dc.contributor.author | Mukuye, Simon | |
dc.date.accessioned | 2019-10-28T07:20:05Z | |
dc.date.available | 2019-10-28T07:20:05Z | |
dc.date.issued | 2019-07-09 | |
dc.identifier.citation | Mukuye, S. (2019). Predictors of traumatic intracranial lesions in clinically diagnosed mild head injury patients at Mulago Hospital. Unpublished master’s thesis, Makerere University, Kampala, Uganda. | en_US |
dc.identifier.uri | http://hdl.handle.net/10570/7531 | |
dc.description | A dissertation submitted in partial fulfilment of the requirements for the award of the Degree of Master of Medicine in General Surgery of Makerere University. | en_US |
dc.description.abstract | 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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | Traumatic intracranial lesions | en_US |
dc.subject | Mild head injury | en_US |
dc.subject | Mulago Hospital | en_US |
dc.title | Predictors of traumatic intracranial lesions in clinically diagnosed mild head injury patients at Mulago Hospital | en_US |
dc.type | Thesis | en_US |