Abstract
OBJECTIVES: Hip fractures in elderly patients are associated with a high mortality rate. Most deaths associated with hip fracture result from complications after surgery. Recent studies suggest that some inflammation biomarkers may be useful to estimate excess mortality. This study aimed to investigate the prognostic value of admission inflammation biomarkers in elderly patients with hip fracture. METHODS: We reports on a retrospective study of elderly hip fracture patients admitted to a hospital in China between January 2015 and December 2019. A total of 1085 patients were included in the study, and their demographic and pre-operative characteristics were analyzed. The inflammation biomarkers included monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), and C-reactive protein (CRP) to albumin ratio (CAR). The predictive performance of NLR, MLR and CAR was assessed by receiver operating characteristics (ROC) curve analysis and the association between admission inflammation markers and mortality was evaluated by Cox proportional regression. RESULTS: The 30-day, 1-year, 2-year, and 4-year mortality were 1.6%, 11.5%, 21.4% and 48.9%, respectively. The optimal cut-off values of admission NLR, MLR and CAR for 1-year mortality were 7.28, 0.76, and 1.36. After adjusting the covariates, preoperative NLR ≥ 7.28 (HR = 1.419, 95% CI: 1.080-1.864, p = 0.012) were found to be only independent risk factors with 4-year all-cause mortality, the preoperative CAR ≥ 1.36 was independently associated with 1-year (HR = 1.700, 95% CI: 1.173-2.465, p = 0.005), 2 year (HR = 1.464, 95% CI: 1.107-1.936, p = 0.008), and 4-year (HR = 1.341, 95% CI: 1.057-1.700, p = 0.016) all-cause mortality, While age, CCI score, and low hemoglobin at admission were also risk factors for postoperative all-cause mortality. CONCLUSION: Admission CAR and NLR may be useful indicators for predicting the long-term mortality of elderly patients undergoing hip fracture surgery, and that more research is needed to validate these findings.