Evidence map›Paper›PMID 29359155›Full record

ArticleBioMed research international2017

The Feasibility of Xpert MTB/RIF Testing to Detect Rifampicin Resistance among Childhood Tuberculosis for Prevalence Surveys in Northern China.

Jie Lu, Huimin Li, Fang Dong, Jin Shi, Hui Yang, Shujing Han, Ping Chu, Yanlin Zhao, Wenqi Song, Yongli Guo and 1 more

Erratum issuedOpen access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BioMed research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 4 pooled it
1.0field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 4 syntheses or guidelines pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Article
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Jie LuBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Huimin LiKey Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Fang DongKey Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Jin ShiBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Hui YangBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Shujing HanBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Ping ChuBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Yanlin ZhaoNational Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.ORCID 0000-0002-7890-4312
Wenqi SongKey Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Yongli GuoBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Shunying ZhaoKey Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.ORCID 0000-0001-5210-2971
Capital Medical University · CNChinese Center For Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug resistance surveillance is crucial for control of drug-resistant tuberculosis (TB). However, limited data exists on the burden of drug-resistant TB in children. The goal of this work was to generate prevalence data regarding rifampicin- (RIF-) resistant childhood TB in northern China and to test the feasibility of Xpert for surveying pediatric TB drug resistance prevalence. We enrolled 362 clinically diagnosed childhood TB patients and collected sputum, gastric lavage aspirate (GLA), bronchoalveolar lavage fluid (BALF), and cerebral spinal fluid (CSF) samples. Xpert and solid culture were utilized to detect RIF resistance. The detection rate of Xpert-positive TB among new clinically diagnosed TB cases was 38.4% (139/362), significantly higher than that of solid culture-positive TB (16.3%, 59/362,

Indexed as

Molecular Diagnostic TechniquesNucleic Acid Amplification TechniquesTuberculosis, Multidrug-ResistantAdolescentAnti-Bacterial AgentsChildChild, PreschoolChinaDrug Resistance, BacterialFeasibility StudiesFemaleHumansInfantMaleMycobacterium tuberculosisPublic Health SurveillanceAnti-Bacterial AgentsRifampin

Identifiers

PMID29359155
PMCPMC5735616
OpenAlexW4235340986

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.