Causes and predictors of failed same-day home discharge following primary hip and knee total joint arthroplasty: a Canadian perspective
Bibliographic record
Abstract
Purpose: Same-day home (SDH) discharge in total joint arthroplasty (TJA) has increased in popularity in recent years. The objective of this study was to evaluate the causes and predictors of failed discharges in planned SDH patients. Methods: A consecutive cohort of patients who underwent total knee (TKA) or total hip arthroplasty (THA) that were scheduled for SDH discharge between 01 April 2019 and 31 March 2021 were retrospectively reviewed. Patient demographics, causes of failed discharge, perioperative variables, 30-day readmissions and 6-month reoperation rates were collected. Multivariate regression analysis was undertaken to identify independent predictors of failed discharge. Results: The cohort consisted of 527 consecutive patients. 101 (19%) patients failed SDH discharge. The leading causes were postoperative hypotension (20%) and patients who were ineligible for the SDH pathway (19%). 2 individual surgeons, later operative start time (OR 1.3; 95% CI, 1.15–1.55; p = 0.001), ASA class IV (OR 3.4; 95% CI, 1.4–8.2; p = 0.006) and undergoing a THA (OR 2.0; 95% CI, 1.2–3.1, p = 0.004) were independent predictors of failed SDH discharge. No differences in age, BMI, gender, surgical approach or type of anaesthetic were found ( p > 0.05). The 30-day readmission or 6-month reoperation were similar between groups ( p > 0.05). Conclusions: Hypotension and inappropriate patient selection were the leading causes of failed SDH discharge. Significant variability existed between individual surgeons failed discharge rates. Patients undergoing a THA, classified as ASA IV or had a later operative start time were all more likely to fail SDH discharge.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".