CN106250680B - Health of heart index detection system - Google Patents
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- CN106250680B CN106250680B CN201610584304.6A CN201610584304A CN106250680B CN 106250680 B CN106250680 B CN 106250680B CN 201610584304 A CN201610584304 A CN 201610584304A CN 106250680 B CN106250680 B CN 106250680B
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- 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
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- G—PHYSICS
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- 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
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
The present invention relates to medical domains, in particular to health of heart index detection system and model building method.The animal model that the present invention is measured by establishing heart age, calculate heart age impact factor score, form heart age determination influences factor score graph, then applied mathematical model method, establish heart age quantitative determination model, to calculate heart age value, essence is in measure people the characteristics of.
Description
Technical field
The present invention relates to medical domains, in particular to health of heart index detection system.
Background technique
The characteristics of heart age is as people is measured, has had attracted more and more attention from people.In real life, people
The appearance phenomenon more either large or small than actual age is easier to be accepted；And the actual age of human heart age and people are not
The completely the same fact is difficult to be understood by ordinary person.Since love degree of the people to heart is different and the shadow of general health
It rings, the actual age of heart age and people are difference.A popular analogy is played, people is compared to a vehicle, then the heart of people
The dirty engine like vehicle.The service life length of engine in addition to having outside the Pass with quality of production itself, also with people are daily makes
Used time Level Of Maintenance has much relations.Human heart is same, is both influenced by gene, and also daily whether carefulness is breathed out with us
Shield has much relations.The unsound life style of usual people, habit, behavior allow it to shift to an earlier date aging.2006, World Heart connection
The investigation display of alliance China: 40 years old or more crowd, only 20% human heart age is light compared with actual age, and 26% people occurs
" people is not old, and the heart first declines " phenomenon, and the actual age " basic synchronization " at 54% human heart age and people.For owner, it is known that
The true heart age of oneself will be helpful to understand the situation of body, understand mode of making the life better, habit, behavior and other preventions
Measure can reduce the risk of future heart morbidity.For most people, calculation method can allow people to know at an early age
Adhere to that the life style, habit, behavior of forming good health have great potential benefit to body, when without having arrived old again
It goes to seek medical advice and medicine.
But there has been no accurate heart age measuring methods in the world at present, mostly using traditional epidemiology tune
Checking method, there are following disadvantages for this method: (1) only focusing on globality, ignore individual difference: such as conventional method, smoking
Person adds 4 years old on the basis of actual age, and love eats meat, and person adds 3 years old.This is that generally speaking, but individual difference is larger, such as one 70 years old
Old man and 10 years old child like to eat meat, but influence on heart age certainly different；(2) lack continuity and real-time,
It is difficult to play timely predicting function.Since heart age is influenced by life style, habit, behavior, its heart of different time sections
Age value changes；(3) accuracy is doubtful, and conventional method all includes whole indexs, between such index
There may be multicollinearities, especially when between each index there is when the relation of interdependence of height, as hypertension with
Hyperlipidemia, hyperglycemia, the relationship between taste weight and body mass index will lead to heart age measurement and inaccuracy occur.
Summary of the invention
In view of this, the present invention provides health of heart index detection system.The present invention is by establishing heart age measurement
Animal model calculates heart age impact factor score, forms heart age determination influences factor score graph, then applies number
Model method is learned, heart age quantitative determination model is established, to calculate heart age value, essence is in measure people the characteristics of.
In order to achieve the above-mentioned object of the invention, the present invention the following technical schemes are provided:
The present invention provides the methods of building health of heart exponential model, include the following steps:
Building influences the index system of health of heart index；
It is constructed according to the impact factor of the index system and obtains health of heart exponential model；
The impact factor includes risk factor, actual age, heart rate, body mass index, gene and protective factors；
The risk factor includes hypertension, hyperlipidemia, hyperglycemia, chronic disease, irritability or irritability, sitting or does not like to transport
In dynamic, smoking, taste, it is fond of that snacks, life is irregular, love is angry, mood is easily fluctuated, indulged in excessive drinking, staying up late, depression, nervous；
The protective factors include aerobic exercise, frank and straightforward, open-minded, mild, diet light, Chang Yincha clearly, are fond of heavily fortified point
Fruit is fond of ocean fish, is not particular about food.
In some specific embodiments of the invention, the protective factors and its corresponding score are as follows:
In some specific embodiments of the invention, the risk factor and its corresponding score are as follows:
In some specific embodiments of the invention, the genic score is 1.0.
In some specific embodiments of the invention, it is strong that acquisition heart is constructed according to the impact factor of the index system
The mode of health exponential model are as follows:
In formula: yiRepresent life style, behavior, habit risk factor score, xiRepresent life style, behavior, habit protection
Factor score, p represent gene score.
The present invention also provides the health of heart exponential models that method building obtains.
The present invention also provides the detection system of health of heart index, including MIM message input module, message processing module and
Message output module；The MIM message input module includes impact factor unit, and the message processing module includes information processing list
Member；The information process unit obtains health of heart index by the instruction that the impact factor unit is collected, then passes through information
Output module exports result.
In some specific embodiments of the invention, impact factor unit described in the detection system include it is dangerous because
Son, actual age, heart rate, body mass index, gene and protective factors；
The risk factor includes hypertension, hyperlipidemia, hyperglycemia, chronic disease, irritability or irritability, sitting or does not like to transport
In dynamic, smoking, taste, it is fond of that snacks, life is irregular, love is angry, mood is easily fluctuated, indulged in excessive drinking, staying up late, depression, nervous；
The protective factors include aerobic exercise, frank and straightforward, open-minded, mild, diet light, Chang Yincha clearly, are fond of heavily fortified point
Fruit is fond of ocean fish, is not particular about food.
In some specific embodiments of the invention, protective factors described in the detection system and its corresponding score
Are as follows:
In some specific embodiments of the invention, risk factor described in the detection system and its corresponding score
Are as follows:
In some specific embodiments of the invention, genic score described in the detection system is 1.0.
