Evidence map›Paper›PMID 31260481›Full record

ArticlePloS one2019

App-based symptoms screening with Xpert MTB/RIF Ultra assay used for active tuberculosis detection in migrants at point of arrivals in Italy: The E-DETECT TB intervention analysis.

Lucia Barcellini, Emanuele Borroni, Claudia Cimaglia, Enrico Girardi, Alberto Matteelli, Valentina Marchese, Giovanna Stancanelli, Ibrahim Abubakar, members of the E-Detect TB Consortium, Daniela Maria Cirillo

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 5 pooled it
1.6field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 5 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Number needed to screen for TB in clinical, structural or occupational risk groups.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
    Pooled it
  4. Evaluating the efficacy of stool sample on Xpert MTB/RIF Ultra and its comparison with other sample types by meta-analysis for TB diagnostics.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2022
    Pooled it
  5. Pooled it
  6. Article
  7. Article
  8. Article
  9. 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

10 authors at 4 institutions in 2 countries.

Lucia BarcelliniEmerging Bacterial Pathogens Unit, Division of Immunology and Infectious Diseases IRCCS San Raffaele Scientific Institute, Milano, Italy.
Emanuele BorroniEmerging Bacterial Pathogens Unit, Division of Immunology and Infectious Diseases IRCCS San Raffaele Scientific Institute, Milano, Italy.
Claudia CimagliaClinical Epidemiology Unit, National Institute for Infectious Disease "Lazzaro Spallanzani"-IRCCS, Rome, Italy.ORCID 0000-0001-6949-3876
Enrico GirardiClinical Epidemiology Unit, National Institute for Infectious Disease "Lazzaro Spallanzani"-IRCCS, Rome, Italy.
Alberto MatteelliInstitute of Infectious and Tropical Diseases, Infectious Disease, University of Brescia, Brescia, Italy.
Valentina MarcheseInstitute of Infectious and Tropical Diseases, Infectious Disease, University of Brescia, Brescia, Italy.
Giovanna StancanelliEmerging Bacterial Pathogens Unit, Division of Immunology and Infectious Diseases IRCCS San Raffaele Scientific Institute, Milano, Italy.ORCID 0000-0002-9729-8071
Ibrahim AbubakarTuberculosis Section, Health Protection Agency Colindale and University College London, London, United Kingdom.ORCID 0000-0002-0370-1430
members of the E-Detect TB Consortium
Daniela Maria CirilloEmerging Bacterial Pathogens Unit, Division of Immunology and Infectious Diseases IRCCS San Raffaele Scientific Institute, Milano, Italy.ORCID 0000-0001-6415-1535
Vita-Salute San Raffaele University · ITIstituto Nazionale per le Malattie Infettive Lazzaro Spallanzani · ITUniversity of Brescia · ITUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFrom 2014 to 2017, the number of migrants who came to Italy via the Mediterranean route has reached an unprecedented level. The majority of refugees and migrants were rescued in the Central Mediterranean and disembarked at ports in the Sicily region. Rapid on-spot active TB screening intervention at the point of arrival will cover most migrants arriving in EU and by detecting TB prevalent cases will limit further transmission of the disease. MATERIAL AND

methodsBetween November 2016 and December 2017 newly arrived migrants at point of arrivals in Sicily, were screened for active Tuberculosis using a smartphone application, followed in symptomatic individuals by fast molecular test, Xpert MTB/RIF Ultra, on collected sputum samples.

resultsIn the study period 3787 migrants received a medical evaluation. Eight hundred and ninety-one (23.5%) reported at least one protocol-defined Tuberculosis symptom. Fifteen (2.7%) were positive to at least one microbiological test revealing a post-entry screening prevalence rate of 396 per 100.000 individuals screened (95% CI: 2.22-6.53). In logistic regression analysis, those with cough and at least one other symptom had an increased probability of testing positive compared to persons with symptoms other than cough. Whole-genome-sequencing demonstrate two separate cases of transmission. DISCUSSION: To our knowledge this study reports first-time results of an active TB case finding strategy based on on-spot symptom screening using a smartphone application, followed by fast molecular test on collected sputum samples. Our preliminary findings reveal a post-entry screening prevalence rate of 396 per 100.000 individuals screened (95% CI: 2.22-6.53).

Indexed as

Mobile ApplicationsTransients and MigrantsAdolescentAdultFemaleHumansLogistic ModelsMaleMass ScreeningMolecular Diagnostic TechniquesMycobacterium tuberculosisPrevalenceSicilySputumTuberculosis, Pulmonary

Identifiers

PMID31260481
PMCPMC6602175
OpenAlexW2955720573

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.