Background and objective: Physiologic variables have traditionally been studied as prognostic factors in severe head injury. Until recently it was not thought that genetic factors might play a role. The main objective of this study was to construct a logistic regression model including physiologic variables and the p53 Arg72Pro polymorphism, which can promote neuron death through apoptosis.
Material and methods: We included 90 patients admitted to the postoperative recovery unit with severe head injury. Patients with previous neurologic deficits were excluded. Clinical variables were recorded. The p53 Arg72Pro polymorphism was analyzed using polymerase chain reaction of DNA in blood. Neurologic outcome was assessed on the Glasgow Outcome Scale. A predictive logistic regression model was then constructed based on relevant candidate variables (sex, age, poor Glasgow score, the Acute Physiology and Chronic Health Evaluation II score, pupil size, pupil reactivity, subarachnoid hemorrhage, number of days in the recovery unit, number of days on mechanical ventilation, and the early development of hypotension) in addition to the p53 Arg72Pro polymorphism.
Results: The Arg/Arg polymorphism was an independent predictor of poor outcome (odds ratio, 3.55; 95% confidence interval [CI], 1.11-1132; P = .032). The selected model (including the variables age, gene polymorphism, pupil reactivity, and Glasgow score) had adequate discriminatory power (sensitivity 823%, 95% CI 72.8%-91.8%; specificity 78.6%, 95% CI 63.4%-93.8%), classifying 81.1% of the patients correctly. The p53 Arg72Pro polymorphism, along with pupil reactivity, age and Glasgow score, is useful in a predictive model of good or poor outcome on discharge after head injury.