In some specific embodiments of the invention, information process unit described in the detection system passes through the shadow
Ring the mode that the instruction that factor unit is collected obtains health of heart index are as follows:
In formula: yiRepresent life style, behavior, habit risk factor score, xiRepresent life style, behavior, habit protection
Factor score, p represent gene score.
In some specific embodiments of the invention, the evaluation method of result described in the detection system are as follows:
The result < actual age 90% is that health status is excellent；
Actual age 90%≤result < actual age 110% is that health status is normal；
Actual age 110%≤result < actual age 120% is that health status is general；
Actual age 120%≤result < actual age 130% is that health status is poor；
Actual age 130%≤result < actual age 140% is that health status is poor；
Result >=the actual age 140% is that health status is very poor.
The present invention also provides the data models or the detection system in preparation detection health of heart index
Application in device.
The present invention also provides a kind of detection methods of health of heart index, pass through the data model or the inspection
Examining system inputs the information of personnel to be measured, obtains health of heart index results.
Heart age assessment (Heart of age appraisal, HAA) is noninvasive as the health of heart of an appraiser
Property index, generally use epidemiological method at present, i.e., on the basis of actual age plus certain impact factor may be to the heart
The dirty age having an impact.But this method is limited to evidence timeliness and audient's range, has rather to current newest idea and dynamic
It is slipped, thus whether its accuracy doubtful? for this purpose, this research uses logistic multinomial logistic regression, principal component
It analyzes (PCA), determines the impact factor for influencing HA, on this basis, form HA animal model, reapply mathematical model method,
HA data model is established, provides accurate, scientific method for individual HA qualitative assessment.
HHA essence is impact factor and heart disease that research influences HA in measuring human heart quality of well being index
The science of quantity dependence and regularity between rate and the events of heart attack incidence.The superior place of the foundation of HA data model
It is that individual HA is quantitatively evaluated, the influence with the impact factor of analyzing influence heart to health of heart, and will fall ill to heart future
A situation arises makes a prediction, while the heart in personal future can be to what extent influenced with the feature, habit, behavior of estimation of personal
Dirty quality of well being index is conducive to medical personnel and gives these individual proposition precautionary measures, reaches accurate prevention and control purpose.
In this research 670 individuals are carried out in 350 healthy individuals, there are 60 HA compared with actual age year in HAA test
Gently, 17.14% is accounted for；There are 212 HA substantially uniform with actual age, accounts for 60.57%, the two amounts to 272 (being shown in Table 6), i.e.,
Rate is complied fully with up to 77.71% with clinical medicine inspection, detection, and display HAA validity is 77.71%.It is shown in table 6: 70
Healthy individuals HA is slightly larger compared with actual age, and K value is expressed as the slight aging of heart, accounts for 20.00%；Originally it researchs and analyses and thinks: due to
Its individual heart slightly damaged leads to the slight aging of heart, but not yet causes heart clinic lesion, i.e., at usually said individual
In sub-health state, medical inspection at present is also difficult to detect, and HAA has filled up the blank, shows: the predictability of HAA.Cause
This, using the HA data model of this research to the accuracy of healthy individuals HAA up to 97.71%.In 320 cardiac disorder individuals
In HAA, it is big that HA is slight compared with actual age are as follows: 44, accounts for 13.75%；Moderate is big are as follows: 132, accounts for 41.25%；Severe is big
Are as follows: 107, account for 33.44%；Pole severe is big are as follows: 30, accounts for 9.37%, four is total are as follows: 313, total accounts for
97.81% (being shown in Table 7).The result shows that: rate is complied fully with up to 97.81% with clinical medicine inspection, detection, shows HAA validity
It is 97.81%, compared with the effective percentage 77.71% of healthy individuals HAA, is statistically significant (P < 0.05) (being shown in Table 8).Table
It is bright: the sensibility that HAA detects cardiac disorder individual；HAA to the accuracy of cardiac disorder individual up to 97.81% (being shown in Table 7), and
Compared with the accuracy 97.71% of healthy individuals HAA, no significant difference (P > 0.05) (being shown in Table 8) shows: HAA detects individual
Sensitivity.Researches show that: the foundation of HA data model to the validity of individual HAA, and accuracy is high, and show: HAA is to individual
Cardiopathic generation and the events of heart attack have predictive, preventative and personalized effect.
In 320 cardiac disorder individual HAA, there are 7 individual HA and actual age substantially uniform (being shown in Table 7), this research
Think: in this 7 cardiac disorder individuals, it is possible to which there are new risk factors not to be included in this research, such as: there are 3
Cardiac disorder whose body weight index is less than 18kg/m2.It can be seen that improve the model, it is also necessary to a large amount of related epidemiology
Research data and evidence-based medicine EBM data are supported.
The reason of it must be admitted that, heart disease generation and the events of heart attack is considerably complicated, the HA number that this research institute establishes at present
According to the impact factor of model evaluation influence heart generally acknowledged at present, and HAA is as blood pressure determination, by different time, difference
Environment, different factors influence, and such as want accurate evaluation, need continuously to monitor, and can not look to once assessing and just get over.HAA is most important
Meaning be not only only that and accurately predict the following health of heart performance figure, also reside in as prevention heart disease and its event
The means of generation, by HAA, compared with actual age, inform individual can identify in time presently, there are risk probability and danger
Dangerous factor, changes undesirable life style, behavior, habit etc., takes intervening measure and processing method in time, reaches precisely anti-
It controls, delays heart ageing process, improves health, improving the purpose of quality of life.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described.
Fig. 1 shows heart age assessment impact factor index system；
Fig. 2 shows heart age animal model.
