A method for comprehensive assessment of patient depression level

Abstract

The present application relates to the technical field of depression evaluation, and particularly relates to a method for comprehensively evaluating the depression level of patients; comprising the following steps: S1, collecting multi-dimensional information and depression values of multiple patients; S2, performing normalization processing on the collected multi-dimensional information through a CPU to obtain corresponding normalized values; S3, in the CPU, taking the normalized values of the multi-dimensional information of each patient as dependent variables, and taking the depression values of the patients as independent variables to construct a regression model; S4, calculating the depression value of a patient to be evaluated according to the regression model, simultaneously calculating the depression recurrence frequency value of the patient, calculating a depression grade evaluation value according to the depression value and the depression recurrence frequency value, setting a depression grade, comparing the depression grade evaluation value of the patient to be evaluated with the depression grade, and obtaining a specific depression grade; the present application improves the accuracy of depression level evaluation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of depression evaluation, and in particular to a method for comprehensively evaluating the depression level of a patient. BACKGROUND

[0002] Depression is a common psychological disorder, and many people around the world are troubled by depression. At present, the treatment methods for depression mainly include drug therapy, psychological therapy and comprehensive therapy. However, the evaluation method of the depression level in the traditional treatment method has certain limitations and is relatively single. The traditional evaluation of depression relies on patient self-rating scales such as PHQ-9 and HAMD, and lacks objective physiological data and behavioral data, resulting in a large subjective bias in the evaluation results.

[0003] Chinese patent CN112927804A discloses a simplified method for evaluating the degree of depression based on HAMD-17 scale. The classical HAMD-17 scale is localized and simplified using item response theory, and 9 items with poor evaluation quality are deleted. The finally retained 8 items are named HAMD-8, and specifically include the following: depressive mood (H1), guilt (H2), suicide (H3), interest (H7), block (H8), spiritual anxiety (H10), somatic anxiety (H11) and general symptoms (H13). Comparing HAMD-8 with HAMD-6, it is found that the HAMD-8 scale can more accurately evaluate depression cases, while shortening the evaluation time, improving the evaluation efficiency and reducing the evaluation burden, and has application value, especially for the evaluation of depression population.

[0004] However, the above-mentioned simplified method for evaluating the degree of depression only evaluates the depression level through a single scale, without considering the influence of objective factors on the evaluation of the depression level, resulting in a deviation in the evaluation results.

[0005] Therefore, it is urgent to provide a method for comprehensively evaluating the depression level of a patient, which improves the accuracy of the evaluation of the depression level compared with the prior art. SUMMARY

[0006] The present application solves the technical problems existing in the prior art, and provides a method for comprehensively evaluating the depression level of a patient.

[0007] To achieve the above-mentioned purpose, the technical solution adopted by the present application is as follows:

[0008] A method for comprehensively evaluating the depression level of a patient, comprising the following steps:

[0009] S1, collecting multi-dimensional information and depression values of a plurality of patients;

[0010] S2, normalize the collected multi-dimensional information by the CPU to obtain corresponding normalized values;

[0011] S3, in the CPU, the normalized value of each patient's multi-dimensional information is taken as the dependent variable, and the patient's depression value is taken as the independent variable to construct a regression model;

[0012] S4, according to the regression model, the depression value of the patient to be evaluated is calculated, and the depression recurrence frequency value of the patient to be evaluated is calculated, the depression grade evaluation value is calculated according to the depression value and the depression recurrence frequency value, the depression grade is set, the depression grade evaluation value of the patient to be evaluated is compared with the depression grade, and the specific depression grade is obtained.

[0013] Further, the depression grade includes a low-risk grade, a medium-risk grade and a high-risk grade;

[0014] When the depression grade evaluation value is less than or equal to 9 points, it is evaluated as a low-risk grade;

[0015] When the depression grade evaluation value is greater than or equal to 10 points and less than or equal to 14 points, it is evaluated as a medium-risk grade;

[0016] When the depression grade evaluation value is greater than 15 points, it is evaluated as a high-risk grade.

[0017] Further, the depression grade evaluation value is calculated by the following formula:

[0018] Sp=Sphq+β×Sre;

[0019] In the above formula, Sp represents the depression grade evaluation value, Sre represents the depression recurrence frequency value, Sphq represents the depression value, and β represents the recurrence risk coefficient.

