The Outcome of Total Knee Arthroplasty for Patients with Psychiatric Disorders: A Single-Center Retrospective Study
Bibliographic record
Abstract
Background and Objectives: For some years, psychiatric illness has been a major factor in evaluating the results of total knee arthroplasty. As with other patient-related items, patients diagnosed with mental illness have higher costs of medical treatment, longer recovery, and longer hospital stays. The aim of this paper is to evaluate the role of mental diseases on the surgical outcome compared with the normal population. Materials and Methods: At our hospital, we undertook a retrospective study between June 2020 and January 2022. The experimental group consisted of patients with mental diseases including schizophrenia, bipolar disease, depression, substance uses, or other psychiatric disorders. The control group consisted of patients who underwent total knee arthroplasty and did not have a mental disease. Postoperative complications and length of stay were also recorded during the study. We used the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Knee Society Score (KSS) as outcome measures. Results: Between June 2020 and January 2022, a total of 634 patients underwent total knee arthroplasty in our clinic, of which 239 had a mental disease. The majority of patients were female (61%), and the average length of stay was significantly longer for patients with mental illness (6.8 vs. 2.8 days). Preoperative WOMAC and KS function scores demonstrated statistically significant differences between groups (67.83 ± 17.8 vs. 62.75 ± 15.7 and 29.31 ± 19.8 vs. 34.98 ± 21.3). KS knee score did not show any significant differences preoperatively. All postoperative functional scores showed significantly better results for the control group compared to the mental illness group. Conclusions: Mental illness appears to be linked with lower TKA scores before and after the surgical procedure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".