Specific embodiment
The invention discloses health of heart index detection system, those skilled in the art can use for reference present disclosure, suitably
Improve realization of process parameters.In particular, it should be pointed out that all similar substitutions and modifications are for a person skilled in the art
It will be apparent that they are considered as being included in the present invention.Method and application of the invention is carried out by preferred embodiment
Description, related personnel obviously can not depart from the content of present invention, in spirit and scope to method described herein and application into
Row change or appropriate changes and combinations, carry out implementation and application the technology of the present invention.
Heart age assessment (Heart of age appraisal, HAA) is noninvasive as the health of heart of an appraiser
Property index, generally use epidemiological method at present, i.e., on the basis of actual age plus certain impact factor may be to the heart
The dirty age having an impact.But this method is limited to evidence timeliness and audient's range, has rather to current newest idea and dynamic
It is slipped, thus whether its accuracy doubtful? for this purpose, this research uses logistic multinomial logistic regression, principal component
It analyzes (PCA), determines the impact factor for influencing HA, on this basis, form HA animal model, reapply mathematical model method,
HA data model is established, provides accurate, scientific method for individual HA qualitative assessment.Currently, the research of rare this respect is reported.
For this purpose, this research establishes situation to HA data model and its accuracy is analyzed.
Impact factor is chosen: quasi- according to scientific, systemic, comprehensive and operability principle by studying, analyzing
The impact factor for influencing HA really is selected, the impact factor index system (see Fig. 1) for influencing HA is established, it can from Fig. 1
Out, influence HA physical condition and life style, behavior, habit two big impact factors in there are also numerous influence factors,
Between these influence factors, it is understood that there may be multicollinearity, especially when there is the mutual of height between each influence factor
When dependency relationships, this can bring unreasonable explanation to HAA.An accurate, reliable HA data model in order to obtain, needs
Picking out from numerous influence factors in this two big impact factor influences big influence factor on HA.For this purpose, this research uses
Principal component analysis (PCA) is to physical condition and life style, behavior, the numerous influence factors being accustomed in two big impact factors
Screened and (be shown in Table 1, table 2, table 3), to eliminate duplicate message, determine the impact factor for influencing HA, formed HA animal model (see
Fig. 2).
Research object: 670 individuals of perspective collection, wherein healthy individuals 350, inclusion criteria: 1. routine physical examination (packet
Include the inspection such as physical examination, rabat, electrocardiogram, blood routine, stool routine examination, urine routine, fasting blood-glucose, Analysis of blood lipid, liver function
Look into) it is normal；2. it is consciously good, without uncomfortable；3. being ready and cooperating questionnaire survey and inspection；Cardiac disorder individual 320, is closed
And hyperpietic 191, merge hyperglycemia person 96, merge dyslipidemia person 320, be associated with 2 kinds of cardiac disorder persons 66,
3 kinds cardiac disorder person 17；Coronarography: 1 lesion 107, double branch lesions 162,3 lesion 51, row PCI hand
Art 253.Inclusion criteria: 1. once in Grade III Class A hospital's hospitalization, underwent coronary radiography, Heart Brightness Mode etc. are checked
Cardiac disorder is made a definite diagnosis；2. being ready and cooperating questionnaire survey and inspection；The basic condition of research object is shown in Table 4.
Epidemiological survey and individual measurement index: epidemiological survey content: 1. life style, behavior, habit: personality
Feature, if sitting, often stay up late, smoke, like angry or mood easily fluctuate, depression, neurotic or nervous, taste is heavy,
Excessive drinking, if frequent physical training, drink tea, diet is light, often feeding ocean fish or nut, life have irregular etc.；2. health
Situation: can both legs jump out of that ground, whether there is or not hypertension, hyperglycemia, dyslipidemias etc.；3. family's angiocarpy medical history etc..Sitting is fixed
Justice: 4 days or more weekly, total seat time >=12h or once a day seat duration >=2h daily；It often stays up late definition: every
Week 4 more than evening, falls asleep after zero point every night；Often eat ocean fish or nut definition: 4 days or more weekly, daily >=1 time；Frequent sport
It takes exercise and defines: aerobic exercise 4 times or more weekly, each duration >=30min.Individual measurement index: 1. individual tranquillization seat
Pareordia 1min heart rate: forbid those selected to smoke, drink tea and drink coffee in 30min before auscultating, lean against and start to listen after sitting quietly 15min
Examine 1min heart rate number；2. the measurement of height, weight: height, weight are measured using corrected RGZ-120 type scale, are selected in
Person takes off one's shoes, wears thin underwear, raises one's hat, and height is accurate to 0.1cm, and weight is accurate to 0.1kg, body mass index=weight/height2
(kg/m2), it is responsible for specially by two people, people measurement a, people checks and approves record.
Impact factor score calculates: on the basis of determining impact factor and HA relationship, being analyzed simultaneously impact factor
Pre-processed, will affect it is factor converting for influence HA Effects of Factors score, this to HAA accurately whether it is most important.Originally it grinds
Study carefully using following methods:
Since the unit of impact factor is different, if heart rate is related to the data of body mass index bigger, in order to eliminate these
To the adverse effect of HAA, the impact factor score that will affect HA is normalized factor, by they zoom to 0 and 1 it
Between, specifically:
In formulaIndicate impact factor original value,For the value after normalization, max and min be respectively maximizing and
Minimum value function.
Calculating influences heart benchmark disease rates: benchmark disease rates be have the individual disease incidence of the minimum impact factor with
The ratio of crowd's total incidence, the calculation formula proposed according to Rothman and Keller:
The individual of Pi exposure certain level impact factor accounts for the ratio of crowd；
RRi: the relative risk of exposure certain level impact factor.
It calculates Effects of Factors score (impact factor score):
Impact factor score=benchmark disease rates × relative risk.
By calculate physical condition and life style, behavior above, respectively influence in two big impact factors of habit because
The influence score of plain score and body mass index, heart rate, gene etc..
Statistical analysis: statistical analysis is carried out using 13.0 software of spss.Measurement data withIt indicates, between two groups
Comparison use independent samples t test；Enumeration data indicates that comparison among groups use x with rate or composition ratio2It examines, P < 0.05 is
Difference is statistically significant.
