Predicting Orthopedic Surgeons’ Preferences for Peripheral Nerve Blocks for Their Patients
Bibliographic record
Abstract
BACKGROUND: A 2002 survey of 468 Canadian orthopedic surgeons found that the "two principal reasons regional anesthesia is not favored" are "delays in operating rooms" and "unpredictable success." We reanalyzed the data from the study to evaluate whether these concerns were the best predictors of an individual surgeon's willingness to use peripheral nerve blocks for their patients. METHODS: Of the five procedures included in the survey, three had relevant questions for our reanalysis of the results: arthroscopic shoulder surgery, arthroscopic anterior cruciate ligament reconstruction, and total knee replacement. RESULTS: A surgeon's preference for peripheral nerve block for him or herself strongly predicted his or her anesthetic preference for patients (all P < 0.001). Concordance rates were 89% for arthroscopic shoulder surgery, 87% for anterior cruciate ligament reconstruction, and 93% for total knee replacement. There was almost no incremental predictive value for the surgeon's preference for patients from the surgeon's perception of the times to perform a block (P > or = 0.27) or perception of block success rate (P > or = 0.30). There was also almost no direct predictive value for the surgeon's preference for patients from the surgeon's perception of the times to perform a block (Kendall's tau < or = 0.04, P > or = 0.28) or perception of block success rate (Kendall's tau < or = 0.02, P > or = 0.24). An economically important percentage of surgeons (37%, 95% confidence interval: 32%-41%) would choose a peripheral nerve block for their own surgery for some, but not all, of the procedures (i.e., for 1 or 2 versus 0 or 3). CONCLUSIONS: A surgeon's preference for peripheral nerve blocks for his or her own surgery predicted a surgeon's preference for his or her patients. Perceptions of delays and success rate did not add sufficient incremental information to the surgeon's preferences to be of economic importance. These results are important to better forecast the net economic impact on an anesthesia group of a regional block team.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".