Evidence map›Paper›PMID 34045573›Full record

ArticleScientific reports2021

A risk score for prediction of poor treatment outcomes among tuberculosis patients with diagnosed diabetes mellitus from eastern China.

Nannan You, Hongqiu Pan, Yi Zeng, Peng Lu, Limei Zhu, Wei Lu, Qiao Liu, Leonardo Martinez

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 pooled it
0.5field-weighted citation impact, top 32% 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

10 citing papers in PubMed, 3 syntheses or guidelines pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Yield and Efficiency of a Population-Based Mass Tuberculosis Screening Intervention Among Persons With Diabetes in Jiangsu Province, China.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Pooled it
  4. Article
  5. Article
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  10. Mass Tuberculosis Screening Among the Elderly: A Population-Based Study in a Well-Confined, Rural County in Eastern China.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    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

8 authors at 5 institutions in 2 countries.

Nannan You *Department of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Hongqiu Pan *Department of Tuberculosis, The Third People's Hospital of Zhenjiang Affiliated To Jiangsu University, Zhenjiang, Jiangsu Province, China.
Yi ZengDepartment of Tuberculosis of Three, Nanjing Public Health Medical Center, Nanjing Second Hospital, Nanjing Hospital Affiliated to Nanjing University of Traditional Chinese Medicine, Nanjing, Jiangsu Province, China.
Peng LuDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Limei ZhuDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Wei LuDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Qiao LiuDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China. liuqiaonjmu@163.com.
Leonardo MartinezDepartment of Epidemiology, School of Public Health, Boston University, Boston, MA, USA.
Jiangsu Provincial Center for Disease Control and Prevention · CNBoston University · USJiangsu University · CNNanjing Second Hospital · CNZhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Persons living with diabetes (PLWD) with newly diagnosed tuberculosis are at greater risk of poor treatment outcomes. Identifying and prioritizing high-risk subgroups of PLWD and tuberculosis for tuberculosis programs to target has been rarely performed. We investigated risk factors for poor tuberculosis treatment outcomes among PLWD and developed a predictive risk score for tuberculosis control prioritization. Among PLWD diagnosed with tuberculosis, demographic, clinical, and tuberculosis treatment outcome data were collected. Poor treatment outcomes included treatment failure, death, default, and transfer. Multivariable logistic regression modeling was used to analyze risk factors of poor treatment outcomes. Risk scores were derived based on regression coefficients to classify participants at low-, intermediate-, and high-risk of poor treatment outcomes. Among 335 PLWD newly diagnosed with tuberculosis, 109 were cured and 172 completed treatment. Multivariable logistic regression found that risk factors of poor treatment outcomes included bacteriologically-positivity, low body mass index, no physical activity, and pulmonary cavitation. Rates of poor treatment outcomes in low- (0-2), intermediate- (3-4), and high-risk (5-8) groups were 4.2%, 10.5%, and 55.4% (P

Indexed as

AgedAntitubercular AgentsChinaDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedPrognosisRisk AssessmentTreatment OutcomeTuberculosis, PulmonaryAntitubercular Agents

Identifiers

PMID34045573
PMCPMC8160203
OpenAlexW3165184772

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.