WO2018131542A1 - 認知機能評価システム - Google Patents
認知機能評価システム Download PDFInfo
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- WO2018131542A1 WO2018131542A1 PCT/JP2018/000085 JP2018000085W WO2018131542A1 WO 2018131542 A1 WO2018131542 A1 WO 2018131542A1 JP 2018000085 W JP2018000085 W JP 2018000085W WO 2018131542 A1 WO2018131542 A1 WO 2018131542A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
- A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
Definitions
- the present invention relates to a cognitive function evaluation system for evaluating the cognitive function of a subject and presenting the risk of dementia according to the underlying disease of dementia.
- a diagnostic support tool as disclosed in Document 1 has been developed. With this diagnostic support tool, it is possible to change the question dynamically according to the subject's prior information and environmental information, and the subject's answer content, and to evaluate the subject's cognitive function.
- dementia is caused by various underlying diseases such as Alzheimer's disease and cerebrovascular dementia, and the symptoms, prognosis, measures, and treatment methods differ depending on the underlying diseases.
- diagnostic support tools such as those disclosed in Patent Document 1 merely assess how well the cognitive function functions as a whole, and the risk of such various underlying diseases As we have not been able to evaluate (which underlying diseases are likely to be affected), the current situation is that specialists have not been able to provide meaningful information for diagnosis. Furthermore, dementia has a progressive course, but the degree of progression depends on the underlying disease. Conventional tools can not predict the progression of the underlying disease because the same evaluation is performed for the entire dementia. Therefore, it is not possible to evaluate the underlying diseases by any intervention, for example, when verifying the effects of drugs.
- the present invention has been made in view of such circumstances, and the object of the present invention is to provide a diagnostic tool capable of evaluating the risk of each underlying disease of dementia when examining the cognitive function of a subject. It is to do.
- the present invention provides a prediction of the progress of each underlying disease.
- it is also possible to carry out physical disability.
- the cognitive function evaluation system in the present invention evaluates the risks of a plurality of underlying diseases in the cognitive function of the subject based on the test item for the cognitive function, and measures the test value of the test item, and the measurement It is characterized by comprising: calculation means for calculating the risk based on the test value measured by the means; and selection means for selecting a basic disease having the highest risk among the calculated risks.
- the factors that affect cognitive function evaluation will be evaluated to improve the accuracy of judgment. It is possible to answer with the upper limbs (fingers), or the lower limbs, or by speaking or blinking.
- the risk can be calculated for each basic disease causing dementia, and it becomes possible to support dementia diagnosis more effectively.
- An embodiment of the present invention is a cognitive function evaluation system implemented in a computer that functions as a so-called stand-alone type that does not require a communication line.
- FIG. 1 schematically shows a computer 1 in which the cognitive function evaluation system of the present embodiment is implemented.
- a cognitive function evaluation system as an embodiment of the present invention is realized by a combination of hardware of the computer 1 and software executed inside the computer.
- the computer is provided with a main body incorporating a CPU, a RAM memory, a ROM, a hard disk and the like, a liquid crystal display for screen display, and a keyboard and a mouse for medical personnel to input various settings and the like.
- a main body incorporating a CPU, a RAM memory, a ROM, a hard disk and the like, a liquid crystal display for screen display, and a keyboard and a mouse for medical personnel to input various settings and the like.
- FIG. 2 is a functional block diagram of the cognitive function evaluation system 10 in the present embodiment.
- the cognitive function evaluation system 10 includes a question storage unit 11, a screen display unit 12, a question change unit 13, an inspection value measurement unit 14, a risk calculation unit 15, a risk selection unit 16, and a result output unit 17. It consists of
- the question storage unit 11 stores the contents of approximately 70 questions implemented in the cognitive function evaluation system 10, the point allocation of each question, the answering time, and the examination items corresponding to each question.
- the examination items include nine items of memory, orientation, aphasia, disbelief, calculation ability, understanding ability, judgment ability, execution function, and correction term, and each question is among these examination items. It corresponds with either.
- the screen display unit 12 is constituted by a liquid crystal display, and displays each question to the subject.
- the subject sequentially answers the questions displayed on the screen display unit 12 using the touch panel, the keyboard, the foot sensor, the blink sensor or the mouse.
- the screen display unit 12 is provided with an imaging unit 23, and changes in blink frequency and expression during a test of the subject are detected.
- the question change unit 13 is a function that allows a medical professional to change the contents of a question according to the subject. Specifically, it is provided with a point allocation changing means capable of changing the point allocation of each question, and an answer time setting means capable of setting an answer time of each question.
- the test value measurement unit 14 as a measurement unit makes a true / false determination on the answer to each question of the subject, and performs scoring based on the points allocated for each question. And the score for every above-mentioned inspection item is measured as an inspection value.
- the risk calculation unit 15 calculates the risk of the underlying disease in the cognitive function of the subject based on the test value (score for each test item) measured by the test value measurement unit 14.
- AD Alzheimer's disease
- VAD cerebrovascular dementia
- DLBD Lewy body dementia
- PPD Parkinson's dementia complex
- FTD cortical basal ganglia degeneration
- encephalitis encephalitis
- metabolic encephalopathy and normal pressure hydrocephalus.
- the degree to which the disease and condition that should be distinguished from dementia, specifically depression, psychogenic reaction, and neurosis, etc. affect cognitive function is calculated, and the accuracy of the risk calculation of the underlying disease due to dementia is calculated. Increase.
- X 1 A 1 ⁇ (memory ability test values: X 1) + A 2 ⁇ ( test values of disorientation: X 2) + A 3 ⁇ ( Test value of aphasia: X 3 ) + A 4 ⁇ (test value of dissatisfaction: X 4 ) + A 5 ⁇ (test value of calculation ability: X 5 ) + A 6 ⁇ (test value of understanding ability: X 6 ) + A 7 ⁇ (Inspection value of judgment: X 7 ) + A 8 ⁇ (Inspection value of execution function: X 8 ) + (Inspection value of correction item: C), the inspection value of each inspection item and A 1 to A 8 It is calculated by a linear expression with a gradient coefficient represented (with regard to memory ability, A 1 is treated as A 1A and A 1B and X 1 is treated as X 1A and X 1B ).