[0020] Further, the depression recurrence frequency value is calculated by the following formula:

[0021]

[0022] In the above formula, n represents the number of historical depression recurrence, θ represents the time decay coefficient, and t represents the time from the last recurrence to the present.

[0023] Further, when t≥2 years, β takes 1.5, and when t≤1 year, β takes 2.0.

[0024] Further, the regression model is specifically represented by the following formula:

[0025] Sphq=α+β1×ANS+β2×ATS+β3×MS+β4×PS+β5×ES+β6×SS+β7×IS+

[0026] β8×ADS+β9×Step+β10 α x Tpm + β 11 α x Tjz + β 12 α x PDn + β

[0027] In the above formula, α represents a constant, β1, β2, β3, β4, β5, β6, β7, β8, β9, β 10 , β 11 , β 12 represent the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, the seventh weight, the eighth weight, the ninth weight, the tenth weight, the eleventh weight, the twelfth weight, respectively, ANS represents the normalized value of the anxiety value, MS represents the normalized value of the memory function value, SS represents the normalized value of the insomnia severity value, IS represents the normalized value of the interpersonal problem scale value, PS represents the normalized value of the processing speed value, ES represents the normalized value of the executive function value, ADS represents the normalized value of the adaptation disorder value, ATS represents the normalized value of the attentional bias value, PDn represents the normalized value of the somatic disease value, Step represents the normalized value of the average daily steps, Tpm represents the normalized value of the average daily screen time, and Tjz represents the normalized value of the average daily sitting time.

[0028] Further, the normalized value of the somatic disease value is calculated according to the following formula:

[0029]

[0030] In the above formula, PD represents the somatic disease value of the patient, C i represents the comorbidity rate of the i-th somatic disease and depression, P i represents the pathogenesis correlation degree of the i-th somatic disease and depression, O i represents the clinical outcome of the i-th somatic disease, I represents the total number of all somatic diseases, i takes 1 to I, and I takes 10.

[0031] Further, the somatic diseases include cardiovascular diseases, diabetes, obesity and metabolic diseases, chronic pain diseases, dementia, Parkinson's disease, tumors, respiratory diseases, digestive system diseases, and chronic kidney diseases, and the somatic disease value is obtained according to the somatic diseases possessed by the patient, and is specifically calculated according to the following formula:

[0032]

[0033] In the above formula, C j represents the comorbidity rate of the j-th somatic disease and depression, P j represents the pathogenesis correlation degree of the j-th somatic disease and depression, O j represents the clinical outcome of the j-th somatic disease, J represents the total number of somatic diseases possessed by the patient, and j takes 1 to J.

[0034] Further, the comorbidity rate of the jth somatic disease and depression is calculated according to the following formula:

[0035]

[0036] In the above formula, represents the actual comorbidity rate of the jth somatic disease and depression, C max represents the maximum comorbidity rate of somatic diseases and depression, C max is 0.4.

[0037] Further, the method for obtaining the correlation degree of the pathogenesis of somatic diseases and depression is that a plurality of correlation degree indicators are set, and the correlation degree of the pathogenesis of each somatic disease and depression is the total number of correlation degree indicators possessed by the somatic disease multiplied by 0.25.

[0038] Further, the method for obtaining the clinical outcome of somatic diseases is that a plurality of clinical outcome indicators are set, and the clinical outcome corresponding to each somatic disease is the total number of clinical outcome indicators possessed by the somatic disease multiplied by 0.25.

[0039] Further, the normalized value of the anxiety value, the normalized value of the memory function value, the normalized value of the insomnia severity value, the normalized value of the interpersonal problem scale value, the normalized value of the processing speed value, the normalized value of the executive function value, and the normalized value of the adaptation disorder value are calculated according to the following formula:

[0040]

[0041] In the above formula, X represents the normalized value of the anxiety value or the normalized value of the memory function value or the normalized value of the insomnia severity value or the normalized value of the interpersonal problem scale value or the normalized value of the processing speed value or the normalized value of the executive function value or the normalized value of the adaptation disorder value, represents the anxiety value or the memory function value or the insomnia severity value or the interpersonal problem scale value or the processing speed value or the executive function value or the adaptation disorder value, and N represents the normalized setting value.

[0042] Further, the normalized value of the attention bias value is calculated according to the following formula:

[0043]

[0044] In the above formula, ATs represents the attention bias value.

