of Western Australia · AU

Funding

Curtin University APP1196549
6 · The paper itself

Abstract

backgroundMultidrug-resistant tuberculosis (MDR-TB) is a global health threat associated with high morbidity and mortality rates. Diagnosis and treatment delays are associated with poor treatment outcomes in patients with MDR-TB. However, the risk factors associated with these delays are not robustly investigated, particularly in high TB burden countries such as China. Therefore, this study aimed to measure the length of diagnosis and treatment delays and identify their risk factors among patients with MDR-TB in Hunan province.

methodsA retrospective cohort study was conducted using MDR-TB data from Hunan province between 2013 and 2018. The main outcomes of the study were diagnosis and treatment delay, defined as more than 14 days from the date of symptom to diagnosis confirmation (i.e., diagnosis delay) and from diagnosis to treatment commencement (i.e., treatment delay). A multivariable logistic regression model was fitted, and an adjusted odds ratio (AOR) with a 95% confidence interval (CI) was used to identify factors associated with diagnosis and treatment delay.

resultsIn total, 1,248 MDR-TB patients were included in this study. The median length of diagnosis delays was 27 days, and treatment delays were one day. The proportion of MDR-TB patients who experienced diagnosis and treatment delay was 62.82% (95% CI: 60.09-65.46) and 30.77% (95% CI: 28.27-33.39), respectively. The odds of experiencing MDR-TB diagnosis delay among patients coming through referral and tracing was reduced by 41% (AOR = 0.59, 95% CI: 0.45-0.76) relative to patients identified through consultations due to symptoms. The odds of experiencing diagnosis delay among ≥ 65 years were 65% (AOR = 0.35, 0.14-0.91) lower than under-15 children. The odds of developing treatment delay among foreign nationalities and people from other provinces were double (AOR = 2.00, 95% CI: 1.31-3.06) compared to the local populations. Similarly, the odds of experiencing treatment delay among severely ill patients were nearly 2.5 times higher (AOR = 2.49, 95% CI: 1.41-4.42) compared to patients who were not severely ill. On the other hand, previously treated TB cases had nearly 40% (AOR = 0.59, 95% CI: 0.42-0.85) lower odds of developing treatment delay compared with new MDR-TB cases. Similarly, other ethnic minority groups had nearly 40% (AOR = 0.57, 95% CI: 0.34-0.96) lower odds of experiencing treatment delay than the Han majority.

conclusionsMany MDR-TB patients experience long diagnosis and treatment delays in Hunan province. Strengthening active case detection can significantly reduce diagnosis delays among MDR-TB patients. Moreover, giving attention to patients who are new to MDR-TB treatment, are severely ill, or are from areas outside Hunan province will potentially reduce the burden of treatment delay among MDR-TB patients.

Indexed as

Treatment DelayTuberculosis, Multidrug-ResistantAntitubercular AgentsChildChinaEthnicityHumansMinority GroupsRetrospective StudiesRisk FactorsAntitubercular AgentsChinaDiagnosis delayHunan ProvinceMultidrug-resistant tuberculosisTreatment delay

Identifiers

PMID38308252
PMCPMC10835895
OpenAlexW4391482337

What OpenQuestion holds

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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.