Devices for providing a parameter indicating an increased likelihood of postoperative delirium.

Abstract

Device for providing a parameter indicating an increased probability of the occurrence of postoperative delirium, wherein the device comprises: - Means (2) designed and equipped to record at least one EEG signal at the patient's head, - Means (2) which are designed and equipped to determine the intraoperative alpha-peak frequency of the EEG signal, wherein the alpha-peak frequency in the power spectrum of the EEG signal is the frequency in the alpha band at which the power is greatest, - Means (2) that are designed and equipped to check whether the determined intraoperative alpha-peak frequency is significantly lower than a predetermined reference value of the alpha-peak frequency, - Means (2) that are designed and equipped to provide appropriate information as a parameter indicating an increased probability of the occurrence of postoperative delirium.

Description

[0001] The invention relates to devices for providing a parameter that indicates an increased probability of the occurrence of postoperative delirium.

[0002] Postoperative delirium (POD) is a common postoperative complication, particularly in older adults, leading to prolonged hospital stays, cognitive decline, a reduced quality of life after surgery, and increased mortality for up to one year postoperatively. Predicting which patients are at increased risk of developing POD is based on the analysis of risk profiles (advanced age, reduced preoperative cognitive abilities, etc.). However, creating a risk profile is not very specific and does not accurately reflect the actual, individual risk of each patient.

[0003] The recording of brain waves using surface electrodes as part of electroencephalography (EEG) was first described at the beginning of the last century. Initially, EEG oscillations were evaluated visually, with a focus primarily on epileptic potentials, sleep stage classification, and coma depth assessment, up to and including the determination of brain death. The introduction of computer-based EEG analysis software has significantly improved the evaluation and reliability of the findings. The use of EEG data for anesthesia management is now a common practice.

[0004] In electroencephalography, different EEG frequency bands are distinguished. Within the scope of this patent application, the following definitions for the EEG frequency bands are used: Delta band: 1.5 to 4 Hz; Theta band: 4 to 12 to 35 Hz; Gamma band: > 35 Hz.

[0005] It is also known that an individual's alpha frequency can be characterized by determining the so-called alpha peak frequency (aFP). This is the frequency in the alpha band with the highest power, i.e., in the power spectrum of an EEG signal, the frequency at which the power or squared amplitude in the alpha band is maximal. Gu Y, Chen J, Lu Y, Pan S.: “Integrative Frequency power of EEG correlates with progression of mild cognitive impairment to dementia in Parkinson's disease”, Clin EEG Neurosci. 2016; 47 (2): 113-117, report that the alpha peak frequency correlates with cognitive abilities.

[0006] FM Radtke, M. Franck, J. Lendner, S. Krüger, KD Wernecke, CD Spies: “Monitoring depth of anaesthesia in a randomized trial decreases the rate of postoperative delirium but not postoperative cognitive dysfunction”, BJA: British Journal of Anaesthesia, Volume 110, Issue suppl_1, 1 June 2013, Pages i98-i105, describe how the incidence of postoperative delirium can be significantly reduced by EEG-based neuromonitoring of the depth of anesthesia. The depth of anesthesia is measured using EEG analysis to allow for more precise anesthesia and thus reduce the incidence of postoperative delirium. M. Kreuzer, “EEG based monitoring of general anesthesia: taking the next steps.” Frontiers in computational neuroscience, 2017, Vol. 11; Page 56 reveals a procedure in which EEG recordings are reviewed during surgical interventions.

[0007] The present invention is based on the objective of providing methods and devices that provide information enabling a physician or anesthesiologist to better assess the probability of a postoperative delirium occurring.

[0008] This problem is solved by a device having the features of claim 1 and a device having the features of claim 10. Embodiments of the invention are specified in the dependent claims.

[0009] In a first aspect of the invention, a device is provided for supplying a parameter indicating an increased probability of postoperative delirium, the device comprising: - means for acquiring at least one EEG signal at the patient's head, - means for determining the intraoperative alpha-peak frequency of the EEG signal, wherein the alpha-peak frequency in the power spectrum of the EEG signal is the frequency in the alpha band at which the power is greatest, - means for checking whether the determined intraoperative alpha-peak frequency is significantly lower than a predetermined reference value of the alpha-peak frequency, - means for supplying corresponding information as a parameter indicating an increased probability of postoperative delirium.

