Significant cost savings and similar patient outcomes associated with early discharge following total knee arthroplasty
Bibliographic record
Abstract
Background: A substantial portion of the cost of total knee arthroplasty (TKA) results from the postoperative inpatient length of stay (LOS). Considering the annual increase in TKAs, reducing LOS represents a potential for cost savings. We sought to compare in-hospital costs and patient-reported outcomes for an early discharge protocol compared with the standard LOS following TKA. Methods: We conducted a retrospective matched cohort study, matching patients on age, sex, body mass index and preoperative Western Ontario & McMaster Universities Osteoarthritis Index (WOMAC) score. We compared costs associated with time in the operating room, intraoperative pain control and inpatient stay as well as 1-year postoperative patient-reported outcomes between early discharge and standard LOS groups. Results: We included 50 patients in our study (25 per group). The average LOS in the early discharge group was 26.5 hours, compared with 48.9 hours in the standard care group. The early discharge group had higher intraoperative costs associated with pain control (mean difference 26.98, 95% confidence interval 14.41–37.90, p < 0.01); however, this difference was offset by substantial savings associated with the reduced LOS. The mean total cost for the early discharge group was $649.62 ± $281.71 versus $1279.71 ± $515.98 for the standard care group. There were no significant differences in SF12 or WOMAC scores between groups at 1 year postoperative. Conclusion: In-hospital costs were significantly lower with a postoperative day 1 discharge protocol than with standard LOS following TKA, with no difference in patient-reported outcomes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".