2 Physiological response to adenosine and splenic switch off
Bibliographic record
Abstract
Introduction Cardiac magnetic resonance perfusion studies require a patient to be ‘adequately’ physiologically stressed to ensure reliable data. The principle aim of this study was to investigate the assumption that the standard adenosine dose (140mcg/kg/min) achieves this stress. A secondary aim was to investigate splenic switch off (SSO), this has recently been reported as a marker of adequate response to adenosine. Methods An adequate stress response was defined as >20% increase in heart rate (HR) plus >3/5 symptom discomfort (5-?point scale). Three separate adenosine infusion protocols were trialled, depending on patient physiological responses. Protocol A: 140 mcg/kg/min for 4mins. Protocol B: 140 mcg/kg/min for 2mins then 210mcg/kg/min for 2mins. Protocol C: 140?mcg/kg/min for 2mins then 210?mcg/kg/min for 4mins. After exclusion of studies that were “off-protocol”, 67 studies were eligible. Splenic enhancement was assessed using CMR42 (Circle CVI, Calgary, Canada) software, creating regions of interest. Significance (P<0.05) was determined using Two-sample T-tests and ANOVAs. Results No significant differences were observed between protocols considering HR response, symptom severity or splenic enhancement. 3 distinct splenic responses were revealed. The ten best enhancing spleens were similar to blood pool whilst the ten lowest resembled SSO. These three subgroups of splenic enhancement showed no correlation to HR or symptom response. Conclusions We would recommend the described adenosine protocol as a consistent way of overcoming poor responses. In terms of SSO, sub group analysis of splenic enhancement shows it is unrelated to HR or symptomatic response, suggesting SSO may not reflect vasodilator stress.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".