scholarly journals Multimodal Long-Term Predictors of Outcome in Out of Hospital Cardiac Arrest Patients Treated with Targeted Temperature Management at 36 °C

2021 ◽  
Vol 10 (6) ◽  
pp. 1331
Author(s):  
Erik Roman-Pognuz ◽  
Jonathan Elmer ◽  
Frank X. Guyette ◽  
Gabriele Poillucci ◽  
Umberto Lucangelo ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
White Matter ◽  
Temperature Management ◽  
Single Test ◽  
Brain Computed Tomography ◽  
Good Outcome ◽  
Eeg Reactivity ◽  
Single Predictor

Introduction: Early prediction of long-term outcomes in patients resuscitated after cardiac arrest (CA) is still challenging. Guidelines suggested a multimodal approach combining multiple predictors. We evaluated whether the combination of the electroencephalography (EEG) reactivity, somatosensory evoked potentials (SSEPs) cortical complex and Gray to White matter ratio (GWR) on brain computed tomography (CT) at different temperatures could predict survival and good outcome at hospital discharge and six months after the event. Methods: We performed a retrospective cohort study including consecutive adult, non-traumatic patients resuscitated from out-of-hospital CA who remained comatose on admission to our intensive care unit from 2013 to 2017. We acquired SSEPs and EEGs during the treatment at 36 °C and after rewarming at 37 °C, Gray to white matter ratio (GWR) was calculated on the brain computed tomography scan performed within six hours of the hospital admission. We primarily hypothesized that SSEP was associated with favor-able functional outcome at distance and secondarily that SSEP provides independent information from EEG and CT. Outcomes were evaluated using the Cerebral Performance Category (CPC) scale at six months from discharge. Results: Of 171 resuscitated patients, 75 were excluded due to missing data or uninterpretable neurophysiological findings. EEG reactivity at 37 °C has been shown the best single predictor of good out-come (AUC 0.803) while N20P25 was the best single predictor for survival at each time point. (AUC 0.775 at discharge and AUC 0.747 at six months follow up). The predictive value of a model including EEG reactivity, average GWR, and SSEP N20P25 amplitude was superior (AUC 0.841 for survival and 0.920 for good out-come) to any combination of two tests or any single test. Conclusions: Our study, in which life-sustaining treatments were never suspended, suggests SSEP cortical complex N20P25, after normothermia and off sedation, is a reliable predictor for survival at any time. When SSEP cortical complex N20P25 is added into a model with GWR average and EEG reactivity, the predictivity for good outcome and survival at distance is superior than each single test alone.

scholarly journals Multimodal Long Term Predictors of Outcome in Out of Hospital Cardiac Arrest Patients Treated with Targeted Temperature Management at 36°C

2021 ◽  
Author(s):  
Erik Roman-Pognuz ◽  
Jonathan Elmer ◽  
Frank X Guyette ◽  
gabriele poillucci ◽  
umberto lucangelo ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
White Matter ◽  
Temperature Management ◽  
Single Test ◽  
Brain Computed Tomography ◽  
Good Outcome ◽  
Eeg Reactivity ◽  
Single Predictor

Introduction Early prediction of long term outcomes in patients resuscitated after cardiac arrest (CA) is still challenging. Guidelines suggested a multimodal approach combining multiple predictors. We evaluated whether the combination of the electroencephalography (EEG) reactivity, somatosensory evoked potentials (SSEPs) cortical complex and Gray to White matter ratio (GWR) on brain computed tomography (CT) at different temperatures could predict survival and good outcome at hospital discharge and after six months. Methods We performed a retrospective cohort study including consecutive adult, non-traumatic patients resuscitated from out-of-hospital CA who remained comatose on admission to our intensive care unit from 2013 to 2017. We acquired SSEPs and EEGs during the treatment at 36°C and after rewarming at 37°C, Gray to white matter ratio (GWR) was calculated on the brain computed tomography scan performed within six hours of the hospital admission. We primarily hypothesized that SSEP was associated with favorable functional outcome at distance and secondarily that SSEP provides independent information from EEG and CT. Outcomes were evaluated using the Cerebral Performance Category (CPC) scale at six months from discharge. Results Of 171 resuscitated patients, 75 were excluded due to missing of data or uninterpretable neurophysiological findings. EEG reactivity at 37 °C has been shown the best single predictor of good outcome (AUC 0.803) while N20P25 was the best single predictor for survival at each time point. (AUC 0.775 at discharge and AUC 0.747 at six months follow up) Predictive value of a model including EEG reactivity, average GWR, and SSEP N20P25 amplitude was superior (AUC 0.841 for survival and 0.920 for good outcome) to any combination of two tests or any single test. Conclusion Our study, in which life-sustaining treatments were never suspended, suggests SSEP cortical complex N20P25, after normothermia ad off sedation, is a reliable predictor for survival at any time. When SSEP cortical complex N20P25 is added into a model with GWR average and EEG reactivity, the predictivity for good outcome and survival at distance is superior than each single test alone.