- the combination of the gradient coefficients represented by (A 1 , A 2 ,..., A 8 ) differs depending on each underlying disease.
- the risk calculation unit 15 calculates the risk of the underlying disease by using a combination of slope coefficients corresponding to the respective underlying diseases.
- the calculation means calculates the risk Y of the underlying disease for each of the underlying diseases by the formula represented by the following formula (1).
- the calculation means calculates the risk Y of the underlying disease for each underlying disease according to a formula represented by the following formula (1 ′).
- the risk calculation unit 15 accumulates the test results of the subject, and based on the accumulated data, the coefficient correction unit 21 corrects the combination of the inclination coefficients of each basic disease by multivariate analysis.
- multivariate analysis generally known logistic regression analysis can be used, for example.
- the risk calculation unit 15 includes a calculation result correction unit 22 that corrects the calculated risk of each basic disease. This is, for example, that if the subject gives a wrong answer for the low difficulty item but corrects the high difficulty item, it is judged that the wrong answer for the low difficulty item is just an error and the risk of the underlying disease is evaluated low. Or if the subject makes a negative input on a question about physical condition, it may be corrected to lower the risk of underlying disease.
- the risk selection unit 16 as selection means has a Y lower than a predetermined basic disease reference value determined to be at risk for the basic disease.
- the basic disease is selected and displayed on the screen display unit 12. That is, among the calculated risks of the underlying disease, the ones with high risk for the subject are displayed. Alternatively, all the calculated underlying diseases can be displayed in order from the highest risk.
- the risk selection unit 16 as selection means has a Y that is equal to or higher than the basic disease reference value among the calculated risks for each basic disease, but is lower than a predetermined MCI reference value judged to have the MCI risk. If there is, then the risk of MCI of the underlying disease is selected.
- the result output unit 17 creates a radar chart for the test result of the subject calculated by the risk calculation unit, and outputs the radar chart as the test result.
- the risk calculation unit 15 is provided with an in-answer time incorrectness recording means for recording whether or not the correct answer can be made within the answer time in each inspection item. In addition, even if it answers within the response time in each inspection item, in the case of a wrong answer, it does not mean that the correct response could be made within the response time. Further, the risk calculation unit 15 includes problem processing ability evaluation means for evaluating the problem processing ability within the time limit for the inspection of the subject based on the number of the inspection items which can be correctly answered within the response time. The evaluation of the subject's problem processing ability is output to the result output unit 17.
- the response time for each test item Memory test response time T 1 , Orientation test response time T 2 , Aphasia test response time T 3 , Disapproval test response time T 4 , computing power test answer time T 5, the response times T 6 of comprehension test, the judgment test response times T 7, and is set as a reply time T 8 of the examination of the execution function.
- the reply time error recording means records this.
- the problem processing ability evaluation means evaluates the subject's problem processing ability in comparison with a predetermined predetermined standard. For example, if you can not answer correctly in the response time in 4 or less inspection items out of 8 inspection items of memory ability, orientation, aphasia, annoyance, calculation ability, understanding ability, judgment ability and execution function, the subject's problem Processing capacity is negatively assessed. Also, for example, among the eight examination items of memory ability, orientation, aphasia, disbelief, calculation ability, comprehension ability, judgment ability, and execution function, the problem treatment of the subject by placing emphasis on the examination items that can be answered in a short time Ability can also be assessed. For example, disapproval is a question as shown in FIG. 6, but it is a problem that can be answered in a short time, but computational power will be asked as in FIG. 7A and FIG. 7B. It is not a problem that can be done.
- the cognitive function evaluation system can diagnose the risk of dementia for each basic disease of dementia.
- Alzheimer's-type recognition can be performed on a subject It can be evaluated as falling under the condition of Alzheimer's disease, but the condition of Alzheimer's disease varies.
- the cognitive function evaluation system according to the present invention since the problem processing ability evaluation means is provided, it is possible not only to judge the underlying disease of dementia but also to evaluate the pathological condition.
- Alzheimer's disease is a disease based on the deterioration of memory impairment, but as its pathophysiology, in addition to memory impairment, disorientation, learning disorders, attention disorders, visual spatial cognitive disorders, problem processing disorders Etc.
- Alzheimer's disease there is a memory disorder, a disorientation disorder, or a problem processing disorder, but there is a memory disorder, no disorientation disorder, problem handling Some people are judged to have a disability.
- the cognitive function evaluation system of the present invention when the subject is judged to have a high risk of, for example, Alzheimer's disease, and the evaluation of the problem processing ability is negatively evaluated (ie, this subject) Is judged to have a high risk of Alzheimer's disease, memory impairment, problem processing ability impairment, etc.) because there is a risk that the subject's daily activities may be dangerous. Should be strengthened.
- the subject is judged to be at high risk of, for example, Alzheimer's disease, and the evaluation of problem processing ability is positively evaluated (ie, this subject is at high risk of Alzheimer's disease, memory It is determined that there is a problem, and there is no problem processing ability failure))
- the subject's memory ability is lowered, the action ability of daily life is not deteriorated, so the care of the subject is strengthened. Should not be as important.
- the risk calculating unit 15 further includes safe driving ability evaluation means for evaluating the safe driving ability of the vehicle based on the subject's problem processing ability within the time limit evaluated by the problem processing ability evaluating means.
- the evaluation of the safe driving ability of the subject is output to the result output unit 17. If the subject's problem-handling ability rating is negative, the subject's safe driving ability is also negatively rated. If the evaluation of the subject's problem processing ability is positive, the safe driving ability of the subject is also positively evaluated.
- dementia is prohibited from driving cars, but MCI (Mild Cognitive Impairment) is not prohibited from driving cars.
- driving a car should be avoided if the subject is judged to have a high risk of, for example, Alzheimer's disease.
