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Urdanibia-Centelles O, Nielsen RM, Rostrup E, Vedel-Larsen E, Thomsen K, Nikolic M, Johnsen B, Møller K, Lauritzen M, Benedek K. Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis. Clin Neurophysiol 2021; 132:2075-2082. [PMID: 34284242 DOI: 10.1016/j.clinph.2021.05.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 04/12/2021] [Accepted: 05/06/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVE In critical care, continuous EEG (cEEG) monitoring is useful for delirium diagnosis. Although visual cEEG analysis is most commonly used, automatic cEEG analysis has shown promising results in small samples. Here we aimed to compare visual versus automatic cEEG analysis for delirium diagnosis in septic patients. METHODS We obtained cEEG recordings from 102 septic patients who were scored for delirium six times daily. A total of 1252 cEEG blocks were visually analyzed, of which 805 blocks were also automatically analyzed. RESULTS Automatic cEEG analyses revealed that delirium was associated with 1) high mean global field power (p < 0.005), mainly driven by delta activity; 2) low average coherence across all electrode pairs and all frequencies (p < 0.01); 3) lack of intrahemispheric (fronto-temporal and temporo-occipital regions) and interhemispheric coherence (p < 0.05); and 4) lack of cEEG reactivity (p < 0.005). Classification accuracy was assessed by receiver operating characteristic (ROC) curve analysis, revealing a slightly higher area under the curve for visual analysis (0.88) than automatic analysis (0.74) (p < 0.05). CONCLUSIONS Automatic cEEG analysis is a useful supplement to visual analysis, and provides additional cEEG diagnostic classifiers. SIGNIFICANCE Automatic cEEG analysis provides useful information in septic patients.
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Affiliation(s)
- Olalla Urdanibia-Centelles
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Valdemar Hansens Vej 1-23, Glostrup, Denmark; Center for Healthy Aging and Department of Neuroscience, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark.
| | - Rikke M Nielsen
- Department of Neuroanesthesiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100 Copenhagen, Denmark
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Valdemar Hansens Vej 1-23, Glostrup, Denmark.
| | - Esben Vedel-Larsen
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Valdemar Hansens Vej 1-23, Glostrup, Denmark.
| | - Kirsten Thomsen
- Center for Healthy Aging and Department of Neuroscience, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark.
| | - Miki Nikolic
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Valdemar Hansens Vej 1-23, Glostrup, Denmark.
| | - Birger Johnsen
- Department of Clinical Neurophysiology, Aarhus University Hospital, Nørrebrogade 44, 8000 Aarhus C, Denmark.
| | - Kirsten Møller
- Department of Neuroanesthesiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100 Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200, Denmark.
| | - Martin Lauritzen
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Valdemar Hansens Vej 1-23, Glostrup, Denmark; Center for Healthy Aging and Department of Neuroscience, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark.
| | - Krisztina Benedek
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Valdemar Hansens Vej 1-23, Glostrup, Denmark.
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Nielsen RM, Urdanibia-Centelles O, Vedel-Larsen E, Thomsen KJ, Møller K, Olsen KS, Lauritsen AØ, Eddelien HS, Lauritzen M, Benedek K. Continuous EEG Monitoring in a Consecutive Patient Cohort with Sepsis and Delirium. Neurocrit Care 2020; 32:121-130. [PMID: 30891696 DOI: 10.1007/s12028-019-00703-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Delirium is common during sepsis, although under-recognized. We aimed to assess the value of continuous electroencephalography (cEEG) to aid in the diagnosis of delirium in septic patients. METHODS We prospectively evaluated 102 consecutive patients in a medical intensive care unit (ICU), who had sepsis or septic shock, without evidence of acute primary central nervous system disease. We initiated cEEG recording immediately after identification. The median cEEG time per patient was 44 h (interquartile range 21-99 h). A total of 6723 h of cEEG recordings were examined. The Confusion Assessment Method for the ICU (CAM-ICU) was administered six times daily to identify delirium. We analyzed the correlation between cEEG and delirium using 1252 two-minute EEG sequences recorded simultaneously with the CAM-ICU scorings. RESULTS Of the 102 included patients, 66 (65%) had at least one delirium episode during their ICU stay, 30 (29%) remained delirium-free, and 6 (6%) were not assessable due to deep sedation or coma. The absence of delirium was independently associated with preserved high-frequency beta activity (> 13 Hz) (P < 10-7) and cEEG reactivity (P < 0.001). Delirium was associated with preponderance of low-frequency cEEG activity and absence of high-frequency cEEG activity. Sporadic periodic cEEG discharges occurred in 15 patients, 13 of whom were delirious. No patient showed clinical or electrographic evidence of non-convulsive status epilepticus. CONCLUSIONS Our findings indicate that cEEG can help distinguish septic patients with delirium from non-delirious patients.
