Evaluation of adding diltiazem therapy to standard treatment of acute renal failure caused by leptospirosis: 18 dogs (1998–2001)
Bibliographic record
Abstract
Abstract Objective:To assess efficacy and safety of intravenous (IV) diltiazem as a treatment for acute renal failure (ARF) secondary to leptospirosis in dogs. Design:Retrospective study Animals:Eighteen dogs with ARF caused byLeptospira spptreated during the months of September to December (1998–2001). Procedure:All dogs treated for ARF caused byLeptospira sppwere enrolled in the study and were treated with standard care consisting of IV fluids, +/− furosemide, and antibiotics. With owner consent some dogs were treated with diltiazem at 0.1–0.5 mg/kg (0.045–0.22 mg/lb) IV slowly, followed by 1–5 μg/kg/minutes (0.45–2.2 mg/lb/minutes) constant rate infusion. Outcome measures were compared between the 2 groups (diltiazemversusstandard). Diltiazem was administered within 60 hours of admission until serum creatinine fell into the normal range or stabilized. The primary outcome measurement of safety was systolic blood pressure (SBP). The primary measurement of efficacy outcome was the rate and magnitude of reduction of serum creatinine Results:Eleven out of 18 dogs received diltiazem. The rate of reduction in creatinine in the diltiazem group was 1.76 times faster than the standard group (P=0.054). Recovery of renal function showed a trend towards significant association with treatment group (exactP=0.08, odds ratio=3.62). This effect may be clinically relevant. Diltiazem had no clinically relevant effect on SBP. Conclusions and clinical relevance:Renal recovery in dogs with acute renal failure secondary to leptospirosis is improved with the administration of diltiazem in addition to ‘standard’ therapy.
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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 | 0.000 | 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".