Evidence map›Paper›PMID 29084286›Full record

SynthesisPloS one2017

EZSCAN for undiagnosed type 2 diabetes mellitus: A systematic review and meta-analysis.

Antonio Bernabe-Ortiz, Andrea Ruiz-Alejos, J Jaime Miranda, Rohini Mathur, Pablo Perel, Liam Smeeth

Abstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Observational
  4. 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

6 authors.

Antonio Bernabe-OrtizCRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.ORCID http://orcid.org/0000-0002-6834-1376
Andrea Ruiz-AlejosCRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
J Jaime MirandaCRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
Rohini MathurFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Pablo PerelFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Liam SmeethFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Funding

University of California Launching Future Leaders in Global Health Research Training ProgramD43TW009343 · FIC · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CRAIG R COHEN, Sung-Jae Lee · 2017 to 2026
$14.7M
FIC NIH HHS D43 TW009343
6 · The paper itself

Abstract

objectivesThe EZSCAN is a non-invasive device that, by evaluating sweat gland function, may detect subjects with type 2 diabetes mellitus (T2DM). The aim of the study was to conduct a systematic review and meta-analysis including studies assessing the performance of the EZSCAN for detecting cases of undiagnosed T2DM. METHODOLOGY/PRINCIPAL

findingsWe searched for observational studies including diagnostic accuracy and performance results assessing EZSCAN for detecting cases of undiagnosed T2DM. OVID (Medline, Embase, Global Health), CINAHL and SCOPUS databases, plus secondary resources, were searched until March 29, 2017. The following keywords were utilized for the systematic searching: type 2 diabetes mellitus, hyperglycemia, EZSCAN, SUDOSCAN, and sudomotor function. Two investigators extracted the information for meta-analysis and assessed the quality of the data using the Revised Version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklist. Pooled estimates were obtained by fitting the logistic-normal random-effects model without covariates but random intercepts and using the Freeman-Tukey Arcsine Transformation to stabilize variances. Heterogeneity was also assessed using the I2 measure. Four studies (n = 7,720) were included, three of them used oral glucose tolerance test as the gold standard. Using Hierarchical Summary Receiver Operating Characteristic model, summary sensitivity was 72.0% (95%CI: 60.0%- 83.0%), whereas specificity was 56.0% (95%CI: 38.0%- 74.0%). Studies were very heterogeneous (I2 for sensitivity: 79.2% and for specificity: 99.1%) regarding the inclusion criteria and bias was present mainly due to participants selection.

conclusionsThe sensitivity of EZSCAN for detecting cases of undiagnosed T2DM seems to be acceptable, but evidence of high heterogeneity and participant selection bias was detected in most of the studies included. More studies are needed to evaluate the performance of the EZSCAN for undiagnosed T2DM screening, especially at the population level.

Indexed as

Diabetes Mellitus, Type 2HumansSweat Glands

Identifiers

PMID29084286
PMCPMC5662214

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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.