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Affiliation(s)
- Rikke M Nielsen
- Department of Neuroanesthesiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Olalla Urdanibia-Centelles
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
| | - Esben Vedel-Larsen
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Kirsten J Thomsen
- Department of Neuroscience, Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
| | - Kirsten Møller
- Department of Neuroanesthesiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Karsten S Olsen
- Department of Neuroanesthesiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anne Ø Lauritsen
- Department of Neuroanesthesiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Heidi S Eddelien
- Department of Neuroanesthesiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Martin Lauritzen
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
- Department of Neuroscience, Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.
| | - Krisztina Benedek
- Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
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Centelles OU, Nielsen RM, Vedel-Larsen E, Nikolic M, Benedek K, Lauritzen M. P33-T Visual vs. automatic cEEG signal analysis in patients with delirium. Clin Neurophysiol 2019. [DOI: 10.1016/j.clinph.2019.04.396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Vedel-Larsen E, Iepsen EW, Lundgren J, Graff C, Struijk JJ, Hansen T, Holst JJ, Madsbad S, Torekov S, Kanters JK. Major rapid weight loss induces changes in cardiac repolarization. J Electrocardiol 2016; 49:467-72. [PMID: 26925492 DOI: 10.1016/j.jelectrocard.2016.02.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Indexed: 11/20/2022]
Abstract
INTRODUCTION Obesity is associated with increased all-cause mortality, but weight loss may not decrease cardiovascular events. In fact, very low calorie diets have been linked to arrhythmias and sudden death. The QT interval is the standard marker for cardiac repolarization, but T-wave morphology analysis has been suggested as a more sensitive method to identify changes in cardiac repolarization. We examined the effect of a major and rapid weight loss on T-wave morphology. METHODS AND RESULTS Twenty-six individuals had electrocardiograms (ECG) taken before and after eight weeks of weight loss intervention along with plasma measurements of fasting glucose, HbA1c, and potassium. For assessment of cardiac repolarization changes, T-wave Morphology Combination Score (MCS) and ECG intervals: RR, PR, QT, QTcF (Fridericia-corrected QT-interval), and QRS duration were derived. The participants lost on average 13.4% of their bodyweight. MCS, QRS, and RR intervals increased at week 8 (p<0.01), while QTcF and PR intervals were unaffected. Fasting plasma glucose (p<0.001) and HbA1c both decreased at week 8 (p<10(-5)), while plasma potassium was unchanged. MCS but not QTcF was negatively correlated with HbA1c (p<0.001) and fasting plasma glucose (p<0.01). CONCLUSION Rapid weight loss induces changes in cardiac repolarization. Monitoring of MCS during calorie restriction makes it possible to detect repolarization changes with higher discriminative power than the QT-interval during major rapid weight loss interventions. MCS was correlated with decreased HbA1c. Thus, sustained low blood glucose levels may contribute to repolarization changes.
