Evaluation of Prognosis of Coma Patients With Acute Brain Injury by Electroencephalogram Bispectral Index Monitoring.

BACKGROUND: The high mortality rate of comatose patients with traumatic brain injury is a prominent public health issue that negatively impacts patients and their families. Objective, reliable tools are needed to guide treatment decisions and prioritize resources. OBJECTIVE: This study aimed to evaluate the prognostic value of the bispectral index (BIS) in comatose patients with severe brain injury. METHODS: This was a retrospective cohort study of 84 patients with severe brain injury and Glasgow Coma Scale (GCS) scores of 8 and less treated from January 2015 to June 2017. Sedatives were withheld at least 24 hr before BIS scoring. The BIS value, GCS scores, and Full Outline of UnResponsiveness (FOUR) were monitored hourly for 48 hr. Based on the Glasgow Outcome Scale (GOS) score, the patients were divided into poor (GOS score: 1-2) and good prognosis groups (GOS score: 3-5). The correlation between BIS and prognosis was analyzed by logistic regression, and the receiver operating characteristic curves were plotted. RESULTS: The mean (SD) of the BIS value: 54.63 (11.76), p = .000; and GCS score: 5.76 (1.87), p = .000, were higher in the good prognosis group than in the poor prognosis group. Lower BIS values and GCS scores were correlated with poorer prognosis. Based on the area under the curve of receiver operating characteristic curves, the optimal diagnostic cutoff value of the BIS was 43.6, and the associated sensitivity and specificity were 85.4% and 74.4%, respectively. CONCLUSION: Taken together, our study indicates that BIS had good predictive value on prognosis. These findings suggested that BIS could be used to evaluate the severity and prognosis of severe brain injury.

Quarantine Vehicle Scheduling for Transferring High-Risk Individuals in Epidemic Areas.

In a large-scale epidemic outbreak, there can be many high-risk individuals to be transferred for medical isolation in epidemic areas. Typically, the individuals are scattered across different locations, and available quarantine vehicles are limited. Therefore, it is challenging to efficiently schedule the vehicles to transfer the individuals to isolated regions to control the spread of the epidemic. In this paper, we formulate such a quarantine vehicle scheduling problem for high-risk individual transfer, which is more difficult than most well-known vehicle routing problems. To efficiently solve this problem, we propose a hybrid algorithm based on the water wave optimization (WWO) metaheuristic and neighborhood search. The metaheuristic uses a small population to rapidly explore the solution space, and the neighborhood search uses a gradual strategy to improve the solution accuracy. Computational results demonstrate that the proposed algorithm significantly outperforms several existing algorithms and obtains high-quality solutions on real-world problem instances for high-risk individual transfer in Hangzhou, China, during the peak period of the novel coronavirus pneumonia (COVID-19).