Using logistic multiplicity, using HA as dependent variable, with actual age, heart rate, body mass index, heredity because
Both legs in son, physical condition cannot jump out of ground, hypertension, hyperglycemia, dyslipidemia, life style, behavior, habit
In risk factor: personality is irritable or irritability, sitting, often stay up late, smoke, like anger or mood easily fluctuate, be depressed, nervousness or
Nervous, taste weighs, indulges in excessive drinking, it is irregular to live；Life style, behavior, the protection factor in habit: personality is frank and straightforward or warm
With frequent physical training, often feeding nut, ocean fish, diet is light, drink tea, rule of life etc. is independent variable, carry out multifactor recurrence
It analyzes (being shown in Table 5).
As a result:
Model realization: it is influenced on HA impact factor fraction basis establishing HA animal model and calculating, using digital mould
Type method and use logistic multinomial logistic regression, establish HA data model: HA=K × Y, K indicates individual heart in formula
Ageing process degree, Y indicate actual age.Wherein:
B represents body mass index in formula, and H represents resting heart rate, and E indicates gene score, yiIndicate life style, row
For, habit in risk factor score, xiIndicate that life style, behavior, the protection factor score in habit, A are expressed as weight
Index and heart rate product influence fractional coefficient.
Validity and accuracy detection: for the validity and accuracy for examining HA data model, the model is commented in this research
Estimate result to be detected.This research is compared according to the calculated individual HAA value of HA data model with actual age, will be a
Body HA point is: 6 types such as year is light-duty, normal type, slight involution form, moderate involution form, severe involution form, pole severe involution form, tool
Body surface is shown as: year is light-duty: K < 90%；Normal type: 90%≤K < 110%；Slight involution form: 110%≤K < 120%；Moderate declines
Old type: 120%≤K < 130%；Severe involution form: 130%≤K < 140%；Pole severe involution form: K >=140%.
350 healthy individuals and 320 cardiac disorder individual HAA results are shown in Table 6, table 7 respectively.As can be seen from Table 6:
HAA validity is 77.71% in healthy individuals group, accuracy 97.71%；As can be seen from Table 7: in cardiac disorder group
HAA validity and accuracy are 97.81%, compared with healthy group: there were significant differences for validity (P < 0.05), and accuracy is without aobvious
It writes difference (P > 0.05), and the two accuracy is high, the results are shown in Table 8.
HHA essence is impact factor and heart disease that research influences HA in measuring human heart quality of well being index
The science of quantity dependence and regularity between rate and the events of heart attack incidence.The superior place of the foundation of HA data model
It is that individual HA is quantitatively evaluated, the influence with the impact factor of analyzing influence heart to health of heart, and will fall ill to heart future
A situation arises makes a prediction, while the heart in personal future can be to what extent influenced with the feature, habit, behavior of estimation of personal
Dirty quality of well being index is conducive to medical personnel and gives these individual proposition precautionary measures, reaches accurate prevention and control purpose.
In this research 670 individuals are carried out in 350 healthy individuals, there are 60 HA compared with actual age year in HAA test
Gently, 17.14% is accounted for；There are 212 HA substantially uniform with actual age, accounts for 60.57%, the two amounts to 272 (being shown in Table 6), i.e.,
Rate is complied fully with up to 77.71% with clinical medicine inspection, detection, and display HAA validity is 77.71%.It is shown in table 6: 70
Healthy individuals HA is slightly larger compared with actual age, and K value is expressed as the slight aging of heart, accounts for 20.00%；Originally it researchs and analyses and thinks: due to
Its individual heart slightly damaged leads to the slight aging of heart, but not yet causes heart clinic lesion, i.e., at usually said individual
In sub-health state, medical inspection at present is also difficult to detect, and HAA has filled up the blank, shows: the predictability of HAA.Cause
This, using the HA data model of this research to the accuracy of healthy individuals HAA up to 97.71%.In 320 cardiac disorder individuals
In HAA, it is big that HA is slight compared with actual age are as follows: 44, accounts for 13.75%；Moderate is big are as follows: 132, accounts for 41.25%；Severe is big
Are as follows: 107, account for 33.44%；Pole severe is big are as follows: 30, accounts for 9.37%, four is total are as follows: 313, total accounts for
97.81% (being shown in Table 7).The result shows that: rate is complied fully with up to 97.81% with clinical medicine inspection, detection, shows HAA validity
It is 97.81%, compared with the effective percentage 77.71% of healthy individuals HAA, is statistically significant (P < 0.05) (being shown in Table 8).Table
It is bright: the sensitivity that HAA detects cardiac disorder individual.Researches show that: the foundation of HA data model to the validity of individual HAA,
And accuracy is high, shows: HAA there is predictive, preventative and individual character to be turned into the generation of individual heart disease and the events of heart attack
With.
In 320 cardiac disorder individual HAA, there are 7 individual HA and actual age substantially uniform (being shown in Table 7), this research
Think: in this 7 cardiac disorder individuals, it is possible to which there are new risk factors not to be included in this research, such as: there are 3
Cardiac disorder whose body weight index is less than 18kg/m2.It can be seen that improve the model, it is also necessary to a large amount of related epidemiology
Research data and evidence-based medicine EBM data are supported.
Raw materials used and reagent can be by health of heart index detection system provided by the invention and model building method
Market reaches.
