Work

Nutritional screening tools as predictors of surgical outcomes in geriatric orthopedic patients: a meta-analysis

Year: 2026
Type: review
Abstract: BACKGROUND: The prevalent preoperative nutritional evaluations in surgical settings tend to rely on isolated biochemical parameters, such as albumin levels, which demonstrate limited precision in forecasting postoperative complications and mortality rate. The primary objective of this study is to evaluate the predictive accuracy of nutrition screening tools in identifying postoperative risks and mortality in various orthopedic surgeries, and to determine which tools are the most reliable. METHODS: A comprehensive search was conducted in PubMed, CNKI, EMBASE, and Cochrane Central databases for studies on the relationship between nutritional status and postoperative outcomes in older orthopedic surgery patients. The search period was from the establishment of the databases to May 2025. Subgroup analyses evaluated the impact of various factors on outcomes. Meta-regression was performed to further explore heterogeneity. RESULTS: The current investigation encompasses 11 studies, inclusive of 201,338 geriatric orthopedic surgery patients. The result showed that malnutrition assessed by nutrition screening tools was significantly associated with postoperative complications (RR = 1.65, 95% CI: 1.26-2.15), and postoperative mortality as well (RR = 2.17, 95% CI: 1.58-3.00). Significant statistical heterogeneity was observed in the primary analyses, but sensitivity analyses confirmed the robustness of the primary findings. Subgroup analyses revealed variations based on factors like study design, geographic location, and Surgical procedure. Meta-regression identified study design as a significant predictor of postoperative complications. CONCLUSION: Nutrition screening tools are effective in identifying preoperative malnutrition and can be utilized as predictive factors for the risk of adverse outcomes in older patients undergoing orthopedic surgeries.
Language: English
Subfield: Physiology
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $4,490
OpenAlex ID: W7123747022
FWCI: 1.968
Cites: 38
Cited by: 1
Related to: