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SAMJ: South African Medical Journal

On-line version ISSN 2078-5135
Print version ISSN 0256-9574

Abstract

NOMLOMO, E  and  NANA, T. The impact of diagnostic methods on the diagnosis of Clostridiodes difficile infection. SAMJ, S. Afr. med. j. [online]. 2020, vol.110, n.2, pp.135-139. ISSN 2078-5135.  http://dx.doi.org/10.7196/samj.2020.v110i2.13684.

BACKGROUND. Clostridiodes difficile is a common cause of healthcare-associated diarrhoea. Laboratory testing for C. difficile infection (CDI) remains an area of confusion, as there is not a single accepted reference standard or a single best test.OBJECTIVES. To analyse the impact of different diagnostic methods on reported CDI rates. In addition, CDI incidence rates at Charlotte Maxeke Johannesburg Academic Hospital (CMJAH), Johannesburg, South Africa, were determined.METHODS. Results of stool samples submitted for C. difficile testing at CMJAH from 1 January 2014 to 31 August 2017 were reviewed. From January 2014 to July 2016, samples were tested by polymerase chain reaction (PCR) or toxin immunoassay, and from August 2016 to August 2017, algorithm-based testing (glutamate dehydrogenase and toxin immunoassay followed by PCR) was performed.RESULTS. A total of 4 829 samples were submitted. For the first period, toxin immunoassay and PCR showed a positivity rate of 11.4% and 21.1%, respectively, with an overall positivity rate of 18.7% (95% confidence interval (CI) 15.6 - 21.9). For the second period, the positivity rate was 15.9% (95% CI 11.3 - 17.7). This rate included samples that were GDH-positive and either showed toxin production or had a positive Xpert result. The CDI incidence for the two periods was different, with an incidence rate of 8.8 and 6.1 per 10 000 patient-days for the first and second periods, respectively.CONCLUSIONS. The choice of laboratory testing method has a major impact on the diagnosis of CDI, and therefore on reported rates of CDI. Standardisation of laboratory testing and incidence rate reporting is required in order to obtain robust and reliable data.

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