[0045] Further, for the normalized value of the average daily sitting time, a first sitting time threshold and a second sitting time threshold are set, the first sitting time threshold is less than the second sitting time threshold, the average daily sitting time is compared with the first sitting time threshold and the second sitting time threshold, and the corresponding normalized value is obtained, specifically:

[0046] When the average daily sitting time is less than or equal to the first sitting time threshold, the normalized value of the average daily sitting time is 1.

[0047] When the average daily sitting time is greater than the first sitting time threshold and less than the second sitting time threshold, the normalized value of the average daily sitting time is calculated by the following formula:

[0048]

[0049] In the above formula, Tjz0 represents the average daily sitting time, Tjz1 represents the first sitting time threshold, and Tjz2 represents the second sitting time threshold.

[0050] When the average daily sitting time is less than or equal to the first sitting time threshold, the normalized value of the average daily sitting time is 0.

[0051] Further, for the normalized value of the average daily screen time, a first screen time threshold and a second screen time threshold are set, the first screen time threshold is less than the second screen time threshold, the average daily screen time is compared with the first screen time threshold and the second screen time threshold, and the corresponding normalized value is obtained, specifically:

[0052] When the average daily screen time is less than or equal to the first screen time threshold, the normalized value of the average daily screen time is 1.

[0053] When the average daily screen time is greater than the first screen time threshold and less than the second screen time threshold, the normalized value of the average daily screen time is calculated by the following formula:

[0054]

[0055] In the above formula, Tpm0 represents the average daily screen time, Tpm1 represents the first screen time threshold, and Tpm2 represents the second screen time threshold.

[0056] When the average daily screen time is less than or equal to the first screen time threshold, the normalized value of the average daily screen time is 0.

[0057] Further, for the normalized value of the average daily steps, a first step threshold and a second step threshold are set, the first step threshold is less than the second step threshold, the average daily steps are compared with the first step threshold and the second step threshold, and the corresponding normalized value is obtained, specifically:

[0058] When the average daily steps are less than or equal to the first step threshold, the normalized value of the average daily steps is 0.

[0059] When the average daily steps are greater than the first step threshold and less than the second step threshold, the normalized value of the average daily steps is calculated by the following formula:

[0060]

[0061] In the above formula, Step0 represents the average daily steps, Step1 represents the first step threshold, and Step2 represents the second step threshold.

[0062] When the average daily steps are less than or equal to the first step threshold, the normalized value of the average daily steps is 1.

[0063] Compared with the prior art, the beneficial effects of the present application are:

[0064] In the evaluation of the patient's depression level, the present application obtains multi-dimensional information of the patient, and normalizes the multi-dimensional information, and constructs a regression model according to the normalized multi-dimensional information and the depression value, so as to obtain a more accurate depression value of the patient, then calculates the depression recurrence frequency value of each patient, and calculates the depression level evaluation value for evaluating the depression level of the patient according to the depression value and the depression recurrence frequency value, so that the depression level evaluation of the patient is more accurate, and the accuracy of the depression level evaluation is improved. BRIEF DESCRIPTION OF DRAWINGS

[0065] Figure 1 is a flowchart of the present application. DETAILED DESCRIPTION

[0066] The technical solutions of the present application will be described in detail below with reference to the accompanying drawings, obviously, the described embodiments are not all embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0067] As Figure 1 shown, the present application provides a comprehensive evaluation method for patient depression level, comprising the following steps:

[0068] S1, collect multi-dimensional information and depression value of the patient, specifically, the patient needs to complete three types of tasks to obtain the multi-dimensional information and depression value of the patient, the three types of tasks that the patient needs to complete include life behavior risk questionnaire task, psychological assessment scale task and cognitive function assessment task; the multi-dimensional information includes anxiety value, attention bias value, memory function value, processing speed value, executive function value, insomnia severity value, interpersonal problem scale value, average daily steps, average daily screen time, average daily sitting and lying time and somatic disease value.

[0069] The life behavior risk questionnaire to be filled in the life behavior risk questionnaire task includes name, gender, date of birth (specifically year, month and day), average daily steps, average daily sitting and lying time, daily screen cumulative use time, somatic disease information, eating habits, training content form preference and training time period preference; wherein the training content form preference includes audio and video, and the training time period preference includes morning, noon and night.

[0070] The scales to be performed in the psychological assessment scale task include depression scale, anxiety scale, insomnia scale, interpersonal problem scale, five-factor mindfulness scale, rumination scale and adjustment disorder scale; wherein the depression scale selects phq-9, the anxiety scale selects HAMA, the insomnia scale selects ISI, the interpersonal problem scale selects IIP-SC, and the rumination scale selects RRS.

