role of folic acid drugs in the treatment with

Research ArticleRole of Folic Acid Drugs in the Treatment with Antithromboticand Anticoagulant Drugs for Patients with CardiovascularDiseases Based on the Analysis of Virtual Reality Medical Data

Aiguo Zhang Jing Wang and Qiang Jing

Pharmaceutical Department e Fourth Peoplersquos Hospital of Jinan Jinan Shandong 250031 China

Correspondence should be addressed to Aiguo Zhang 149264196163com and Qiang Jing jingq123mailsdufeeducn

Received 20 March 2021 Revised 23 May 2021 Accepted 13 June 2021 Published 5 August 2021

Academic Editor Zhihan Lv

Copyright copy 2021 Aiguo Zhang et al is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

In recent years with the continuous progress and development of science and technology and the increasing maturity of medicaltechnology the incidence of cardiovascular diseases has gradually increased with the age of the population In the case ofcardiovascular disease proper anticoagulant therapy can effectively prevent bleeding in the occurrence of events so a moreeffective treatment of cardiovascular disease is considered a difficult problem to overcomeerefore this article proposes the roleof folic acid drugs based on virtual reality medical data analysis in the treatment of cardiovascular disease patients withantithrombotic and anticoagulant drugs in order to improve providing help for cardiovascular disease is study selectedpatients with cardiovascular disease who were admitted to the hospital and extracted 100 patients with complete data and a one-year follow-up period covering the overall status of the patientsrsquo cardiovascular risk factors cardiovascular disease degree and theoccurrence of major cardiovascular adverse events During the follow-up period we analyzed the specific status of majorcardiovascular adverse events and the occurrence of bleeding events and compared and analyzed the effects of folic acid drugs onthe treatment with antithrombotic and anticoagulant drugs in patients with cardiovascular disease Experiments have proved thatthe differences in the degree of cardiovascular stenosis and the number of cardiovascular disease vessels in the four groups arestatistically significant (Plt 001)e degree of cardiovascular stenosis in group D was lighter than that in groups A B and C andthe number of cardiovascular lesions was also less than that in groups A B and C e differences were statistically significant(Plt 005) is indicates that folic acid can effectively treat cardiovascular stenosis prevent cardiovascular disease and then treatpatients with cardiovascular disease with antithrombotic and anticoagulant drugs It provides an important basis for accurateclinical diagnosis and treatment

1 Introduction

With the development of urbanization and the improvementof peoplersquos living standards the aging of the population hasbecome more and more serious which is also accompaniedby a rapid increase in cardiovascular diseases Relevant datashow that the incidence of cardiovascular disease in China isas high as 40 Among the cardiovascular drug treatmentsantithrombotic and anticoagulant drug therapy occupies ahigh position which can effectively prevent the occurrenceof cardiovascular disease and improve cardiovascular dis-easee cure rate of the disease reduces the mortality rate ofpatients with cardiovascular diseases In most cases data

centers in traditional hospitals are operated independentlyusing multiple application systems As system usage andscale grows over time equipment operation and mainte-nance costs increase making it impossible to meet the highperformance high availability and security requirements ofinformation system data However virtual reality and cloudcomputing technologies can effectively solve these problemsand provide powerful and important support for the analysisof medical data

Antithromboticanticoagulant treatment for cardiovas-cular disease overseas is much faster than in China and thedevelopment and renewal of antithromboticanticoagulanttreatment technology for cardiovascular disease is

HindawiJournal of Healthcare EngineeringVolume 2021 Article ID 9914787 9 pageshttpsdoiorg10115520219914787

progressing rapidly Antithrombotic and anticoagulanttreatments and treatments for cardiovascular disease havebeen significantly improved and developed It is believedthat the use of folic acid drugs to treat cardiovascular dis-eases will become an important breakthrough in the nearfuture Fernandez-Montero et al concluded that new oralanticoagulants have a relatively lower important bleedingrisk In terms of effectiveness the recurrence rate ofthrombosis after treatment with new anticoagulants is un-doubtedly not inferior to warfarin and it has not been seento significantly increase the risk of bleeding except forgastrointestinal bleeding [1] Leone et al used a heparincoating method based on hyaluronic acid Clinical studieshave shown that the coating method has better effects andless inflammatory response and can safely reduce theamount of heparinized heparin throughout the body duringcardiopulmonary bypass [2] Klingel et al proposed to ex-tend the anticoagulation time while reducing the recurrenceof the disease while the incidence of major bleeding in-creased by more than 3 times of which the gastrointestinaltract is the most common bleeding site [3]

e use of folic acid drugs for the treatment withantithrombotic and anticoagulant drugs for cardiovasculardisease began in Western countries Compared to Westerncountries my countryrsquos antithrombotic and anticoagulanttreatment technologies for cardiovascular disease begin in thesecond half of clinical practice and their development isrelatively slow With the continuous progress and develop-ment of modern science and technology and the increasingmaturity of medical technology the use of folic acid drugs totreat cardiovascular diseases will be an important researchwork Joo et al studied the morphology adhesion andproliferation of cells on PVC pipes with different coatings Forthe coating of cell adhesion it is mainly determined by theuniformity of the coating rather than the coating material [4]Leiter et al used a photochemical fixation method to cova-lently bond dipyridamole to the polyurethane surface It wasfound that dipyridamole significantly reduced the thrombusformation of the polyurethane surface and significantly re-duced the adhesion of platelets thereby improving the bloodcompatibility of the polyurethane [5] Ozkan et al pointed outthat it is necessary to enhance the positive attitude of patientsto treatment reduce their anxiety depression and othernegative emotions extend the survival period of cancer pa-tients improve their quality of life and improve the recoveryrate of patients we believe that we will provide clinicalstandards for this illness [6ndash8]

