ABSTRACT
Currently, urine samples for bacterial or fungal infections require a long diagnostic period (48 h). In the present work, a point-of-care device known as an electronic nose (eNose) has been designed based on the "smell print" of infections, since each one emits various volatile organic compounds (VOC) that can be registered by the electronic systems of the device and recognized in a very short time. Urine samples were analyzed in parallel using urine culture and eNose technology. A total of 203 urine samples were analyzed, of which 106 were infected and 97 were not infected. A principal component analysis (PCA) was performed using these data. The algorithm was initially capable of correctly classifying 49% of the total samples. By using SVM-based models, it is possible to improve the accuracy of the classification up to 74% when randomly using 85% of the data for training and 15% for validation. The model is evaluated as having a correct classification rate of 74%. In conclusion, the diagnostic accuracy of the eNose in urine samples is high, promising and amenable for further improvement, and the eNose has the potential to become a feasible, reproducible, low-cost and high-precision device to be applied in clinical practice for the diagnosis of urinary tract infections.
Subject(s)
Electronic Nose , Urinary Tract Infections , Humans , Urinary Tract Infections/diagnosis , Algorithms , Electronics , Point-of-Care SystemsABSTRACT
INTRODUCTION: The main objective of this work is to carry out the clinical validation of the trial with the AMR Direct Flow Chip starting from either nasal swabs, rectal swabs directly or from isolated strains to detect antibiotic resistance genes. METHODS: We developed the preclinical validation of the assay with 104 known bacterial isolates. A total of 210 nasal or rectal swab samples were analyzed. The AMR assay is based on multiplex PCR followed by reverse dot blot hybridization on DNA arrays fully automated by using the HS24 platform. RESULTS: Both the sensitivity and specificity of the preclinical assay were 100%, with the 104 samples correctly identified. In the clinical validation, the sensitivity was 100% and the specificity was between 100% in nasal swabs and 97% in rectal swabs. CONCLUSIONS: The AMR Direct Flow Chip® is a rapid and effective assay for the detection of multidrug-resistant microorganisms (MDR) from nasal and rectal swab samples.
Subject(s)
Anti-Bacterial Agents , Multiplex Polymerase Chain Reaction , Anti-Bacterial Agents/pharmacology , Drug Resistance, MicrobialABSTRACT
INTRODUCTION: The main objective of this work is to carry out the clinical validation of the trial with the AMR Direct Flow Chip® starting from either nasal swabs, rectal swabs directly or from isolated strains to detect antibiotic resistance genes. METHODS: We developed the preclinical validation of the assay with 104 known bacterial isolates. A total of 210 nasal or rectal swab samples were analyzed. The AMR assay is based on multiplex PCR followed by reverse dot blot hybridization on DNA arrays fully automated by using the HS24 platform. The completion time of the full analysis is 3 hours. RESULTS: Both the sensitivity and specificity of the preclinical assay were 100%, with the 104 samples correctly identified. In the clinical validation, the sensitivity was 100% and the specificity was between 100% in rectal swabs and 97% in nasal swabs. CONCLUSIONS: The AMR Direct Flow Chip® is a rapid and effective assay for the detection of multidrug-resistant microorganisms from nasal and rectal swab samples.