- the subject is judged to have a high risk of MCI of Alzheimer's disease and the safety driving ability is also negatively evaluated because the evaluation of the problem handling ability is negative, the automobile is driven. Things should be avoided.
- the self-driving of the automobile is self-restrained. There is little need to do it.
- Flow of inspection The flow of an examination using the cognitive function evaluation system according to the present embodiment will be described below. Approximately 70 questions are prepared for the cognitive function evaluation system according to the present embodiment. Profile information is entered by the examiner. Profile information includes residence, date of birth, gender and the like. Subject answers various questions such as physical condition on the day of the examination, sleep condition on the previous day, recent subjective symptoms, recent habits, etc. toward the liquid crystal display which is the screen display unit 12, and various questions prepared for evaluating cognitive function Will answer.
- the various questions correspond to any of the nine inspection items as described above.
- Nine examination items are memory (X 1 ), orientation (X 2 ), aphasia (X 3 ), disconfirmation (X 4 ), calculation (X 5 ), understanding (X 6 ), judgment (X) 7 )
- An execution function (X 8 ) and a correction term (C) and the memory (X 1 ) is further classified into immediate memory (X 1A ) and recent memory (X 1B ).
- X 1, X 2, ... X 8 are allocated points each 10 points, C has a 20-point, and be evaluated in a total of 100 points.
- the higher the score the higher the cognitive function is maintained, the lower the risk of dementia, and the lower the score, the lower the cognitive function, and the higher the risk of dementia.
- Memory is the ability to memorize things, and in this system immediate and recent memories are measured.
- the immediate storage is the ability to store a few seconds ago, and questions such as those in FIG. 3A and FIG. 3B are asked.
- the recent memory is the ability to memorize a few minutes ago, and for example, a question as shown in FIG. 3C will be asked immediately before the end of the main examination.
- Orientation refers to basic status grasping such as the present year, month, time, and where you are. For example, a question as shown in FIG. 4 will be asked.
- Aphasia refers to a decline in the ability to understand and manipulate words.
- Disapproval means that the cognitive ability through the five senses is lowered, and for example, a question as shown in FIG. 6 is asked.
- Computational power is the ability to perform computations such as arithmetic operations, and questions such as those shown in FIG. 7A and FIG. 7B will be asked.
- Judgment refers to the ability to judge the situation, and questions such as those shown in FIG. 9 will be asked.
- An execution function is a function that executes things in order. For example, the question is asked as shown in FIG.
- the correction term is a test item other than the above, and for example, it is asked whether or not there is awareness of dementia.
- the correction term will be described in detail in the process of the calculation result correction unit 22 described later.
- the combination of the gradient coefficients (A 1A, A 1B, A 2 ,..., A 8 ) differs depending on each basic disease, and the following formula is used as an initial value as a specific calculation formula.
- AD Alzheimer's disease
- the risk is calculated using a calculation formula different for each underlying disease.
- the combination of the gradient coefficients (A 1A, A 1B, A 2 ,..., A 8 ) as the initial value is determined by medical knowledge, but it may be corrected by multiple regression analysis as described later. It is possible.
- the initial gradient coefficient can be calculated by expressing how much each cognitive function is likely to be impaired in each basic disease, and then dividing each coefficient by their sum and then multiplying each by 10.
- the independent variable may be either binary, category, ordinal, or numerical variable.
- the dependent variable may be binary or in order.
- the model may be linear or non-linear.
- numerical variables may be logarithmically converted.
- the underlying disease is not necessarily limited to the above. This is because similar processing can be performed if there is information.
- the result calculated in the calculation result correction unit 22 is corrected using the inspection value C of the correction term.
- the contents of the correction for example, when the subject makes a negative input to the question about the physical condition on the day of the examination and the sleep condition on the previous day, which is questioned at the beginning of the examination, a predetermined score is given as the correction term C and the risk of underlying disease Evaluate low. This is because patients with dementia often do not have negative views about their sleep status or their physical condition. Depression and psychogenic reactions are likely to be negative. It is desirable to give two points for negative opinion and one point for slightly negative opinion as an amendment item, and to separately indicate these evaluation items.
- a predetermined score is given as the correction term C to evaluate the risk of the underlying disease low. This is because most people with dementia have no awareness of dementia. Depression and neurosis are often accompanied by excessive anxiety. It is desirable to give two points for negative opinion and one point for slightly negative opinion as an amendment item, and to separately indicate these evaluation items.
- the gradient term of the calculation power is increased as the correction term C.
- the length of education history can be defined, for example, depending on the subject's university graduation. Alternatively, it can be defined as the number of years of elementary school, junior high school, high school, university, and graduate school. As information used for multivariate analysis, numerical information is better as the amount of information than information grouped into categories.
- the influence of educational history on cognitive function varies depending on the cognitive function area and questions, it is desirable to make corrections according to each.
- the educational history does not affect the cognitive function of recognizing an apple as an apple and the cognitive function of identifying an expression.
- the slope coefficient of the cognitive function area can be corrected.
- the inclination coefficient of orientation is increased as the correction term C. This is to increase the influence of the sense of orientation in the risk calculation and to make it easier to expose the risk of dementia, as the older age tends to lower the sense of orientation.
- the age is preferably the actual age (numerical information). This is because the amount of information increases in multivariate analysis.
- the slope coefficient of the cognitive function area can be corrected. Since age also affects hearing ability, visual acuity and movement speed, age information can be simultaneously obtained and corrected at the time of cognitive function evaluation. The slope coefficient of each cognitive function area can be corrected.
- the choice frequency of “I don't know” also differs depending on the underlying disease. For example, the “don't know” choice is more frequent than other underlying diseases, as a response is seen in AD. In FTD, the frequency of “I don't know” is higher than in other basic diseases of dementia because the attitude of the approach to the test changes. In NPH, the frequency of “don't know” selection is low. Thus, the “don't know” choice is a cognitive function assessment that helps to differentiate underlying disease.
- the combination of the low difficulty question and the “don't know” choice for the high difficulty question, described below, is useful for diagnosing and differentiating dementia. For example, if "I do not know” is selected for the low difficulty level problem and "I do not understand” for the high difficulty level problem, the risk of dementia is lowered. Furthermore, in the case of a correct answer to the high difficulty problem, factors other than dementia, ie "depression” and psychogenic reactions should be considered.