Below with reference to embodiment, the present invention is further explained:
Embodiment 1
Qiu, male, nineteen sixty-five life on November 20, village cadre, height 1.7m do HAA inspection on December 5th, 2014.It checks:
Weight 78kg, 77 times/min of resting heart rate, epidemiological survey: personality is frank and straightforward, drinks tea, usually sitting, and taste weight is often stayed up late, family
Race's absent cardiovascular medical history.According to the above basic document, Qiu's HA value is calculated according to HA data model are as follows: 66.19 years old, K value was
35.08%, show heart severe aging.Inquire medical history, Qiu often feels uncomfortable in chest, palpitaition, dizziness.It is recommended that: bland diet, appropriate fortune
It is dynamic, it is few to sit, frequency of staying up late is reduced, while suggesting being further examined to hospital.Hospital checks: fasting blood-glucose: 11.6mmol/L,
Cholesterolemia: 7.3mmol/L, triglycerides: 2.28mmol/L, Bp:156/94mmHg, electrocardiogram: visible hunchbacked to mo(u)ld top half ST
Section is raised, and coronarography shows double branch lesions.That is hospitalization gives decompression, hypoglycemic, Lipid modulating, percutaneous hat
Shape arterial Interventional Therapy (PCI) is left hospital for 22 days in hospital.On December 20th, 2015, row HAA was checked again, was checked: weight: 72kg,
66 times/min of resting heart rate, epidemiological survey: personality is frank and straightforward, drink tea, diet is light, and appropriate physical training daily 30~
40min, it is few to sit, it does not stay up late；Physical condition inspection: both legs can jump out of ground, Bp:132/82mmHg, fasting blood-glucose:
5.5mmol/L, cholesterolemia: 6.1mmol/L, triglycerides: 1.9mmol/L.According to the above data, according to HA data model meter
Calculate Qiu HA value are as follows: 54.16 years old, K value are as follows: 8.35%.Show that heart ageing process obviously delays, heart damage is repaired
It is multiple.It is recommended that: adhere to taking medicine, controls weight in right amount.Case prompt: HAA provides non-invasive, timely for individual heart illness
Property, universality method for early warning, and the HAA that is established as of HA data model provides quantitative, accurate effective means, has reached the reduction heart
The purpose of heart ageing process occurs, delays for popular name for event.
Embodiment 2
Hu, male, the life on the 1st of September in 1963, height 1.70m, weight 72kg, 76 beats/min of heart rate, sitting, smoking, personality
Mildly, bland diet, Chang Yincha, it is remaining without special.
According to the above basic condition, Hu's actual age is 52 years old, body mass index 24.9, risk factor score are as follows:
0.25+0.2=0.45, protective factors score are as follows: 0.3+0.1+0.15=0.55, then
I.e. Hu's heart age is 62.7 years old, bigger than actual age by 20.6%.It is recommended that: smoking cessation, moderate exercise avoid long
It sits, is further examined to hospital.Hospital checks discovery: Bp:152/90mmHg. cholesterol: 7.10mmol/L, triglycerides:
2.16mmol/L, electrocardio diagram: myocardial ischemia.Therefore, heart age quantitative determination is predicted cardiovascular disease significant.
Embodiment 3
Qiu, male, nineteen sixty-five life on November 20, public institution cadre, height 1.7m.It is strong to do heart on December 29th, 2015
The assessment intelligence measurement of health performance figure.Check: weight 72kg, 66 beats/min of heart rate, personality is frank and straightforward, and Chang Yincha, diet is light, raw
Rule living, moves 1 hour, sitting, Bp:132/80mmHg, cholesterol daily: 6.1mmol/L, triglycerides: 1.98mmol/L,
There is History of Coronary Heart Disease.According to the above basic condition, actual age 50 years old, weight 72kg, height 1.7m is inputted, 66 beats/min of heart rate, point
Hit " personality is frank and straightforward, and Chang Yincha, diet is light, rule of life, aerobic exercise 1 hour, sitting, hyperlipidemia, chronic disease 1 " item
Mesh, i.e. output measurement result are as follows: health of heart performance figure assessed value 53.63 years old, health of heart performance figure was normal.
Embodiment 4
Lee: life on June 10 in 1981, female, nurse, height 1.63m do heart age intelligent testing on November 10th, 2015
It is fixed.Check: weight 55kg, 72 beats/min of heart rate, Bp:120/78mmHg, personality is irritable, and diet is light, lives and owes rule, stays up late,
It is remaining without special.According to the above basic condition, actual age 34 years old, weight 55kg, height 1.63m is inputted, 72 beats/min of heart rate, point
Hit " irritable, diet is light, lives irregular, stays up late " project, i.e. output measurement result are as follows: heart age 34.55 years old.
Embodiment 5
Hu, female, the birth of in August, 1979, public institution staff, 1.60 meters of height, on December 10th, 2015 does the heart
Dirty aging degree assessment measurement.Weight 56kg, 76 beats/min of heart rate, taste weight moves or so half an hour daily, remaining without special.Root
Upper basic document accordingly, Hu's life style, behavior, habit risk factor score be 0.1, protective factors score is 0.1, is lost
Pass factor score 1.0, heart aging degree assessed value are as follows:
It indicates that heart age is big compared with actual age by 11.26%, shows that heart is slightly damaged, although Hu's subjective symptoms is without obvious
Sense of discomfort, the related inspection of medicine, inspection do not find positive indication, and Hu is in sub-health state, but still suggests that it answers light drink
Food, periodic review.
