Abstract
Open tibial fractures can be difficult to manage, with a range of factors that could affect treatment and outcome. We present a large cohort of patients, and analyse which factors have significant associations with infection outcome. Elucidation will allow clinicians to strive for treatment optimisation, and patients to be advised on likely complications
Open tibia fractures treated at a major trauma centre between 2015-2021 were included. Mean age at injury was 55.4 (range 13-102). Infection status was categorized into no infection, superficial infection, and osteomyelitis.
Age, mode of injury, polytrauma, fibula status, Gustilo-Anderson (GA) classification, wound contamination, time from injury to: first procedure/definitive plastics procedure/definitive fixation, type of definitive fixation, smoking and diabetic status, and BMI, were collected. Multicollinearity was calculated, with highly correlated factors removed. Multinomial logistic regression was performed. Chi Squared testing, with Post Hoc Bonferroni correction was performed for complex categorical factors.
Two hundred forty-four patients with open tibial fractures were included. Forty-five developed superficial infection (18.4%), and thirty-nine developed osteomyelitis (16.0%).
Polytrauma, fibula status, and type of definitive fixation were excluded from the multivariate model due to strong multicollinearity with other variables.
With reference to the non-infected outcome; superficial infection patients had higher BMI (p<0.01), higher GA grade (p<0.01), osteomyelitis patients had longer time to definitive fixation (p=0.049) and time to definitive plastics procedure (p=0.013), higher GA grade (p<0.01), and positive wound contamination(p=0.015).
Poc hoc analysis showed “no infection” was positively associated with GA-I (p=0.029) and GA-II (p<0.01), and negatively associated with GA-IIIC (p<0.01). Osteomyelitis was positively associated with GA-IIIc (p<0.01)
This study investigated the associations between the injury and presentation factors that may affect infection outcome. The variables highlighted are the factors clinicians should give extra consideration to when treating cases, and take preventative measures to optimize treatment and mitigate infection risk.