- the “don't know” choice, frequency, which questions were selected for, and distribution are useful for dementia risk assessment.
- the presence or absence of the "I do not know” selection can be displayed as a list. By performing multivariate analysis on the presence or absence of the “don't know” selection, the accuracy of the dementia risk determination can be enhanced.
- the blink frequency of the subject is detected using the imaging unit 23 provided in the screen display unit 12, and when the blink frequency is low, a predetermined score is reduced as the correction term C to highly evaluate the risk of the underlying disease. .
- the blink frequency per unit time may be compared. Because the movement of the upper eyelid is greater than the movement of the lower eyelid, the movement of the upper eyelid can also be detected and measured. It is also possible to evaluate the disappearance of the corneal reflex and the shielding of the pupil.
- the decrease in blink frequency depends on the underlying disease of dementia. For example, in PDD, the degree of decrease is greater than in AD. Thus, blink frequency is also useful for differentiating underlying diseases. It also depends on the stage of progression of dementia.
- the slope coefficient of each cognitive function area can be corrected. Furthermore, correction can also be performed using a non-linear model.
- a change in the expression of the subject is detected using the imaging unit 23, and when the change in expression is below a predetermined reference, a predetermined score is reduced as the correction term C to highly evaluate the risk of the underlying disease.
- Changes in expression are evaluated by capturing the eyelid, eyebrow, chin, nose, nasolabial fold, and mouth in 3D.
- the decrease in facial expression changes depends on the underlying disease of dementia. For example, in PDD and DLDB, the degree of decrease is larger than that in AD. It also decreases for FTD and NPH. The degree of this decrease does not coincide with the above-mentioned blink reduction.
- the risk selection unit 16 selects one with a high risk with respect to the calculation result of the corrected risk of each basic disease.
- the selection means is the calculated risk for each underlying disease, which is higher than or equal to the basic disease reference value but lower than the predetermined MCI (mild cognitive impairment) reference value judged to be at risk for MCI. If so, select as at risk for MCI of the underlying disease.
- memory X 1
- orientation X 2
- aphasia X 3
- disconfirmation X 4
- calculation X 5
- comprehension comprehension
- judgment X 7
- X 1 In the inspection item consisting of execution function (X 8 ) and correction term (C), X 1, X 2 ,...
- X 8 have 10 points each and C 20 points, for a total of 100 points
- the basic disease standard value is 70 points and the MCI standard value is 80 points
- the basic disease standard value is 70 points and the score obtained by the above calculation formula and correction is 69 points or less as a basic disease with high risk of dementia.
- the basic disease of 70 to 79 points is displayed on the screen display unit 12 together with the calculation result, assuming that there is a risk of MCI.
- all the calculated basic diseases may be displayed on the screen display unit 12 in descending order of risk (in order of decreasing score). At this time, it is possible to show the possibility of dementia and to indicate which underlying disease is caused by dementia. Judgment of the presence or absence of dementia is performed by the calculation result showing the highest risk.
- a subject who falls under MCI is more likely to be given the risk Y or formula given by the above-mentioned formula (1) than a subject who falls under the basic disease of dementia.
- the gradient coefficients A 1 to A 8 of Equation (1) and Equation (1 ′) It is also possible to determine the risk of MCI of each underlying disease by multiplying the and the correction term C by the respective cutoff coefficients.
- the cutoff factor can be set for each MCI of each underlying disease in consideration of the characteristics of each underlying disease, and can be set, for example, in the range of 0.5 to 0.9. More specifically, in the case of Alzheimer type dementia (AD), the cutoff coefficient is 0.9, and in the case of vascular dementia (VaD), the cutoff coefficient is 0.5, and Lewy body dementia is In the case of (DLBD), the cutoff coefficient is 0.6, in the case of Parkinson's dementia complex (PDD), the cutoff coefficient is 0.6, and in the case of frontotemporal dementia (FTD), the cutoff coefficient is 0.9, the cut-off coefficient is 0.8 for cortical basal ganglia degeneration, the cut-off coefficient is 0.6 for encephalitis (sequelae), and the cut-off coefficient is 0 for metabolic encephalopathy. In the case of normal pressure hydrocephalus, the cutoff coefficient can be 0.6.
- the result output unit 17 creates and outputs a radar chart for the calculation result.
- this radar chart the calculation result and the type of each underlying disease can be compared and confirmed. By doing this, the medical worker can visually and easily evaluate the cognitive function and the risk of the underlying disease on the test result of the subject.
- the type-specific probability can be displayed, and quantitative judgment is also possible.
- the radar chart can also be displayed enlarged while retaining similarity. Judgment becomes easy when comparing with each type of radar chart. It is also possible to display the area of the radar chart, the sum of intercept values, and the sum of intercept value squares. It is also possible to display the sum of intercepts with each type of radar chart and the intercept sum of squares.
- the radar chart in the present invention is useful for particularly early judgment of dementia. Because the outline of the radar chart differs depending on the underlying disease, the underlying disease can be estimated from the form of the subject's radar chart. Even if the score is high, when it has a shape similar to the radar chart of the underlying disease, it can be estimated that it is the underlying disease, or its early stage, or a reserve of the underlying disease.
- the cognitive function evaluation system medical personnel can change the contents of questions according to the subject.
- the change work is performed using the question change unit 13 including the point change means capable of changing the point allocation of each inspection value and the response time setting means capable of setting the response time of each question.
- the present cognitive function evaluation system includes a coefficient correction unit 21 that stores the risk calculation result of the subject for whom the test is completed, and corrects the combination of the inclination coefficients by multiple regression analysis.
- a coefficient correction unit 21 that stores the risk calculation result of the subject for whom the test is completed, and corrects the combination of the inclination coefficients by multiple regression analysis.
- the results can be stored for each basic disease, and the results of multiple tests can be compared. Therefore, it is possible to predict the degree of progression by the underlying disease.
