Resilience as a psychiatric factor affecting outcomes after total joint arthroplasty: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Mental and psychiatric status continue to be underscreened prior to total joint arthroplasty (TJA). Research on the role of resilience as a psychiatric factor affecting TJA outcomes remains limited. Therefore, our systematic review sought to evaluate the impact of patient resilience in TJA. METHODS: A systematic review of the literature from the Pubmed, MEDLINE, EBSCOhost, and Google Scholar online databases was performed in abidance with Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Studies reporting on outcomes following primary total hip arthroplasty (THA) and/or total knee arthroplasty (TKA) segregated by patient resilience were included. Case reports, reviews, meta-analyses, and conference abstracts were excluded. Primary outcomes of interest included patient-reported outcomes (PROs), surgical outcomes, and postoperative opioid consumption. RESULTS: Twelve articles were included reporting on a total of 1,577 TJAs. There was a strong agreement that the Patient Reported Outcomes Measurement Information System (PROMIS)-Physical Health and Mental Health components were strongly predicted by patient resilience. However, there was inconclusive evidence regarding the impact of resilience on UCLA Activity Scales (UCLA) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) outcomes as well as postoperative hip and knee function. Similarly, conflicting evidence was presented regarding the effect of resilience on length of stay (LOS). Greater resilience was associated with reduced opioid usage in the immediate inpatient postoperative period. However, resilience had no significant effect on opioid requirements in the postoperative outpatient follow-up time frame. CONCLUSION: The present analysis demonstrated mixed, inconclusive evidence regarding the impact of resilience on postoperative outcomes. The paucity of research evaluating this relationship warrants further investigation, examining both short and long-term outcomes. Due to the limited literature evaluating resilience as a predictor of outcomes following TJA, we cannot definitively rule out resilience as a valuable metric and must further examine its utility as a preoperative screening tool. LEVEL OF EVIDENCE: III.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".