Use of Electrohydraulic Lithotripsy in 28 Dogs with Bladder and Urethral Calculi
Bibliographic record
Abstract
BACKGROUND: Electrohydraulic lithotripsy (EHL) has been used as an alternative to cystotomy in human medicine to remove urinary calculi. This prospective study evaluated the efficacy and safety of EHL to remove urinary calculi in dogs. HYPOTHESIS: EHL is an efficient and safe method of treatment of bladder and urethral calculi in dogs. METHODS: Dogs presented between January 1, 2005 and June 1, 2007 with lower urinary tract calculi diagnosed by radiographs or ultrasound examination were included in the study. Physical examination, CBC, biochemistry, urinalysis, and urine culture were performed at presentation. EHL and voiding urohydropulsion were performed under general anesthesia. Patients received IV fluids for 12 hours after which they were rechecked by ultrasound examination and discharged with antibiotics and anti-inflammatory drugs for 5 days. All patients were reevaluated 1, 3, and 6 months after presentation by physical examination, urinalysis, and ultrasonography. RESULTS: Twenty-eight dogs (19 males, 9 females) presented with bladder or urethral calculi or both underwent lithotripsy. Their median weight was 8.3 kg. Calcium oxalate calculi were present in 22 dogs, struvite in 4, and mixed calculi in 2. Fragmentation was done in the bladder (23 dogs) and in the urethra (12 dogs). Calculus-free rate was higher for urethral than for bladder calculi in males and higher for bladder calculi in females than in males. No major complications were reported. Twelve dogs relapsed within 6 months. CONCLUSIONS: Results of this study support the use of EHL as a minimally invasive treatment for bladder calculi in females and for urethral calculi in male dogs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".