Monitoring urinary tract infections and bacterial vaginosis

Persaud, Krishna; Pisanelli, Anna Maria; Evans, P J; Travers, Paul

doi:10.1016/j.snb.2005.12.062

Cited by 16 publications

(11 citation statements)

References 12 publications

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“…The following sections provide an overview of the state-of-the-art of the application of electronic noses for the analysis of urine samples by classifying those applications depending on the target investigated, thus including the discrimination of bacteria cultures (Section 2.2) [49,50,51,52], or the detection of urinary tract infections (Section 2.3) [53,54,55,56,57,58], cancer diseases (Section 2.4) [59,60,61,62,63,64,65,66], diabetes (Section 2.5) [67,68], kidney diseases (Section 2.6) [69,74], bowel diseases (Section 2.7) [70,71,72] and exposure to toxic agents (Section 2.8) [73] (reference [74] wasn’t included in Table 1 since it refers to breath analysis).…”

Section: Electronic Noses For Urine Sample Analysismentioning

confidence: 99%

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Application and Uses of Electronic Noses for Clinical Diagnosis on Urine Samples: A Review

Capelli

Taverna

Bellini

et al. 2016

Sensors

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The electronic nose is able to provide useful information through the analysis of the volatile organic compounds in body fluids, such as exhaled breath, urine and blood. This paper focuses on the review of electronic nose studies and applications in the specific field of medical diagnostics based on the analysis of the gaseous headspace of human urine, in order to provide a broad overview of the state of the art and thus enhance future developments in this field. The research in this field is rather recent and still in progress, and there are several aspects that need to be investigated more into depth, not only to develop and improve specific electronic noses for different diseases, but also with the aim to discover and analyse the connections between specific diseases and the body fluids odour. Further research is needed to improve the results obtained up to now; the development of new sensors and data processing methods should lead to greater diagnostic accuracy thus making the electronic nose an effective tool for early detection of different kinds of diseases, ranging from infections to tumours or exposure to toxic agents.

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Section: Electronic Noses For Urine Sample Analysismentioning

confidence: 99%

“…Finally, it is worth to discuss an additional study by Persaud et al [58], which focuses both on UTI and on bacterial vaginosis (BV). Bacterial vaginosis (BV) is the most common cause of vaginitis symptoms among women, whose causes are unknown.…”

Section: Electronic Noses For Urine Sample Analysismentioning

confidence: 99%

Application and Uses of Electronic Noses for Clinical Diagnosis on Urine Samples: A Review

Capelli

Taverna

Bellini

et al. 2016

Sensors

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“…Each class must be composed of representative and reproducible samples. In the case of clinical cases, it is usually difficult to obtain a massive number of samples from the National Health Service (NHS) laboratories, and emphasis is given to the quality of data rather than the quantity [5], [8]. Each of the ENRBF subnetworks consisted of four outputs corresponding to each of the classes and 14 inputs, while six local neurons have been used with the corresponding linear models.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

“…The analysis of infectious diseases represents by far the largest clinical research area for e-nose technology attracting TABLE I DETECTION THRESHOLD LEVELS OF HUMAN OLFACTORY SYSTEMS AND ELECTRONIC NOSES both academic and commercial interest [5], [6]. However, given the low repeatability of the data patterns extracted from these sensors and the fuzzy nature of odor patterns, the use of advanced soft computing intelligence techniques is considered a necessity for accurate diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Artificial Odor Discrimination System Using Electronic Nose and Neural Networks for the Identification of Urinary Tract Infection

Kodogiannis

Lygouras

Tarczyński

et al. 2008

IEEE Trans. Inform. Technol. Biomed.

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“…Besides the food application, there is an increasing interest to use EN's for the diagnosis of infectious diseases such as bacterial vaginosis 9 , skin 10 , pulmonary 11 , laryngeal 12 and urinary tract-infections 13,14,15 as well as breath analysis of patients suffering from diabetes 16 uremia 17 asthma 18 and lung cancer 19 . Also M. tuberculosis when grown in large quantities has a smell that the human nose perceives as a mixture of daffodils, pineapple, hyacinth and honey (personal observation).…”

Section: Introductionmentioning

confidence: 99%

Novel approaches in diagnosing tuberculosis

Kolk

Dang²,

Kuijper

et al. 2011

SPIE Proceedings

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The WHO declared tuberculosis (TB) a global emergency. An estimated 8-9 million new cases occur each year with 2-3 million deaths. Currently, TB is diagnosed mostly by chest-X ray and staining of the mycobacteria in sputum with a detection limit of 1x10 4 bacteria /ml. There is an urgent need for better diagnostic tools for TB especially for developing countries. We have validated the electronic nose from TD Technology for the detection of Mycobacterium tuberculosis by headspace analysis of 284 sputum samples from TB patients. We used linear discriminant function analysis resulting in a sensitivity of 75% a specificity of 67% and an accuracy of 69%. Further research is still required to improve the results by choosing more selective sensors and sampling techniques.We used a fast gas chromatography-mass spectrometry method (GC-MS). The automated procedure is based on the injection of sputum samples which are methylated inside the GC injector using thermally assisted hydrolysis and methylation (THM-GC-MS). Hexacosanoic acid in combination with tuberculostearic acid was found to be specific for the presence of M. tuberculosis. The detection limit was similar to microscopy. We found no false positives, all microscopy and culture positive samples were also found positive with the THM-GC-MS method. The detection of ribosomal RNA from the infecting organism offers great potential since rRNA molecules outnumber chromosomal DNA by a factor 1000. It thus may possible to detect the organism without amplification of the nucleic acids (NA). We used a capture and a tagged detector probe for the direct detection of M. tuberculosis in sputum. So far the detection limit is 1x10 6 bacteria / ml. Currently we are testing a Lab-On-A-Chip Interferometer detection system. The World Health Organization (WHO) declared tuberculosis (TB) a global emergency. It is estimated that 1/3rd of the World's population is infected with Mycobacterium tuberculosis (M. tuberculosis). An estimated 8-9 million new cases occur each year with 2-3 million deaths. The majority of cases occur in sub-Saharan Africa, South and Southeast Asia, Latin America and the Caribbean. The recent increase in TB is related to the increase in HIV infections.WHO global targets are 70% detection rate of estimated smear positive TB patients and a cure rate of 85%. The WHO launched the STOP TB program, Direct Observed Treatment Short course (DOTS). The DOTS program alone is incapable of reducing the TB burden because the detection rate of 70% is not reached in many high burden countries. In 2006 overall case detection was 60% (confidence interval 52-69%; treatment success was 84%. Both targets were achieved in the Western Pacific Region, and treatment success exceeded 85% in the South-East Asia region.Early diagnosis of TB followed by appropriate treatment will reduce the burden of TB. Currently, TB is diagnosed by chest X-ray, staining of the mycobacteria in sputum after Ziehl-Neelsen staining (ZN), culture and nucleic acid amplification techniques. These methods are not sati...

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Monitoring urinary tract infections and bacterial vaginosis

Cited by 16 publications

References 12 publications

Application and Uses of Electronic Noses for Clinical Diagnosis on Urine Samples: A Review

Application and Uses of Electronic Noses for Clinical Diagnosis on Urine Samples: A Review

Artificial Odor Discrimination System Using Electronic Nose and Neural Networks for the Identification of Urinary Tract Infection

Novel approaches in diagnosing tuberculosis

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