A Retrospective Study to Compare Early Outcomes of Bilateral Total Knee Replacement Done in Single Sitting versus Double Sitting
Bibliographic record
Abstract
Aim: We aimed to conduct a study comparing early outcomes of bilateral total knee replacement (BTKR) done in single sitting versus double sitting. Materials and Methods: The study included 58 patients who were already operated case of BTKR done in single sitting (sequential BTKR) – Group I ( n = 30) and double sitting (staged BTKR) – Group II ( n = 27), during time period April 2016 to May 2019. At follow-up, functional outcome in both the groups was assessed by Knee Injury and Osteoarthritis (OA) Outcome Score, Western Ontario and McMaster Universities OA Index score, and Visual Analog Scale scores. Results: The mean age in Group I was 64.5 ± 10.52 years and in Group II was 63.92 ± 5.76 years. The mean body mass index (BMI) in Group I was 28.42 ± 1.365 kg/m 2 , whereas the mean BMI in Group II was 29.19 ± 1.898 kg/m 2 . The mean length of hospital stay in Group I was 15.23 ± 2.921 days as compared to 23.69 ± 5.259 days in Group II. There was no mortality in both the groups within 90 days after operation in both the groups. There was significantly less requirement of hospital stay in Group I as compared to Group II ( P = 0.001, Mann–Whitney U -test). Conclusion: We found that the single sitting BTKR is cost-effective and a relatively safe surgery. There was significantly lower length of hospital stay in single sitting BTKR along with no major complication in our study. Thus we advocate BTKR as a single sitting surgery with proper patient selection and preanesthetic workup.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".