Predictors of traumatic intracranial lesions in clinically diagnosed mild head injury patients at Mulago hospital.
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Background Head injury is one of the most common causes of admission at Mulago hospital with the bigger proportion of it being categorised as mild head injury (MHI). Study Aims The main aims of this study were to determine the prevalence of traumatic intracranial lesions (TICLs) and to identify the most reliable clinical predictors of TICLs in clinically-diagnosed adult MHI patients at Mulago hospital Methods This was a cross-sectional study of 204 clinically diagnosed adult mild head injury patients at Mulago hospital. We did cross-tabulation to study the association between clinical features and a traumatic intracranial lesion (TICL) through a Chi square (X2) test. To determine the strength and direction of association we estimated the odds ratios using simple logistic regression. We finally did a correlation analysis of all clinical characteristics to select one of each correlated clinical characteristics which we included into a multivariate logistic regression and then ran multiple analyses on all variables having a P-Value less than or equal to 0.1(10%) We then did model performance comparison using Akaike Information Criteria (AIC) and the adjusted Macfadden R2 values to identify the best performing predictor model. Results The prevalence of TICLs identifiable on head CT scan was estimated at 66 % [95% CI (59-72%)] The most frequent TICL identified was a cerebral contusion with a prevalence of 33.8% [95%CI (25.99%-39.24%)] and the least frequent TICLs were sub-arachnoid and intra-cerebral haemorrhages each with a prevalence of 5.4% [95%CI (3.08%-10.5%)] We identified a set of 6 factors that showed the highest reliability in identifying patients with TICLs (sensitivity 89.63%, specificity of 43.48%) Individual predictors within the set included Severe and moderate headache, a referred patient, male gender, GCS=13, and presence of raccoon eyes. The strongest individual predictor of a TICL in a clinically-diagnosed Mild Head injury (MHI) patient was severe headache with an adjusted odds ratio of 5.7. Conclusion Our study established 6 clinical features that could be used to identify patients with clinically-diagnosed mild head injury who would benefit from a head CT scan. They included Severe and moderate headache, a referred patient, male gender, GCS=13, and presence of raccoon eyes. These factors could be considered positive indicators for the need of a head CT scan for clinically diagnosed MHI patients and allow clinicians to be more selective in use of the CT scan without compromising patient care.