[0071] The cognitive function evaluation task includes point detection task, spatial recognition task, symbol-digit conversion and STROOP task.

[0072] Specifically, the average daily steps, average daily screen time and average daily sitting and lying time of the patient are obtained by performing the life behavior risk questionnaire task on the patient, the anxiety value, insomnia severity value, interpersonal problem scale value and adjustment disorder value of the patient are obtained by performing the psychological assessment scale task on the patient, the attention bias value of the patient is obtained by the point detection task, the memory function value of the patient is obtained by the spatial recognition task, the processing speed value of the patient is obtained by the symbol-digit conversion, and the executive function value of the patient is obtained by the STROOP task.

[0073] The somatic diseases that have strong correlation with depression include cardiovascular disease, diabetes, obesity and metabolic disease, chronic pain disease, dementia, Parkinson's disease, tumor, respiratory disease, digestive system disease and chronic kidney disease, and the somatic disease value of each patient is obtained by whether each patient has the above somatic diseases.

[0074] The somatic disease value of each patient is calculated by the following formula:

[0075]

[0076] In the above formula, PD represents the somatic disease value of the patient, C j represents the comorbidity rate of the jth somatic disease and depression, P j represents the pathogenesis correlation degree of the jth somatic disease and depression, O j represents the clinical outcome of the jth somatic disease, J represents the total number of somatic diseases possessed by the patient, j takes 1 to J, represents the actual comorbidity rate of the jth somatic disease and depression, C max represents the maximum comorbidity rate of somatic diseases and depression, C max is 0.4.

[0077] The pathogenesis correlation degree of somatic diseases and depression is related to the correlation index, and the pathogenesis correlation degree of each somatic disease and depression is the total number of correlation indexes possessed by the somatic disease multiplied by 0.25; the correlation index includes neuroinflammation, neuroendocrine abnormalities (HPA axis), neurotransmitter disorders, and brain structure and function abnormalities.

[0078] The clinical outcome of the somatic disease is related to the clinical outcome index, and the clinical outcome corresponding to each somatic disease is the total number of clinical outcome indexes possessed by the somatic disease multiplied by 0.25; the clinical outcome index includes possessing death risk, slow functional recovery, high recurrence frequency, and decreased quality of life, and the four indexes are judged according to medical standards.

[0079] The specific values of the comorbidity rate of each somatic disease and depression, the actual comorbidity rate of each somatic disease and depression, the pathogenesis correlation degree with depression, and the clinical outcome are obtained according to Table 1:

[0080] Table 1

[0081]

[0082]

[0083] S2, in the CPU, the corresponding normalized value calculation is performed on the multi-dimensional information of each patient.

[0084] (1) For the normalized value of the average daily sitting and lying time, it is calculated by the following formula:

[0085] A first sitting and lying time threshold and a second sitting and lying time threshold are set, the first sitting and lying time threshold is less than the second sitting and lying time threshold, the average daily sitting and lying time is compared with the first sitting and lying time threshold and the second sitting and lying time threshold, and the corresponding normalized value is obtained, which is:

[0086] When the average daily sitting and lying time is less than or equal to the first sitting and lying time threshold, the normalized value of the average daily sitting and lying time is taken as 1.

[0087] When the average daily sitting time is greater than the first sitting time threshold and less than the second sitting time threshold, the normalized value of the average daily sitting time is calculated by the following formula:

[0088]

[0089] In the above formula, Tjz represents the normalized value of the average daily sitting time, Tjz0 represents the average daily sitting time, Tjz1 represents the first sitting time threshold, and Tjz2 represents the second sitting time threshold.

[0090] When the average daily sitting time is less than or equal to the first sitting time threshold, the normalized value of the average daily sitting time is 0.

[0091] The first sitting time threshold and the second sitting time threshold are respectively 2 hours and 6 hours.

[0092] (2) The normalized value of the average daily screen time is calculated by the following formula:

[0093] The first screen time threshold and the second screen time threshold are set, the first screen time threshold is less than the second screen time threshold, and the average daily screen time is compared with the first screen time threshold and the second screen time threshold to obtain the corresponding normalized value, which is:

[0094] When the average daily screen time is less than or equal to the first screen time threshold, the normalized value of the average daily screen time is 1.

