Management of the articular degenerative disease of the dog: comparison of physical and pharmacological therapies.
Bibliographic record
Abstract
Degenerative Joint Disease (DJD) is one of the most common and disabling orthopaedic conditions of pets. The most recent therapeutic approach consists in the combination of different therapeutic options, such as the use of conventional drugs, the use of alternative treatments (i.e. homeopathy, phytotherapy, acupuncture), the oral administration of chondroprotectors (i.e. nutraceuticals), body weight control, rehabilitation and correct home management. This study compared the efficacy on arthritic pain control of a physical therapy protocol, including MLS® treatment and hydrotherapy, versus traditional nonsteroidal anti-inflammatory drug (NSAID) therapy. Sixteen Labrador dogs, older than 5 years and affected by osteoarthritis have been included in the study. After the baseline visit, the animals matching inclusion criteria have been allocated to one of the treatment groups. The treatment efficacy has been assessed at 15 and 45 days via pet owner’s evaluation, using the Liverpool Osteoarthritis in Dogs (LOAD) and the Canine Brief Pain Inventory (CBPI), and by the clinical assessment of a technical expert. In both groups, a general improvement in symptoms has been observed, confirming that both physical therapy with MLS® and drug therapy are valuable aids in the management of pain symptoms associated with degenerative joint disease. In particular, for the treatment of ostearthrosis, when long term treatments are necessary, MLS® laser therapy is a valid alternative to pharmacological therapy, allowing for treating old dogs without worsening the condition of other compromised organs.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".