is article mainly studies the role of folic acid drugs inthe treatment with antithrombotic and anticoagulant drugsfor patients with cardiovascular diseases based on virtualreality medical data analysis rough the design ofantithrombotic and anticoagulant drug treatment experi-ments for patients with cardiovascular diseases the indi-cators of cardiovascular disease patients are analyzed at thesame time the logistic regression analysis method was usedto correct various factors affecting recurring adverse car-diovascular events and finally the various test data of pa-tients were analyzed [9 10] e innovations in this articlenot only pay attention to the role of folic acid in the

treatment of patients with cardiovascular disease withantithrombotic and anticoagulant drugs but also use virtualreality medical data analysis techniques to comprehensivelyand experimentally obtain experimental results It is a sys-tematic analysis that facilitates the treatment of cardiovasculardisease processes and developmental research [11 12]

2 Cardiovascular Disease and Antithromboticand Anticoagulant Treatment

21 Image Processing

211 Diffusion Tensor Imaging Diffusion tensor imagingfirst assumes that the movement of molecules is a simpleanisotropic diffusion process and calculates a representationof the diffusion tensor under the premise that the probabilitydensity function p satisfies a Gaussian distribution modelwith three variables of zero mean e calculation method isshown in the following formula

p(x) G(x Y t) (1)

e Gaussian probability distribution function here issatisfied

G(x Y t) (4πt)3det(Y)1113960 1113961

minus12

1113874 1113875exp minus

xTY

minus 1x

4t1113888 1113889 (2)

Here Y is the diffusion tensor and t is the diffusion timeIf we transpose formula (1) we can get

A(q) exp minus tqTYq1113872 1113873 (3)

If the logarithm of both sides of formula (3) is taken hereat the same time then a linear constraint on the unknownquantity Y expressed by A(q) can be obtained Among themthe diffusion tensor Y can be written in the form of a matrix

Y

Yxx Yxy Yxz

Yyx Yyy Yyz

Yzx Yzy Yzz

⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (4)

where Y is a symmetric positive semidefinite tensor that isthere is always Yij Yji for all i j z y z In order toobtain a complete evaluation value of the diffusion amountof a volume element the average diffusion value is intro-duced as an invariant into the diffusion tensor imaging It isan independent quantity that has nothing to do with thedirection It can measure the deviation of the uniformmolecular motion on the surface of a body Directly use thetrace of the diffusion tensor Y to directly represent thediffusionmean MY and the calculationmethod is as follows

MY tr(Y)

3

Yxx + Yyy + Yzz

3

(5)

e average diffusion value will be lower in the ischemicarea of the brain which is of great significance to the clinical

2 Journal of Healthcare Engineering

application of medicine Calculating the diffusion meanrequires a correct estimation of the diffusion tensor Yerefore various sampling schemes and linear optimiza-tion methods are used to calculate the diffusion tensor YAccording to the diffusion tensor Y Yapp(x) can be used torepresent the characteristic diffusion coefficient in the x(

[x1 x2 x3]) direction and the calculation formula is asfollows

Yapp(x) 1113944

3

ij1Yijxixj (6)

where x is the unit vector which satisfies the conditionxxT 1

e three most commonly used invariant indicators arerelative anisotropy anisotropy comparison value and vol-ume ratio e definition of relative anisotropy is as follows

RA

λ1 minus λ1113872 11138732

+ λ2 minus λ1113872 11138732

+ λe minus λ1113872 11138732

3λ

11139741113972

(7)

Among them

λ λ1 + λ2 + λ3( 1113857

3 (8)

e anisotropy comparison value is defined as follows

FA

32

1113970

λ1 minus λ1113872 11138732

+ λ2 minus λ1113872 11138732

+ λe minus λ1113872 11138732

λ21 + λ22 + λ231113872 1113873

11139741113972

(9)

Finally the definition of body proportion is

VR 3λ1λ3

Yij(t) 12tlangsisjrang

(10)

Relative anisotropy is a unitized standard deviation andit can also represent the ratio between the anisotropic partand the isotropic part of the diffusion tensor Y e an-isotropy comparison value measures the difference in thediffusion size of the diffusion tensor Y in different directionsand it can accurately summarize the degree of anisotropydiffusion [13 14]

212 Image Classification Based on Deep ConvolutionalNetwork (1) Relative Entropy Relative entropy is KL di-vergence which is used to measure the difference between twoprobability distributions It means that the distribution q(x)

simulates the real distribution p(x) compared to the simu-lation p(x) with p(x) which requires additional information[15] e calculation formula of the relative entropy is

KL(pq) minus 1113946 p(x)ln q(x)dx minus minus 1113946 p(x) ln p(x)dx1113874 1113875

(11)

Because the status of p(x) and q(x) in the above formulais not equal

KL(pq)neKL(qp) (12)

If the values of p(x) and q(x) are slightly different thenKL is greater than zero Only when p(x) q(x) KL is equalto 0

(2) Cross-Entropy Assuming there are two distributionsp(x) and p(x) their cross-entropy on a given sample set isdefined as follows

H(p q) minus 1113946 p(x)ln q(x)dx (13)

Cross-entropy is used to measure the similarity betweentwo probability distributions It represents the informationneeded to simulate the real distribution p(x) with distri-bution q(x)

(3) Cross-Entropy Loss Definition of cross-entropy lossfunction is

CE(p y) minus log(p) y 1

minus log(1 minus q) others1113896 (14)

For convenience use pt instead of p then

pt p y 1

1 minus p others1113896 (15)

en cross-entropy can be abbreviated as

CE(p y) CE pt( 1113857

minus log pt( 1113857(16)

where p represents the probability the value of y is 1 or minus 1and the range of p is 0 to 1 In order to improve the problemof unbalanced class standard samples some scholars haveproposed weighted cross-entropy loss [16 17]