Embodiment 6
Xiao, male, in April, 1958 birth, evalution of agricultural land price, 1.72 meters of height, on December 5th, 2014 does heart aging degree
Assessed value measurement.Weight 78kg, 77 beats/min of heart rate, personality is frank and straightforward, Chang Yincha, usually sitting, and taste weight is often stayed up late.According to
Upper basic document, Xiao's life style, behavior, habit risk factor score are as follows: 0.2+0.1+0.15=0.45, life side
Formula, behavior, habit protective factors score are as follows: 0.2+0.15=0.35, gene score 1.0, heart aging degree are commented
Valuation are as follows:
It indicates that heart age is big compared with actual age by 31.90%, is the aging of heart severe.It is recommended that: bland diet, it is appropriate to transport
It is dynamic, it is few to sit, frequency of staying up late is reduced, while suggesting being further examined to hospital.Hospital's inspection result: fasting blood-glucose 11.3mol/
L, cholesterolemia 7.3mol/L, triglycerides 2.28mol/L, Bp:156/94mmHg, electrocardiogram: the visible back of a bow is to ST sections of mo(u)ld top half
It raises, wide and depth Q wave, coronarography shows double branch lesions.That is hypoglycemic, decompression, lipid-loweringing etc. are given in hospitalization
Reason, undergoing percutaneous coronary interventional therapy (PCI) are left hospital after 20 days in hospital.On December 20th, 2015 does heart aging degree again
Assessed value measurement.Check: weight 72kg, 66 beats/min of heart rate, personality is frank and straightforward, drinks tea, and diet is light, and daily moderate exercise half is small
When or so, it is few to sit, it does not stay up late；Bp:132/82mmHg, fasting blood-glucose 5.5mol/L, cholesterolemia 6.1mol/L, triglycerides
1.92mol/L has History of Coronary Heart Disease.According to the above data, Xiao current weight 72kg, 66 beats/min of heart rate, life style, behavior,
The risk factor score of habit are as follows: 0.3+0.5=0.8, protective factors score are as follows: 0.2+0.15+0.1+0.1=0.55, Xiao
Current heart aging degree assessed value are as follows:
It indicates that heart age is big compared with actual age by 5.81%, shows that heart damage is clearly better earlier above, heart ageing process is bright
It is aobvious to delay.It is recommended that: adhere to taking medicine, controls weight, periodic review in right amount.Case prompt: heart aging degree assessed value measurement
Provide non-invasive, timeliness, universality method for early warning for individual heart disease patient, reached reduction the events of heart attack occur,
Delay the purpose of heart ageing process.
Embodiment 7
The detection system of health of heart index provided by the invention, including MIM message input module, message processing module and letter
Cease output module；The MIM message input module includes impact factor unit, and the message processing module includes information process unit；
The information process unit obtains health of heart index by the instruction that the impact factor unit is collected, then is exported by information
Module exports result.
Impact factor unit includes risk factor, actual age, heart rate, body mass index, gene and protective factors；
Risk factor includes hypertension, hyperlipidemia, hyperglycemia, chronic disease, irritability or irritability, sitting or does not like movement, inhales
In cigarette, taste, it is fond of that snacks, life is irregular, love is angry, mood is easily fluctuated, indulged in excessive drinking, staying up late, depression, nervous；
Protective factors include aerobic exercise, frank and straightforward, open-minded, mild, diet light, Chang Yincha clearly, are fond of nut, happiness
Eat ocean fish, not particular about food.
Protective factors and its corresponding score are as follows:
Risk factor and its corresponding score are as follows:
Genic score is 1.0.
Information process unit is in such a way that the instruction that the impact factor unit is collected obtains health of heart index are as follows:
In formula: yiRepresent life style, behavior, habit risk factor score, xiRepresent life style, behavior, habit protection
Factor score, p represent gene score.
As a result evaluation method are as follows:
The result < actual age 90% is that health status is excellent；
Actual age 90%≤result < actual age 110% is that health status is normal；
Actual age 110%≤result < actual age 120% is that health status is general；
Actual age 120%≤result < actual age 130% is that health status is poor；
Actual age 130%≤result < actual age 140% is that health status is poor；
Result >=the actual age 140% is that health status is very poor.
Research object: 670 individuals of perspective collection, wherein healthy individuals 350, inclusion criteria: 1. routine physical examination (packet
Include the inspection such as physical examination, rabat, electrocardiogram, blood routine, stool routine examination, urine routine, fasting blood-glucose, Analysis of blood lipid, liver function
Look into) it is normal；2. it is consciously good, without uncomfortable；3. being ready and cooperating questionnaire survey and inspection；Cardiac disorder individual 320, is closed
And hyperpietic 191, merge hyperglycemia person 96, merge dyslipidemia person 320, be associated with 2 kinds of cardiac disorder persons 66,
3 kinds cardiac disorder person 17；Coronarography: 1 lesion 107, double branch lesions 162,3 lesion 51, row PCI hand
Art 253.Inclusion criteria: 1. once in Grade III Class A hospital's hospitalization, underwent coronary radiography, Heart Brightness Mode etc. are checked
Cardiac disorder is made a definite diagnosis；2. being ready and cooperating questionnaire survey and inspection；The basic condition of research object is shown in Table 4.
Epidemiological survey and individual measurement index: epidemiological survey content: 1. life style, behavior, habit: personality
Feature, if sitting, often stay up late, smoke, like angry or mood easily fluctuate, depression, neurotic or nervous, taste is heavy,
Excessive drinking, if frequent physical training, drink tea, diet is light, often feeding ocean fish or nut, life have irregular etc.；2. health
Situation: can both legs jump out of that ground, whether there is or not hypertension, hyperglycemia, dyslipidemias etc.；3. family's angiocarpy medical history etc..Sitting is fixed
Justice: 4 days or more weekly, total seat time >=12h or once a day seat duration >=2h daily；It often stays up late definition: every
Week 4 more than evening, falls asleep after zero point every night；Often eat ocean fish or nut definition: 4 days or more weekly, daily >=1 time；Frequent sport
It takes exercise and defines: aerobic exercise 4 times or more weekly, each duration >=30min.Individual measurement index: 1. individual tranquillization seat
Pareordia 1min heart rate: forbid those selected to smoke, drink tea and drink coffee in 30min before auscultating, lean against and start to listen after sitting quietly 15min
Examine 1min heart rate number；2. the measurement of height, weight: height, weight are measured using corrected RGZ-120 type scale, are selected in
Person takes off one's shoes, wears thin underwear, raises one's hat, and height is accurate to 0.1cm, and weight is accurate to 0.1kg, body mass index=weight/height2
(kg/m2), it is responsible for specially by two people, people measurement a, people checks and approves record.
