Predicting outcomes after traumatic brain injury: A novel hospital prediction model for a patient reported outcome

Background: Estimation of long-term quality of life in patients sustaining Traumatic brain injuries is a difficult but important task during the early hospitalization. There are very limited tools to assess these outcomes, therefore we aimed to develop a predictive model for quality-of-life that could be used in hospitalized adults with TBIs. Methods: The TRACK-TBI dataset was used to identify adult patients with TBI from 2014 to 2018. Multiple variables were assessed to predict favorable versus unfavorable scores on the Quality of Life after Brain Injury -Overall Scale (QOLIBRI-OS). Results: We included 1549 subjects. 57% had a favorable outcome, and were more likely to have private in-surance, higher GCS scores, and fewer comorbidities. A model (TBI-PRO) for 3, 6, and 12-month QOLIBRI score was created. The AUROCs for predicting 3, 6 and 12-month favorable QOLIBRI scores were 0.81, 0.79, and 0.76, respectively. Conclusion: The TBI-PRO model adequately estimates long-term outcomes in patients with TBI.

Automated summary

This study aimed to develop a model for predicting the quality of life in hospitalized adults with Traumatic brain injuries (TBIs). By analyzing the dataset, researchers found that private insurance, higher Glasgow Coma Scale (GCS) scores, and fewer comorbidities were associated with better quality of life. They developed a model (TBI-PRO) for predicting the quality of life scores at different time points and concluded that the model adequately estimates long-term outcomes in patients with TBI.