- the present cognitive function evaluation system it is possible to store the risk calculation result of the subject whose examination has been completed, and compare the examination results of a plurality of times. Therefore, it is possible to quantitatively evaluate the progress of cognitive impairment. From the evaluation results of a plurality of cases, it is possible to calculate the degree of progress of the whole or the basic disease as a slope coefficient by multiple regression analysis. This makes it possible to predict the progression of cognitive impairment in a subject. In addition, with respect to the prediction, it is possible to evaluate the deviation of the actual value of the cognitive function of the subject.
- the present invention is not limited to the above embodiments, and may be implemented as, for example, a client-server system, and the client side may be a tablet terminal or a smartphone.
- the display color can be changed for people with color blindness. Voice output is possible, and the volume can also be adjusted.
- touch operation In addition to finger operation, blink operation, foot tap (foot switch) and voice input can be performed.
- the foot sensor and voice sensor can be connected to the measurement site via USB etc. For example, it is possible to select an option by sending a signal such as a blink when the option is sequentially highlighted on the screen and the place to be selected is highlighted. This signal may be sent by foot tap or voice.
- the sex of the subject, the amount of alcohol consumed, the amount of smoking, etc. can be adopted as the correction term. By doing so, it is possible to further eliminate the bias of cognitive function evaluation due to these factors. Also in these cases, the present invention can obtain the same effect as the above embodiment.
- the subject's movement, intellectual activity, and social activity can be evaluated. For example, it may be evaluated by the walking time, the reading time, the number of activities in a circle activity or a senile association. In dementia, these activities decrease. Therefore, the risk of dementia is higher if it is less. Since these activities are effective for preventing dementia, simultaneous information acquisition and evaluation can be useful for dementia control. Information may be obtained from something other than the subject who knows the subject's situation.
- the subjective assessment and the assessment obtained from other than this subject may be different.
- the accuracy of evaluation based on only one information can be raised and corrected by simultaneously obtaining a plurality of cognitive function evaluations judged as correct and correct, subjective symptoms, subject's own self evaluations or objective evaluations, and the relationship between both It can be considered.
- Example 1 Two subjects were examined using the cognitive function evaluation system in the present invention. And the risk assessment was calculated for each underlying disease.
- test values of the test items of subjects A and B are shown in Table 1.
- Table 1 shows the test values of the test items in Example 1 using the cognitive function evaluation system.
- subjects A and B both have a total score of 70 points.
- 80 or more points are normal, 70 to 79 points are mild cognitive impairment (MCI), and 69 or less points are criteria for dementia. Therefore, in the conventional method of simply evaluating the total points, subjects A and B both have the same test result of mild cognitive impairment, and no further information can be obtained when the specialist examines them thereafter.
- MCI mild cognitive impairment
- the risk of underlying disease is calculated based on the test values of the test items as described above.
- the calculation results are shown in Table 2.
- Table 2 shows the risk calculation results of the underlying disease in Example 1 using the cognitive function evaluation system.
- the risk calculation result of Alzheimer type dementia is 54.2 points, which is 69 points or less which is the standard of dementia.
- the subject A can be evaluated as having a high risk of dementia based on Alzheimer's disease.
- subject B has a calculated result of risk of cerebrovascular dementia (VaD) of 66.7 points, which is 69 points or less, which is the standard of dementia, cerebrovascular dementia is regarded as an underlying disease It can be evaluated that the risk of dementia is high.
- VaD cerebrovascular dementia
- AD 54.2 high possibility of dementia due to Alzheimer's disease
- VaD 79.4 not vascular disease
- DLBD 79.7 not dementia due to Lewy body disease
- PDD 79.6 not PDD
- FTD 80.7 not dementia due to FTD
- Corticobasal degeneration 79.7 Not corticobasal degeneration
- Encephalitis sequelae 81.2 Disementia due to encephalitis sequelae Not, metabolic encephalopathy 82.5 (not with dementia due to metabolic encephalopathy), normal pressure hydrocephalus 82.5 (not with dementia due to normal pressure hydrocephalus). You may rearrange and display in an order from a high possibility thing.
- Example 2 Logistic regression analysis was performed using the coefficient correction unit 21 of the cognitive function evaluation system according to the present invention, and the results are shown in Tables 3 to 5. Tables 3 to 5 are preconditions for the logistic regression analysis in Example 2 using the cognitive function evaluation system. Here, the correct answer is 1 and the wrong answer is 0 for each term.
- the AD group is 1, the VaD group is 0, and the T is a positive item number, it can be confirmed from Tables 3 and 4 that there is no significant difference between the two groups.
- Table 5 shows the results of logistic regression analysis between the two groups.
- Exp (B) is the odds ratio, and the odds ratio estimated in the itemized evaluation of AD is the reciprocal.
- the AD group may be 1 and the normal group may be 0 for comparison.
- the AD group may be further classified into severity, in which case an ordinal logistic regression model may be used instead of the binomial logistic regression model.
- FIG. 11 The radar chart created by the cognitive function evaluation system in the present invention is shown in FIG. FIG. 11
- A is a subject of a basic disease A (Alzheimer's disease).
- B is a subject of the underlying disease B.
- C is that of the subject U.
- D is that of the subject.
- E is that of the subject o.
- F is that of the subject.
- (B) is different from the underlying disease A.
- (C) it is known that the area of the radar chart is small and dementia is present, and the basic disease is A because the shape is similar to (A).
- (D) it is known that the area of the radar chart is small and dementia is present, and the basic disease is B because the shape is similar to (B).
- Example 4 Logistic regression analysis was performed using the coefficient correction unit 21 of the cognitive function evaluation system according to the present invention, and the result is shown in FIG. 12 (A).
- the broken line 1 represents the change over time of the underlying disease I by linear regression.
- the temporal transition of the subject belonging to the underlying disease I is predicted as a broken line 1.
- the solid lines 2 and 3 respectively show the time-course transition of the subjects A and B belonging to the underlying disease I by linear regression. In the case of the solid line 2, ie, above the broken line 1, it indicates that the prognosis of A is better than expected, and for example, if there is an intervention, it is considered that this a was effective.