Statistical analysis: statistical analysis is carried out using 13.0 software of spss.Measurement data withIt indicates, two groups
Between comparison use independent samples t test；Enumeration data indicates that comparison among groups use x with rate or composition ratio2It examines, P < 0.05
It is statistically significant for difference.
Using logistic multiplicity, using HA as dependent variable, with actual age, heart rate, body mass index, heredity because
Both legs in son, physical condition cannot jump out of ground, hypertension, hyperglycemia, dyslipidemia, life style, behavior, habit
In risk factor: personality is irritable or irritability, sitting, often stay up late, smoke, like anger or mood easily fluctuate, be depressed, nervousness or
Nervous, taste weighs, indulges in excessive drinking, it is irregular to live；Life style, behavior, the protection factor in habit: personality is frank and straightforward or warm
With frequent physical training, often feeding nut, ocean fish, diet is light, drink tea, rule of life etc. is independent variable, carry out multifactor recurrence
It analyzes (being shown in Table 5).
Validity and accuracy detection: for the validity and accuracy for examining HA data model, the model is commented in this research
Estimate result to be detected.This research is compared according to the calculated individual HAA value of HA data model with actual age, will be a
Body HA point is: 6 types such as year is light-duty, normal type, slight involution form, moderate involution form, severe involution form, pole severe involution form, tool
Body surface is shown as: year is light-duty: K < 90%；Normal type: 90%≤K < 110%；Slight involution form: 110%≤K < 120%；Moderate declines
Old type: 120%≤K < 130%；Severe involution form: 130%≤K < 140%；Pole severe involution form: K >=140%.
350 healthy individuals and 320 cardiac disorder individual HAA results are shown in Table 6, table 7 respectively.As can be seen from Table 6:
HAA validity is 77.71% in healthy individuals group, accuracy 97.71%；As can be seen from Table 7: in cardiac disorder group
HAA validity and accuracy are 97.81%, compared with healthy group: there were significant differences for validity (P < 0.05), and accuracy is without aobvious
It writes difference (P > 0.05), and the two accuracy is high, the results are shown in Table 8.
Table 1: physical condition principal component analysis result
Note: first 4 are accumulative are as follows: and 97.64%, latter 3 add up to be 2.36%.
Table 2: life style, behavior, habit (risk factor) principal component analysis result
Note: first 10 are accumulative are as follows: and 98.11%, latter 2 add up to be 1.89%.
Table 3: life style, behavior, habit (protection factor) principal component analysis result
Note: first 6 are accumulative are as follows: and 98.14%, latter 2 add up to be 1.86%.
Table 4: the basic condition of research object
Note: 1mmHg=0.133kpa；aWithIt indicates,bIt is indicated with example (%), compared with healthy individuals,cP < 0.01,dp
<0.05。
Table 5: the Multiple linear regression of heart age impact factor analyzes (total factor)
Note: using HA as dependent variable, with actual age, heart rate, body mass index, hypertension, hyperglycemia, dyslipidemia, smoking,
Sitting, often stay up late, be irritable, depression, neurotic, taste weight, frequent physical training, it is light, drink tea, often eat nut, ocean fish, life
Rule, gene etc. are independent variable,aAdjust R2=0.501,bAdjust R2=0.508,cAdjust R2=0.503,dAdjust R2=
0.505。
6:350 healthy individuals HAA results of table
7:320 cardiac disorder individual HAA results of table
Table 8: research object HAA validity, accuracy compare
Note: compared with healthy individuals group:ap<0.05,bp>0.05.
In this research 670 individuals are carried out in 350 healthy individuals, there are 60 HA compared with actual age year in HAA test
Gently, 17.14% is accounted for；There are 212 HA substantially uniform with actual age, accounts for 60.57%, the two amounts to 272 (being shown in Table 6), i.e.,
Rate is complied fully with up to 77.71% with clinical medicine inspection, detection, and display HAA validity is 77.71%.It is shown in table 6: 70
Healthy individuals HA is slightly larger compared with actual age, and K value is expressed as the slight aging of heart, accounts for 20.00%；Originally it researchs and analyses and thinks: due to
Its individual heart slightly damaged leads to the slight aging of heart, but not yet causes heart clinic lesion, i.e., at usually said individual
In sub-health state, medical inspection at present is also difficult to detect, and HAA has filled up the blank, shows: the predictability of HAA.Cause
This, using the HA data model of this research to the accuracy of healthy individuals HAA up to 97.71%.In 320 cardiac disorder individuals
In HAA, it is big that HA is slight compared with actual age are as follows: 44, accounts for 13.75%；Moderate is big are as follows: 132, accounts for 41.25%；Severe is big
Are as follows: 107, account for 33.44%；Pole severe is big are as follows: 30, accounts for 9.37%, four is total are as follows: 313, total accounts for
97.81% (being shown in Table 7).The result shows that: rate is complied fully with up to 97.81% with clinical medicine inspection, detection, shows HAA validity
It is 97.81%, compared with the effective percentage 77.71% of healthy individuals HAA, is statistically significant (P < 0.05) (being shown in Table 8).Table
It is bright: the sensibility that HAA detects cardiac disorder individual；HAA to the accuracy of cardiac disorder individual up to 97.81% (being shown in Table 7), and
Compared with the accuracy 97.71% of healthy individuals HAA, no significant difference (P > 0.05) (being shown in Table 8) shows: HAA detects individual
Sensitivity.Researches show that: the foundation of HA data model to the validity of individual HAA, and accuracy is high, and show: HAA is to individual
Cardiopathic generation and the events of heart attack have predictive, preventative and personalized effect.
