Bone Resorption Markers and Dual‐Energy<scp>X</scp>‐Ray Absorptiometry in Dogs with Avascular Necrosis, Degenerative Joint Disease, and Trauma of the Coxofemoral Joint
Bibliographic record
Abstract
OBJECTIVES: To compare the ability of N-terminal telopeptide (NTx) assays and dual-energy x-ray absorptiometry (DEXA) to detect bone resorption in dogs with nonneoplastic bone lysis and evaluate the correlation between these diagnostic tools. STUDY DESIGN: Prospective, cross-sectional clinical study. ANIMALS: Dogs (n = 35; 39 femoral heads) that had femoral head and neck ostectomy and 6 cadaver specimens from healthy immature small dogs. METHODS: Small dogs with avascular necrosis (n = 12), a reference group of small dogs (7), large dogs with degenerative joint disease (DJD; 10), and large dogs with trauma (10) were studied in addition to 6 femoral heads harvested from 6 small immature and healthy dogs euthanatized for reasons unrelated to this study. Densitometric measurements of femoral heads, urine NTx excretion, and serum NTx concentration were compared between groups. RESULTS: Avascular necrosis resulted in a decrease in bone mineral density (BMD) (0.18 ± 0.01 g/cm(2;) P < .01) of the femoral head and elevation of serum NTx (159.3 ± 59.4 nM; P = .03) compared to small dog controls (0.28 ± 0.02 g/cm(2) ; 18.7 ± 1.83 nM, respectively), but did not seem to affect urine NTx. DJD in large dogs did not seem to affect any of the densitometric parameters evaluated. BMD (P = .03) and serum NTx (P = .04) were lower in small compared to large dogs. Serum NTx and densitometric measurements correlate inversely with each other (P = .001) but neither test correlated with urine NTx (P = .8-.9). CONCLUSION: Serum NTx levels vary with dog size but seem to correlate better with BMD better than urine NTx excretion in dogs with nonneoplastic bone resorption.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".