[0095] When the average daily screen time is greater than the first screen time threshold and less than the second screen time threshold, the normalized value of the average daily screen time is calculated by the following formula:

[0096]

[0097] In the above formula, Tpm represents the normalized value of the average daily screen time, Tpm0 represents the average daily screen time, Tpm1 represents the first screen time threshold, and Tpm2 represents the second screen time threshold.

[0098] When the average daily screen time is less than or equal to the first screen time threshold, the normalized value of the average daily screen time is 0.

[0099] The first screen time threshold and the second screen time threshold are respectively 1 hour and 4 hours.

[0100] (3) The normalized value of the average daily step count is calculated by the following formula:

[0101] a first step number threshold and a second step number threshold are set, the first step number threshold is less than the second step number threshold, the average daily step number is compared with the first step number threshold and the second step number threshold, so as to obtain a corresponding normalized value, specifically:

[0102] When the average daily step number is less than or equal to the first step number threshold, the normalized value of the average daily step number is 0.

[0103] When the average daily step number is greater than the first step number threshold and less than the second step number threshold, the normalized value of the average daily step number is calculated by the following formula:

[0104]

[0105] In the above formula, Step represents the normalized value of the average daily step number, Step0 represents the average daily step number, Step1 represents the first step number threshold, and Step2 represents the second step number threshold.

[0106] When the average daily step number is less than or equal to the first step number threshold, the normalized value of the average daily step number is 1.

[0107] The first step number threshold and the second step number threshold are 3000 steps and 7000 steps respectively.

[0108] (4) The normalized value of the somatic disease value is calculated according to the following formula:

[0109]

[0110] In the above formula, PDn represents the normalized value of the somatic disease value, C i represents the comorbidity rate of the i th somatic disease and depression, P i represents the pathogenesis correlation degree of the i th somatic disease and depression, O i represents the clinical outcome of the i th somatic disease, and I represents the total number of all somatic diseases, i is 1 to I, and I is equal to 10.

[0111] (5) The normalized value of the anxiety value, the normalized value of the memory function value, the normalized value of the insomnia severity value, the normalized value of the interpersonal problem scale value, the normalized value of the processing speed value, the normalized value of the executive function value, and the normalized value of the adaptation disorder value are calculated according to the following formula:

[0112]

[0113] In the above formula, X represents the normalized value of the anxiety value or the normalized value of the memory function value or the normalized value of the insomnia severity value or the normalized value of the interpersonal problem scale value or the normalized value of the processing speed value or the normalized value of the executive function value or the normalized value of the adaptation disorder value, Sphq = a + b1 x ANS + b2 x ATS + b3 x MS + b4 x PS + b5 x ES + b6 x SS + b7 x IS + b8 x ADS + b9 x Step + b10 x Tpm + b11 x Tjz + b12 x PDn; wherein Sphq represents the depression value, a represents a constant, b1, b2, b3, b4, b5, b6, b7, b8, b9, b10, b11, and b12 represent the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, the seventh weight, the eighth weight, the ninth weight, the tenth weight, the eleventh weight, and the twelfth weight, respectively, ANS represents the normalized value of the anxiety value, MS represents the normalized value of the memory function value, SS represents the normalized value of the insomnia severity value, IS represents the normalized value of the interpersonal problem scale value, PS represents the normalized value of the processing speed value, ES represents the normalized value of the executive function value, and ADS represents the normalized value of the adaptation disorder value.

[0114] The normalized setting value corresponding to the anxiety value is 56, the normalized setting value corresponding to the memory function value is 100, the normalized setting value corresponding to the insomnia severity value is 28, the normalized setting value corresponding to the interpersonal problem scale value is 128, the normalized setting value corresponding to the processing speed value is 110, the normalized setting value corresponding to the executive function value is 300, and the normalized setting value corresponding to the adaptation disorder value is 80.

[0115] (6) The normalized value of the attention bias value is calculated according to the following formula:

[0116]

[0117] In the above formula, ATS represents the normalized value of the attention bias value, and ATs represents the attention bias value.

