Comparison of surgical versus medical treatment of nephrosplenic entrapment of the large colon in horses: 19 cases (1992–2002)
Bibliographic record
Abstract
OBJECTIVE: To compare the outcome of horses with nephrosplenic entrapment of the large colon (NSELC) treated surgically or medically by rolling, administration of phenylephrine hydrochloride (or both), and exercise. DESIGN: Retrospective study. ANIMALS: 11 medically treated horses and 8 surgically treated horses with NSELC. PROCEDURE: Medical records of horses with nephrosplenic entrapment between 1992 and 2002 were reviewed. Medically treated horses were included if diagnosis and outcome of treatment of nephrosplenic entrapment were confirmed via transrectal examination and ultrasonographic examination. Surgically treated horses were included if the diagnosis was confirmed by exploratory laparotomy. Horses in which the large colon was entrapped between the spleen and body wall were not included. RESULTS: Significant differences in mean age, heart rate, and duration of colic prior to treatment were not detected between horses treated surgically or medically. Ten medically treated horses recovered without complications, and 1 died. In the surgically treated group, 6 of 8 horses recovered without complications and 2 died. Mortality rate did not differ between treatments. Duration of hospitalization for medically treated horses was significantly shorter and the cost significantly less than for surgically treated horses. CONCLUSIONS AND CLINICAL RELEVANCE: Results indicated that medical treatment of horses with NSELC via administration of phenylephrine hydro-chloride, rolling during general anesthesia, or both appears to be as effective as and less expensive than surgical treatment.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".