The Effect of Anxiety and Depression on the Quality of Life in Patients Before and After Knee Arthroplasty
Bibliographic record
Abstract
Introduction: Osteoarthritis (OA) is a common degenerative joint disease, affecting 10% of adults. It leads to functional limitations . The aim of this study was to compare patients’ depression, anxiety, and quality of life (QOL) before and after total knee arthroplasty (TKA). Materials and Methods: This prospective study was conducted on patients with knee OA who were eligible for elective TKA at a Hospital in Sari, Iran, between 2020 and 2022. Patients completed four questionnaires before and 6 months after surgery: the hospital anxiety and depression scale (HADS), the McGill pain questionnaire (MPQ), the visual analog scale (VAS), and the 36-item short form health survey (SF-36). The significance level for all statistical tests was set at 0.05. Results: Fifty-eight patients, including 7 men (12.1%) and 51 women (87.9%), were included in the study. The mean age was 64.91 ± 7.64 years. Postoperative evaluation revealed that the prevalence of anxiety and depression among patients was 44.8% and 27.6%, respectively. However, there was no significant difference compared to preoperative levels (P-value > 0.05). Discussion: A comparison of patients’ QOL before and after surgery showed that patients’ physical limitation, emotional function, and pain decreased significantly, and their physical function and emotional role limitation score increased significantly. Anxiety and depression before surgery, with and without controlling for the variables of age, sex, and other QOL components, had no significant effect on the perception of pain after surgery (after controlling for variables, P-value for depression = 0.16, P-value for anxiety = 0.60). Conclusion: Performing TKA significantly reduces physical limitations, emotional functioning, and pain. However, anxiety and depression had no effect on pain perception after surgery. This study demonstrates that older age is associated with an increased risk of postoperative failure, while better general health scores may reduce the risk.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".