[0010] If the intraoperative alpha peak frequency is significantly lower than the predefined reference value, this information is provided as a parameter, indicating an increased probability of postoperative delirium. A physician can use this parameter, in conjunction with other parameters, to decide whether to initiate early therapeutic treatment for the patient.

[0011] It should be noted that the step of checking whether the intraoperative alpha peak frequency is significantly lower than a predefined reference value involves calculating the difference between the predefined reference value and the intraoperative alpha peak frequency. If this difference meets certain criteria, e.g., is greater than a predefined value, the intraoperative alpha peak frequency is considered "significantly" lower than a predefined reference value. Furthermore, it should be noted that the parameter indicating an increased probability of postoperative delirium is precisely that which indicates a significantly lower intraoperative alpha peak frequency than the predefined reference value.

[0012] It is further pointed out that, according to one embodiment of the invention, the test to determine whether the specific intraoperative alpha-peak frequency is significantly lower than a predetermined reference value can be carried out using machine learning, wherein an artificial system learns from examples of a significantly lower intraoperative alpha-peak frequency and can generalize these examples after the learning phase has ended, recognizing patterns and regularities in the learning data.

[0013] The invention is based on the surprising finding that the intraoperatively determined alpha-peak frequency, or its deviation from a reference value, can provide a parameter with which the development of postoperative delirium can be predicted or at least better assessed. This enables early therapeutic intervention, which could prevent or reduce the sometimes serious complications in patients suffering from postoperative delirium.

[0014] Since this is a device-based examination that is easy to implement in everyday clinical practice, the invention can significantly increase diagnostic accuracy. According to the invention, a warning can be issued intraoperatively, allowing for the initiation of supportive therapeutic measures. The patient can also be treated accordingly in the recovery room and on the ward where they continue to receive care, and their further progress can be carefully monitored.

[0015] One embodiment of the invention provides that the predetermined reference value is determined by averaging the measured intraoperative alpha-peak frequencies of a plurality of patients who did not develop postoperative delirium. It may be provided that the reference value is predetermined depending on the patient's age group. Thus, for example, a first reference value for a first age group (e.g., 65-70 years) is determined by averaging the intraoperative alpha-peak frequencies measured in a plurality of patients of this first age group. A second reference value for a second age group (e.g., 70-80 years) is determined by averaging the intraoperative alpha-peak frequencies measured in a plurality of patients of this second age group.By selecting a reference value that depends on a specific age group, the probability of correctly predicting the occurrence of postoperative delirium is improved. However, it should be noted that determining the reference value based on age group is only one embodiment of the invention.

[0016] Further implementations may stipulate that the specified reference value is determined by considering the measured intraoperative alpha peak frequencies of a majority of patients who did not develop postoperative delirium, as well as by considering the measured intraoperative alpha peak frequencies of a majority of patients who did develop postoperative delirium. This allows the typical frequency difference of the alpha peak between patients who develop postoperative delirium and those who do not to be taken into account when determining the reference value.

[0017] Another embodiment of the invention provides that the intraoperative alpha-peak frequency is determined at a time when the patient is under stable anesthesia. For example, the intraoperative alpha-peak frequency is measured 15 minutes after intubation or the onset of unconsciousness. However, these values ​​are only examples.

[0018] It may be planned that the patient's intraoperative alpha-peak frequency is measured multiple times over a defined intraoperative time window and an average value is calculated.

[0019] As explained, the device according to the invention checks whether the intraoperative alpha peak frequency is significantly lower than a predetermined reference value for the alpha peak frequency and, if so, outputs corresponding information as a parameter. A significantly lower alpha peak frequency exists, for example, if the difference between the predetermined reference value and the intraoperative alpha peak frequency exceeds a defined percentage deviation from the reference value or a defined absolute difference between the intraoperative alpha peak frequency and the reference value. In the first case, for example, it is checked whether the intraoperative alpha peak frequency deviates from the reference value by at least X%, for example, at least 10%.In the second case, for example, it is checked whether the frequency difference between the intraoperative alpha peak frequency and the reference value exceeds a predefined value, for example 1 Hertz.

[0020] According to the invention, a frontal EEG signal is preferably recorded, i.e., a frontal recording is made, wherein the EEG signal is measured at at least two electrodes that are arranged at different locations on the patient's forehead. It may be provided that several frontal EEG signals are recorded and averaged to determine the alpha peak frequency. In the typically used 10-20 system, for example, signals are recorded from electrodes positioned at F7, F8, Fp1, Fp2, and Fpz.