CE pt( 1113857 minus atlog pt( 1113857 (17)

(4) Loss of Focus Although weighted cross-entropy cancontrol the weight of positive and negative samples it cannotcontrol the weight of easy to classify and difficult to classifysamples So there is the focus loss function

FL pt( 1113857 minus 1 minus pt( 1113857clog pt( 1113857 (18)

Here c is called the focal length parameter and λge 0 and(1 minus pt)

c are called the modulation coefficient

22 Smart Medical

221 SmartMedical Needs e smart medical system uses aportable ubiquitous network so that users no longer need tomonitor physiological information at a designated locationwhich is of great significance to elderly patients who havedifficulty moving Moreover some diseases require long-termmonitoring to obtain their signs such as sudden pauses

Journal of Healthcare Engineering 3

in heartbeat In these cases long-term stable and uninter-rupted monitoring is required Long-term stable monitoringis also needed to prevent the irreversible trauma caused bysudden outbreaks to the human body [18 19] If long-termmonitoring of the abovementioned patients can be achievedit will not only dig out the deep-seated pathology of thepatients to facilitate targeted treatment but at the sametime it is also very helpful for urgent treatment of diseasesbecause actually the best treatment period for these diseasesis at the beginning of the outbreak If the most beneficialtreatment can be carried out on the patient at the firstmoment the userrsquos condition will be better Realizing themonitoring of userrsquos physiological information anytime andanywhere is an important part of modernmedical treatmenterefore the proposal of smart medical treatment is alsoproposed by using the technological development of modernwireless communication and portable equipment [20 21]

Respiration signals are also very beneficial to humanhealth is is because for a normal healthy subject morethan ten breathing processes are required under normalcircumstances In some tired and large exercise states thehuman bodyrsquos breathing will change It is generally believedthat the heart can complete four movements to complete acycle of breathing so the human bodyrsquos breathing cannot betoo fast or too slow If the smart medical system considersthat the userrsquos video information needs to be transmitted tothe smart medical diagnostic center under special circum-stances the portable terminal will start the video capture andtransmission function [22 23] is function collects theuserrsquos video and audio signals through the camera andmicrophone system on the portable terminal en theportable terminal transmits the collected audio and videosignals to the smart medical storage and processing terminalfor processing via the wireless network in a timely and fastmanner [24]

222 Smart Medical Construction Goals e portableterminal is used to collect the physiological information ofthe human body and the collected physiological informa-tion terminal systemwill be transmitted to the smart medicalstorage and processing terminal through the wireless net-work in the shortest time [25 26] e storage and pro-cessing system module will realize the real-time storage ofthe userrsquos physiological information transmitted from eachterminal and the smart medical system will also display thephysiological information of the human body in time so thatthe doctor can view the physiological monitoring infor-mation of the user concerned in real time e informationtransmission and data storage module mainly realizes thereal-time transmission of the information collected by theportable terminal to the storage end of the intelligentmedical system

Considering that diseases such as heart disease are verysensitive to rescue time the time delay between informationcollection wireless transmission and data storage must betaken into consideration when designing the informationtransmission and data storage function modules At thesame time in order to facilitate the diagnostician to have a

better grasp of the status of the patient the main body visualvideo transmission function is turned on when necessary[27 28] e information collected by the mobile device issent to the information storage and the smart medicalprocess is completed is makes it possible to monitor thehealth of the human body Smart medical processing enablesreal-time display of data collected on mobile devices andsends human physiological information to relevant diag-nosticians via a smart medical system so that doctors can getreal-time patient information as quickly as possible You canquickly create diagnostic information It helps to achievetimely rescue of the patient

3 Experimental Design of Antithrombotic andAnticoagulantDrugTherapyforPatientswithCardiovascular Diseases

31 Test Subject e trial selected 336 patients with car-diovascular disease admitted to a hospital from January toJuly 2019 and recorded the main adverse cardiovascularevents and bleeding events of the patients in January Juneand one year after antiplatelet drug treatment In this studythere were 107 patients with complete data and consistentfollow-up time of 1 year We selected 100 patients egeneral information of these 100 patients is shown in Table 1According to different antiplatelet treatments it is dividedinto clopidogrel and aspirin dual-treatment group clopi-dogrel group aspirin group and folic acid drug groupAnalyze the overall situation of the patientsrsquo cardiovascularrisk factors the degree of cardiovascular disease the oc-currence of major adverse cardiovascular events the specificsituation of the major adverse cardiovascular events duringthe follow-up period and the occurrence of bleeding eventsand compare and analyze the antithrombotic effects of folicacid in patients with cardiovascular diseases and the role ofanticoagulant therapy

32 Test Method All patients receive second-line preventivetreatment for angiotensin-converting enzyme inhibitors ni-trates statin lipid-lowering agents β-receptor blockers cal-cium channel blockers and other standardized cardiovasculardiseases depending on their condition to select Based onGroup A use aspirin 100mg+ clopidogrel 75mg given orallyonce daily Group B clopidogrel 75mg orally once dailyGroup C aspirin 100mg orally administered once daily andGroup D folic acid drug 100mg orally administered oncedaily All patients were followed up for 1 year

33 Observation Indicators General clinical data and car-diovascular risk factors for patients with cardiovasculardisease include age smoking history hypertension diabeteshyperlipidemia length of disease and degree of diseaseMultivariate logistic regression analysis was used to adjustfor various factors that influence the recurrence of majorcardiovascular adverse events Major cardiovascular adverseevents during the 1-month 6-month and 1-year follow-upof antiplatelet drug treatment and bleeding complicationsafter 1 year were recorded


