The use of a gas chromatograph coupled to a metal oxide sensor for rapid assessment of stool samples from irritable bowel syndrome and inflammatory bowel disease patients

There is much clinical interest in the development of a low-cost and reliable test for diagnosing inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), two very distinct diseases that can present with similar symptoms. The assessment of stool samples for the diagnosis of gastro-intestinal diseases is in principle an ideal non-invasive testing method. This paper presents an approach to stool analysis using headspace gas chromatography and a single metal oxide sensor coupled to artificial neural network software. Currently, the system is able to distinguish samples from patients with IBS from patients with IBD with a sensitivity and specificity of 76% and 88% respectively, with an overall mean predictive accuracy of 76%.

Towards point of care testing for C. difficile infection by volatile profiling, using the combination of a short multi-capillary gas chromatography column with metal oxide sensor detection

Rapid volatile profiling of stool sample headspace was achieved using a combination of short multi-capillary chromatography column (SMCC), highly sensitive heated metal oxide semiconductor (MOS) sensor and artificial neural network (ANN) software. For direct analysis of biological samples this prototype offers alternatives to conventional GC detectors and electronic nose technology. The performance was compared to an identical instrument incorporating a long single capillary column (LSCC). The ability of the prototypes to separate complex mixtures was assessed using gas standards and homogenised in house 'standard' stool samples, with both capable of detecting more than 24 peaks per sample. The elution time was considerably faster with the SMCC resulting in a run time of 10 minutes compared to 30 minutes for the LSCC. The diagnostic potential of the prototypes was assessed using 50 C. difficile positive and 50 negative samples. The prototypes demonstrated similar capability of discriminating between positive and negative samples with sensitivity and specificity of 85% and 80% respectively. C. difficile is an important cause of hospital acquired diarrhoea, with significant morbidity and mortality around the world. A device capable of rapidly diagnosing the disease at the point of care would reduce cases, deaths and financial burden.