Disclosure of Risks Associated With Regional Anesthesia: A Survey of Academic Regional Anesthesiologists
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In view of the relatively few large studies available to estimate the rates of complications following regional anesthesia, we aimed to identify and quantify the risks that academic regional anesthesiologists and regional anesthesia fellows disclose to their patients before performing central and peripheral nerve blockade. METHODS: We asked 23 North American regional anesthesia fellowship program directors to distribute a questionnaire to the regional anesthesiologists and regional anesthesia fellows at their institutions. The questionnaire was designed to capture the risks and corresponding incidences that are routinely disclosed to patients before performing the most common central and peripheral nerve block techniques. RESULTS: The total number of respondents was 79 from 12 different institutions. Fifty-eight (74%) respondents disclose risks of regional anesthesia in order to allow their patients to make an informed choice, whereas 20 (26%) disclose risks for medicolegal reasons. For central neural blockade, the most commonly disclosed risks are headache, local pain/discomfort, and infection. For peripheral nerve blockade, the most commonly disclosed risks are transient neuropathy, local pain/discomfort, and infection. For both central and peripheral nerve blockade, the risks most commonly disclosed are also those with the highest-reported incidences. CONCLUSIONS: The risks of regional anesthesia most commonly disclosed to patients by academic regional anesthesiologists and regional anesthesia fellows are benign in nature and occur frequently. Severe complications of regional anesthesia are far less commonly disclosed. The incidences of severe complications disclosed by academic regional anesthesiologists and their fellows can be inconsistent with those cited in the contemporary literature.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".