SENSITIVITY AND SPECIFICITY OF RADIOGRAPHIC DETECTION OF CANINE ELBOW INCONGRUENCE IN AN IN VITRO MODEL
Bibliographic record
Abstract
Canine elbow incongruence is believed to be the consequence of underdevelopment of the radius. The purpose of this study is to determine the sensitivity and specificity of radiography to detect elbow incongruence in an in vitro model and to assess the optimal elbow angle and radiographic beam position. Five normal cadaveric canine left forelimbs were used. A four-pin, type 1 external fixator with a linear motor side bar was fixed to the cranial part of the radius of each limb and a 1 cm segment of bone was removed from the mid-diaphysis to allow radial shortening. Each elbow was subjected to the same protocol. They were radiographed at two different angles (90 degrees and 135 degrees) of flexion, with 10 different radiographic beam positions (centered on the humeral condyle, 3 cm cranial, 3 cm caudal, 3 cm distal, 3 cm proximal, 3 cm cranio-proximal, 3 cm cranio-distal, 3 cm caudo-proximal, 3 cm caudo-distal and on the shoulder joint) and at four different level of radial shortening (0, 1, 2 and 3 mm). In addition, a radiographic view centered on the elbows flexed at 135 degrees was made after simulating weight bearing. The acquired digital images were independently evaluated by three evaluators unaware of the elbows status. The elbows were judged normal, incongruent or borderline based on specific criteria. The sensitivity for detection of elbow incongruence at and beyond 2 mm was excellent at 90 degrees (median = 100% for all views) and good at 135 degrees (median = 80%) of flexion with no difference between examiners. The sensitivity at 1 mm of incongruence was unchanged at 135 degrees but was reduced at 90 degrees of flexion (median = 60%) with a significant difference between the evaluators. The specificity was significantly different between the evaluators and ranged from 70% to 90% at 90 degrees of flexion and from 50% to 80% at 135 degrees. The lowest specificities at 90 degrees were obtained with the proximal displacements of the X-ray beam. Simulating weight bearing significantly decreased the sensitivity at 1 mm (from 80% to 50%) and 3 mm (from 100% to 80%) of incongruence and slightly increased the specificity (from 55% to 65%). Radiography is a sensitive and specific test to detect moderate-to-severe radio-ulnar incongruence (2 mm and over) if the elbow is flexed at a 90 degrees angle regardless of the radiographic beam position. Finally, canine elbow incongruence appeared reduced after an in vitro weight-bearing simulation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".