Prognostic indicators at presentation for canine parvoviral enteritis: 322 cases (2001‐2018)
Bibliographic record
Abstract
OBJECTIVE: To evaluate clinicopathological prognostic indicators associated with survival based on hematology and serum biochemistry profile findings at presentation of dogs with canine parvoviral enteritis (CPE). Secondary objectives were to describe the signalment, history, physical examination findings, and progression of disease while in hospital and correlate them to survival. DESIGN: Retrospective study from medical records of dogs diagnosed with CPE between 2001 and 2018. SETTING: University teaching hospital. ANIMALS: Three hundred twenty-two dogs diagnosed with CPE that received in-hospital treatment. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 322 hospitalized dogs, 294 dogs (91%) survived infection with a median hospitalization time of 79 hours. Multivariable analysis showed that glucose (P = 0.04), total magnesium (P = 0.011), and the dichotomized variable of a low HCT (P = 0.033) on presentation were significantly associated with survival. For every 1 mmol/L (18 mg/dL) decrease in glucose concentration, cases had 1.85 lower odds of survival. For every 0.1 mmol/L (0.2 mEq/L) increase in total magnesium concentration, cases had 2.50 lower odds of survival. Cases with a low HCT had 10.69 lower odds of survival. On univariable analyses, non-survivors had a lower median body weight (P = 0.006) and presented more commonly for diarrhea (P = 0.015). At least 1 episode of diarrhea (P = 0.003) and hematochezia or melena (P < 0.001) in hospital were negatively associated with outcome, in addition to the persistence of diarrhea (P = 0.026) and hyporexia (P = 0.018) in hospital for 5 to 6 days. CONCLUSIONS: Survival rates of 91% were achieved with in-hospital treatment in this cohort of dogs. Negative biochemical prognostic indicators affecting survival include a low HCT, decreased blood glucose concentrations, and increased total serum magnesium concentrations at presentation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".