[0021] A bipolar recording (difference between two active electrodes) or a unipolar recording (difference between several active electrodes against a common reference) can be performed.

[0022] Another approach involves determining the intraoperative alpha-peak frequency from the EEG signal after it has been filtered through a bandpass filter. The bandpass filter is configured, for example, to allow only signals in the frequency range of 0.5–40 Hz to pass through.

[0023] In a second aspect of the invention, the invention relates to a device for providing a parameter indicating an increased probability of postoperative delirium, the device comprising: - means for acquiring at least one EEG signal at the patient's head, - means for determining the power of the alpha band of the EEG signal, wherein the power of the alpha band in the power spectrum of the EEG signal is defined as the integral of the power over all frequencies in the alpha band, - wherein a first power of the alpha band is determined at a preoperative time point prior to the administration of an anesthetic-inducing drug, and a second power of the alpha band is determined at an intraoperative time point prior to the onset of anesthetic-induced unconsciousness, - means for checking whether the increase in the power of the alpha band from the first power point to the second power point is below a predefined level.- Means of providing relevant information as a parameter indicating an increased probability of postoperative delirium occurring.

[0024] The procedure involves measuring an initial alpha-band level preoperatively, before the administration of an anesthetic, and a second alpha-band level intraoperatively, after the onset of anesthetic-induced unconsciousness. The procedure then assesses whether the increase in alpha-band level between the first and second measurements falls below a predefined threshold. If so, this information is used as a parameter indicating an increased likelihood of postoperative delirium.

[0025] The second aspect of the invention is based on the fundamental fact that alpha-band activity increases during anesthesia. This is because intraoperative activation of GABA neurons in the frontal lobe leads to alpha activation. The invention has now revealed the surprising correlation that alpha-band activity increases less under anesthesia in patients who develop postoperative delirium than in patients who do not. In other words, in patients who develop postoperative delirium, the increase in alpha-band activity from the first (preoperative) to the second (intraoperative) level is below a predefined threshold (which, in extreme cases, even includes a decrease in alpha-band activity from preoperative to intraoperative).

[0026] It is noted that, according to one embodiment of the invention, the test to determine whether the increase in alpha band power from the first power to the second power is below a predefined level can be carried out using machine learning, wherein an artificial system learns from examples of reduced increases in alpha band power and can generalize these examples after the learning phase has ended, recognizing patterns and regularities in the learning data.

[0027] The second aspect of the invention also offers the advantage that, since it is a device-based examination that is easy to implement in everyday clinical practice, diagnostic accuracy can be significantly increased. A warning can be issued intraoperatively, allowing for the initiation of supportive therapeutic measures. The patient can also be treated accordingly in the recovery room and on the ward where they continue to receive care, and their further progress can be carefully monitored.

[0028] The second aspect of the invention can be realized independently of the first aspect of the invention or in combination with it.

[0029] One embodiment of the second aspect of the invention provides that the predefined level, below which the increase in alpha-band power from the first level to the second level must lie in order for the information to be provided, is determined by: - ​​comparing the average first alpha-band power with the average second alpha-band power for a number of patients who have not developed postoperative delirium, thereby establishing a first reference value; - comparing the average first alpha-band power with the average second alpha-band power for a number of patients who have developed postoperative delirium, thereby establishing a second reference value; - establishing the predefined level based on the difference between the first reference value and the second reference value.

[0030] The assessment of the difference in alpha-band performance of a patient between preoperative and intraoperative measurements, to determine whether a condition exists that increases the likelihood of postoperative delirium, is thus based on reference values. These reference values ​​form the basis for the relevant "predefined measure." The reference values ​​are determined from patients who did not develop postoperative delirium or who did develop postoperative delirium.

[0031] The comparison of the averaged first power of the alpha band with the averaged second power of the alpha band to form the first and second reference values ​​can be done, for example, by calculating the difference or a quotient of these values.

[0032] One implementation stipulates that the predefined measure is calculated as the difference between the first and second reference values, plus a percentage or absolute tolerance value. The percentage tolerance value can, for example, correspond to the standard deviation.

