The Interval Between Staged Bilateral Total Knee Arthroplasties Does Not Affect Early Complications of the Second Knee or Long-term Function of the First and Second Knees
Bibliographic record
Abstract
Abstract Background: This study explored the optimal time interval between staged bilateral total knee arthroplasty (BTKA) to minimise early complications of the second TKA and maximise long-term function of the first and second knees.Methods: We retrospectively reviewed 266 patients who underwent staged BTKA between 2010 and 2015. Groups 1–4 had time intervals between BTKAs of 1–6, 6–12, 12–18, and 18–24 months, respectively. Demographics, postoperative complications within 90 days of the second TKA, Knee Society Score (KSS), and Western Ontario and McMaster Universities Arthritis Index (WOMAC) score were compared among the groups.Results: In total, 54, 96, 75, and 41 patients were assigned to groups 1–4, respectively. Although group 1 had the highest overall complication rate (11.11%), there was no significant difference in the complication rate among the four groups. Also, no significant differences were found among the four groups in functional and patient-reported outcomes, in either the first or second knee at 5 years postoperatively, including KSS-knee, KSS-function, WOMAC-pain, WOMAC-stiffness, and WOMAC-physical function. The interval between BTKA did not influence complications or the function of the second knee. The TKA type (posterior-stabilised vs. medial-pivot) and age did not correlate significantly with any scores.Conclusions: There was no group difference in early complications of the second TKA, and postoperative function was equivalent between the two knees and did not vary by the interval between surgeries. Our results can help surgeons discuss the timing of the second TKA with patients, which should be based on their own preferences. If patients cannot tolerate severe symptoms in the contralateral knee after the first TKA, the second TKA should be performed as early as possible.
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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 | 0.000 |
| 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".