High efficiency pathway for lower limb orthopedic surgery: A matched historic cohort study
Bibliographic record
Abstract
BACKGROUND In 2017, our institution implemented a high efficiency (HE) pathway for lower limb orthopedic surgery. The employed strategy included patient selection, surgical instrument standardization, preoperative surgical nerve blocks, avoidance of general anesthesia and bypassing phase one recovery. We conducted a historic cohort study whose primary outcome was the postoperative recovery time between the HE and traditional (T) pathway. AIM To determine whether the implementation of a HE pathway was correlated with a reduction in postoperative recovery time. METHODS Patients who had unilateral elective lower limb orthopedic procedures through the T and HE pathway were screened between 2017 to 2019. Patients were at least 18 years old, and American Society of Anesthesiologists (ASA) Physical Status I to III without major systemic comorbidities were included. Propensity score was generated using multivariable regression taking age, body mass index, sex, ASA class and surgical type as covariates using nearest neighbour methods between the two pathways. Mann Whitney U test were used to analyzed total postoperative time. RESULTS There was an associated reduction in total postoperative recovery time of 63 minutes (95%CI: -69 to –57) in the HE group. The operating room time and total length of stay also had an associated decrease of 20 minutes (95%CI: -23 to -17) and 84 minutes (95%CI: -92 to -75) respectively. CONCLUSION Utilizing multifaceted strategies to improve perioperative efficiency was associated with a reduction in the postoperative recovery time in our retrospective study. This model can be a potential strategy to deal with surgical backlog in the face of ongoing human resource challenges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".