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

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.研究目标 EZSCAN是一款无创设备，通过评估汗腺功能，可识别未确诊的2型糖尿病（type 2 diabetes mellitus, T2DM）受试者。本研究旨在开展系统评价与荟萃分析，纳入所有评估EZSCAN用于检测未确诊2型糖尿病病例性能的相关研究。 研究方法与主要结果 我们检索了截至2017年3月29日的OVID（含Medline、Embase、Global Health）、CINAHL（护理与联合卫生文献累积索引）及SCOPUS数据库，并辅以二次检索资源，纳入评估EZSCAN检测未确诊2型糖尿病病例的诊断准确性与性能的观察性研究。系统检索采用的关键词包括：2型糖尿病、高血糖症、EZSCAN、SUDOSCAN及泌汗功能（sudomotor function）。由两名研究者提取用于荟萃分析的相关数据，并采用《诊断准确性研究质量评价修订版（Quality Assessment of Diagnostic Accuracy Studies-2, QUADAS-2）》量表评估数据质量。通过拟合不含协变量但包含随机截距的logistic正态随机效应模型，并使用Freeman-Tukey反正弦变换稳定方差，得到合并效应量。同时采用I²统计量评估研究间异质性。最终纳入4项研究，共涉及7720名受试者，其中3项研究以口服葡萄糖耐量试验作为金标准。采用分层汇总受试者工作特征（Hierarchical Summary Receiver Operating Characteristic, HSROC）模型进行分析，汇总灵敏度为72.0%（95%置信区间：60.0%~83.0%），汇总特异度为56.0%（95%置信区间：38.0%~74.0%）。纳入研究间异质性较高（灵敏度I²=79.2%，特异度I²=99.1%），主要偏倚来源为受试者选择偏倚。 研究结论 EZSCAN用于检测未确诊2型糖尿病的灵敏度尚可，但纳入的多数研究存在较高异质性及受试者选择偏倚。仍需开展更多研究以评估EZSCAN用于未确诊2型糖尿病筛查的性能，尤其是在人群水平的筛查场景中。