Assessment of real-time PCR cycle threshold values in <i>Microsporum canis</i> culture-positive and culture-negative cats in an animal shelter: a field study
Bibliographic record
Abstract
Objectives Real-time PCR provides quantitative information, recorded as the cycle threshold (Ct) value, about the number of organisms detected in a diagnostic sample. The Ct value correlates with the number of copies of the target organism in an inversely proportional and exponential relationship. The aim of the study was to determine whether Ct values could be used to distinguish between culture-positive and culture-negative samples. Methods This was a retrospective analysis of Ct values from dermatophyte PCR results in cats with suspicious skin lesions or suspected exposure to dermatophytosis. Results One hundred and thirty-two samples were included. Using culture as the gold standard, 28 were true positives, 12 were false positives and 92 were true negatives. The area under the curve for the pretreatment time point was 96.8% (95% confidence interval [CI] 94.2-99.5) compared with 74.3% (95% CI 52.6-96.0) for pooled data during treatment. Before treatment, a Ct cut-off of <35.7 (approximate DNA count 300) provided a sensitivity of 92.3% and specificity of 95.2%. There was no reliable cut-off Ct value between culture-positive and culture-negative samples during treatment. Ct values prior to treatment differed significantly between the true-positive and false-positive groups ( P = 0.0056). There was a significant difference between the pretreatment and first and second negative culture time points ( P = 0.0002 and P <0.0001, respectively). However, there was substantial overlap between Ct values for true positives and true negatives, and for pre- and intra-treatment time points. Conclusions and relevance Ct values had limited usefulness for distinguishing between culture-positive and culture-negative cases when field study samples were analyzed. In addition, Ct values were less reliable than fungal culture for determining mycological cure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".