Asad · Cureus 2026 · systematic review and meta-analysis · n=9 studies (1,328 patients)

The Association of Preoperative Patient Resilience With Postoperative Patient-Reported Outcomes Following Total Joint Arthroplasty: A Systematic Review and Meta-Analysis.

Cited 0 times in the scientific literature.

Level 3 - non-randomized controlled study

Systematic review and meta-analysis of observational prognostic studies

PubMed 42422666 · doi:10.7759/cureus.110469 · record verified 2026-08-29

What was done

A systematic review and meta-analysis evaluated the association between preoperative psychological resilience and postoperative patient-reported outcome measures (PROMs) following total joint arthroplasty (TJA). Searches of PubMed, Embase, and Scopus identified 9 eligible studies published between 2019 and 2022, encompassing 1,328 patients (pooled mean age 67.5 years). Preoperative resilience was evaluated using the Brief Resilience Scale (6 studies) or the Connor-Davidson Resilience Scale (3 studies). Methodological quality was appraised across the included cohorts.

What was found

Studies demonstrated a low to moderate risk of bias. Higher preoperative resilience was significantly associated with superior postoperative scores across multiple PROM instruments: PROMIS Physical Health (p < 0.001), PROMIS Mental Health (p < 0.001), KOOS (p < 0.05), EQ-5D (p < 0.001), EQ-VAS (p < 0.001), and WOMAC (p < 0.05). Meta-analysis specifically confirmed statistically significant associations with PROMIS-PH, PROMIS-MH, and KOOS. Exact pooled effect sizes and confidence intervals were not reported in the abstract.

Why it matters

Identifying preoperative resilience as a prognostic factor suggests that psychological status could serve as an actionable target for pre-surgical interventions to improve functional recovery and patient satisfaction following joint replacement.

Limits

The review included only 9 observational studies with relatively small collective sample sizes (1,328 patients). Resilience and outcomes were evaluated across varying scales without standardized instruments. Because all underlying data are observational, causation cannot be established, and the abstract omitted specific quantitative effect estimates and heterogeneity metrics.

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