Does the preoperative presence of central sensitization affect sleep quality and pain after total knee arthroplasty?
Bibliographic record
Abstract
Objectives: This study aims to investigate the presence of central sensitization before total knee arthroplasty (TKA) in patients with knee osteoarthritis, to explore its relationship with sleep quality after this surgery, and to evaluate postoperative pain intensity, neuropathic pain, anxiety, depression, and functional status. Patients and methods: Between May 2022 and May 2023, a total of 31 patients (8 males, 23 females; mean age: 68.1±2.8 years; range, 62 to 73 years) who underwent a radiographic examination, had Stage 3-4 osteoarthritis based on the Kellgren-Lawrence classification, and had TKA indications at the discretion of the orthopedic surgeon were included in this single-center, one-group, quasi-experimental, prospective study. The Central Sensitization Inventory (CSI) and International Physical Activity Questionnaire-Short Form (IPAQ) were used to evaluate patients scheduled for TKA due to osteoarthritis of the related joint. The Visual Analog Scale (VAS), painDETECT, the Pittsburgh Sleep Quality Index (PSQI), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Hospital Anxiety and Depression Scale were applied to all patients preoperatively and at one and three months postoperatively. Results: The postoperative PSQI, VAS, and painDETECT scores were significantly higher in those with central sensitization compared to non-central sensitization group after surgery (p<0.001). The CSI score had a positive correlation with the PSQI, VAS, and painDETECT scores, and a negative correlation with the preoperative IPAQ score (p<0.05). Conclusion: Our study results suggest that, in patients with knee osteoarthritis waiting for TKA, central sensitization status has an adverse impact on postoperative pain and sleep quality.
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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 | 0.000 | 0.001 |
| 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".