Perioperative risk factors for puppies delivered by cesarean section in the United States and Canada
Bibliographic record
Abstract
The purpose of this study was to evaluate perioperative risk factors affecting neonatal survival after cesarean section. Data from 807 cesarean-derived litters (3,908 puppies) was submitted by 109 practices in the United States and Canada. Survival rates immediately, two hours, and seven days after delivery were 92% (n=3,127), 87% (n=2,951), and 80% (n=2,641), respectively, for puppies delivered by cesarean section (n=3,410) and were 86% (n=409), 83% (n=366), and 75% (n=283), respectively, for puppies born naturally (n=498). Maternal mortality rate was 1% (n=9). Of 776 surgeries, 453 (58%) were done on an emergency basis. The most common breed of dog was bulldog (n=138; 17%). The most common methods of inducing and maintaining anesthesia were administration of isoflurane for induction and maintenance (n=266; 34%) and administration of propofol for induction followed by administration of isoflurane for maintenance (n=237; 30%). A model of cesarean-derived puppies surviving to birth, between birth and two hours, and between two hours and seven days was designed to relate litter survival to perioperative factors. The following factors increased the likelihood of all puppies being alive: the surgery was not an emergency; the dam was not brachycephalic; there were four puppies or less in the litter; there were no naturally delivered or deformed puppies; all puppies breathed spontaneously at birth; at least one puppy vocalized spontaneously at birth; and neither methoxyflurane nor xylazine was used in the anesthetic protocol.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".