ESRA19-0218 ‘Fast-track’ patients to phase II recovery and decrease pacu duration in ambulatory arthroscopic shoulder surgery with combined peripheral nerve block and monitored anesthesia care
Bibliographic record
Abstract
Background and aims An estimated 460,000 rotator cuff surgeries are performed in the United States annually.1 We commonly perform these ambulatory arthroscopic shoulder surgeries (AASS) using a combination of an Interscalene block and superficial cervical plexus block under monitored anesthesia care (MAC). Our objective was to investigate how a change in anesthesia practice for AASS has impacted on the duration of PACU stay, and the ability to ‘fast-track’ patients to Phase II recovery, directly from the operating room. Methods A 6-year retrospective electronic chart review was performed (OHSN-REB ethical approval) including all AASS at the Riverside Campus, the Ottawa Hospital from 01 January 2012 to 31 December 2107. Data were collected on type of anesthesia; general anesthesia (GA), GA and peripheral nerve block (PNB) or MAC and PNB, Phase I recovery duration (PACU) and the number of direct admissions to Phase II recovery. Results 882 AASSs were performed in total from 2012 to 2017 (figure 1). the number of surgeries performed under MAC and PNB increased each year from 4 in 2012 to 195 in 2017. the direct admission rate to Phase II recovery increased from 0 in 2012 to 85 in 2017 (figure 2). the Phase I recovery (PACU) duration decreased from 72 minutes in 2012 to 41 minutes in 2017 (figure 3). Conclusions This retrospective data collected, demonstrated how a change in anesthesia practice from GA and PNB to MAC and PNB reduced Phase I recovery duration and increased direct admission rate to Phase II recovery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".