34 Statistical Processing Statistical analysis was performedwith SPSS 130 statistical software e significance test ofthe difference was performed by one-way analysis of vari-ance e difference between the two groups was tested byLSD-t e effect of folic acid on the treatment of cardio-vascular disease patients with antithrombotic and antico-agulant drugs was performed by group t-test Plt 005 isconsidered to be statistically significant

4 Antithrombotic and Anticoagulant DrugTherapy for Patients withCardiovascular Diseases

41 Evaluation Index System Based on Index ReliabilityTesting Here we perform reliability analysis on all reli-ability indicators of each object and the reliability indicatorswe choose for each object are slightly different e resultsare shown in Table 2

It can be seen from Figure 1 the overall situation of thepatientrsquos major adverse cardiovascular events the specificsituation of the major adverse cardiovascular events duringthe follow-up period and the occurrence of bleeding eventse data obtained from various indicators have a very goodeffect on this experiment (αgt 08) the data obtained fromthe patientrsquos cardiovascular risk factors and the degree ofcardiovascular disease have an acceptable impact on thisexperiment (αgt 07) indicating that this article is studyingthe effects of folic acid in the cardiovascular system e fiveindicators selected for the role of antithrombotic and an-ticoagulant drugs in the treatment of disease patients arereasonable which provide a basis for subsequent continuedexperiments

42 Evaluation Index System Based on Test Data

421 Analysis Based on Cardiovascular Risk FactorsHere we analyze the risk factors that cause cardiovasculardisease and analyze the occurrence of different risk factorse results are shown in Table 3

As can be seen from Figure 2 Group A had 11 cases(44) with a history of smoking 17 cases (68) with hy-pertension 7 cases (28) with diabetes and 15 cases withhigh total cholesterol 60 of patients had a low-densitylipoprotein concentration of 414 mmolL while those with alow-density lipoprotein concentration higher than 18mmolL accounted for 80 Group B had 9 patients (36)with a history of smoking 16 patients (67) with hyper-tension 7 patients (28) with diabetes mellitus 16 patients(60) with total cholesterol exceeding 414mmolL and 21

cases (84) with low-density lipoprotein above 18 mmolLGroup C had 10 patients (40) with smoking history 16patients (64) with hypertension 9 patients (36) withdiabetes 13 patients (52) with total cholesterol above414mmolL 20 cases (80) with low-density lipoproteinabove 18 mmolL and 6 cases (24) with a history ofsmoking Group D had 10 cases (40) with hypertension 5cases (20) with diabetes 9 cases (36) with total choles-terol above 414mmolL and 17 cases (68) with low-density lipoprotein more than 18mmolL (68) e fourgroups of patients had no difference in the statistical sig-nificance of smoking history hypertension history diabeteshistory total cholesterol and low-density lipoprotein(Pgt 005)

422 Comparison of the Degree of Cardiovascular DiseaseHere we analyze the degree of cardiovascular disease andanalyze the degree of cardiovascular disease in the patientaccording to the degree of cardiovascular stenosis and thenumber of diseased vesselse results are shown in Tables 4and 5

As can be seen from Figure 3 and Table 4 the dif-ferences in the degree of cardiovascular stenosis and thenumber of cardiovascular disease vessels in the fourgroups were statistically significant (Plt 001) e resultsof the pairwise comparison showed that the degree ofcardiovascular stenosis in group D was lighter than that ingroups A B and C and the number of cardiovascularlesions was also lower than that in groups A B and C edifference was statistically significant (Plt 005) isshows that folic acid drugs are effective in treating car-diovascular stenosis and preventing cardiovasculardisease

423 Multivariate Logistic Regression Analysis of Risk Fac-tors for Major Adverse Cardiovascular Events e riskfactors of major adverse cardiovascular events in patientswith cardiovascular diseases were analyzede results of the1-year follow-up are shown in Table 6

It can be seen from Figure 4 that smoking historyhypertension and diabetes are risk factors for major adversecardiovascular events in patients with cardiovascular dis-ease e OR values are 0663 0546 and 0179 respectivelywhich are all statistically significant (Plt 005) High totalcholesterol high-low-density lipoprotein number of dis-eased vessels and degree of diseased vessel stenosis are notrisk factors for recurring adverse cardiovascular events inpatients with cardiovascular disease

Table 1 General information of the two groups of patients

GroupNumber of cases

Years Course of disease Years of educationMale Female

A 14 11 6743plusmn 642 127plusmn 67 11plusmn 312B 17 8 6862plusmn 453 119plusmn 94 11plusmn 257C 15 10 6695plusmn 816 130plusmn 33 10plusmn 438D 17 11 6784plusmn 574 115plusmn 112 11plusmn 411


424 Overall Situation of Major Adverse CardiovascularEvents e overall situation of the major adverse cardio-vascular events is analyzed here and the results of the 1-yearfollow-up are shown in Table 7

It can be seen from Figure 5 that the overall main adversecardiovascular events of the four groups of patients were28 40 36 and 16 and the differences were statis-tically significant (P 0021 and Plt 005) ere was a

Table 2 Data sheet of evaluation index system for index reliability testing

Very clear Clear General Not clear Chaotic AlphaCardiovascular risk factors 369 435 400 043 056 08662Degree of cardiovascular disease 394 347 394 033 047 08754Overall situation of adverse cardiovascular events 355 404 439 054 053 07831Specific circumstances of adverse cardiovascular events during follow-up 353 347 450 075 034 07416Occurrence of bleeding events 372 366 469 070 052 07364

