Research article Special Issues

Assessment of cardiovascular risk factors among HIV-infected patients aged 50 years and older in Cameroon

  • Background 

    Increasing the longevity of people living with HIV (PLHIV) around the world has been accompanied by an increase in the prevalence of cardiovascular disease (CVD) risk factors and morbidity. The impact of these trends on the epidemiology of CVD among PLHIV is less clear. The aim of this study was to assess the risk factors for CVD, and to estimate these risks at 10 years in PLHIV aged 50 and above.

    Methods 

    This was a descriptive and analytical study carried out at Mvog Ada District Hospital in Yaounde, Cameroon from January 2020 to January 2021. Descriptive bivariate analyses were used to present the data. The data are presented as frequencies and percentages for categorical variables, and in terms of means and standard deviations for continuous variables where appropriate. The 10-year CVD risk score was calculated using two tools: the validated Framingham risk score (FRS) (low < 10%, moderate 10–20% and high ≥ 20%) and SCORE score (SSC) (low < 3%, moderate 3–4% and high ≥ 5%). Multiple logistic regression models were constructed to examine the respective relationships between the binary dependent variable high CVD risk (FRS ≥ 20%) and the population group, alcohol consumption (more than 10 glasses of beer per week, or more than 35.7 cl/day) and hypertriglyceridemia (independent variables). A p-value less than or equal to 0.05 was considered statistically significant.

    Results 

    A total of 112 people aged 50 and above were enrolled in the study out of 180 people registered at the HIV care unit, that is a participation rate of 62.22%. The average age of the participants was 57.3 ± 6.4 years, and the female/male ratio was 1.6. The majority of participants (53.57%) had normal glycaemia levels (<1.10 g/L), 4.46% were diabetic and 46.40% had high blood pressure. The adherence rate for ARV treatment was 98.20%; most participants (77.20%) were alcohol consumers, and 28.10% of participants had hypertriglyceridemia. The estimates of overall cardiovascular risk in 10 years presented 50.90% of participants with low risk, 33% with moderate risk and 16.10% with high risk.

    Conclusions 

    Our study indicated an overall risk of cardiovascular events in 10 years is 16.10%, with the main conditional risk factor being hypertriglyceridemia and alcohol consumption, which appeared to triple the risk of CVD among PLHIV.

    Citation: Henri Olivier Tatsilong Pambou, Amandine Gagneux-Brunon, Bertrand Tatsinkou Fossi, Frederic Roche, Jessica Guyot, Elisabeth Botelho-Nevers, Caroline Dupre, Bienvenu Bongue, Celine Nguefeu Nkenfou. Assessment of cardiovascular risk factors among HIV-infected patients aged 50 years and older in Cameroon[J]. AIMS Public Health, 2022, 9(3): 490-505. doi: 10.3934/publichealth.2022034

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  • Background 

    Increasing the longevity of people living with HIV (PLHIV) around the world has been accompanied by an increase in the prevalence of cardiovascular disease (CVD) risk factors and morbidity. The impact of these trends on the epidemiology of CVD among PLHIV is less clear. The aim of this study was to assess the risk factors for CVD, and to estimate these risks at 10 years in PLHIV aged 50 and above.

    Methods 

    This was a descriptive and analytical study carried out at Mvog Ada District Hospital in Yaounde, Cameroon from January 2020 to January 2021. Descriptive bivariate analyses were used to present the data. The data are presented as frequencies and percentages for categorical variables, and in terms of means and standard deviations for continuous variables where appropriate. The 10-year CVD risk score was calculated using two tools: the validated Framingham risk score (FRS) (low < 10%, moderate 10–20% and high ≥ 20%) and SCORE score (SSC) (low < 3%, moderate 3–4% and high ≥ 5%). Multiple logistic regression models were constructed to examine the respective relationships between the binary dependent variable high CVD risk (FRS ≥ 20%) and the population group, alcohol consumption (more than 10 glasses of beer per week, or more than 35.7 cl/day) and hypertriglyceridemia (independent variables). A p-value less than or equal to 0.05 was considered statistically significant.

    Results 

    A total of 112 people aged 50 and above were enrolled in the study out of 180 people registered at the HIV care unit, that is a participation rate of 62.22%. The average age of the participants was 57.3 ± 6.4 years, and the female/male ratio was 1.6. The majority of participants (53.57%) had normal glycaemia levels (<1.10 g/L), 4.46% were diabetic and 46.40% had high blood pressure. The adherence rate for ARV treatment was 98.20%; most participants (77.20%) were alcohol consumers, and 28.10% of participants had hypertriglyceridemia. The estimates of overall cardiovascular risk in 10 years presented 50.90% of participants with low risk, 33% with moderate risk and 16.10% with high risk.

