Aims and background: Traumatic brain injury (TBI) presents complex challenges in clinical settings, with outcomes varying widely based on injury severity. The Madras Head Injury Prognostic Scale (MHIPS) is an indigenously developed tool designed specifically for head injuries, integrating key parameters such as Glasgow Coma Scale (GCS) scores and computed tomography (CT) scan findings whereas Revised Trauma Score (RTS) is the standard scale used to assess prognosis in trauma patients worldwide.
This study aims to compare the prognostic accuracy of the MHIPS and the RTS in predicting outcomes among patients with head injuries. The specific objectives include assessing the correlation between MHIPS and Glasgow Outcome Scale (GOS) scores, evaluating the predictive value of MHIPS for mortality, and comparing these findings with those obtained using RTS.
Materials and methods: A longitudinal study was conducted on 100 patients admitted between December 2010 and January 2012 in a rural tertiary care center. MHIPS and RTS scores were assessed upon admission, and actual outcomes were measured using GOS after following up with the patients for 1 month post-admission. Correlation and regression analyses were conducted to evaluate the relationship between prognostic scales and actual patient outcomes.
Results: Analysis revealed a strong positive correlation between RTS and GOS scores (r = 0.751, p < 0.001) but a stronger correlation between MHIPS and GOS scores (r = 0.890, p < 0.001). Regression analysis demonstrated MHIPS as a better predictor of GOS (β = 0.788, p < 0.001) and mortality (Exp(B) = 2.821, p = 0.006) compared to RTS.
Conclusion: This study underscores the effectiveness of MHIPS as a reliable tool for prognosticating outcomes in TBI patients. MHIPS showed strong correlations with GOS scores and proved to be a better predictor of mortality compared to RTS.
Clinical significance: These findings highlight the importance of integrating MHIPS into clinical practice to enhance the management and prognosis assessment of head injury cases, particularly in settings where precise prognostication is crucial for guiding treatment decisions and improving patient outcomes. It can help in the early identification of high-risk patients, leading to tailored interventions and improved management of TBI cases.
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