[0118] S3, in the CPU, a regression model is obtained according to the normalized values of the multidimensional information and the depression values of all patients, specifically, the depression value of each patient is taken as the dependent variable, the normalized values of the multidimensional information of each patient are taken as the independent variables, a regression model is constructed by using a multiple linear regression method, and the regression coefficients in the regression model are calculated by a least squares method; the expression of the regression model is specifically:

[0119] Sphq = a + b1 x ANS + b2 x ATS + b3 x MS + b4 x PS + b5 x ES + b6 x SS + b7 x IS + b8 x ADS + b9 x Step + b10 x Tpm + b11 x Tjz + b12 x PDn; wherein Sphq represents the depression value, a represents a constant, b1, b2, b3, b4, b5, b6, b7, b8, b9, b10, b11, and b12 represent the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, the seventh weight, the eighth weight, the ninth weight, the tenth weight, the eleventh weight, and the twelfth weight, respectively, ANS represents the normalized value of the anxiety value, MS represents the normalized value of the memory function value, SS represents the normalized value of the insomnia severity value, IS represents the normalized value of the interpersonal problem scale value, PS represents the normalized value of the processing speed value, ES represents the normalized value of the executive function value, and ADS represents the normalized value of the adaptation disorder value.

[0120] b8 x ADS + b9 x Step + b10 x Tpm + b11 x Tjz + b12 x PDn; wherein Sphq represents the depression value, a represents a constant, b1, b2, b3, b4, b5, b6, b7, b8, b9, b10, b11, and b12 represent the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, the seventh weight, the eighth weight, the ninth weight, the tenth weight, the eleventh weight, and the twelfth weight, respectively, ANS represents the normalized value of the anxiety value, MS represents the normalized value of the memory function value, SS represents the normalized value of the insomnia severity value, IS represents the normalized value of the interpersonal problem scale value, PS represents the normalized value of the processing speed value, ES represents the normalized value of the executive function value, and ADS represents the normalized value of the adaptation disorder value. 10 11 12

[0121] In the above formula, Sphq represents the depression value, a represents a constant, b1, b2, b3, b4, b5, b6, b7, b8, b9, b10, b11, and b12 represent the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, the seventh weight, the eighth weight, the ninth weight, the tenth weight, the eleventh weight, and the twelfth weight, respectively, ANS represents the normalized value of the anxiety value, MS represents the normalized value of the memory function value, SS represents the normalized value of the insomnia severity value, IS represents the normalized value of the interpersonal problem scale value, PS represents the normalized value of the processing speed value, ES represents the normalized value of the executive function value, and ADS represents the normalized value of the adaptation disorder value. 10 11 12 ​​​​​​

[0122] The first weight takes 0.32, the second weight takes 0.15, the third weight takes -0.18, the fourth weight takes -0.09, the fifth weight takes -0.12, the sixth weight takes 0.27, the seventh weight takes 0.21, the eighth weight takes 0.23, the ninth weight takes -0.14, the tenth weight takes 0.11, the eleventh weight takes 0.08, the twelfth weight takes 0.19, and a takes 4.75.

[0123] S4, in the CPU, evaluating the patient's depression level, specifically comprising the following steps:

[0124] S41, calculating the depression value of the patient, obtaining the anxiety value, memory function value, insomnia severity value, interpersonal problem scale value, attention bias value, processing speed value, executive function value, adaptation disorder value, average daily screen time, average daily sitting and lying time, average daily steps, and somatic disease value of the patient by the method in step S1, then using the method in step S2 to obtain the corresponding normalized value of the obtained data, and bringing the obtained various normalized values into the regression model constructed in step S3 to obtain the depression value of the patient.

[0125] S42, calculating the depression recurrence frequency value of the patient, specifically calculated by the following formula:

[0126]

[0127] In the above formula, Sre represents the depression recurrence frequency value, n represents the number of historical depression recurrence, θ represents the time decay coefficient, θ takes 0.5, t represents the time from the last recurrence to the present, the unit of t is year, if there is no recurrence, t takes 0, if the recurrence time is less than one year, t takes 1, if the recurrence time is less than two years but more than one year, t takes 2, and so on.

[0128] S43, calculating the depression level evaluation value according to the depression value and the depression recurrence frequency value, setting the depression level, the depression level including low risk level, medium risk level and high risk level, comparing the depression level evaluation value of the patient with the three depression levels to obtain the specific depression level of the patient.

[0129] The depression level evaluation value is calculated by the following formula:

[0130] Sp=Sphq+β×Sre;

[0131] In the above formula, Sp represents the depression level evaluation value, and β represents the recurrence risk coefficient, when t≥2, β takes 1.5, and when t≤1, β takes 2.0.

[0132] The score segments of the three depression levels are respectively represented as:

[0133] When the depression level evaluation value is less than or equal to 9 points, it is a low risk level.

[0134] When the depression level evaluation value is greater than or equal to 10 points and less than or equal to 14 points, it is a medium risk level.