369394

355 353 372

435

347

404

347366

4 394439 45 469

043 033054

075 07056 047

053 034 052

005

115

225

335

445

5

Factors Disease InterventionAttributes

Cardiovascular Occurrence

Val

ueIndicator reliability test analysis chart

Very clearClearGeneral

Not clearChaotic

Figure 1 Indicator reliability test analysis chart

Table 3 Cardiovascular disease risk factor data sheet

Attributes A () B () C () D () T P

Smoking 11 (44) 9 (36) 10 (40) 6 (24) 2453 0280High blood pressure 17 (68) 16 (64) 16 (64) 10 (40) 1310 0579Diabetes 7 (28) 7 (28) 9 (36) 5 (20) 1436 0433Total cholesterol 15 (60) 16 (64) 13 (52) 9 (36) 1489 0372Low-density lipoprotein 20 (80) 21 (84) 20 (80) 17 (68) 0479 0751

11

17

7

15

20

9

16

7

16

21

10

169 13

20

6

10

5

9

17

0

5

10

15

20

25

Smoking Pressure DiabetesAttributes

Cholesterol Lipoprotein

Val

ue

A ()B ()

C ()D ()

Figure 2 Cardiovascular disease risk factor analysis chart


statistically significant difference in the major adverse car-diovascular events between group D and groups A B and C(Plt 005)

425 Usage Rate of Proton Pump Inhibitors and BleedingEvents Here the use rate of proton pump inhibitors and theoccurrence of bleeding events are analyzed and the resultsare shown in Table 8

It can be seen from Table 8 that the use rate of protonpump inhibitors in group A is 24 that in group B is 8that in group C is 16 and that in group D is 8 and thedifference is statistically significant (P 0002 Plt 001)After 1 year of follow-up the incidence of bleeding eventswas 4 in group A group B and group C ere was nobleeding event in group D and the difference was notstatistically significant (P 0433 and Pgt 005)

5 Conclusions

Currently there is no standard monitoring method forassessing the anticoagulant effect of new anticoagulants

Table 4 Cardiovascular stenosis data sheet

Cardiovascular stenosis A B C DModerate 5 10 20 22Severe 20 15 5 3

Table 5 Data sheet of diseased vessels

Diseased vessels A B C D1 12 15 19 212 6 5 5 43 7 5 1 0

12

15

1921

65 5 4

7

5 1 00

5

10

15

20

25

A B C D

Value

Group

123

Figure 3 Analysis of the number of diseased vessels

Table 6 Multivariate logistic regression analysis of risk factors

SE Wald OR P

Smoking 0203 0249 0663 0005High blood pressure 0194 0823 0546 0001Diabetes 0175 0191 0179 0001Total cholesterol 0196 0070 0831 0089Low-density lipoprotein 0261 0844 0634 0126Diseased vessels 0103 0032 0977 0987Cardiovascular stenosis 0187 0032 0996 0939

0203

0194

0175

0196

0261

0103

0187

0249

0823

0191

007

0844

0032

0032

0663

0546

0179

0831

0634

0977

0996

0005

0001

0001

0089

0126

0987

0939

0 02 04 06 08 1 12

Smoking

High bloodpressure

Diabetes

Total cholesterol

Low-densitylipoprotein

Diseased vessels

Cardiovascularstenosis

Value

Attr

ibut

e

POR

WaldSE

Figure 4 Multivariate logistic regression analysis chart of risk factors

Table 7 Data sheet on the overall situation of major adversecardiovascular events

A B C D X2 P

Overall major adverse cardiovascularevents 7 10 9 4 7375 0021

Death 0 1 1 0 5406 0061Angina pectoris 6 7 7 2 3543 0076Myocardial infarction 1 1 0 0 2430 0080Stent stenosis 0 0 0 0 9401 0065

7

109

4

01 1

0

67 7

21 1

0 00 0 0 00

2

4

6

8

10

12

A B C DV

alue

Group

Overall major adversecardiovascular eventsDeath

Angina pectorisMyocardial infarctionStent stenosis

Figure 5 Analysis chart of the overall situation of major adversecardiovascular events

Table 8 Bleeding incident data sheet

A B C D X2 PProton pump inhibitor 6 2 4 2 3236 0002Bleeding event 1 1 1 0 1610 0433


Even if they affect coagulation function the relationshipbetween these effects and bleeding and thrombosis has notbeen quantified For drugs such as warfarin which have anarrow therapeutic range the anticoagulant effect should bemonitored regularly for a long period of time in consid-eration of the safety of patient use So far there is no specificantagonist for complications such as bleeding caused by neworal anticoagulants e degree of cardiovascular stenosis ingroup D was lighter than that in groups A B and C and thenumber of cardiovascular lesions was also less than that ingroups A B and C e differences were statistically sig-nificant (Plt 005) is shows that folic acid medicine hasthe effect of treating cardiovascular stenosis and preventingcardiovascular disease e shortcoming of this study is thatin the design stage of the study it was not considered thatdifferent genders of patients may have different psycho-logical endurance which may have a certain impact on theresults of psychological interventions and should be takeninto consideration

Data Availability

Data sharing is not applicable to this article as no datasetswere generated or analyzed during the current study

Conflicts of Interest

e authors declare that they have no conflicts of interestregarding the publication of this study

References

[1] J V Fernandez-Montero P Barreiro C De MendozaP Labarga and V Soriano ldquoHepatitis C virus coinfectionindependently increases the risk of cardiovascular disease inHIV-positive patientsrdquo Journal of Viral Hepatitis vol 23no 1 pp 47ndash52 2016

[2] S Leone M Prosperi S Costarelli et al ldquoIncidence andpredictors of cardiovascular disease chronic kidney diseaseand diabetes in HIVHCV-coinfected patients who achievedsustained virological responserdquo European Journal of ClinicalMicrobiology amp Infectious Diseases vol 35 no 9 pp 1511ndash1520 2016

