Evidence map›Paper›PMID 31169732›Full record

ArticleMedicine2019

IP-10 for the diagnosis of tuberculosis in children: Protocol for a systematic review and meta-analysis.

Weijun Zhang

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

1 author at 1 institution in 1 country.

Weijun ZhangDepartment of Clinical Laboratory Center, the Second Hospital of Lanzhou University, Lanzhou, China.
Lanzhou University Second Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis (TB) is a highly contagious and chronic disease. The microbiological examination to confirm children TB disease are limited due to paucibacillary Mycobacterium, specimens and detecting facilities. Considering these limitations in diagnosing children TB, new and reliable methods that detect children TB should be developed. Recently, Interferon gamma-induced protein 10 (IP-10) has been identified as a sensitive parameter in detecting children TB. The present study aims to synthesis and analysis the diagnostic value of IP-10 for children TB.

methodsWe will search PubMed, Embase, the Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure, and Chinese Biological Medical Databases. We will search relevant citations up to May 2019. The quality of individual study will be assessed using the Quality Assessment of Diagnostic Accuracy Studies tool-2 (QUADAS-2). Stata 14.0 software will be used to calculate the pooled sensitivity, pooled specificity, pooled positive likelihood ratio (PLR), pooled negative likelihood ratio (NLR), pooled diagnostic odds ratio (DOR), pre-test probability, post-test probability and the hierarchical summary receiver operating characteristic (HSROC) curve.

resultsThe results of this study will be published in a peer-reviewed journal. DISCUSSION: The evidence will indicate that IP-10 test is an alternative immunological test in detecting children TB. This is a protocol of systematic review and meta-analysis, so the ethical approval and patient consent are not required. PROTOCOL REGISTRATION NUMBER: CRD42019129743.

Indexed as

AdolescentCase-Control StudiesChemokine CXCL10ChildChild, PreschoolCohort StudiesFemaleHumansImmunologic TestsInfantLikelihood FunctionsMaleMeta-Analysis as TopicMycobacteriumResearch DesignSensitivity and SpecificityChemokine CXCL10CXCL10 protein, human

Identifiers

PMID31169732
PMCPMC6571383
OpenAlexW2985454529

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.