Serial analysis of blood biomarker concentrations in dogs with pneumonia, septic peritonitis, and pyometra
Bibliographic record
Abstract
BACKGROUND: Prolonged antimicrobial drug (AMD) treatment is associated with antimicrobial resistance development. Biomarker measurement may aid treatment decision-making. OBJECTIVES: Investigate temporal changes in blood biomarker concentrations in dogs undergoing treatment for pulmonary and intra-abdominal infections; compare time to biomarker concentration normalization with duration of clinician-directed AMD treatment. ANIMALS: Forty-two client-owned dogs with pneumonia (n = 22), septic peritonitis (n = 10), or pyometra (n = 10). METHODS: Plasma concentrations of C-reactive protein (CRP), serum amyloid A (SAA), haptoglobin, procalcitonin, nucleosomes, cell-free DNA (cfDNA), high-mobility group box-1 (HMGB1), CC-motif chemokine ligand-2 (CCL2), CXC-motif chemokine ligand-8 (CXCL8), and keratinocyte chemoattractant-like (KC-Like) were quantitated in samples collected on days 1, 3, 7, 14, 28, and 60. Treatment was directed by clinicians blinded to biomarker concentrations. RESULTS: Concentrations of CCL2, CRP, and KC-Like were maximal on D1, concentrations of SAA, cfDNA, HMGB1, and nucleosomes were maximal on D3 and haptoglobin concentrations were maximal on D7. These maximal concentrations were significantly different from those on D60. Concentrations of CRP and SAA decreased by 80% from peak and into respective reference intervals before AMDs were discontinued. For CRP, the median (interquartile range [IQR]) times to 20% peak and normal were 7 (6-9) and 7 (6-12) days, respectively, and for SAA they were 4 (4, 5) and 6 (5-8) days, respectively, compared to a median (IQR) duration of AMD prescribing of 16 (12-23) days (all P < .0001). CONCLUSIONS AND CLINICAL IMPORTANCE: Biomarker concentrations normalized within 7 to 14 days. Serial measurements of CRP and SAA might aid identification of disease resolution and could help guide AMD prescription decision-making.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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 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".