Table 3 Multivariable predictive model Performance of the model The model showed good discrimination, with a c-statistics of 0.71. It demonstrated good calibration graphically and after evaluation with the Hosmer-Lemeshow test (Figure ​(Figure11). Figure 1 Calibration of final

model. Internal validation We did not find evidence of a significant overoptimism in our model development. The overoptimism for the c-statistic with the bootstrapping procedure was 0.15%. Clinical risk score Individual risk scores can be calculated from Table ​Table44 Inhibitors,research,lifescience,medical and are associated with a corresponding risk percentage (Table ​(Table5).5). For example, the risk of intracranial hemorrhage in a 55-year-old TBI www.selleckchem.com/products/MDV3100.html patient with a GCS score of 12, reactive pupils, no major extracranial injury who presents 3 hours after injury would have a calculated risk score of 14 which corresponds with an 60-<65% Inhibitors,research,lifescience,medical risk of intracranial hemorrhage. Table 4 Estimation of the risk score of intracranial hemorrhage Table 5 Percentage risk of intracranial hemorrhage according to the risk score Discussion We have developed a prognostic model utilizing readily available clinical data to predict the risk of intracranial Inhibitors,research,lifescience,medical hemorrhage in TBI patients from LMIC.

The model has demonstrated good discrimination, excellent calibration and has been internally validated. Advanced age, GCS, pupil reactivity, the presence of a major extracranial injury and time from injury to presentation were all found to be predictors for intracranial hemorrhage (ICH). GCS demonstrated a Inhibitors,research,lifescience,medical linear relationship with increased risk for intracranial hemorrhage, except for those with a calculated score of three. This could be attributed to those patients that have been sedated and intubated prior to recording of GCS, as Inhibitors,research,lifescience,medical these are given a score of three by default [27]. A linear relationship between advanced age and increased risk of poor outcome after TBI has been documented previously and was demonstrated in our study [24]. The increasing risk of hemorrhage with increasing time from injury to presentation may reflect the fact that slower bleeds are more likely to be detected at a later

scan and could have been missed in early imaging. This can also be attributed to prolong extrication times, which has been demonstrated to be associated with major injury [25]. Additionally the possibility of bias must be considered, as patients referred for more serious injury may be more likely to present with a bleed. Also a change in Dacomitinib neurological status or development of new clinical selleck symptoms may prompt patients to seek delayed care after injury. This study has limitations. In order to explore the generalisability of a prognostic model to a similar patient population within a different setting, external validation is necessary [28]. However, we did not have access to data that contains the patient population and variables included in this study, so external validation was not possible.