Unravelling pain in Göttingen Minipigs undergoing experimentally induced closed-chest myocardial infarction: a prospective cohort study
Bibliographic record
Abstract
The pain associated with experimental myocardial infarction in pigs has never been investigated. We aimed at assessing pain and its correlation with myocardial damage. Twenty-four Göttingen minipigs undergoing closed chest myocardial infarction followed by coronary reperfusion under general balanced anaesthesia were included in the trial. Pain was assessed through mechanical and thermal thresholds, sensitivity to Von Frey filaments and behavioural indicators before (Pre MI), the day after (Post MI) and at the study endpoint (Post MI-endpoint). Over time differences in mechanical thresholds (MT) and thermal thresholds (TT) were assessed using one-sample t-test and their correlations with troponin I/cytokines using logistic regression. In four minipigs at Post MI acute pain requiring analgesia was identified. Pain thresholds decreased significantly at Post MI (MT: 51 [35.6; 74] TT: 44.8 [42.7; 48.7]) and Post MI-endpoint (MT: 47.5 [35; 64.3]; TT: 44.3 [43.1; 48.6]) compared to Pre MI (MT: 72 [53.4; 84], TT: 46.3 [43.8; 53.8]). The response to von Frey filaments remained sporadic. Troponin I highly increased at Post MI, but no correlations with pain thresholds were found. Following balanced anaesthesia, acute pain had low incidence and mild to moderate intensity. Somatic hyperalgesia remained until the study endpoint, but its relevance remains to be unravelled.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".