Survival and prognostic indicators in downer dairy cows presented to a referring hospital: A retrospective study (1318 cases)
Bibliographic record
Abstract
BACKGROUND: Downer cow syndrome, a common problem in dairy cattle, represents a diagnostic and therapeutic challenge for the attending veterinarian. Identifying prognostic indicators and assessing the odds of survival may improve the accuracy of the clinician's prognosis at the time of diagnosis. OBJECTIVE: To describe a population of downer dairy cows referred to a hospital and investigate predictors of outcome. ANIMALS: Recumbent adult dairy cows (cows unable or unwilling to stand without help) treated at a referral hospital. METHODS: Data at the time of admission were collected from medical records of downer dairy cows treated at the Centre Hospitalier Universitaire Vétérinaire between 1994 and 2016. Simple and multivariable logistic regression analyses were performed to assess the association of predictors with the outcome. RESULTS: Among 1318 cows included, 727 (55%) cows were discharged, and 591 (45%) cows died or were euthanized. Cows with longer time of recumbency before referral (odds ratio [OR] = 3.6), tachycardia (100-120 beats per minute [bpm], OR = 1.93; >120 bpm, OR = 2.92), tachypnea (OR = 1.76), hypothermia (OR = 2.08), anemia (OR = 3.30), neutropenia (OR = 1.7), high aspartate aminotransferase activity (500-1000 U/L, OR = 2.16; >1000 U/L, OR = 6.69), and increased serum creatinine concentration (OR = 1.75) had higher odds of nonsurvival. CONCLUSIONS AND CLINICAL IMPORTANCE: These findings may help the practitioner to consider treatment options and decide if referral is likely beneficial based on the odds of success. Early recognition of low chance of survival may facilitate an early decision for euthanasia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".