Anesthetic practice and pattern for total hip and knee replacement in Canada: a 5 year cross-sectional study
Bibliographic record
Abstract
Purpose: The objective of the study was to examine choice of anesthesia for total hip arthroplasty (THA) and total knee arthroplasty (TKA) in different provinces of Canada over a five-year period.bIn a retrospective, cross-sectional study, national data for patients undergoing THAs and TKAs between 1st April 2011 and 31st March 2016 was examined. The primary outcome was the anesthetic type used in the surgery, which was categorized as general, spinal, combined, or ‘other’. Total number and percentage of surgeries carried out using each anesthetic type were calculated per fiscal year, in non-teaching and TIs, in each Canadian province and territories, exclusive of Québec. Non-parametric statistics (Pearson Chi square tests) were used to compare the choice of anesthetic type by fiscal year and institution type.Results: During the study period, neuraxial anesthesia (NA) was used for 74.7% of all THAs and 80.3% of all TKAs nationwide. In NTIs, 76.2% of THAs and 80.5% of TKAs were carried out with NA. This trend was similar to that within teaching hospitals, where 73.1% of THAs and 80.6% of TKAs were carried out with NA. Interprovincial comparisons demonstrated a greater preference for NA for both THAs and TKAs in majority of the provinces. There were no significant differences in anesthetic choice between teaching and NTIs.Conclusion: Neuraxial anesthesia was the anesthesia of choice for THA and TKA during the entire study period in Canada, both in teaching and non-teaching institutions. During the study period, a majority of provinces showed a trend of increasing use of neuraxial anesthesia for both THA and TKA, with few exceptions.Citation: Pandey M, Johnson K, Siddiqui MA. Anesthetic practice and pattern for total hip and knee replacement in Canada: a 5 year cross-sectional study. Anaesth pain & intensive care 2019;23(3):301-310
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".