[0135] When the depression level evaluation value is greater than 15 points, it is a high risk level.

[0136] Set an interval time, and re-perform steps S1-S4, dynamic adjustment of the weight in step S3, and re-determination of the depression level of the patient every interval time.

[0137] In the evaluation of the depression level of the patient, the multi-dimensional information of the patient is obtained, and the multi-dimensional information is normalized, a regression model is constructed according to the normalized multi-dimensional information and the depression value, so that a more accurate depression value of the patient is obtained, then the depression recurrence frequency value of each patient is calculated, and the depression level evaluation value for evaluating the depression level of the patient is calculated according to the depression value and the depression recurrence frequency value, so that the evaluation of the depression level of the patient is more accurate, and the accuracy of the evaluation of the depression level is improved.

[0138] Finally, it should be noted that the above content is only used to illustrate the technical solutions of the present application, and is not a limitation on the protection scope of the present application. Simple modifications or equivalent replacements of the technical solutions of the present application made by those skilled in the art do not deviate from the essence and scope of the technical solutions of the present application.

Claims

1. A method for comprehensive assessment of a patient's depression level, characterized by, The method comprises the following steps: S1, collecting multi-dimensional information and depression values of a plurality of patients; S2, normalizing the collected multi-dimensional information by a CPU to obtain corresponding normalized values; S3, in the CPU, taking the normalized values of the multi-dimensional information of each patient as the dependent variable and the depression value of the patient as the independent variable to construct a regression model; S4, calculating the depression value of the patient to be evaluated according to the regression model, calculating the depression recurrence frequency value of the patient to be evaluated, calculating the depression level evaluation value according to the depression value and the depression recurrence frequency value, setting the depression level, comparing the depression level evaluation value of the patient to be evaluated with the depression level, and obtaining the specific depression level; The depression level evaluation value is calculated by the following formula: ； In the above formula, denotes the depression grade evaluation value, denotes the depression recurrence frequency value, denotes the depression value, denotes the recurrence risk coefficient; The depression recurrence frequency value is calculated by the following formula: ； In the above formula, represents the number of times of historical depression relapse, represents a time decay coefficient, represents the time from the most recent relapse to the present.

2. The method of claim 1, wherein, The depression level includes a low-risk level, a medium-risk level and a high-risk level; When the depression level evaluation value is less than or equal to 9 points, the evaluation is a low-risk level; When the depression level evaluation value is greater than or equal to 10 points and less than or equal to 14 points, the evaluation is a medium-risk level; When the depression level evaluation value is greater than 15 points, the evaluation is a high-risk level.

3. The method of claim 2, wherein the method further comprises: When at 1.5, at 1.5, at 1.5, at 2.

0.

4. The method of claim 2, wherein, The regression model is specifically represented by the following formula: ； In the above formula, represents a constant, , , , , , , , , , , , respectively represent a first weight, a second weight, a third weight, a fourth weight, a fifth weight, a sixth weight, a seventh weight, an eighth weight, a ninth weight, a tenth weight, an eleventh weight, a twelfth weight, represents a normalized value of an anxiety value, represents a normalized value of a memory function value, represents a normalized value of an insomnia severity value, represents a normalized value of an interpersonal problem scale value, represents a normalized value of a processing speed value, represents a normalized value of an executive function value, represents a normalized value of an adjustment disorder value, represents a normalized value of an attention bias value, represents a normalized value of a somatic disease value, represents a normalized value of an average daily step count, represents a normalized value of an average daily screen time, represents a normalized value of an average daily sitting and lying time.

5. The method of claim 4, wherein the method further comprises: The normalized value of the somatic disease value is calculated according to the following formula: ； In the above formula, represents the value of the somatic disease of the patient, represents the comorbidity rate of the i-th somatic disease and depression, represents the pathogenesis correlation degree of the i-th somatic disease and depression, represents the clinical result of the i-th somatic disease, I represents the total number of all somatic diseases, i takes 1 to I, and I takes 10.

6. The method of claim 5, wherein the method further comprises: The somatic diseases include cardiovascular diseases, diabetes, obesity and metabolic diseases, chronic pain diseases, dementia, Parkinson's disease, tumors, respiratory system diseases, digestive system diseases and chronic kidney diseases, and the somatic disease value is obtained according to the somatic diseases possessed by the patient and is specifically calculated according to the following formula: ； In the above formula, represents the comorbidity rate of the jth somatic disease and depression, represents the pathogenesis correlation of the jth somatic disease and depression, represents the clinical outcome of the jth somatic disease, J represents the total number of somatic diseases possessed by the patient, and j takes 1 to J.