- FIG. 13A shows the relationship between the lifestyle, for example, the presence or absence of a walk A and the cognitive function (the other factors are corrected). It can be understood that the cognitive function of the walk group is good by the difference shown in the figure.
- logistic regression analysis is performed with A functional group and non-group as independent factors and cognitive function as dependent factors.
- the presence or absence of a walk is added to the adjustment factor, it can be understood that the presence or absence of a walk is a mediator in the evaluation of cognitive function if this “difference” is not significant. Therefore, it is not necessary to correct cognitive function evaluation depending on the presence or absence of a walk.
- the "difference" remains significant, it is considered that the part is not a mediator, and a correction of cognitive function evaluation is necessary. This "difference" is different for each dementia basic disease.
- FIG. 13 (B) shows the relationship between the lifestyle, for example, the stroll time A and the cognitive function (the other factors are corrected).
- the relationship between the two draws a S-shaped curve as shown in the figure. That is, although the cognitive function is improved as A increases, the relationship is not linear, and the cognitive function is not improved when the amount of A is a certain value or less when the amount is smaller than a certain value, conversely, a certain amount Deterioration of cognitive function is not seen at the following times either.
- the general form of this figure also differs according to the underlying disease of dementia.
- Example 6 An example of a test using a blink sensor is shown.
- neuromuscular diseases such as myotrophic lateral sclerosis (ALS)
- ALS myotrophic lateral sclerosis
- speech can not be made, and it is difficult to determine the presence or absence of dementia.
- the subject is in bed lying, he can communicate his intention with blinks.
- the use of the present system is possible because the sight and hearing are less impaired.
- ALS the eyelid and eye muscles are not easily damaged, and blink action is possible. Do the same for problem presentation.
- the answer is an option
- one of the options can be highlighted.
- the subject blinks when the option he wants to select is highlighted.
- the system senses the blink and the movement of the highlight pauses. Then, if the subject determines that the option is good, the choice is determined by performing the blink again. If the highlight is selected by mistake and the highlight stops, the blink is regarded as a misselection by moving the highlight to the next option. In this way, the answers are determined one by one.
- evaluation of cognitive function and dementia evaluation according to the basic disease of dementia are performed as in the other embodiments according to selection accuracy, distribution, and the like. For example, even in the case of ALS, dementia may be merged. In this way, even in the case of a subject in a bed rest condition, which was conventionally difficult, diagnosis of dementia becomes possible.
- the present invention is extremely useful in the field of dementia medical care. Specifically, since the dementia consisting of a plurality of basic diseases can be determined separately according to the basic diseases, the following can be made.
