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| Content Provider | PubMed Central |
|---|---|
| Author | Deng, Ruoxian Young, Leanne M. Jia, Xiaofeng |
| Abstract | Therapeutic hypothermia has been regarded as one of the most effective post-cardiac arrest (CA) treatments to improve survival and functional recovery. However, many clinical prognostic markers after resuscitation have become less reliable under hypothermia. In this study, we applied and compared two developed quantitative measures - information quantity (IQ) and sub-band IQ (SIQ) - to evaluate the accuracy of EEG markers on predicting cortical recovery under therapeutic hypothermia. A total of 14 rats under 9-min asphyxial-CA, leading to severe brain injury, were randomly divided into two groups: hypothermia (32°C-34°C) and normothermia (36.5–37.5°C) (n=7 per group). For each rat, EEG and temperature were continuously recorded for the first 15 hrs. EEG was then recorded for serial 30 mins at 24, 48 and 72 hrs. The neurologic deficit score was evaluated daily to assess the neurologic recovery. Early SIQ and IQ were both significantly correlated with the 72-hr NDS, when the rats remained comatose. Both IQ and SIQ were able to discriminate the animals with good and bad functional outcomes starting from 1 hr after resuscitation. There was no significant difference in 72-hr NDS results (hypothermia (median (25th, 75th), 65 (52, 67)) versus normothermia (53.5 (52.25, 66.75))) (p>0.05) due to the high mortality rate (5/14) with severe brain injury. Contrary to IQ recovery but similarly to NDS scores, the SIQ recovery was not significantly different between the hypothermia (0.66±0.04) and normothermia (0.64±0.04) groups (p>0.05). IQ could identify the presence of high-frequency oscillations during the recovery from severe brain injury. We demonstrated that while SIQ was able to provide additional sub-band EEG information related to the recovery of different brain functions, both early IQ and SIQ markers are able to accurately predict neurologic outcome after CA. |
| Related Links | http://dx.doi.org/10.1109/embc.2015.7319905 |
| Starting Page | 6598 |
| File Format | |
| ISSN | 1557170X |
| Journal | Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference |
| Volume Number | 2015 |
| Language | English |
| Publisher Date | 2015-08-01 |
| Access Restriction | Open |
| Subject Keyword | Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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