High Spinal Anesthesia Enhances Anti-Inflammatory Responses in Patients Undergoing Coronary Artery Bypass Graft Surgery and Aortic Valve Replacement: Randomized Pilot Study
Bibliographic record
Abstract
BACKGROUND: Cardiac surgery induces many physiologic changes including major inflammatory and sympathetic nervous system responses. Here, we conducted a single-centre pilot study to generate hypotheses on the potential immune impact of adding high spinal anaesthesia to general anaesthesia during cardiac surgery in adults. We hypothesized that this strategy, previously shown to blunt the sympathetic response and improve pain management, could reduce the undesirable systemic inflammatory responses caused by cardiac surgery. METHODS: This prospective randomized unblinded pilot study was conducted on 14 patients undergoing cardiac surgery for coronary artery bypass grafting and/or aortic valve replacement secondary to severe aortic stenosis. The primary outcome measures examined longitudinally were serum pro-inflammatory (IL-6, IL-1b, CCL2), anti-inflammatory (IL-10, TNF-RII, IL-1Ra), acute phase protein (CRP, PTX3) and cardiovascular risk (sST2) biomarkers. RESULTS: The kinetics of pro- and anti-inflammatory biomarker was determined following surgery. All pro-inflammatory and acute phase reactant biomarker responses induced by surgical stress were indistinguishable in intensity and duration between control groups and those who also received high spinal anaesthesia. Conversely, IL-10 levels were markedly elevated in both intensity and duration in the group receiving high spinal anesthesia (p = 0.005). CONCLUSIONS: This hypothesis generating pilot study suggests that high spinal anesthesia can alter the net inflammatory response that results from cardiac surgery. In appropriately selected populations, this may add incremental benefit by dampening the net systemic inflammatory response during the week following surgery. Larger population studies, powered to assess immune, physiologic and clinical outcomes in both acute and longer term settings, will be required to better assess potential benefits of incorporating high spinal anesthesia. TRIAL REGISTRATION: ClinicalTrials.gov NCT00348920.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".