Ischemic Tolerance in Uremic Rabbits
Bibliographic record
Abstract
Background: Cardiac complications after myocardial infarction are believed to be worse in the presence of comorbidities; we tested whether experimentally induced prolonged uremia exacer-bated myocardial necrosis in a rabbit preparation of ischemia-reperfusion injury. In addition, we examined if treatment with an angiotensin converting enzyme inhibitor (Enalapril, ENA, 3 mg/Kg, IV) could reduce post-ischemic myocardial damage. Methods: Prolonged uremia was induced by a two-stage subtotal nephrectomy and confirmed by marked increases in serum creatinine and urea levels; after 5 weeks, four groups of rabbits were exposed to 45-min acute coronary occlusion followed by 180-min reperfusion. In treated animals, ENA was administered 5-min before onset of coronary reperfusion. All data from uremic animals were compared with time-matched controls. Results: Cardiac hemodynamics was similar for all groups during the development of kidney failure; heart rate in uremic rabbits was significantly lower for the duration of ischemia-reperfusion. In this animal model, the absence of coronary collateral circulation provides a stable ischemic substrate for evaluation of cellular necrosis. Infarct size (expressed as percent risk zone size) was: control, 48 ± 16; uremia, 36 ± 5; control + ENA, 51 ± 19; and uremia + ENA, 41 ± 16; risk zone size was similar for all animals. Conclusion: The present findings are inconsistent with the view that post-ischemic cardiac injury is greater in animals with pre-existent uremia. In addition, we were unable to show a significant beneficial effect with an angiotensin converting enzyme inhibitor on infarct size in either control or uremic rabbits. It remains to be proven in animal models with comorbidities such as manifest kidney disease that ischemic tolerance can be substantially reduced by either pharmacologic or non-pharmacologic interventions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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".