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Identification of Patients With High Mortality Risk and Prediction of Outcomes in Delirium by Bispectral EEG.

ABSTRACT: BACKGROUND:Delirium is common and dangerous, yet underdetected and undertreated. Current screening questionnaires are subjective and ineffectively implemented in busy hospital workflows. Electroencephalography (EEG) can objectively detect the diffuse slowing characteristic of delirium, but it is not suitable for high-throughput screening due to size, cost, and the expertise required for lead placement and interpretation. This study hypothesized that an efficient and reliable point-of-care EEG device for high-throughput screening could be developed. METHODS:This prospective study, which measured bispectral EEG (BSEEG) from elderly inpatients to assess their outcomes, was conducted at the University of Iowa Hospitals and Clinics from January 2016 to October 2017. A BSEEG score was defined based on the distribution of 2,938 EEG recordings from the 428 subjects who were assessed for delirium; primary outcomes measured were hospital length of stay, discharge disposition, and mortality. RESULTS:A total of 274 patients had BSEEG score data available for analysis. Delirium and BSEEG score had a significant association (P < .001). Higher BSEEG scores were significantly correlated with length of stay (P < .001 unadjusted, P = .001 adjusted for age, sex, and Charlson Comorbidity Index [CCI] score) as well as with discharge not to home (P < .01). Hazard ratio for survival controlling for age, sex, CCI score, and delirium status was 1.35 (95% CI,1.04 to 1.76; P = .025). CONCLUSIONS:In BSEEG, an efficient and reliable device that provides an objective measurement of delirium status was developed. The BSEEG score is significantly associated with pertinent clinical outcomes of mortality, hospital length of stay, and discharge disposition. The BSEEG score better predicts mortality than does clinical delirium status. This study identified a previously unrecognized subpopulation of patients without clinical features of delirium who are at increased mortality risk.

SUBMITTER: Shinozaki G

PROVIDER: S-EPMC7181374 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Identification of Patients With High Mortality Risk and Prediction of Outcomes in Delirium by Bispectral EEG.

Shinozaki Gen G Bormann Nicholas L NL Chan Aubrey C AC Zarei Kasra K Sparr Nicholas A NA Klisares Mason J MJ Jellison Sydney S SS Heinzman Jonathan T JT Dahlstrom Elijah B EB Duncan Gabrielle N GN Gaul Lindsey N LN Wanzek Robert J RJ Cramer Ellyn M EM Wimmel Charlotte G CG Sabbagh Sayeh S Yuki Kumi K Weckmann Michelle T MT Yamada Thoru T Karam Matthew D MD Noiseux Nicolas O NO Shinozaki Eri E Cho Hyunkeun R HR Lee Sangil S Cromwell John W JW

The Journal of clinical psychiatry 20190903 5

<h4>Background</h4>Delirium is common and dangerous, yet underdetected and undertreated. Current screening questionnaires are subjective and ineffectively implemented in busy hospital workflows. Electroencephalography (EEG) can objectively detect the diffuse slowing characteristic of delirium, but it is not suitable for high-throughput screening due to size, cost, and the expertise required for lead placement and interpretation. This study hypothesized that an efficient and reliable point-of-car ...[more]

PMID: 31483958

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Project description:Complications of delirium and dementia increase mortality; however, it is difficult to diagnose delirium accurately, especially among dementia patients. The bispectral electroencephalography score can detect delirium and predict mortality in elderly patients. We aimed to develop an efficient and reliable bispectral electroencephalography device for high-throughput screening. We also hypothesized that bispectral electroencephalography score can predict mortality among dementia patients. A prospective cohort study was conducted between January 2016 and December 2018 to measure bispectral electroencephalography from elderly patients and correlate with outcomes. A total of 502 elderly (55 years old or older) patients with and without dementia were enrolled. For a replication of the utility of bispectral electroencephalography, mortalities between bispectral electroencephalography-positive and bispectral electroencephalography-negative group were compared. In addition, patients with and without dementia status were added to examine the utility of bispectral electroencephalography among dementia patients. The mortality within 180 days in the bispectral electroencephalography-positive group was higher than that of the bispectral electroencephalography-negative group in both the replication and the total cohorts. Mortality of those in the bispectral electroencephalography-positive group showed a dose-dependent increase in both cohorts. When the dementia patients showed bispectral electroencephalography positive, their mortality was significantly higher than those with dementia but who were bispectral electroencephalography-negative. Mortality within 30 days in the bispectral electroencephalography-positive group was significantly higher than that of the bispectral electroencephalography-negative group. The utility of the bispectral electroencephalography to predict mortality among large sample of 502 elderly patients was shown. The bispectral electroencephalography score can predict mortality among elderly patients in general, and even among dementia patients, as soon as 30 days.

