Preventable risk factors of mortality after hip fracture surgery: Systematic review and meta-analysis.

Objective: Although many studies have reported risk factors of mortality following hip fracture surgery, the preventable risk factors of mortality following hip fracture surgery have not been well-identified. The aim of this study was to identify the preventable risk factors of mortality following hip fracture surgery.

Methods: We searched PubMed, Web of Science, Google scholar, and the Chinese National Knowledge Infrastructure (CNKI) databases from January 1997 to March 2017 for studies reporting risk factors of mortality following hip fracture surgery. The primary outcomes assessed in this meta-analysis were time to surgery, residential status, smoking, cardiovascular disease, pulmonary disease, diabetes, and malignancy. All analyses were conducted using Stata/SE version 11.0 software.

Results: Sixteen studies involving 25 349 patients meeting the inclusion criteria were included. Statistically significant associations between the mortality after hip fracture surgery and the risk factors, including the time to surgery (>2days/<2days) (odds ratio[OR] = 1.91; 95%CI, 1.14-3.18; P = 0.013), residential status (nursing home/home) (OR = 1.97; 95%CI, 1.02-3.78; P = 0.043), cardiovascular disease (OR = 1.14; 95%CI, 1.03-1.26; P = 0.012), pulmonary disease (OR = 1.52; 95%CI, 1.37-1.69; P < 0.001), diabetes (OR = 1.41; 95%CI, 1.19-1.67; P < 0.001), and malignancy (OR = 2.99, 95%CI, 1.14-7.83; P = 0.013) were established. However, the available data failed to demonstrate an association between the mortality, and time to surgery (>1day/<1day) (OR = 1.25; 95%CI, 0.93-1.66; P = 0.136) and smoking (OR = 0.89; 95%CI, 0.69-1.14; P = 0.340).

Conclusion: This meta-analysis explicitly indicated that malignancy, nursing home residence, time to surgery (>2days/<2days), pulmonary disease, diabetes, and cardiovascular disease significantly increased the risk of mortality after hip fracture surgery. These preventable risk factors may be used to create algorithms that are more effective and pertinent to reduce the mortality following hip fracture surgery.