Ghosh Chiranjit, Maity Abhijit, Banik Gourab D, Som Suman, Chakraborty Arpita, Selvan Chitra, Ghosh Shibendu, Ghosh Barnali, Chowdhury Subhankar, Pradhan Manik
Department of Chemical, Biological and Macromolecular Sciences, S. N. Bose National Centre for Basic Sciences, Salt Lake, JD Block, Sector III, Kolkata-700098, India.
J Breath Res. 2014 Sep;8(3):036001. doi: 10.1088/1752-7155/8/3/036001. Epub 2014 Jun 19.
We report, for the first time, the clinical feasibility of a novel residual gas analyzer mass spectrometry (RGA-MS) method for accurate evaluation of the (13)C-glucose breath test ((13)C-GBT) in the diagnosis of pre-diabetes (PD) and type 2 diabetes mellitus (T2D). In T2D or PD, glucose uptake is impaired and results in blunted isotope enriched (13)CO2 production in exhaled breath samples. Using the Receiver operating characteristics (ROC) curve analysis, an optimal diagnostic cut-off point of the (13)CO2/(12)CO2 isotope ratios expressed as the delta-over-baseline (DOB) value, was determined to be δDOB(13)C‰ = 28.81‰ for screening individuals with non-diabetes controls (NDC) and pre-diabetes (PD), corresponding to a sensitivity of 100% and specificity of 94.4%. We also determined another optimal diagnostic cut-off point of δDOB(13)C‰ = 19.88‰ between individuals with PD and T2D, which exhibited 100% sensitivity and 95.5% specificity. Our RGA-MS methodology for the (13)C-GBT also manifested a typical diagnostic positive and negative predictive value of 96% and 100%, respectively. The diagnostic accuracy, precision and validity of the results were also confirmed by high-resolution optical cavity enhanced integrated cavity output spectroscopy (ICOS) measurements. The δDOB(13)C‰ values measured with RGA-MS method, correlated favourably (R(2) = 0.979) with those determined by the laser based ICOS method. Moreover, we observed that the effects of endogenous CO2 production related to basal metabolic rates in individuals were statistically insignificant (p = 0.37 and 0.73) on the diagnostic accuracy. Our findings suggest that the RGA-MS is a valid and sufficiently robust method for the (13)C-GBT which may serve as an alternative non-invasive point-of-care diagnostic tool for routine clinical practices as well as for large-scale diabetes screening purposes in real-time.
我们首次报告了一种新型残余气体分析仪质谱法（RGA-MS）在准确评估用于诊断糖尿病前期（PD）和2型糖尿病（T2D）的（13）C-葡萄糖呼气试验（（13）C-GBT）中的临床可行性。在T2D或PD中，葡萄糖摄取受损，导致呼出气体样本中同位素富集的（13）CO2产生减弱。使用受试者工作特征（ROC）曲线分析，确定以超过基线的差值（DOB）值表示的（13）CO2/（12）CO2同位素比率的最佳诊断切点为δDOB（13）C‰ = 28.81‰，用于筛查非糖尿病对照（NDC）和糖尿病前期（PD）个体，相应的灵敏度为100%，特异性为94.4%。我们还确定了另一个在PD和T2D个体之间的最佳诊断切点δDOB（13）C‰ = 19.88‰，其灵敏度为100%，特异性为95.5%。我们用于（13）C-GBT的RGA-MS方法还分别表现出典型的诊断阳性预测值和阴性预测值为96%和100%。结果的诊断准确性、精密度和有效性也通过高分辨率光腔增强集成腔输出光谱（ICOS）测量得到证实。用RGA-MS方法测量的δDOB（13）C‰值与基于激光的ICOS方法确定的值具有良好的相关性（R（2） = 0.979）。此外，我们观察到个体中与基础代谢率相关的内源性CO2产生对诊断准确性的影响在统计学上不显著（p = 0.37和0.73）。我们的研究结果表明，RGA-MS是一种用于（13）C-GBT的有效且足够稳健的方法，可作为常规临床实践以及大规模糖尿病实时筛查目的的替代非侵入性即时诊断工具。