scholarly journals The prognostic value of gray–white matter ratio on brain computed tomography in adult comatose cardiac arrest survivors

2018 ◽  
Vol 81 (7) ◽  
pp. 599-604 ◽  
Author(s):  
Gan-Nan Wang ◽  
Xu-Feng Chen ◽  
Jin-Ru Lv ◽  
Na-Na Sun ◽  
Xiao-Quan Xu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
White Matter ◽  
Prognostic Value ◽  
Brain Computed Tomography

Abstract 418: Categorization of Post-Cardiac Arrest Patients According to the Pattern of Amplitude-Integrated Electroencephalography After Return of Spontaneous Circulation: Analysis of Long-Term Prognosis

Circulation ◽  
2019 ◽  
Vol 140 (Suppl_2) ◽  
Author(s):  
Kazuhiro Sugiyama ◽  
Kazuki Miyazaki ◽  
Yuichi Hamabe
Keyword(s):  
Cardiac Arrest ◽  
Hospital Discharge ◽  
Spontaneous Circulation ◽  
Neurological Function ◽  
Temperature Management ◽  
Return Of Spontaneous Circulation ◽  
Good Outcome ◽  
Long Term Prognosis ◽  
One Year

Introduction: Amplitude-integrated electroencephalography (aEEG) is a type of quantitative EEG easily interpreted by emergency physicians and intensivists at the bedside. We previously reported that categorizing post-cardiac arrest patients according to the pattern of aEEG, after return of spontaneous circulation (ROSC), could help predict the neurological function at hospital discharge (Critical Care. 2018;20:226). In post-cardiac arrest patients, increasing importance is being placed on long-term prognosis. In this study we evaluated the neurological outcome of patients in each category from our previous study, one year after cardiac arrest. Methods: We assessed the outcomes of patients who received post-cardiac arrest care, including targeted temperature management (TTM) and aEEG monitoring, in our tertiary emergency center, between March 2013 and April 2017. The patients were divided into four categories: C1 included those who displayed continuous normal voltage (CNV), within 12 hours of ROSC, and the best aEEG pattern in post-cardiac arrest patients; C2 included those who recovered CNV between 12 and 36 hours after ROSC; C3 included those with no CNV up to 36 hours after ROSC; and C4 included those who revealed burst suppression any time after ROSC. A good outcome was defined as a cerebral performance category (CPC) of 1 or 2, one year after cardiac arrest. Results: A total of 60 patients, with a median age of 60 years, were assessed; of them, 41 (68%) had an initial shockable rhythm. A good outcome was recorded in 18/19 (95%) C1 patients, 8/14 (57%) C2 patients, 1/10 (10%) C3 patients, and 0/14 C4 patients. Three patients could not be categorized because the recording period was too short. Conclusion: The categorization of post-cardiac arrest patients according to the pattern of aEEG after ROSC may be useful to predict long-term neurological function. C1 patients had excellent prognosis, while C3 and C4 patients had poor prognosis. However, one patient in the C3 group had CPC 3 at hospital discharge and then recovered to CPC 2 within one year. Withdrawal of care should be considered cautiously, using a multimodal approach, for patients in this category. C2 patients have borderline prognosis and are targets for intensive post-cardiac neurological care.

scholarly journals Differences in the gray-to-white matter ratio according to different computed tomography scanners for outcome prediction in post-cardiac arrest patients receiving target temperature management

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258480
Author(s):  
Jae Hun Oh ◽  
Seung Pill Choi ◽  
Jong Ho Zhu ◽  
Soo Hyun Kim ◽  
Kyu Nam Park ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
White Matter ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Internal Capsule ◽  
Temperature Management ◽  
Target Temperature Management ◽  
Ct Scanners ◽  
The Difference

The gray-to-white matter ratio (GWR) has been used to identify brain damage in comatose patients after cardiac arrest. However, Hounsfield units (HUs), the measurement of brain density on computed tomography (CT) images, may vary depending on the machine type or parameter. Therefore, differences in CT scanners may affect the GWR in post-cardiac arrest patients. We performed a retrospective study on comatose post-cardiac arrest patients who visited the hospital from 2007 to 2017. Two CT, Lightspeed and SOMATOM, scanners were used. Two observers independently measured the HUs of the caudate nucleus, putamen, posterior internal capsule, and corpus callosum using regions of interest. We compared the GWR calculated from the HUs measured at different CT scanners. The analysis of different scanners showed statistically significant differences in the measured HUs and GWR. The HUs and GWR of Lightspeed were measured lower than SOMATOM. The difference between the two CT scanners was also evident in groups divided by neurological prognosis. The area under the curve of the receiver operating characteristic curve to predict poor outcomes of Lightspeed was 0.798, and the cut-off value for 100% specificity was 1.172. The SOMATOM was 0.855, and the cut-off value was 1.269. The difference in scanners affects measurements and performance characteristics of the GWR in post-cardiac arrest patients. Therefore, when applying the results of the GWR study to clinical practice, reference values for each device should be presented, and an integrated plan should be prepared.

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