Electroencephalography as a Biomarker of Prognosis in Acute Brain Injury.

Electroencephalography (EEG) is a noninvasive tool that allows the monitoring of cerebral brain function in critically ill patients, aiding with diagnosis, management, and prognostication. Specific EEG features have shown utility in the prediction of outcomes in critically ill patients with status epilepticus, acute brain injury (ischemic stroke, intracranial hemorrhage, subarachnoid hemorrhage, and traumatic brain injury), anoxic brain injury, and toxic-metabolic encephalopathy. Studies have also found an association between particular EEG patterns and long-term functional and cognitive outcomes as well as prediction of recovery of consciousness following acute brain injury. This review summarizes these findings and demonstrates the value of utilizing EEG findings in the determination of prognosis.

The Prevalence of Depression Symptoms and Frequency of Risk Factors in Medical and Nursing Students: A Descriptive Cross-sectional Study.

OBJECTIVE: Currently, in Puerto Rico, there is a paucity of data regarding emotional health and depression in health professionals, specifically regarding trainees such as medical students and nursing students. The study intended to shed light on the prevalence of depression symptoms among medical and nursing students at a school of medicine in Puerto Rico. METHODS: In the fall of 2019, a descriptive cross-sectional study that included nursing and medical students in their first, second, and third years was performed. A survey consisting of the Patient Health Questionnaire (PHQ-9) and sociodemographic questions were used for data collection. Logistic regression analyses were used to determine the association of PHQ-9 scores and the risk factors linked to depression symptoms. RESULTS: A total of 173 (83.2%) out of 208 enrolled students participated in the study. Of the participants, 75.7% were medical students and 24.3% were nursing students. Of the risk factors studied, feelings of regret and lack of sleep were associated with a higher frequency of depression symptoms in medical students. For the nursing student population, suffering from a chronic disease was associated with a higher frequency of depression symptoms. CONCLUSION: Due to the increased risk of depression in healthcare professionals, identifying risk factors that can be addressed through early changes in behavior, or in institutional policies, is important in terms of working to mitigate the risk of mental health problems in this vulnerable population.