Investigation of a Commercial ELISA for the Detection of Canine Procalcitonin
Bibliographic record
Abstract
BACKGROUND: Rapid identification of sepsis enables prompt administration of antibiotics and is essential to improve patient survival. Procalcitonin (PCT) is a biomarker used to diagnose sepsis in people. Commercial assays to measure canine PCT peptide have not been validated. OBJECTIVE: To investigate the validity of a commercially available enzyme-linked immunosorbent assay (ELISA) marketed for the measurement of canine PCT. ANIMALS: Three dogs with sepsis, 1 healthy dog, 1 dog with thyroid carcinoma. METHODS: Experimental study. The ELISA's ability to detect recombinant and native canine PCT was investigated and intra-assay and interassay coefficients of variability were calculated. Assay validation including mass spectrometry of the kit standard solution was performed. RESULTS: The ELISA did not consistently detect recombinant canine PCT. Thyroid lysate yielded a positive ELISA signal. Intra-assay variability ranged from 18.9 to 77.4%, while interassay variability ranged from 56.1 to 79.5%. Mass spectrometry of the standard solution provided with the evaluated ELISA kit did not indicate presence of PCT. CONCLUSIONS AND CLINICAL IMPORTANCE: The results of this investigation do not support the use of this ELISA for the detection of PCT in dogs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".