Blood and Peritoneal Lactate, Ratio and Difference, and Peritoneal Lactate to Total Solids Ratio for Detection of Intestinal Strangulating Obstructions in Horses
Bibliographic record
Abstract
BACKGROUND: The effectiveness of the peritoneal fluid L-lactate-to-total solids ratio (PFL:PFTS) as a diagnostic marker for strangulating lesions of the small intestine (SI) and large colon (LC) has not been investigated. OBJECTIVES: Describe and compare the PFL:PTFS and blood lactate (BL), peritoneal fluid lactate (PFL) and PFL:BL difference and PFL:BL ratio of horses with SI and LC strangulating (SO) and non-strangulating (NSO) obstructions and determine sensitivity and specificity to predict SO. ANIMALS: A total of 282 horses, 117 with SI lesions (59 classified as SINSO and 58 as SISO), and 165 with LC lesions, 126 categorized as LCNSO and 39 as LCSO. METHODS: Retrospective study. Receiver operating characteristic (ROC) curves were generated to identify optimal cut-off points to maximize sensitivity and specificity to predict SO. RESULTS: A PFL:PFTS ratio of 2.9 had fair (area under the curve [AUC], 0.76; 95% confidence interval [CI], 0.67-0.84) ability to discriminate between SISO and SINSO, with sensitivity of 66.7% and specificity of 78.3% to predict SISO. A PFL: PFTS ratio of 3.6 had good ability to discriminate between LCSO and LCNSO (AUC, 0.84; 95% CI, 0.78-0.90) with sensitivity and specificity of 78% and 81% to predict LCSO, respectively. Peritoneal fluid lactate, PFL:BL difference, and PFL:BL ratio also had a low to moderate sensitivity to predict ischemic strangulating lesions of the SI and LC. CONCLUSION AND CLINICAL IMPORTANCE: Strangulating obstructions are critical conditions requiring prompt intervention. The low to moderate sensitivity identified suggests that PFL, PFL:BL difference and ratio, and PFL:PFTS ratio should be interpreted with clinical signs and the response to initial treatment to determine SO accurately.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".