- dementia can indicate the condition that should be distinguished from dementia. For example, “depression” or “neuropathy” can lead to a prognosis of dementia in which the dementia may not be evaluated correctly. Since the prognosis of dementia varies depending on the underlying disease of dementia, it is desirable to consider the underlying diseases separately.
- the treatment differs depending on the underlying disease for dementia, and the effect also varies depending on the underlying disease for dementia, so it is desirable to evaluate cognitive function in consideration of the underlying disease for dementia.
- cognitive function evaluation can be performed even if the hand operation is difficult. Specifically, it can also be carried out for bedsores. Even in bed rest, people with dementia and those with normal cognitive function are found.
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Abstract
Description
本発明の実施形態は、通信回線を必要としない、いわゆるスタンドアローン型として機能するコンピュータ内に実装された認知機能評価システムである。図1は、本実施形態の認知機能評価システムが実装されたコンピュータ1を模式的に示している。本発明の実施形態としての認知機能評価システムは、このコンピュータ1のハードウェアとその内部で実行されるソフトウェアとの組合せにより実現される。
以下に、本実施形態に係る認知機能評価システムを用いた検査の流れを説明する。本実施形態に係る認知機能評価システムには、およそ70の設問が用意されている。プロファイル情報は検査者が入力する。プロファイル情報とは、居住地、生年月日、性別などである。被験者は画面表示部12である液晶ディスプレイに向かって、検査当日の体調や前日の睡眠状況、最近の自覚症状、最近の習慣などに回答した後に、認知機能を評価するために用意された各種設問に回答していくこととなる。
Y=3.7X1(=1.2X1A+2.5X1B)+2.0X2+1.2X3+0.8X4+0.2X5+0.7X6+1.1X7+0.3X8
Y=1.6X1(=0.7X1A+0.9X1B)+1.0X2+1.9X3+1.4X4+0.8X5+0.6X6+0.6X7+2.1X8
Y=1.3X1(=0.5X1A+0.8X1B)+1.4X2+1.1X3+1.6X4+0.5X5+0.9X6+1.2X7+2.0X8
Y=1.4X1(=0.5X1A+0.9X1B)+1.3X2+1.1X3+1.6X4+0.5X5+0.9X6+1.2X7+2.0X8
Y=1.6X1(=0.7X1A+0.9X1B)+1.0X2+1.1X3+1.5X4+0.5X5+1.1X6+1.2X7+2.0X8
Y=1.6X1(=0.5X1A+1.1X1B)+1.0X2+1.5X3+0.9X4+0.5X5+0.9X6+1.2X7+2.4X8
Y=1.4X1(=0.7X1A+0.7X1B)+1.2X2+1.1X3+1.6X4+1.1X5+0.9X6+1.2X7+1.5X8
Y=1.2X1(=0.5X1A+0.7X1B)+1.2X2+1.1X3+1.6X4+1.0X5+1.1X6+1.4X7+1.4X8
Y=1.2X1(=0.5X1A+0.7X1B)+1.2X2+1.3X3+1.6X4+1.2X5+1.1X6+1.2X7+1.2X8
以上述べたように、本発明の実施形態に係る認知機能評価システムでは、基礎疾患ごとのリスクをそれぞれ算出するので、被験者がどの基礎疾患のリスクが高いかを評価することができ、その後の専門医による診断及び医療行為に対して有益な情報を提供することができる。認知機能障害は基礎疾患別に異なる。また障害進行も基礎疾患別に異なる。本システムによって、基礎疾患別の進行予測ができる。また基礎疾患に応じた介入効果を評価できる。
なお、本発明は、上記各実施形態に限定されず、例えばクライアント-サーバシステムとして実装してもよく、クライアント側はタブレット端末やスマートフォンなどとすることもできる。色覚障害者に対しては表示色を変更することができる。音声出力が可能であり、音量も調整できる。指による操作以外に、瞬目操作、フットタップ(フットスイッチ)、音声入力ができる。フットセンサー、音声センサーはUSBなどで測定部位と接続できる。例えば画面上で選択肢が順次ハイライトされ、選択する場所がハイライトされた時に瞬目などの信号を送ることにより選択肢を選ぶことができる。この信号をフットタップや、音声で送っても良い。
本発明における認知機能評価システムを用いて2人の被験者に対して検査を行った。そして、各基礎疾患についてリスク評価を算出した。
Y=A1A+A2+6A3+8A4+10A5+10A6+7A7+9A8+C
被験者Bについて
Y=2A1B+10A2+2A3+5A4+10A5+10A6+10A7+3A8+C
となる。
本発明における認知機能評価システムの係数修正部21を用いたロジスティック回帰分析を行い、その結果を表3~表5に示した。表3~表5は、認知機能評価システムを用いた実施例2におけるロジスティック回帰分析の前提条件である。ここで、それぞれの項について正答を1、誤答を0としている。
本発明における認知機能評価システムにより作成したレーダーチャートを図11に示す。
図11(A)は基礎疾患A(アルツハイマー病)の被験者アのものである。(B)は基礎疾患Bの被験者イのものである。(C)は被験者ウのものである。(D)は被験者エのものである。(E)は被験者オのものである。(F)は被験者カのものである。
本発明における認知機能評価システムの係数修正部21を用いたロジスティック回帰分析を行い、その結果を図12(A)に示した。破線1は基礎疾患Iの継時的変化を線形回帰で示したものである。基礎疾患Iに属する被験者の継時的推移は破線1として予測される。実線2,3はそれぞれ、基礎疾患Iに属する被験者AとBの継時的スコア推移を線形回帰で示したものである。実線2の場合、即ち破線1を上回る時、Aの予後は予想されたより良かったことを示しており、この間に例えば介入アがあったとすればこのアは有効であったと見做せる。
認知機能に影響する因子の補正方法を具体的に示す。
図13(A)は生活習慣、例えば散歩Aの有無と認知機能の関係を示したものである(他の因子は補正してある)。図で示した「差」分だけ散歩有群の認知機能が良いことが分かる。この時、A有群と無群を独立因子として、認知機能を従属因子としてロジスティック回帰分析を行う。散歩の有無を調整因子に加えた時、この「差」が有意で無くなれば、認知機能評価において散歩の有無が仲介因子となっていることが分かる。従って、散歩の有無で認知機能評価を補正する必要はない。逆に「差」が有意として残った場合、その部分は仲介因子では無いと考えられるため、認知機能評価の補正が必要である。この「差」は認知症基礎疾患別に異なる。
瞬目センサーを用いた検査の例を示す。筋委縮性側索硬化症(ALS)に代表される神経筋疾患では、四肢の動きが制限され、発語もできなくなり認知症の有無の判定が困難になる。被験者はベッド臥床状態であるが、瞬目で自分の意思を伝達することができる。視覚、聴覚が障害されることは少ないため、本システムの使用は可能である。また、ALSでは眼輪筋は障害されにくいため、瞬目動作は可能である。問題提示については同様に行う。
認知症の予後を予測することができる。認知症の予後は、認知症基礎疾患によって異なるため、基礎疾患別に考慮するのが望ましい。