[0033] Another approach involves determining the predefined measure based on the patient's age group. For example, reference values ​​are established for a first age group (e.g., 65-70 years) and a second age group (e.g., 70-80 years). For each patient under consideration, the reference values ​​for their age group are used, thus improving the probability of correctly predicting the onset of postoperative delirium.

[0034] Another approach involves determining the first and second alpha band powers, as well as the increase in alpha band power from the first to the second power, in dB. Furthermore, the threshold below which this increase must fall for the information to be considered valid and verifiable is also specified in dB. Modern EEG anesthesia monitors directly output these corresponding power values ​​in dB, making them readily available.

[0035] One embodiment provides that the increase in the power of the alpha band from the first power to the second power must be below 15 dB, in particular below 12 dB, in order for the information to be provided or the parameter to be generated.

[0036] In the second aspect of the invention, the power of the alpha band is also determined according to one embodiment of the device using an EEG signal after it has been filtered by a bandpass filter. Preferably, at least one frontal EEG signal is acquired at the patient's head, and it may be possible to acquire several frontal EEG signals from the patient, which are then averaged to determine the power of the alpha band. For example, the signal is recorded from electrodes positioned at F7, F8, Fp1, Fp2, and Fpz in the 10-20 system.

[0037] The methods according to the invention are automated, in particular by a computer program.

[0038] The aforementioned means can be implemented by a microprocessor in conjunction with program code that the microprocessor executes. The parameter mentioned is, for example, displayed on a monitor.

[0039] In a further aspect of the invention, the invention relates to an EEG anesthesia monitor with a device according to claim 1 and / or with a device according to claim 10. The device according to the invention is thus integrated into an EEG anesthesia monitor, which is designed and configured to analyze EEG data in real time.

[0040] The invention is explained in more detail below with reference to the figures in the drawing, using several exemplary embodiments. The figures show: Fig. 1. Exemplary EEG signals in the waking state and after anesthesia-induced unconsciousness, each both as a time-dependent signal and in the power spectrum; Fig. 2. As an example of the range of services, the intraoperative alpha-peak frequency is measured for both a patient group that has not developed postoperative delirium (nonPOD) and a patient group that has developed postoperative delirium (POD); Fig. 3. For example, the difference between the preoperative and intraoperative alpha band power measured in dB, where the alpha band power was measured for both a patient group that did not develop postoperative delirium (nonPOD) and a patient group (POD) that did develop postoperative delirium; Fig. 4 a flowchart of an initial procedure for providing a parameter indicating an increased probability of postoperative delirium occurring; Fig. 5 a flowchart of a second procedure for providing a parameter indicating an increased probability of postoperative delirium occurring; Fig. 6. By way of example, a device for carrying out the procedures of Fig. 4 and / or 5; and Fig. 7 positioning points for EEG electrodes according to the 10-20 system.

[0041] The invention comprises two variants, one variant of which considers the determination of the intraoperative alpha peak frequency of a patient and the second variant of which considers the determination of the difference between the preoperative and intraoperative performance of the alpha band of a patient.

[0042] Based on the Fig. 1 and Fig. 2. The connection first identified according to the first embodiment of the invention, which has been demonstrated by a study, is explained. Based on the Fig. 1 and Fig. 3 explains the connection first recognized according to the second variant of the invention, which has also been proven by a study.

[0043] The Fig. Figure 1 shows, to illustrate the background of the invention, an EEG signal as it occurs in a waking patient in the upper diagram (“baseline”). The signal is shown both as a time signal (left) and, after spectral analysis, as a power spectrum (right). In the power spectrum, the power (the square of the amplitude) in µV² is plotted against the frequency in Hz. The power spectrum represents the respective contribution of each frequency range to the total power component of the raw signal.

[0044] The lower illustration (“Anesthesia”) of the Fig. Figure 1 shows an EEG signal under anesthesia. It is evident that the overall frequency spectrum is shifted to the left compared to the value in the awake patient. Specifically, under anesthesia, there is an increase in frequencies from the delta, theta, and alpha bands, while the beta and gamma waves decrease. (See Purdon PL, Pierce ET, Mukamel EA, Prerau MJ, Walsh JL, Wong KFK, Salazar-Gomez AF, Harrell PG, Sampson AL, Cimenser A, Ching S, Kopell NJ, Tavares-SToeckel C, Habeeb K, Merhar R, Brown E.: “Electroencephalogram signatures of loss and recovery of consciousness from propofol”, PNAS 2013;) 110 (12): E1142-1151, showed that deep unconsciousness induced by GABA-activating anesthetics leads to frontal alpha band activation.

