Latent Class Analysis for the Diagnosis of Clostridioides difficile Infection. (14th October 2020)
- Record Type:
- Journal Article
- Title:
- Latent Class Analysis for the Diagnosis of Clostridioides difficile Infection. (14th October 2020)
- Main Title:
- Latent Class Analysis for the Diagnosis of Clostridioides difficile Infection
- Authors:
- Doolan, Cody P
Louie, Thomas
Lata, Christopher
Larios, Oscar E
Stokes, William
Kim, Joseph
Brown, Kristen
Beck, Paul
Deardon, Rob
Pillai, Dylan R - Abstract:
- Abstract: Background: Clostridioides difficile infection (CDI) is an opportunistic disease that lacks a gold-standard test. Nucleic acid amplification tests such as real-time polymerase chain reaction (PCR) demonstrate an excellent limit of detection (LOD), whereas antigenic methods are able to detect protein toxin. Latent class analysis (LCA) provides an unbiased statistical approach to resolving true disease. Methods: A cross-sectional study was conducted in patients with suspected CDI (N = 96). Four commercial real-time PCR tests, toxin antigen detection by enzyme immunoassay (EIA), toxigenic culture, and fecal calprotectin were performed. CDI clinical diagnosis was determined by consensus majority of 3 experts. LCA was performed using laboratory and clinical variables independent of any gold standard. Results: Six LCA models were generated to determine CDI probability using 4 variables including toxin EIA, toxigenic culture, clinical diagnosis, and fecal calprotectin levels. Three defined zones as a function of real-time PCR cycle threshold (Ct) were identified using LCA: CDI likely (>90% probability), CDI equivocal (<90% and >10%), CDI unlikely (<10%). A single model comprising toxigenic culture, clinical diagnosis, and toxin EIA showed the best fitness. The following Ct cutoffs for 4 commercial test platforms were obtained using this model to delineate 3 CDI probability zones: GeneXpert®: 24.00, 33.61; Simplexa®: 28.97, 36.85; Elite MGB®: 30.18, 37.43; and BD Max™:Abstract: Background: Clostridioides difficile infection (CDI) is an opportunistic disease that lacks a gold-standard test. Nucleic acid amplification tests such as real-time polymerase chain reaction (PCR) demonstrate an excellent limit of detection (LOD), whereas antigenic methods are able to detect protein toxin. Latent class analysis (LCA) provides an unbiased statistical approach to resolving true disease. Methods: A cross-sectional study was conducted in patients with suspected CDI (N = 96). Four commercial real-time PCR tests, toxin antigen detection by enzyme immunoassay (EIA), toxigenic culture, and fecal calprotectin were performed. CDI clinical diagnosis was determined by consensus majority of 3 experts. LCA was performed using laboratory and clinical variables independent of any gold standard. Results: Six LCA models were generated to determine CDI probability using 4 variables including toxin EIA, toxigenic culture, clinical diagnosis, and fecal calprotectin levels. Three defined zones as a function of real-time PCR cycle threshold (Ct) were identified using LCA: CDI likely (>90% probability), CDI equivocal (<90% and >10%), CDI unlikely (<10%). A single model comprising toxigenic culture, clinical diagnosis, and toxin EIA showed the best fitness. The following Ct cutoffs for 4 commercial test platforms were obtained using this model to delineate 3 CDI probability zones: GeneXpert®: 24.00, 33.61; Simplexa®: 28.97, 36.85; Elite MGB®: 30.18, 37.43; and BD Max™: 27.60, 34.26. Conclusions: The clinical implication of applying LCA to CDI is to report Ct values assigned to probability zones based on the commercial real-time PCR platform. A broad range of equivocation suggests clinical judgment is essential to the confirmation of CDI. Abstract : Diagnosis of Clostridioides difficile infection is complicated by the lack of a definitive laboratory test. This study used latent class analysis (LCA) models applied to multiple laboratory and clinical variables in an effort to determine true clinical disease. … (more)
- Is Part Of:
- Clinical infectious diseases. Volume 73:Number 9(2021)
- Journal:
- Clinical infectious diseases
- Issue:
- Volume 73:Number 9(2021)
- Issue Display:
- Volume 73, Issue 9 (2021)
- Year:
- 2021
- Volume:
- 73
- Issue:
- 9
- Issue Sort Value:
- 2021-0073-0009-0000
- Page Start:
- e2673
- Page End:
- e2679
- Publication Date:
- 2020-10-14
- Subjects:
- latent class analysis -- C. difficile -- diagnosis -- real-time PCR -- toxin
Communicable diseases -- Periodicals
616.905 - Journal URLs:
- http://cid.oxfordjournals.org ↗
http://ukcatalogue.oup.com/ ↗
http://www.journals.uchicago.edu/CID/journal ↗
http://www.jstor.org/journals/10584838.html ↗ - DOI:
- 10.1093/cid/ciaa1553 ↗
- Languages:
- English
- ISSNs:
- 1058-4838
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3286.293860
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24961.xml