Epidural Analgesia in Cardiac Surgery: An Updated Risk Assessment
Bibliographic record
Abstract
INTRODUCTION: The use of epidural anesthesia carries risks that have been known for 50 years. The debate about the use of locoregional technique in cardiac anesthesia continues. The objective of this report is to estimate the risks and their variability of a catheter-related epidural hematoma in cardiac surgery patients and to compare it with other anesthetic and medical procedures. METHODS: Case series reporting the use of epidural anesthesia in cardiac surgery were researched through Medline. Additional references were retrieved from the bibliography of published articles and from the internet. Risks of complications in other anesthetic and medical activity were retrieved from recent reviews. RESULTS: Based on the present evidence, the risk of epidural hematoma in cardiac surgery is 1:12,000 (95% CI of 1:2100 to 1:68,000), which is comparable to the risk in the nonobstetrical population of 1:10,000 (95% CI 1:6700 to 1:14,900). The risk of epidural hematoma is comparable to the risk of receiving a wrong blood product or the yearly risk of having a fatal road accident in Western countries. CONCLUSIONS: The risk of a hematoma after epidural in cardiac surgery is comparable to other nonobstetrical surgical procedures. Its routine application in a controlled setting should be encouraged.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".