7. The method of claim 6, wherein the method further comprises: The comorbidity rate of the jth somatic disease and depression is calculated according to the following formula: ； In the above formula, represents the actual comorbidity rate of the jth somatic disease and depression, represents the maximum comorbidity rate of the somatic disease and depression, is taken as 0.

4.

8. The method of claim 6, wherein the method further comprises: The method for obtaining the mechanism correlation degree of somatic diseases and depression is to set a plurality of correlation degree indexes, and the mechanism correlation degree of each somatic disease and depression is the total number of correlation degree indexes possessed by the somatic disease multiplied by 0.

25.

9. The method of claim 6, wherein the method further comprises: The method for obtaining the clinical outcome of somatic diseases is to set a plurality of clinical outcome indexes, and the clinical outcome corresponding to each somatic disease is the total number of clinical outcome indexes possessed by the somatic disease multiplied by 0.

25.

10. The method of claim 4, wherein, The normalized value of the anxiety value, the normalized value of the memory function value, the normalized value of the insomnia severity value, the normalized value of the interpersonal problem scale value, the normalized value of the processing speed value, the normalized value of the executive function value and the normalized value of the adaptation disorder value are calculated according to the following formula: ； In the above formula, a normalized value of the anxiety value or a normalized value of the memory function value or a normalized value of the insomnia severity value or a normalized value of the interpersonal problems scale value or a normalized value of the processing speed value or a normalized value of the executive function value or a normalized value of the adjustment disorder value, an anxiety value or a memory function value or an insomnia severity value or an interpersonal problems scale value or a processing speed value or an executive function value or an adjustment disorder value, a normalized set value.

11. The method of claim 4, wherein the method further comprises: The normalized value of the attention bias value is calculated according to the following formula: ； In the above formula, represents the attention bias value.

12. The method of claim 4, wherein, For the normalized value of the average daily sitting and lying time, a first sitting and lying time threshold and a second sitting and lying time threshold are set, the first sitting and lying time threshold is less than the second sitting and lying time threshold, the average daily sitting and lying time is compared with the first sitting and lying time threshold and the second sitting and lying time threshold, and the corresponding normalized value is obtained, which is specifically: When the average daily sitting and lying time is less than or equal to the first sitting and lying time threshold, the normalized value of the average daily sitting and lying time is 1; When the average daily sitting and lying time is greater than the first sitting and lying time threshold and less than the second sitting and lying time threshold, the normalized value of the average daily sitting and lying time is calculated by the following formula: ； In the above formulae, denotes the average daily sitting and lying time, denotes the first sitting and lying time threshold, denotes the second sitting and lying time threshold; When the average daily sitting and lying time is less than or equal to the first sitting and lying time threshold, the normalized value of the average daily sitting and lying time is 0.

13. The method of claim 4, wherein the method further comprises: For the normalized value of the average daily screen time, a first screen time threshold and a second screen time threshold are set, the first screen time threshold is less than the second screen time threshold, the average daily screen time is compared with the first screen time threshold and the second screen time threshold, and the corresponding normalized value is obtained, specifically: When the average daily screen time is less than or equal to the first screen time threshold, the normalized value of the average daily screen time is 1; When the average daily screen time is greater than the first screen time threshold and less than the second screen time threshold, the normalized value of the average daily screen time is calculated by the following formula: ； In the above formulae, denotes the average daily screen time, denotes the first screen time threshold, denotes the second screen time threshold; When the average daily screen time is less than or equal to the first screen time threshold, the normalized value of the average daily screen time is 0.

14. The method of claim 4, wherein, For the normalized value of the average daily step count, a first step threshold and a second step threshold are set, the first step threshold is less than the second step threshold, the average daily step count is compared with the first step threshold and the second step threshold, and the corresponding normalized value is obtained, specifically: When the average daily step count is less than or equal to the first step threshold, the normalized value of the average daily step count is 0; When the average daily step count is greater than the first step threshold and less than the second step threshold, the normalized value of the average daily step count is calculated by the following formula: ； In the above formulae, represents the average daily steps, represents the first steps threshold, represents the second steps threshold; When the average daily step count is less than or equal to the first step threshold, the normalized value of the average daily step count is 1.

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