Project description:BackgroundPostoperative delirium (POD) is the most common postoperative complication in elderly patients, especially in older aged patients (aged 75 years or over). The development of electroencephalography analysis could provide indicators for early detection, intervention, and evaluation. If there are pathophysiological changes in the brain, the BIS value will also change accordingly. In this study, we investigated the predictive value of the preoperative bispectral (BIS) index in POD for patients aged over 75 years.MethodsIn this prospective study, patients (≥ 75 years) undergoing elective non-neurosurgery and non-cardiac surgery under general anesthesia were included (n = 308). Informed consent was obtained from all involved patients. Before the operation and during the first 5 postoperative days, delirium was assessed with the confusion assessment method by trained researchers twice every day. Thereafter, the preoperative bedside BIS of each patient was dynamically acquired by the BIS VISTA monitoring system and the BIS monitoring of electrodes. A series of evaluation scales were assessed before and after surgery. A preoperative predictive score was generated according to the results of multivariable logistic regression. The receiver operating characteristic curves were drawn and the area under the curves was estimated to evaluate the perioperative diagnostic values of BIS and preoperative predictive score for POD. The specificity, sensitivity, positive predictive value (PPV), and negative predictive (NPV) value were calculated.ResultsDelirium occurred in 50 of 308 (16.2%) patients. The median BIS of delirious patients was 86.7 (interquartile range [IQR] 80.0-94.0), lower than that of the non-delirious 91.9 (IQR 89.7-95.4, P < 0.001). According to the ROC curve of the BIS index, the optimal cut-off value was 84, with a sensitivity of 48%, specificity of 87%, PPV 43%, NPV 89% for forecasting POD and the area under curves was 0.67. While integrating BIS, mini-mental state examination, anemia, activities of daily living, and blood urea nitrogen, the model had a sensitivity of 78%, specificity of 74%, PPV of 0.37%, and NPV of 95% for forecasting POD, and the area under curves was 0.83.ConclusionsPreoperative bedside BIS in delirium patients was lower than that in non-delirium patients when undergoing non-neurosurgery and non-cardiac surgery in patients aged over 75. The model of integrating BIS, mini-mental state examination, anemia, activities of daily living, and blood urea nitrogen is a promising tool for predicting postoperative delirium in patients aged over 75.

Project description:Background: The difficulty in timely evaluating patient response to antidepressants has brought great challenge to the treatment of major depressive disorder (MDD). Some studies found that the electroencephalogram (EEG) microstates might be a reliable marker to evaluate patient response to treatment. The present study aims to evaluate the relationship between EEG microstate parameters and MDD symptoms before and after treatment to identify predictive biological markers for patient response. Methods: Thirty drug-naïve MDD patients (20 females and 10 males) were enrolled in this study. All the patients received effective dosages of selective serotonin reuptake inhibitors, and EEG recordings were collected at baseline and 2 weeks of treatment. Brain activities during the eyes-closed state were recorded using 64-channel electroencephalography, and the patients' microstates were clustered into four maps according to their topography (labeled A, B, C, and D). The differences of EEG microstates before and after treatment were compared using paired t-test. Spearman correlation coefficients were calculated to identify the relationships between the improvement of depression and anxiety symptoms and microstate parameters. Results: The mean duration (69.67 ± 10.33 vs. 64.00 ± 7.70, p < 0.001) and occurrence (4.06 ± 0.69, vs. 3.69 ± 0.70, p = 0.002) of microstate B decreased significantly after treatment. The proportion of microstate B also decreased (27.53 ± 5.81, vs. 23.23 ± 4.61, p < 0.001), while the occurrence of microstate A increased after treatment. A significant negative correlation was found between the change of score of Hamilton Rating Scale for Anxiety and the increase of the occurrence of microstate A (r = -0.431, p < 0.05) after 2 weeks of treatment. The reduction of the duration of microstate B was found to be predictive of patient response to antidepressants after 3 months. Conclusion: This study explored the relationship between changes of EEG microstates and patient response to antidepressants. Depression symptoms might be associated with the duration of microstate B and anxiety symptoms related to the occurrence of microstate A. Therefore, the duration of microstate B and the occurrence of microstate A are potential biological markers for MDD patients' early response and further clinical outcomes.

Dataset Information

Identification of Patients With High Mortality Risk and Prediction of Outcomes in Delirium by Bispectral EEG.

Publications

Identification of Patients With High Mortality Risk and Prediction of Outcomes in Delirium by Bispectral EEG.

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