The Definition of Block “Success” in the Contemporary Literature
Bibliographic record
Abstract
A successful nerve block is the common goal that shapes modern regional anesthesia practice and research, yet the meaning of block "success" can be open to interpretation. For this Special Article, we reviewed all applicable randomized controlled trials published over the last decade to determine the most commonly used definitions of block success. We also sought to uncover which relevant indicators of block success are routinely reported in the contemporary literature. Twenty-two trials that explicitly designated the term block "success" as their primary outcome measure were identified. The most common definition of block success was the achievement of a surgical block within a designated period, used in half of the trials. Block success was inconsistently defined in the remaining 11 trials. Patient-related indicators of block success including postoperative pain and patient satisfaction were measured in only 4 trials, whereas anesthesiologist-related indicators such as block onset time and complications were reported most frequently. Surgeon- and hospital administrator-related indicators were not collected in any trial. We found that the definition of block success is highly variable in the contemporary regional anesthesia literature. Our findings underscore the clear and present need for a comprehensive definition of block success, whereas future research should endeavor to capture the indicators of block success that are important to all key perioperative stakeholders.
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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 | 0.028 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".