11 設問記憶部
12 画面表示部
13 設問変更部
14 検査値計測部
15 リスク算出部
16 リスク選定部
17 結果出力部
21 係数修正部
22 算出結果補正部
23 撮像部
Claims (25)
- 被験者の認知機能における複数の基礎疾患のリスクを、各認知機能についての検査項目に基づいて評価する認知機能評価システムであって、
前記検査項目の検査値を計測する計測手段と、
前記計測手段により計測された検査値を基に前記リスクを算出する算出手段と、
前記算出したリスクの中から、リスクの高い基礎疾患を選定する選定手段とを備えることを特徴とする認知機能評価システム。 - 前記基礎疾患は、アルツハイマー型認知症、脳血管性認知症、レビー小体型認知症、パーキンソン認知症複合、前頭側頭型認知症、皮質基底核変性症、脳炎(後遺症)、代謝性脳症、又は、正常圧水頭症の中のいずれか1つ以上であることを特徴とする請求項1に記載の認知機能評価システム。
- 前記検査項目は、記憶力、見当識、失語、失認、計算力、理解力、判断力、及び、実行機能の中のいずれか1つ以上であることを特徴とする請求項1又は2に記載の認知機能評価システム。
- 前記検査値の配点を変更できる配点変更手段を更に備えることを特徴とする請求項1~3のいずれか1つに記載の認知機能評価システム。
- 前記検査項目の回答時間を設定できる回答時間設定手段を更に備えることを特徴とする請求項1~4のいずれか1つに記載の認知機能評価システム。
- 前記算出手段は、前記リスクの算出式を多変量解析によって修正する修正機能を備えることを特徴とする請求項1~5のいずれか1つに記載の認知機能評価システム。
- 前記多変量解析は重回帰分析であることを特徴とする請求項6に記載の認知機能評価システム。
- 前記検査項目は高難易度項目と低難易度項目とからなり、
被験者が低難易度項目は誤答したが高難易度項目を正答した場合、前記基礎疾患のリスクを補正評価することを特徴とする請求項1~7のいずれか1つに記載の認知機能評価システム。 - 前記被験者の身体の状態に関する事項を入力する入力手段を更に有し、
被験者が身体の状態に関する事項に否定的に入力された場合、前記基礎疾患のリスクを補正評価することを特徴とする請求項1~8のいずれか1つに記載の認知機能評価システム。 - 前記被験者の認知症の自覚に関する事項を入力する入力手段を更に有し、
被験者が認知症の自覚に関する事項に肯定的に入力された場合、前記基礎疾患のリスクを補正評価することを特徴とする請求項1~9のいずれか1つに記載の認知機能評価システム。 - 前記被験者の教育歴に関する事項を入力する入力手段を更に有し、
被験者の教育歴が長い場合、前記計算力の傾斜係数を増加させることを特徴とする請求項3に記載の認知機能評価システム。 - 前記被験者が、検査項目がわからないことを入力する入力手段を更に有し、
わからないことが入力される割合が一定頻度以上の場合、前記基礎疾患のリスクを補正評価する請求項1~11のいずれか1つに記載の認知機能評価システム。 - 被験者の瞬目頻度を検出する瞬目頻度検出手段を更に有し、
前記瞬目頻度が少ない場合に前記基礎疾患のリスクを補正評価することを特徴とする請求項1~12のいずれか1つに記載の認知機能評価システム。 - 被験者の表情の変化を検出する表情検出手段を更に有し、
前記表情の変化が所定の基準以下の場合に前記基礎疾患のリスクを補正評価する請求項1~13のいずれか1つに記載の認知機能評価システム。 - 前記検査項目の検査値を基にレーダーチャートを作成し、予め定められた基礎疾患の病型別のレーダーチャートと対比して表示する表示手段を更に備えることを特徴とする請求項1~14のいずれか1つに記載の認知機能評価システム。
- 前記検査項目の検査値を複数回記録することによって、基礎疾患別に予後予測を行う請求項1~15のいずれか1つに記載の認知機能評価システム。
- 前記検査項目の検査結果から、基礎疾患の病型別に、進行度を予測することを特徴とする請求項1~16のいずれか1つに記載の認知機能評価システム。
- 前記検査項目の検査値を複数回記録することによって、基礎疾患の病型別の予後予測と対比して進行度合いを評価することを特徴とする請求項1~17のいずれか1つに記載の認知機能評価システム。
- 被験者の認知機能における複数の基礎疾患のリスクを、各認知機能についての検査項目に基づいて評価する認知機能評価システムであって、
前記複数の基礎疾患は、アルツハイマー型認知症(AD)、脳血管性認知症(VAD)、レビー小体型認知症(DLBD)、パーキンソン認知症複合(PDD)、前頭側頭型認知症(FTD)、皮質基底核変性症、脳炎(後遺症)、代謝性脳症、又は、正常圧水頭症の何れかであり、
前記検査項目は、記憶力、見当識、失語、失認、計算力、理解力、判断力、及び、実行機能からなり、
各検査項目の各検査値であるX1(記憶力の検査値)、X2(見当識の検査値)、X3(失語の検査値)、X4(失認の検査値)、X5(計算力の検査値)、X6(理解力の検査値)、X7(判断力の検査値)、及び、X8(実行機能の検査値)を、認知機能が維持されている場合は高い点数で、認知機能が維持されていない場合は低い点数で計測する計測手段と、
前記計測手段により計測された各検査値(X1、X2、X3、X4、X5、X6、X7、及び、X8)に、各基礎疾患ごとの傾斜係数(A1、A2、A3、A4、A5、A6、A7、及び、A8)をそれぞれ掛け合わせた各値を全て足し合わせた基礎疾患のリスクYを基礎疾患ごとに算出する、下記式(1)で示される算出手段と、
Y=A1X1+A2X2+A3X3+A4X4+A5X5+A6X6+A7X7+A8X8・・・(1)
算出した基礎疾患ごとのYの中で、基礎疾患のリスクがあると判断される予め定められた基礎疾患基準値よりも低いYがある場合、そのYの基礎疾患をリスクの高い基礎疾患として選定する選定手段と、
を備えることを特徴とする認知機能評価システム。 - 前記各検査項目の各検査値(X1、X2、X3、X4、X5、X6、X7、及び、X8)を基にレーダーチャートを作成し、予め定められた基礎疾患ごとのレーダーチャートと対比して表示する表示手段と、
を備えることを特徴とする請求項19に記載の認知機能評価システム。 - 前記検査項目は、記憶力、見当識、失語、失認、計算力、理解力、判断力、実行機能、及び、補正項からなり、
前記算出手段は、前記計測手段により計測された各検査値(X1、X2、X3、X4、X5、X6、X7、及び、X8)に、各基礎疾患ごとの傾斜係数(A1、A2、A3、A4、A5、A6、A7、及び、A8)をそれぞれ掛け合わせた各値を全て足し合わせ、更に、C(補正項の検査値)を足し合わせた基礎疾患のリスクYを基礎疾患ごとに算出する下記式(1’)
Y=A1X1+A2X2+A3X3+A4X4+A5X5+A6X6+A7X7+A8X8+C・・・(1’)
を備えることを特徴とする請求項19又は20に記載の認知機能評価システム。 - 前記選定手段は、算出した基礎疾患ごとのYの中で、前記基礎疾患基準値以上であるが、MCIのリスクがあると判断される予め定められたMCI基準値よりも低いYがある場合、その基礎疾患のMCIのリスクがあるとして選定する、ことを特徴とする請求項19~20の何れか1項に記載の認知機能評価システム。
- 前記各検査項目の回答時間をそれぞれ設定できる回答時間設定手段を更に備えることを特徴とする請求項19~22のいずれか1つに記載の認知機能評価システム。
- 前記各検査項目において前記回答時間内に正答できたか否かを記録する回答時間内正誤記録手段と、
前記回答時間内に正答できた検査項目の個数に基づいて、被検者の検査に対する制限時間内の問題処理能力を評価する問題処理能力評価手段と、
備えることを特徴とする請求項23に記載の認知機能評価システム。 - 前記問題処理能力評価手段により評価された被験者の制限時間内の問題処理能力に基づき、自動車の安全運転能力を評価する安全運転能力評価手段
を備えることを特徴とする請求項24に記載の認知機能評価システム。
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