[3] R Klingel A Heibges and C Fassbender ldquoPrevention ofcardiovascular complications in patients with Lp(a)-hyper-lipoproteinemia and progressive cardiovascular disease bylong-term lipoprotein apheresis according to German na-tional guidelinesrdquo Clinical Research in Cardiology Supple-ments vol 12 pp 38ndash43 2017

[4] H Joo P Zhang and G Wang ldquoCost of informal care forpatients with cardiovascular disease or diabetes current ev-idence and research challengesrdquo Quality of Life Researchvol 26 no 6 pp 1ndash8 2016

[5] L A Leiter W T Cefalu TW A De Bruin et al ldquoLong-termmaintenance of efficacy of dapagliflozin in patients with type 2diabetes mellitus and cardiovascular diseaserdquo DiabetesObesity and Metabolism vol 18 no 8 pp 766ndash774 2016

[6] S G Ozkan H Yazisiz A Behlul Y A Gokbelen F Borluand V Yazisiz ldquoPrevalence of metabolic syndrome and degreeof cardiovascular disease risk in patients with psoriatic ar-thritisrdquo European Journal of Rheumatology vol 4 no 1pp 40ndash45 2017

[7] X Liu Y Sang S Ding et al ldquoExperimental study on themechanics characteristics of CFRP strengthening of highwaytunnels at different damage statesrdquo Geofluids vol 2020 no 711 pages Article ID 6665996 2020

[8] Z Lv D Chen R Lou and H Song ldquoIndustrial securitysolution for virtual realityrdquo IEEE Internet of ings Journalvol 8 no 8 pp 6273ndash6281 2020

[9] S Sun M Kadoch L Gong and B Rong ldquoIntegratingnetwork function virtualization with SDR and SDN for 4G5Gnetworksrdquo IEEE Network vol 29 no 3 pp 54ndash59 2015

[10] M S Dzeshka and G Y H Lip ldquoAntithrombotic and anti-coagulant therapy for atrial fibrillationrdquoHeart Failure Clinicsvol 12 no 2 pp 257ndash271 2016

[11] H Zhou M Jia B Liu and Z Chen ldquoermal sensation intransient conditions at subway stations during the winterrdquoInternational Journal of Heat and Technology vol 35 no 2pp 371ndash377 2017

[12] Y Shindo S Matsumoto H Miyatani Y Yoshida andH Mashima ldquoRisk factors for postoperative bleeding aftergastric endoscopic submucosal dissection in patients underantithromboticsrdquo World Journal of Gastrointestinal Endos-copy vol 8 no 7 pp 349ndash356 2016

[13] F Vincenz De M Raffaele and Z Angelo ldquo[Antithrombotictherapy and digestive endoscopy a difficult management]rdquoRecenti Progressi in Medicina vol 110 no 11 pp 535ndash5422019

[14] D Caldeira H Pereira and A Marques ldquoAdjuvant antith-rombotic therapy in ST-elevation myocardial infarctioncontemporaneous Portuguese cross-sectional datardquo RevistaPortuguesa de Cardiologia vol 38 no 11 pp 809ndash814 2019

[15] E Y F Wan D Y T Fong C S C Fung and C L K LamldquoIncidence and predictors for cardiovascular disease in crdquoJournal of Diabetes and Its Complications vol 30 no 3pp 444ndash450 2016

[16] E Y F Wan C S C Fung C K H Wong W Y Chin andC L K Lam ldquoAssociation of h levels with cardiovasculardisease and mortality in chinese patients with diabetesrdquoJournal of the American College of Cardiology vol 67 no 4pp 456ndash458 2016

[17] M Krikke R Hoogeveen A Hoepelman F Visseren andJ Arends ldquoCardiovascular risk prediction in HIV-infectedpatients comparing the f) systematic coronary risk evalua-tion for e Netherlands (SCORE-NL) and data collection onadverse events of anti-HIV drugs (DAD) risk predictionmodelsrdquo HIV Medicine vol 17 no 4 pp 289ndash297 2016

[18] R H Mackey L H Kuller and L W Moreland ldquoCardio-vascular disease risk in patients with rheumatic diseasesrdquoClinics in Geriatric Medicine vol 33 no 1 pp 105ndash117 2017

[19] K Dimitropoulos M I Omar A Chalkias E ArnaoutoglouJ Douketis and S Gravas ldquoPerioperative antithrombotic(antiplatelet and anticoagulant) therapy in urological practicea critical assessment and summary of the clinical practiceguidelinesrdquo World Journal of Urology vol 38 no 11pp 2761ndash2770 2020

[20] Z Wengen G Linjuan L Fadi et al ldquoEfficacy and safety oftriple versus dual antithrombotic therapy in atrial fibrillationand ischemic heart disease a systematic review and meta-analysisrdquo Oncotarget vol 8 no 46 pp 81154ndash81166 2017

[21] Y P Skirdenko N A Nikolaev M A Livzan andA V Ershov ldquoAnticoagulant therapy for atrial fibrillation inreal practice problems and prospectsrdquo Annals of the RussianAcademy of Medical Sciences vol 74 no 2 pp 98ndash107 2019

[22] K-H Jung K-H Yu Y-D Kim et al ldquoFocused update ofguidelines for antithrombotic management of patients with


atrial fibrillation and ischemic stroke or transient ischemicattackrdquo Journal of the Korean Neurological Associationvol 34 no 3 pp 184ndash192 2016

[23] K Wook-Joo P Jong-Moo K Kyusik et al ldquoAdherence toguidelines for antithrombotic therapy in patients with atrialfibrillation according to CHADS2 score before and afterstroke a multicenter observational study from koreardquo Journalof Clinical Neurology vol 12 no 1 pp 34ndash41 2016

