On the Optimization of Clostridioides difficile Diagnostics Through RT-PCR Cycle Threshold Defined Zones of Disease Probability

dc.contributor.advisorPillai, Dylan
dc.contributor.authorDoolan, Cody Patrick
dc.contributor.committeememberBeck, Paul
dc.contributor.committeememberSpackman, Eldon
dc.date2022-06
dc.date.accessioned2022-02-04T14:51:38Z
dc.date.available2022-02-04T14:51:38Z
dc.date.issued2022-02-02
dc.description.abstractClostridioides difficile is an opportunistic pathogen with a large burden of disease and no gold standard test. Quantitative polymerase chain reaction (qPCR) offers excellent sensitivity but overcalls clinical C. difficile infections (CDI) due to the prevalence of colonization. The hypothesis of this thesis is that the CDI qPCR results can be titrated to determine clinical CDI more accurately and aid in predicting disease severity. A cross-sectional study was conducted on suspected CDI patients evaluating if qPCR cycle threshold (Ct) can be correlated to probability of CDI. Latent class analysis (LCA) was employed with observed variables including four commercial qPCR tests, toxin detection by enzyme immunoassay, toxigenic culture, fecal calprotectin, and clinical diagnosis. Three defined zones as a function of qPCR cycle threshold (Ct) were identified: CDI likely (>90% probability), CDI equivocal (<90% and >10%), CDI unlikely (<10%). A model comprising toxigenic culture, clinical diagnosis, and toxin EIA demonstrated the best fitness. The following Ct cut-offs for 4 commercial test platforms delineated 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. A prospective cohort study was conducted to investigate if these zones can be further correlated to indicators of severe CDI. Primary diagnosis, demographic data and indicators of disease severity were captured: white blood cell, creatinine, albumin, C-reactive protein, and hospital length of stay. A sub analysis was conducted evaluating a subset of the patient population attempting to isolate patients whose clinical variables were most influenced by CDI. No significant correlations were found between the clinical variables investigated and Ct values or Ct zones. This work establishes a method of using deployed diagnostics to allow clinicians to reduce overdiagnosis of CDI. Decreasing false positives could have broad impacts, increase targeted treatments, and decrease antibiotics. The average cost attributed to CDI for one patient is estimated at $11,917. LCA models predict that qPCR confirmation overdiagnoses patients in Calgary by at least 20.9%. If CDI confirmation were reduced by 20.9% this could equate to massive savings; Foothills Medical Center alone could save over $929,000 annually with no additional investment in laboratory infrastructure.en_US
dc.identifier.citationDoolan, C. P. (2022). On the Optimization of Clostridioides difficile Diagnostics Through RT-PCR Cycle Threshold Defined Zones of Disease Probability (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/39597
dc.identifier.urihttp://hdl.handle.net/1880/114396
dc.language.isoengen_US
dc.publisher.facultyCumming School of Medicineen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectClostridioides difficileen_US
dc.subjectDiagnosticsen_US
dc.subjectLatent Class Analysisen_US
dc.subjectPolymerase Chain Reactionen_US
dc.subject.classificationMicrobiologyen_US
dc.subject.classificationBiophysics--Medicalen_US
dc.titleOn the Optimization of Clostridioides difficile Diagnostics Through RT-PCR Cycle Threshold Defined Zones of Disease Probabilityen_US
dc.typemaster thesisen_US
thesis.degree.disciplineMedicine – Microbiology & Infectious Diseasesen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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