Literature DB >> 26679923

Detection of intestinal parasites by use of the cuvette-based automated microscopy analyser sediMAX(®).

J Intra1, E Taverna2, M R Sala2, R Falbo2, F Cappellini2, P Brambilla2.   

Abstract

Microscopy is the reference method for intestinal parasite identification. The cuvette-based automated microscopy analyser, sediMAX 1, provides 15 digital images of each sediment sample. In this study, we have evaluated this fully automated instrument for detection of enteric parasites, helminths and protozoa. A total of 700 consecutively preserved samples consisting of 60 positive samples (50 protozoa, ten helminths) and 640 negative samples were analysed. Operators were blinded to each others' results. Samples were randomized and were tested both by manual microscopy and sediMAX 1 for parasite recognition. The sediMAX 1 analysis was conducted using a dilution of faecal samples, allowing determination of morphology. The data obtained using sediMAX 1 showed a specificity of 100% and a sensitivity of 100%. Some species of helminths, such as Enterobius vermicularis, Strongyloides stercolaris, the Ancylostoma duodenale/Necator americanus complex, and schistosomes were not considered in this work, because they are rare in stool specimens, are not easily detectable with microscopy analysis, and require specific recovery techniques. This study demonstrated for the first time that sediMAX 1 can be an aid in enteric parasite identification.
Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Digital images; enteric; helminths; identification; protozoa

Mesh:

Year:  2015        PMID: 26679923     DOI: 10.1016/j.cmi.2015.11.014

Source DB:  PubMed          Journal:  Clin Microbiol Infect        ISSN: 1198-743X            Impact factor:   8.067


  4 in total

1.  Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network.

Authors:  Orly Ardon; Marc Roger Couturier; Blaine A Mathison; Jessica L Kohan; John F Walker; Richard Boyd Smith
Journal:  J Clin Microbiol       Date:  2020-05-26       Impact factor: 5.948

2.  Improvement in the detection of enteric protozoa from clinical stool samples using the automated urine sediment analyzer sediMAX® 2 compared to sediMAX® 1.

Authors:  J Intra; M R Sala; R Falbo; F Cappellini; P Brambilla
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2016-09-20       Impact factor: 3.267

Review 3.  Is the Medium Still the Message? Culture-Independent Diagnosis of Gastrointestinal Infections.

Authors:  Neil Sood; Gary Carbell; Holly S Greenwald; Frank K Friedenberg
Journal:  Dig Dis Sci       Date:  2021-11-30       Impact factor: 3.199

4.  Utility of an Automatic Vision-Based Examination System (AVE-562) for the Detection of Clonorchis sinensis Eggs in Stool.

Authors:  Yu Jeong Lee; Eun Jeong Won; Young-Chang Cho; Soo Hyun Kim; Myung Geun Shin; Jong Hee Shin
Journal:  Ann Lab Med       Date:  2021-03-01       Impact factor: 3.464

  4 in total

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