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Affiliation(s)
- Esben Vedel-Larsen
- Laboratory of Experimental Cardiology, Departtment of Biomedical Sciences, University of Copenhagen, Denmark; Danish National Research Foundation Centre for Cardiac Arrhythmia, Denmark; Department of Clinical Neurophysiology, Glostrup Hospital, Denmark
| | - Eva Winning Iepsen
- NNF Center for Basic Metabolic Research, University of Copenhagen, Denmark; Endocrinology Research Section, Department of Biomedical Sciences, University of Copenhagen, Denmark
| | - Julie Lundgren
- NNF Center for Basic Metabolic Research, University of Copenhagen, Denmark; Endocrinology Research Section, Department of Biomedical Sciences, University of Copenhagen, Denmark
| | - Claus Graff
- Department of Health Science and Technology, Aalborg University, Denmark
| | - Johannes J Struijk
- Department of Health Science and Technology, Aalborg University, Denmark
| | - Torben Hansen
- NNF Center for Basic Metabolic Research, University of Copenhagen, Denmark
| | - Jens Juul Holst
- NNF Center for Basic Metabolic Research, University of Copenhagen, Denmark; Endocrinology Research Section, Department of Biomedical Sciences, University of Copenhagen, Denmark
| | - Sten Madsbad
- Department of Endocrinology, Hvidovre Hospital, Denmark
| | - Signe Torekov
- NNF Center for Basic Metabolic Research, University of Copenhagen, Denmark; Endocrinology Research Section, Department of Biomedical Sciences, University of Copenhagen, Denmark
| | - Jørgen K Kanters
- Laboratory of Experimental Cardiology, Departtment of Biomedical Sciences, University of Copenhagen, Denmark.
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Hong L, Andersen L, Graff C, Vedel-Larsen E, Wang F, Struijk J, Sogaard P, Hansen P, Yang Y, Christiansen M, Toft E, Kanters J. T-wave morphology analysis of competitive athletes. J Electrocardiol 2015; 48:35-42. [DOI: 10.1016/j.jelectrocard.2014.10.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Indexed: 12/09/2022]
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Wang F, Jensen BT, Abildstrom SZ, Vedel-Larsen E, Torp-Pedersen C, Olesen SP, Kanters JK. Subdivision of heart rate variability VLF band contains prognostic value of all-cause mortality after acute myocardial infarction. J Electrocardiol 2012. [DOI: 10.1016/j.jelectrocard.2012.08.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Haarmark C, Kyvik KO, Vedel-Larsen E, Budtz-Jørgensen E, Kanters JK. Heritability of Tpeak-Tend interval and T-wave amplitude: a twin study. ACTA ACUST UNITED AC 2011; 4:516-22. [PMID: 21836130 DOI: 10.1161/circgenetics.111.959551] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Tpeak-Tend interval (TpTe) and T-wave amplitude (Tamp) carry diagnostic and prognostic information regarding cardiac morbidity and mortality. Heart rate and QT interval are known to be heritable traits. The heritability of T-wave morphology parameters such as TpTe and Tamp is unknown. TpTe and Tamp were evaluated in a large sample of twins. METHODS AND RESULTS Twins from the GEMINAKAR study (611 pairs, 246 monozygotic, 365 dizygotic; mean age, 38±11 years; 49% men) who had an ECG performed during 1997 to 2000 were included. Tamp was measured in leads V1 and V5. Duration variables (RR interval, QTpeak and QTend interval) were measured and averaged over 3 consecutive beats in lead V5. TpTe was calculated as the QTend- and QTpeak-interval difference. Heritability was assessed using structural equation models adjusting for age, sex, and body mass index. All models were reducible to a model of additive genetics and unique environment. All variables had considerable genetic components. Adjusted heritability estimates were as follows: TpTe, 46%; Tamp lead V1, 34%; Tamp lead V5, 47%; RR interval, 55%; QT interval, 67%; and Bazett-corrected QT interval, 42%. CONCLUSIONS RR interval, QT interval, Tamp, and TpTe interval are heritable ECG parameters.