[0045] The Fig. Figure 2 shows the intraoperative alpha peak frequency in the power spectrum, plotted against frequency in dB, for both a patient group that did not develop postoperative delirium and a patient group that did. The alpha peak frequency is defined as the frequency in the alpha band at which the power is greatest.

[0046] A prospective observational study demonstrated that the intraoperative alpha peak frequency is higher in patients who do not develop postoperative delirium (non-POD patients) than in patients who do develop postoperative delirium (POD patients). The alpha peak frequency α P1 In the figure, the alpha peak frequency for non-POD patients is 10.1 Hertz. In POD patients, the alpha peak frequency α is... P2at 8.8 Hertz, and therefore significantly lower. The standard deviation of the value at 10.1 Hertz was 0.77 Hertz. The standard deviation of the value at 8.8 Hertz was 0.87 Hertz.

[0047] The study was conducted on a patient group consisting of 11 POD patients and 11 non-POD patients. It was thus demonstrated that the intraoperative alpha-peak frequency is significantly lower in POD patients than in non-POD patients.

[0048] The Fig. Figure 3 shows a diagram illustrating the difference between the preoperative and intraoperative alpha-band power, measured in dB, for a non-POD patient group and a POD patient group. A prospective observational study demonstrated that the alpha-band power increases less sharply from preoperative to intraoperative in POD patients than in non-POD patients. Thus, according to the Fig. 3. The mean difference Δ from intraoperative to preoperative measurement for non-POD patients is approximately 21 dB. For POD patients, this mean value is approximately 10 dB, and thus significantly lower. The standard deviation for non-POD patients was approximately 13 dB. The standard deviation for POD patients was approximately 11.5 dB. The standard deviation is in the Fig. 3 also shown.

[0049] The study was conducted on a patient group consisting of 19 POD patients and 35 non-POD patients, with anesthesia induction using one of the most commonly used anesthetics, namely propofol. It was thus demonstrated that the increase in EEG signal intensity in the alpha band from preoperative to intraoperative time was significantly reduced in POD patients, and consequently, the difference in alpha band intensity between intraoperative and preoperative time was significantly smaller in POD patients. The measurements according to Fig. 2 and Fig. 3 were carried out as follows: a) EEG recording:

[0050] A continuous intraoperative EEG was recorded using an EEG-based brain function monitor (the "SEDLine Monitor" from Masimo Corporation, Irvine, California) from the start of anesthesia until its end. Surface EEG adhesive electrodes (Masimo, 4248RD SEDLine Sensor, Single Patient Use, Non-Sterile) were placed at positions F7, F8, FP1, and FP2 according to the 10 / 20 system, with Fpz as the ground electrode and the reference electrode approximately 1 cm above Fpz. The patient's forehead and temples were thoroughly disinfected and freed of skin oils. The impedance of each electrode was less than 5 kΩ, and the sampling rate was 250 Hz.

[0051] After attaching the adhesive electrodes to the EEG-based brain function monitor, continuous 4-channel EEG recording was initiated. The patients were still awake at this point, so the initial recordings represented baseline activity. To define specific time points during the EEG recording, "event markers" were manually inserted into the EEG. Event markers: "Baseline" = awake patient, before administration of anesthetic; "Start of Anesthesia" = commencement of anesthetic administration; "Loss of Consciousness" = absence of eyelid reflex; "ITN" = intubation of the patient; "OP" = stable intraoperative phase 15-30 minutes after ITN. All patients received intravenous propofol for induction of anesthesia; maintenance was achieved with intravenous propofol or with the inhalation anesthetics desflurane or sevoflurane. The recorded EEG data were exported from the SEDLine monitor. b) EEG evaluation:

[0052] The raw EEG data were processed with a bandpass filter of 0.5–40 Hz (Brain Vision Analyzer software). Subsequently, a visual EEG data analysis was performed, selecting a 10-second artifact-free EEG time window at both the "Baseline" and "OP" time points. The EEG data were segmented into a "Baseline" and an "Intraoperative" EEG. Further data analysis was performed using the Chronux Toolbox (Bookil et al., 2010) for Matlab (The MathWorks, Inc., Natick, Massachusetts, United States). The power spectrum across all frequency bands (slow and fast delta, theta, alpha, beta) was calculated using a multitaper method with 2-second time windows, 1.9-second overlap, a time-bandwidth product (TW) of 3, a number of tapers (K) of 5, and a spectral resolution of 2W = 3 Hz. The calculation was performed using digital, computer-aided EEG signal processing.This is based on the spectral analysis of the raw EEG using Fast Fourier Transform, which allows the calculation of power components for the current time window being analyzed. The data were then transformed into a decibel scale. Power(dB)=10log10(Power(μ))

