Results of Primary Total Knee Arthroplasty in Patients on Chronic Psychotropic Medications
Bibliographic record
Abstract
BACKGROUND: Psychotropic medications are commonly used to treat several mental health conditions. The aim of this study was to determine the impact of psychotropic medications in patients undergoing primary total knee arthroplasty (TKA) with respect to postoperative opioid use, complications, patient-reported outcome measures, and satisfaction. METHODS: This is a retrospective cohort study of 514 consecutive patients undergoing primary TKA. There were 120 patients (23.3%) who were excluded due to preoperative opioid usage. The remaining 394 patients had a minimum 1-year follow-up. Of those, 133 (34%) were on psychotropic medications preoperatively and were compared to the remaining 261 (66%) patients who were not on psychotropics. Clinical data, satisfaction, Knee Society (KS) scores, Western Ontario McMaster Universities Arthritis Index, Patient-Reported Outcomes Measurement Index Score, Forgotten Joint Scores, Knee Injury and Osteoarthritis Outcome Score for Joint Replacement, postoperative opioid medication usage, and complications were compared. RESULTS: The study cohort (psychotropic medications) had significantly lower postoperative KS Function, KS Knee, Forgotten Joint Scores, Knee Injury and Osteoarthritis Outcome Score for Joint Replacement, Western Ontario McMaster Universities Arthritis Index, and Patient-Reported Outcomes Measurement Index Score compared to the control group. The study group had a lower overall satisfaction score (Likert scale 1 to 5) and a lower percentage of patients either satisfied or very satisfied (4.55 versus 4.79, P < .001; 92.0 versus 97.24%, P = .03, respectively). Postoperative opioid usage was significantly greater in the study group at both 6.4 weeks (range, 4 to 8) and 12-month follow-up (52.76 versus 13.33%, P < .001; 5.51 versus 0.39%, P = .002, respectively). There were no differences in complications and revisions between the groups. CONCLUSIONS: Patients on psychotropic medications should be educated on the risk of increased opioid consumption, diminished satisfaction, and patient-reported outcome measures following primary TKA. Given the large number of patients on psychotropic medications undergoing TKA, additional studies are needed to further improve clinical outcomes in this group.
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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 | 0.001 |
| 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) | 0.003 | 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".