Recognizing uterine torsion as a differential diagnosis in pregnant cats with severe anemia to provide appropriate and timely care in the absence of a definitive presurgical diagnosis.
Bibliographic record
Abstract
A pregnant female domestic longhair cat ~8 mo of age was referred to the Western College of Veterinary Medicine (Saskatoon, Saskatchewan) for a diagnostic evaluation of severe anemia (PCV: 10.8%) after a 2-day period of lethargy. A CBC, serum biochemistry profile, FeLV/FIV testing, and abdominal radiographs were completed and did not determine a cause for the anemia. Abdominal ultrasonography identified 1 viable and 6 nonviable and fetuses, anechoic fluid in the uterus, and a mild volume of peritoneal effusion. A whole-blood transfusion and C-section with ovariohysterectomy were performed even though a definitive presurgical diagnosis for the anemia had not yet been established. Exploratory surgery revealed a left uterine horn torsion with a necrotic base, severe congestion, and 7 nonviable fetuses. Following surgery, the queen made a full clinical recovery. Key clinical message: Uterine torsion can be easily overlooked as a cause of severe anemia due to the relative infrequency of this condition in cats and the low sensitivity of ultrasonography to provide a definitive presurgical diagnosis. Client communication must emphasize the need for a prompt surgical intervention to establish the diagnosis and to save the cat, despite poor rates of neonatal survival. Once the animal is stabilized after surgery, further diagnostic tests and procedures are indicated if the cause of anemia has not yet been identified.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".