[24] Z Lv ldquoVirtual reality in the context of internet of thingsrdquoNeural Computing amp Applications vol 32 no 2 pp 1ndash102019

[25] A L Melkumyan A L Berkovskiy S A Vasiliev andE V Sergeeva ldquorombotic diseases and conditions-diag-nosis and monitoring of anticoagulant therapyrdquo Meditsinskiysovet Medical Council no 21 pp 256ndash266 2021

[26] D Nikolopoulos A Fanouriakis and D Boumpas ldquoCere-brovascular events in systemic lupus erythematosus diagnosisand managementrdquo Mediterranean Journal of Rheumatologyvol 30 no 1 pp 7ndash15 2019

[27] T Georgios G Paraskevas S P Loannis andT Konstantinos ldquoAntithrombotic treatment is associatedwith small-bowel video capsule endoscopy positive findings inobscure gastrointestinal bleeding a systematic review andmeta-analysisrdquo Digestive Diseases and Sciences vol 64 no 1pp 15ndash24 2019

[28] D Sibbing D J Angiolillo and K Huber ldquoAntithrombotictherapy for acute coronary syndrome past present and fu-turerdquo rombosis amp Haemostasis vol 117 no 7pp 1240ndash1248 2017


progressing rapidly Antithrombotic and anticoagulanttreatments and treatments for cardiovascular disease havebeen significantly improved and developed It is believedthat the use of folic acid drugs to treat cardiovascular dis-eases will become an important breakthrough in the nearfuture Fernandez-Montero et al concluded that new oralanticoagulants have a relatively lower important bleedingrisk In terms of effectiveness the recurrence rate ofthrombosis after treatment with new anticoagulants is un-doubtedly not inferior to warfarin and it has not been seento significantly increase the risk of bleeding except forgastrointestinal bleeding [1] Leone et al used a heparincoating method based on hyaluronic acid Clinical studieshave shown that the coating method has better effects andless inflammatory response and can safely reduce theamount of heparinized heparin throughout the body duringcardiopulmonary bypass [2] Klingel et al proposed to ex-tend the anticoagulation time while reducing the recurrenceof the disease while the incidence of major bleeding in-creased by more than 3 times of which the gastrointestinaltract is the most common bleeding site [3]

e use of folic acid drugs for the treatment withantithrombotic and anticoagulant drugs for cardiovasculardisease began in Western countries Compared to Westerncountries my countryrsquos antithrombotic and anticoagulanttreatment technologies for cardiovascular disease begin in thesecond half of clinical practice and their development isrelatively slow With the continuous progress and develop-ment of modern science and technology and the increasingmaturity of medical technology the use of folic acid drugs totreat cardiovascular diseases will be an important researchwork Joo et al studied the morphology adhesion andproliferation of cells on PVC pipes with different coatings Forthe coating of cell adhesion it is mainly determined by theuniformity of the coating rather than the coating material [4]Leiter et al used a photochemical fixation method to cova-lently bond dipyridamole to the polyurethane surface It wasfound that dipyridamole significantly reduced the thrombusformation of the polyurethane surface and significantly re-duced the adhesion of platelets thereby improving the bloodcompatibility of the polyurethane [5] Ozkan et al pointed outthat it is necessary to enhance the positive attitude of patientsto treatment reduce their anxiety depression and othernegative emotions extend the survival period of cancer pa-tients improve their quality of life and improve the recoveryrate of patients we believe that we will provide clinicalstandards for this illness [6ndash8]

is article mainly studies the role of folic acid drugs inthe treatment with antithrombotic and anticoagulant drugsfor patients with cardiovascular diseases based on virtualreality medical data analysis rough the design ofantithrombotic and anticoagulant drug treatment experi-ments for patients with cardiovascular diseases the indi-cators of cardiovascular disease patients are analyzed at thesame time the logistic regression analysis method was usedto correct various factors affecting recurring adverse car-diovascular events and finally the various test data of pa-tients were analyzed [9 10] e innovations in this articlenot only pay attention to the role of folic acid in the

treatment of patients with cardiovascular disease withantithrombotic and anticoagulant drugs but also use virtualreality medical data analysis techniques to comprehensivelyand experimentally obtain experimental results It is a sys-tematic analysis that facilitates the treatment of cardiovasculardisease processes and developmental research [11 12]

2 Cardiovascular Disease and Antithromboticand Anticoagulant Treatment

21 Image Processing

211 Diffusion Tensor Imaging Diffusion tensor imagingfirst assumes that the movement of molecules is a simpleanisotropic diffusion process and calculates a representationof the diffusion tensor under the premise that the probabilitydensity function p satisfies a Gaussian distribution modelwith three variables of zero mean e calculation method isshown in the following formula

p(x) G(x Y t) (1)

e Gaussian probability distribution function here issatisfied

G(x Y t) (4πt)3det(Y)1113960 1113961

minus12

1113874 1113875exp minus

xTY

minus 1x

4t1113888 1113889 (2)

Here Y is the diffusion tensor and t is the diffusion timeIf we transpose formula (1) we can get

A(q) exp minus tqTYq1113872 1113873 (3)

If the logarithm of both sides of formula (3) is taken hereat the same time then a linear constraint on the unknownquantity Y expressed by A(q) can be obtained Among themthe diffusion tensor Y can be written in the form of a matrix

Y

Yxx Yxy Yxz

Yyx Yyy Yyz

Yzx Yzy Yzz

⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (4)

where Y is a symmetric positive semidefinite tensor that isthere is always Yij Yji for all i j z y z In order toobtain a complete evaluation value of the diffusion amountof a volume element the average diffusion value is intro-duced as an invariant into the diffusion tensor imaging It isan independent quantity that has nothing to do with thedirection It can measure the deviation of the uniformmolecular motion on the surface of a body Directly use thetrace of the diffusion tensor Y to directly represent thediffusionmean MY and the calculationmethod is as follows