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Affiliation(s)
- Christian Haarmark
- Laboratory of Experimental Cardiology, University of Copenhagen, Copenhagen, Denmark
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Vedel-Larsen E, Fuglø J, Channir F, Thomsen CE, Sørensen HBD. A comparative study between a simplified Kalman filter and Sliding Window Averaging for single trial dynamical estimation of event-related potentials. Comput Methods Programs Biomed 2010; 99:252-260. [PMID: 20227130 DOI: 10.1016/j.cmpb.2009.12.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2008] [Revised: 10/01/2009] [Accepted: 12/18/2009] [Indexed: 05/28/2023]
Abstract
The classical approach for extracting event-related potentials (ERPs) from the brain is ensemble averaging. For long latency ERPs this is not optimal, partly due to the time-delay in obtaining a response and partly because the latency and amplitude for the ERP components, like the P300, are variable and depend on cognitive function. This study compares the performance of a simplified Kalman filter with Sliding Window Averaging in tracking dynamical changes in single trial P300. The comparison is performed on simulated P300 data with added background noise consisting of both simulated and real background EEG in various input signal to noise ratios. While both methods can be applied to track dynamical changes, the simplified Kalman filter has an advantage over the Sliding Window Averaging, most notable in a better noise suppression when both are optimized for faster changing latency and amplitude in the P300 component and in a considerably higher robustness towards suboptimal settings. The latter is of great importance in a clinical setting where the optimal setting cannot be determined.
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Affiliation(s)
- Esben Vedel-Larsen
- Department of Electrical Engineering, Technical University of Denmark, 2800, Lyngby, Denmark
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Vedel-Larsen E, Haarmark C, Graff C, Andersen MP, Toft E, Struijk JJ, Kanters J. T-wave morphology in long-QT syndrome. J Electrocardiol 2009. [DOI: 10.1016/j.jelectrocard.2009.08.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Haarmark C, Hansen PR, Vedel-Larsen E, Pedersen SH, Graff C, Andersen MP, Toft E, Wang F, Struijk JJ, Kanters JK. The prognostic value of the Tpeak-Tend interval in patients undergoing primary percutaneous coronary intervention for ST-segment elevation myocardial infarction. J Electrocardiol 2009; 42:555-60. [PMID: 19643432 DOI: 10.1016/j.jelectrocard.2009.06.009] [Citation(s) in RCA: 93] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2009] [Indexed: 01/07/2023]
Abstract
INTRODUCTION The Tpeak-Tend interval (TpTe) has been linked to increased arrhythmic risk. TpTe was investigated before and after primary percutaneous coronary intervention (pPCI) in patients with ST-segment elevation myocardial infarction (STEMI). METHOD Patients with first-time STEMI treated with pPCI were included (n = 101; mean age 62 years; range 39-89 years; 74% men). Digital electrocardiograms were taken pre- and post-PCI, respectively. Tpeak-Tend interval was measured in leads with limited ST-segment deviation. The primary end point was all-cause mortality during 22 +/- 7 months (mean +/- SD) of follow-up. RESULTS Pre- and post-PCI TpTe were 104 milliseconds [98-109 milliseconds] and 106 milliseconds [99-112 milliseconds], respectively (mean [95% confidence interval], P = .59). A prolonged pre-PCI TpTe was associated with increased mortality (hazard ratio, 10.5 [1.7-20.4] for a cutoff value of 100 milliseconds). Uncorrected QT and heart rate-corrected QT intervals (Fridericia-corrected QT) were prolonged after PCI (QT: 401 vs 410 milliseconds, P = .022, and Fridericia-corrected QT: 430 vs 448 milliseconds, P < .0001). CONCLUSION In patients with STEMI undergoing pPCI, pre-PCI TpTe predicted subsequent all-cause mortality, and the QT interval was increased after the procedure.
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Affiliation(s)
- Christian Haarmark
- Laboratory of Experimental Cardiology, University of Copenhagen, Copenhagen, Denmark
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Kanters JK, Haarmark C, Vedel-Larsen E, Andersen MP, Graff C, Struijk JJ, Thomsen PEB, Christiansen M, Jensen HK, Toft E. TpeakTend interval in long QT syndrome. J Electrocardiol 2008; 41:603-8. [DOI: 10.1016/j.jelectrocard.2008.07.024] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2008] [Revised: 07/04/2008] [Accepted: 07/05/2008] [Indexed: 12/17/2022]
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