Evidence map›Paper›PMID 29580276›Full record

ArticleInfectious diseases of poverty2018

Indicators for prediction of Mycobacterium tuberculosis positivity detected with bronchoalveolar lavage fluid.

Xi Liu, Xing-Fang Hou, Lei Gao, Guo-Fang Deng, Ming-Xia Zhang, Qun-Yi Deng, Tao-Sheng Ye, Qian-Ting Yang, Bo-Ping Zhou, Zhi-Hua Wen and 3 more

Open access · goldAbstract read
In one paragraph

Article in Infectious diseases of poverty, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 21% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

  1. Pooled it
  2. Article
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  4. Article
  5. Article
  6. Frontiers in medicine · 2023
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  7. Bacterial dissemination inThe Indian journal of medical research · 2023
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  13. Article
  14. Comprehensive Determination ofFrontiers in cellular and infection microbiology · 2020
    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

13 authors at 6 institutions in 2 countries.

Xi LiuShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Xing-Fang HouShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Lei GaoMinistry of Health Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Guo-Fang DengShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Ming-Xia ZhangShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Qun-Yi DengShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Tao-Sheng YeShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Qian-Ting YangShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Bo-Ping ZhouShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China.
Zhi-Hua WenYuebei Second People's Hospital, Shaoguan, China.
Hai-Ying LiuMinistry of Health Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Hardy KornfeldDepartment of Medicine, University of Massachusetts Medical School, Worcester, MA, 01655, USA.
Xin-Chun ChenShenzhen Key Laboratory of Infection & Immunity, Shenzhen Third People's Hospital (The Second Affiliated Hospital of Shenzhen University), Shenzhen University School of Medicine, Shenzhen, China. chenxinchun@szu.edu.cn.
Shenzhen Third People’s Hospital · CNShenzhen University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNFifth Affiliated Hospital of Sun Yat-sen University · CNShantou University · CNUniversity of Massachusetts Chan Medical School · US

Funding

National Nature Science Foundation of China 81525016National Nature Science Foundation of China 81770013National Nature Science Foundation of China 81772145Sanming Project of Medicine in Shenzhen GCZX2015043015340574Shenzhen Science & Technology Grant JCYJ20170412101048337Shenzhen Science & Technology Grant JCYJ20170412151620658Shenzhen Science & Technology Grant JSGG20160427104724699
6 · The paper itself

Abstract

backgroundThe diagnosis of active pulmonary tuberculosis (TB) remains a challenge in clinic, especially for sputum negative pulmonary TB. Bronchoalveolar lavage fluid (BALF) has higher sensitivity than sputum for detection of Mycobacterium tuberculosis (Mtb). However, bronchoscopy is invasive and costly, and not suitable for all patients. In order to make TB patients get more benefit from BALF for diagnosis, we explore which indicator might be used to optimize the choice of bronchoscopy.

methodsA total of 1539 sputum-smear-negative pulmonary TB suspects who underwent bronchoscopy were recruited for evaluation. The sensitivity, specificity and accuracy of Mtb detection in sputum and BALF were compared. Odds ratios and 95% confidence intervals were used to assess variables that associated with positive acid-fast bacilli (AFB) smear, Mtb culture and nucleic acid amplification test (NAAT) of BALF in sputum-negative and non-sputum-producing pulmonary TB suspects.

resultsBALF has significantly higher sensitivity (63.4%) than sputum (43.5%) for Mtb detection by culture and NAAT. 19.7% (122/620) sputum-negative and 40.0% (163/408) non-sputum-producing suspects had positive bacteriological results in BALF. Among sputum-negative and non-sputum-producing pulmonary TB suspects, the positivity of Mtb detection in BALF is associated with a younger age, the presence of pulmonary cavities and a positive result of interferon-gamma release assay (IGRA). Sputum-negative patients under 35 years old with positive IGRA and pulmonary cavity had 84.8% positivity of Mtb in BALF.

conclusionsOur study indicated that combination of age, the presence of pulmonary cavity, and the result of IGRA is useful to predict the positivity of Mtb detection in BALF among sputum-negative and non-sputum producing pulmonary TB suspects. Those who are under 35 years old, positive for the presence of pulmonary cavity and IGRA, should undergo bronchoscopy to collect BAFL for Mtb tests, as they have the highest possibility to get bacteriologically confirmation of TB.

Indexed as

Mycobacterium tuberculosisAdultAgedBronchoalveolar Lavage FluidFemaleHumansInterferon-gamma Release TestsMaleMiddle AgedPredictive Value of TestsRadiography, ThoracicRetrospective StudiesRisk FactorsSputumTuberculosis, PulmonaryYoung AdultBronchoalveolar lavage fluidDetectionMycobacterium tuberculosisPredictive factorsPulmonary tuberculosis

Identifiers

PMID29580276
PMCPMC5868051
OpenAlexW2797806679

What OpenQuestion holds

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LicenceCC BY
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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.