In 320 cardiac disorder individual HAA, there are 7 individual HA and actual age substantially uniform (being shown in Table 7), this research
Think: in this 7 cardiac disorder individuals, it is possible to which there are new risk factors not to be included in this research, such as: there are 3
Cardiac disorder whose body weight index is less than 18kg/m2。
The validity of 8 intelligent evaluation system of embodiment
From 3215 number of cases, 120 experimental datas of extraction carry out emulation testing experiment in, wherein normal health subjects sample
Data 60 (check, make a definite diagnosis coronary heart disease 50, congenital heart disease 4, Myocardial damage 6) through Grade III Class A hospital.In this 120 samples
70 are randomly choosed in this again and is used as training sample, 50 are used as test sample, and emulation carries out 10 times, using support vector machines pair
Training sample is learnt, and linear kernel function, Jing Xiangji kernel function is respectively adopted, and sigmoid kernel function etc. establishes health of heart
Performance figure assessment models, and test sample is assessed, the mean heart quality of well being index of their 10 emulation is commented
Estimate accuracy rate and be shown in Table 9:
Table 9: the result of intelligent heart quality of well being index assessment algorithm
Note: health of heart performance figure is general, poor, poor, very poor to be referred to as health of heart performance figure bad.
Know from upper table, in all kernel functions, using through establishing health of heart performance figure intelligence to base kernel function
System performance is best, and health of heart performance figure assessment accuracy rate is up to 97.92%, analyzes assessment accuracy rate with prospective study
97.81% is close.Therefore, the model should be selected to carry out check and evaluation, while check and evaluation result explanation individual to be checked
, present invention proposition health of heart performance figure assessment models are a kind of effective, high precision health of heart performance figure assessments
System, this method is practical, conveniently, can continuous monitoring, be suitable for routine physical examination.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (1)
1. the detection system of health of heart index, which is characterized in that defeated including MIM message input module, message processing module and information
Module out；The MIM message input module includes impact factor unit, and the message processing module includes information process unit；It is described
Information process unit obtains health of heart index by the instruction that the impact factor unit is collected, then passes through message output module
Export result；
The impact factor unit includes risk factor, actual age, heart rate, body mass index, gene and protective factors；
The risk factor includes hypertension, hyperlipidemia, hyperglycemia, chronic disease, irritability or irritability, sitting or does not like movement, inhales
In cigarette, taste, it is fond of that snacks, life is irregular, love is angry, mood is easily fluctuated, indulged in excessive drinking, staying up late, depression, nervous；
The protective factors include aerobic exercise, frank and straightforward, open-minded, mild, diet light, Chang Yincha clearly, are fond of nut, happiness
Eat ocean fish, not particular about food；
The protective factors and its corresponding score are as follows:
The risk factor and its corresponding score are as follows:
The genic score is 1.0；
The information process unit is in such a way that the instruction that the impact factor unit is collected obtains health of heart index are as follows:
<1>(heart rate >=55 beat/min)
<2>
(heart rate≤54 beat/min)
In formula: yiRepresent life style, behavior, habit risk factor score, xiRepresent life style, behavior, habit protective factors
Score, p represent gene score；
The evaluation method of the result are as follows:
The result < actual age 90% is that health status is excellent；
Actual age 90%≤result < actual age 110% is that health status is normal；
Actual age 110%≤result < actual age 120% is that health status is general；
Actual age 120%≤result < actual age 130% is that health status is poor；
Actual age 130%≤result < actual age 140% is that health status is poor；
Result >=the actual age 140% is that health status is very poor.
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| CN107066798A (en) * | 2016-12-30 | 2017-08-18 | 曾金生 | A kind of health of heart quality pre-alert system and its method for early warning |
| CN109949921A (en) * | 2017-05-09 | 2019-06-28 | 北京华信诚达科技有限公司 | A kind of system of remote evaluation Patients with SLE cardiac function |
| CN109583272B (en) * | 2017-09-29 | 2020-10-30 | 大连恒锐科技股份有限公司 | Footprint system capable of acquiring living state of human body |
| CN108565022B (en) * | 2018-03-13 | 2021-12-03 | 合肥趣陪信息技术有限公司 | Method for establishing child growth assessment model |
| CN110379522B (en) * | 2019-07-23 | 2022-08-12 | 四川骏逸富顿科技有限公司 | Disease prevalence trend prediction system and method |
| CN111710425A (en) * | 2020-06-19 | 2020-09-25 | 复旦大学附属中山医院 | Method, system and device for evaluating cardiotoxicity of immune checkpoint inhibitor |
| CN113160989A (en) * | 2021-04-30 | 2021-07-23 | 华中科技大学同济医学院附属同济医院 | Ovary function age calculating system based on support vector machine algorithm and method and application thereof |
| CN115458172B (en) * | 2022-11-11 | 2023-04-28 | 中山大学附属第一医院 | Heart risk assessment system, device and medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102084368A (en) * | 2008-05-02 | 2011-06-01 | 荷兰联合利华有限公司 | Heart age assessment |
| CN105147252A (en) * | 2015-08-24 | 2015-12-16 | 四川长虹电器股份有限公司 | Heart disease recognition and assessment method |
| CN105708426A (en) * | 2016-04-15 | 2016-06-29 | 北京工业大学 | Dynamic evaluation method for cardiac reserve function of healthy pregnant women in moderate-intensity exercises |
| CN105726000A (en) * | 2016-01-29 | 2016-07-06 | 北京工业大学 | Method for calculating heart and vessel functional parameters based on blood pressure and pulses of four limbs |
-
2016
- 2016-07-22 CN CN201610584304.6A patent/CN106250680B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102084368A (en) * | 2008-05-02 | 2011-06-01 | 荷兰联合利华有限公司 | Heart age assessment |
| CN105147252A (en) * | 2015-08-24 | 2015-12-16 | 四川长虹电器股份有限公司 | Heart disease recognition and assessment method |
| CN105726000A (en) * | 2016-01-29 | 2016-07-06 | 北京工业大学 | Method for calculating heart and vessel functional parameters based on blood pressure and pulses of four limbs |
| CN105708426A (en) * | 2016-04-15 | 2016-06-29 | 北京工业大学 | Dynamic evaluation method for cardiac reserve function of healthy pregnant women in moderate-intensity exercises |
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