[0053] To better represent frontal EEG power, a pooled frontal electrode was calculated, incorporating the equally weighted signals from electrodes Fp1, Fp2, F7, and F8. Based on the resulting spectra, the peak frequency (Hz) in the alpha band (8-12 Hz) (aPF) was determined accordingly. Fig. 2. Furthermore, the difference between the signal strength in the alpha band between intraoperative and preoperative was determined according to the Fig. 3 calculated (difference of alpha-band power operation to alpha-band power baseline). c) Delirium Screening:

[0054] Following surgery, delirium scoring was performed regularly from the time of admission to the recovery room. Postoperative delirium was defined according to the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders) criteria. During the patient's stay in the recovery room, the Nurse Detection Score (NuDESC) was recorded at regular intervals. All patients with a NuDESC score ≥ 2 at any time during their stay in the recovery room were classified as having postoperative delirium (POD group), and patients with a NuDESC score < 1 were classified as not having postoperative delirium (non-POD group). d) Statistical analysis: Statistical calculations of the alpha peak frequency and the difference between the alpha-band power during surgery and the alpha-band power baseline were performed using SPSS, version 24 (Copyright SPSS, Inc., Chicago, IL 60606, USA) with the Mann-Whitney U test and the Kruskal-Wallis test.

[0055] According to the invention, the determined correlations are evaluated electronically or by computer and used to determine the intraoperative alpha-peak frequency or the degree of increase in the power of the EEG signal in the alpha band from preoperative to intraoperative in a patient. The associated program can be integrated as a software tool into an EEG-based brain function monitor or electroencephalograph.

[0056] The Fig. Figure 4 shows the procedure for determining a parameter indicating a loss of consciousness in a patient under anesthesia. According to step 401, at least one frontal EEG signal is recorded from a patient. For example, four EEG signals are recorded via electrodes at positions F7, F8, FP1, and FP2 according to the 10 / 20 system, with Fpz as the reference electrode, and these signals are averaged. An additional grounding electrode is placed slightly above Fpz.

[0057] In step 402, the intraoperative alpha peak frequency of the EEG signal is then determined. This is done when the patient is under stable anesthesia, approximately 15–30 minutes after the onset of unconsciousness. Next, it is checked whether the measured intraoperative alpha peak frequency is significantly lower than a predefined reference value. This reference value was determined by averaging the measured intraoperative alpha peak frequencies of a number of patients who did not develop postoperative delirium. The reference value is selected based on the patient's age group.The currently determined intraoperative alpha-peak frequency is significantly lower than the specified reference value, for example, if the difference between the specified reference value and the measured intraoperative alpha-peak frequency exceeds a defined percentage deviation from the reference value or a defined absolute difference between the intraoperative alpha-peak frequency and the reference value. According to the values ​​of the . Fig. 2. The reference value is 10.1 Hertz and a significant deviation is assumed, for example, if the measured value of the alpha peak frequency is below 9.5 Hertz.

[0058] In this case, according to step 404, corresponding information is provided as a parameter indicating an increased probability of the occurrence of postoperative delirium.

[0059] The Fig. Figure 4 shows the procedure for determining a parameter that indicates a loss of consciousness in a patient under anesthesia. According to step 501, at least one frontal EEG signal is again recorded from a patient. For example, four EEG signals are recorded via electrodes at positions F7, F8, FP1, and FP2 according to the 10 / 20 system, with Fpz as the reference electrode, and these signals are averaged.

[0060] According to step 502, the power of the alpha band of the EEG signal is then determined, where the power of the alpha band in the power spectrum of the EEG signal is defined as the integral of the power over all frequencies in the alpha band. Thus, according to step 503, a first power of the alpha band is determined at a preoperative time point, before the administration of an anesthetic-inducing drug, and a second power of the alpha band is determined at an intraoperative time point, after the onset of anesthetic-induced unconsciousness.