MY tr(Y)

3

Yxx + Yyy + Yzz

3

(5)

e average diffusion value will be lower in the ischemicarea of the brain which is of great significance to the clinical




Yapp(x) 1113944

3

ij1Yijxixj (6)



RA

λ1 minus λ1113872 11138732

+ λ2 minus λ1113872 11138732

+ λe minus λ1113872 11138732

3λ

11139741113972

(7)

Among them

λ λ1 + λ2 + λ3( 1113857

3 (8)


FA

32

1113970

λ1 minus λ1113872 11138732

+ λ2 minus λ1113872 11138732

+ λe minus λ1113872 11138732

λ21 + λ22 + λ231113872 1113873

11139741113972

(9)


VR 3λ1λ3


(10)





(11)


KL(pq)neKL(qp) (12)









pt p y 1



CE(p y) CE pt( 1113857








22 Smart Medical


































369394

355 353 372

435

347

404

347366

4 394439 45 469

043 033054

075 07056 047

053 034 052

005

115

225

335

445

5



Val



Not clearChaotic





11

17

7

15

20

9

16

7

16

21

10

169 13

20

6

10

5

9

17

0

5

10

15

20

25



Val

ue

A ()B ()

C ()D ()






5 Conclusions






12

15

1921

65 5 4

7

5 1 00

5

10

15

20

25

A B C D

Value

Group

123



SE Wald OR P


0203

0194

0175

0196

0261

0103

0187

0249

0823

0191

007

0844

0032

0032

0663

0546

0179

0831

0634

0977

0996

0005

0001

0001

0089

0126

0987

0939

0 02 04 06 08 1 12

Smoking

High bloodpressure

Diabetes

Total cholesterol


Diseased vessels


Value

Attr

ibut

e

POR

WaldSE



A B C D X2 P



7

109

4

01 1

0

67 7

21 1

0 00 0 0 00

2

4

6

8

10

12

A B C DV

alue

Group








Data Availability




References


































Yapp(x) 1113944

3

ij1Yijxixj (6)



RA

λ1 minus λ1113872 11138732

+ λ2 minus λ1113872 11138732

+ λe minus λ1113872 11138732

3λ

11139741113972

(7)

Among them

λ λ1 + λ2 + λ3( 1113857

3 (8)


FA

32

1113970

λ1 minus λ1113872 11138732

+ λ2 minus λ1113872 11138732

+ λe minus λ1113872 11138732

λ21 + λ22 + λ231113872 1113873

11139741113972

(9)


VR 3λ1λ3


(10)





(11)


KL(pq)neKL(qp) (12)









pt p y 1



CE(p y) CE pt( 1113857








22 Smart Medical


































369394

355 353 372

435

347

404

347366

4 394439 45 469

043 033054

075 07056 047

053 034 052

005

115

225

335

445

5



Val



Not clearChaotic





11

17

7

15

20

9

16

7

16

21

10

169 13

20

6

10

5

9

17

0

5

10

15

20

25



Val

ue

A ()B ()

C ()D ()






5 Conclusions






12

15

1921

65 5 4

7

5 1 00

5

10

15

20

25

A B C D

Value

Group

123



SE Wald OR P


0203

0194

0175

0196

0261

0103

0187

0249

0823

0191

007

0844

0032

0032

0663

0546

0179

0831

0634

0977

0996

0005

0001

0001

0089

0126

0987

0939

0 02 04 06 08 1 12

Smoking

High bloodpressure

Diabetes

Total cholesterol


Diseased vessels


Value

Attr

ibut

e

POR

WaldSE



A B C D X2 P



7

109

4

01 1

0

67 7

21 1

0 00 0 0 00

2

4

6

8

10

12

A B C DV

alue

Group








Data Availability




References































































369394

355 353 372

435

347

404

347366

4 394439 45 469

043 033054

075 07056 047

053 034 052

005

115

225

335

445

5



Val



Not clearChaotic





11

17

7

15

20

9

16

7

16

21

10

169 13

20

6

10

5

9

17

0

5

10

15

20

25



Val

ue

A ()B ()

C ()D ()






5 Conclusions






12

15

1921

65 5 4

7

5 1 00

5

10

15

20

25

A B C D

Value

Group

123



SE Wald OR P


0203

0194

0175

0196

0261

0103

0187

0249

0823

0191

007

0844

0032

0032

0663

0546

0179

0831

0634

0977

0996

0005

0001

0001

0089

0126

0987

0939

0 02 04 06 08 1 12

Smoking

High bloodpressure

Diabetes

Total cholesterol


Diseased vessels


Value

Attr

ibut

e

POR

WaldSE



A B C D X2 P



7

109

4

01 1

0

67 7

21 1

0 00 0 0 00

2

4

6

8

10

12

A B C DV

alue

Group








Data Availability




References



































5 Conclusions






12

15

1921

65 5 4

7

5 1 00

5

10

15

20

25

A B C D

Value

Group

123



SE Wald OR P


0203

0194

0175

0196

0261

0103

0187

0249

0823

0191

007

0844

0032

0032

0663

0546

0179

0831

0634

0977

0996

0005

0001

0001

0089

0126

0987

0939

0 02 04 06 08 1 12

Smoking

High bloodpressure

Diabetes

Total cholesterol


Diseased vessels


Value

Attr

ibut

e

POR

WaldSE



A B C D X2 P



7

109

4

01 1

0

67 7

21 1

0 00 0 0 00

2

4

6

8

10

12

A B C DV

alue

Group








Data Availability




References

































Data Availability




References
































role of folic acid drugs in the treatment with

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