[0061] The next step is to check whether the increase in alpha band power from the first to the second measurement is below a predefined threshold. This predefined threshold is established, for example, based on reference values ​​measured in POD and non-POD patients. The predefined threshold could be, for instance, a specific dB value by which the alpha band power may increase from preoperative to intraoperative levels for statistical significance to be reached. According to the values ​​of the Fig. For example, if the specified threshold is 15 dB, meaning that if the power in the alpha band increases by less than 15 dB from preoperative to intraoperative, significance is assumed, then, according to step 505, corresponding information is provided as a parameter that indicatively suggests the onset of postoperative delirium.

[0062] To carry out the two procedures in accordance with the Fig. 3 and Fig. 4. An EEG-based brain function monitor or, more generally, a computer can be used. The procedural steps for determining the intraoperative alpha peak frequency and comparing it with the reference value ( Fig. 3) The tasks for determining the alpha band power of the EEG signal and for verifying whether the increase in alpha band power from the first to the second measurement is below a predefined threshold are performed by program code executed in a processor. This program code is stored in the processor's memory or is loaded into it before execution. The processor executing the program code can be the main processor of the EEG monitor or a separate processor.

[0063] The Fig. Figure 6 shows an example of a possible implementation of such an EEG-based brain function monitor 1. The EEG monitor 1 includes a microprocessor 2, a memory 3, a control unit 4, an output unit 5 and an interface 7 for connecting EEG cables.

[0064] EEG cables with EEG electrodes 61, 62 can be connected to the EEG monitor 1 via interface 7. Two EEG cables are shown as examples, each receiving an EEG signal; additional EEG cables may be provided for receiving a multi-channel EEG signal.

[0065] The EEG signal is fed to microprocessor 2. The program code is stored in memory 3, or program code can be loaded into memory 3 which, when executed in microprocessor 2, determines the behavior related to the... Fig. 4 and / or that in relation to the Fig. The procedure described in section 5 is executed. The process can be controlled via the control unit 4, which can be configured to receive corresponding input commands. The control unit 4 can be a main processor of the EEG monitor 1 or contain one. Alternatively, the functionality of the microprocessor 2 can be taken over by the control unit 4. Further functionalities of the EEG monitor 1 can be implemented via the control unit 4 and / or other modules not shown.

[0066] During execution of the loaded program code, the microprocessor 2 determines the intraoperative alpha peak frequency, compares it to a reference value, and determines whether the determined intraoperative alpha peak frequency is significantly lower than a predefined reference value. The corresponding information is transmitted to the output unit 5 and displayed there. This can be done, for example, via a monitor 51 and / or an acoustic unit 52.

[0067] Alternatively or additionally, microprocessor 2 evaluates the performance in the alpha band according to the following when executing the loaded program code: Fig.5. This checks whether the increase in alpha band power from preoperative to intraoperative power remains below a predefined threshold. The corresponding information is transmitted to output unit 5 and displayed there. This can be done via monitor 51 and / or acoustic unit 52.

[0068] It is understood that the invention is not limited to the embodiments described above and that various modifications and improvements can be made without deviating from the concepts described herein. Any of the features can be used separately or in combination with any other features, provided they are not mutually exclusive, and the disclosure extends to and includes all combinations and subcombinations of one or more features described herein. Where ranges are defined, these include all values ​​within those ranges as well as all sub-ranges that fall within a range.

Claims

[1] Device for providing a parameter indicating an increased probability of the occurrence of postoperative delirium, wherein the device comprises: - Means (2) designed and equipped to record at least one EEG signal at the patient's head, - Means (2) which are designed and equipped to determine the intraoperative alpha-peak frequency of the EEG signal, wherein the alpha-peak frequency in the power spectrum of the EEG signal is the frequency in the alpha band at which the power is greatest, - Means (2) that are designed and equipped to check whether the determined intraoperative alpha-peak frequency is significantly lower than a predetermined reference value of the alpha-peak frequency, - Means (2) that are designed and equipped to provide appropriate information as a parameter indicating an increased probability of the occurrence of postoperative delirium. [2] Device according to claim 1, characterized by , that the specified reference value is determined by averaging the measured intraoperative alpha-peak frequencies of a majority of patients who did not develop postoperative delirium. [3] Device according to claim 2, characterized by that the specified reference value depends on the age group in which the patient is located. [4] Device according to any one of the preceding claims, characterized by , that the means (2) are provided and arranged to determine the intraoperative alpha peak frequency at a time when the patient is under stable anesthesia. [5] Device according to any of the preceding claims, characterized by, that the means (2) are provided and set up to ensure that the intraoperative alpha-peak frequency is significantly lower than a predetermined reference value of the alpha-peak frequency if the difference between the predetermined reference value and the intraoperative alpha-peak frequency exceeds a defined percentage deviation from the reference value or a defined absolute difference between the intraoperative alpha-peak frequency and the reference value. [6] Device according to one of the preceding claims, characterized by , that the means (2) are provided and set up to record at least one frontal EEG signal at the patient's head. [7] Device according to one of the preceding claims, characterized by , that the means (2) are provided and set up to record multiple frontal EEG signals of the patient, which are averaged to determine the alpha peak frequency. [8] Device according to any of the preceding claims, characterized by , that the means (2) are provided and set up to determine the alpha peak frequency of the EEG signal after it has been filtered through a bandpass filter. [9] Device according to any of the preceding claims, characterized by that furthermore - the means (2) are provided and set up to determine the power of the alpha band of the EEG signal, wherein the power of the alpha band in the power spectrum of the EEG signal is defined as the integral of the power over all frequencies in the alpha band, - the means (2) are provided and set up to determine a first performance of the alpha band at a preoperative time point, prior to the administration of an anesthetic-inducing drug, and a second performance of the alpha band at an intraoperative time point, prior to the onset of anesthetic-induced unconsciousness, - the means (2) provided and established to check whether the increase in the power of the alpha band from the first power to the second power is below a predefined level, - the means (2) are provided and established to provide, in this case, appropriate information as a parameter indicating an increased probability of the occurrence of postoperative delirium. [10] Device for providing a parameter indicating an increased probability of the occurrence of postoperative delirium, wherein the device comprises: - Means (2) designed and equipped to record at least one EEG signal at the patient's head, - Means (2) which are designed and equipped to determine the power of the alpha band of the EEG signal, wherein the power of the alpha band in the power spectrum of the EEG signal is defined as the integral of the power over all frequencies in the alpha band, - wherein a first alpha-band performance is determined at a preoperative time point, prior to the administration of an anesthetic-inducing drug, and a second alpha-band performance is determined at an intraoperative time point, after the onset of anesthetic-induced unconsciousness, - Means (2) designed and equipped to check whether the increase in alpha band power from the first power to the second power is below a predefined level, the predefined level being determined depending on the age group in which the patient is located, - Means (2) which are designed and equipped to provide appropriate information as a parameter indicating an increased probability of the occurrence of postoperative delirium. [11] Device according to claim 10, characterized by , that the predefined level below which an increase in the power of the alpha band from the first power to the second power must lie in order for the information to be provided, is determined by means (2) by the fact that - for a majority of patients who did not develop postoperative delirium, the average first alpha-band power is compared with the average second alpha-band power, establishing an initial reference value, - for a majority of patients who have developed postoperative delirium, the average first alpha-band power is compared with the average second alpha-band power, forming a second reference value, - the predefined measure is formed based on the difference between the first reference value and the second reference value. [12] Device according to claim 11, characterized by , that the predefined measure is formed by the difference between the first reference value and the second reference value minus a percentage or absolute tolerance value. [13] Device according to any one of claims 10 to 12, characterized by, that the first power of the alpha band and the second power of the alpha band, as well as the increase in the power of the alpha band from the first power to the second power, is determined in dB, and the level below which an increase in the power of the alpha band from the first power to the second power must lie in order for the information to be provided and verified, is also given in dB. [14] Device according to any one of claims 10 to 13, characterized by , that the increase in alpha band power from the first power to the second power is below 15 dB, in particular below 12 dB, so that the information is provided. [15] Device according to any one of claims 10 to 14, characterized by , that the power of the alpha band is determined on the EEG signal after it has been filtered through a bandpass filter. [16] Device according to any one of claims 10 to 15, characterized bythat at least one frontal EEG signal is recorded at the patient's head. [17] Device according to any of the preceding claims, characterized by , that in the 10-20 system signals are derived from electrodes positioned at positions F7, F8, Fp1, Fp2 and Fpz. [18] EEG anesthesia monitor (1) with a device according to claim 1 and / or with a device according to claim 10.

Images