    Conclusions 

    Our study indicated an overall risk of cardiovascular events in 10 years is 16.10%, with the main conditional risk factor being hypertriglyceridemia and alcohol consumption, which appeared to triple the risk of CVD among PLHIV.


    Abbreviations

    ART:

    Antiretroviral therapy; 

    BMI:

    Body mass index; 

    CI:

    Confident interval; 

    CVD:

    Cardiovascular disease; 

    DAD:

    Data collection on adverse effects of anti-HIV drugs; 

    DBP:

    Diastolic blood pressure; 

    FRS:

    Framingham Risk Score; 

    HDL-C:

    High density lipoproteins-cholesterol; 

    HIV:

    Human immunodeficiency virus; 

    LDL-C:

    Low-density lipoproteins-cholesterol; 

    PLHIV:

    People Living with HIV; 

    SBP:

    Systolic blood pressure; 

    SCORE:

    Systemic coronary risk evaluation; 

    SSC:

    Score of SCORE; 

    SD:

    Standard deviation

    In Industry 5.0, blockchain technology, and Encryption ciphers play an essential role in designing and deploying various real-time applications. All applications are currently transferring from Industry 4.0 to Industry 5.0 because of increasing adaptability, productivity, and creating a responsive working environment. It has an impact on cost reduction [1]. This technology mainly focuses on the interaction between machines and human intelligence. It helps to design and deploy the applications to a new level of speed and performance.

    Furthermore, Blockcert is an open standard used for creating, viewing, verifying, and issuing any blockchain-related certificates [2]. Number of applications such as supply chain, Internet of things (IoT) [3], agriculture [4], aquaculture [5], health care departments can be benefited from the combination of Industry 5.0 and blockchain technology. Rapid growth in blockchain utilization is because of its advanced features like immutability, transparency, distribution, accountability, security, and reliability [6]. Moreover, it enhances the integration of other disruptive technologies [7] like machine learning, artificial intelligence, and others. Therefore, the proposed system is designed by considering domain expert knowledgeable users as entities to automate the proposed proposes over a blockchain. Many countries want to conduct their elections by a fully transparent voting system using blockchain technology. Russia has launched a blockchain-based electronic-voting system pilot project with the association of the City Election Commission of Moscow and the Department of Information Technology (DIT) [8]. Similarly, some countries like the United States, Netherlands, UK, Sweden, and India announced that blockchain technology-based real estate and land registry processes would be started shortly.

    This paper discusses the design and development of a distributed application for managing medical certificates. Logistic Map Encryption (LME) cipher [9] is used to encrypt the existing medical certificates before passing them over a blockchain by an expert agent, i.e., a doctor. Generally, a healthcare center's authority issued medical certificates such as birth, death, and sick (HCC). These are issued for various reasons like birth, death, and some health-related issues for employees to claim their leaves in their working environment. This application helps to avoid fraud in the generation of medical certificates from the healthcare centers.

    The remaining paper is organized as follows. Section 2 presents a literature survey. The proposed architecture based on Industry 5.0 and blockchain is discussed in section 3. Section 4 depicts results and analysis. The paper is concluded in section 5.

    Chuka Oham et al. [9] proposed a framework for vehicle security, B-FERL, using blockchain technology. By using blockchain, B-FERL identifies whether an intelligent vehicle's ECU is compromised by checking the interior disposition of the vehicle. When a compromise is spotted, it is escalated to rightful officials to take necessary actions to avert the compromised automobiles from begetting harm to the vehicular complex. The proposed framework works for both identification and response operations. B-FERL, a framework, helps us to safeguard the automobile against exploitation.

    Abdellatif et al. [10] proposed a system that allows the local nodes or servers to exchange medical data through a secure blockchain network. The system contains a local network and a blockchain network where the local network processes medical data for optimization, and the vital information is shared through a blockchain network. The local data is collected through IoMT (Internet of Medical Things) and LHSP (Local Healthcare Service Provider). This entities-based network sharing helps in extensive data storing through processing and a secure approach to developing medical record exchange.

    B. K. Mohanta et al. [11] discussed various real-time security, privacy issues, and solutions regarding the Ethereum blockchain technology. The main factors are mainly low processing power, unsuitable cryptography techniques, and storage capacities. The problems based on IoT are also mentioned concerning various security layers with the integration of blockchain. The layers such as network, physical, and application are categorized into multiple risk zones based on the earlier issues. This differentiation helps to choose different data collection factors, aggregation, and analysis for risk-free security techniques.

    Anushree Tandon et al. [12] discussed sharing electronic of medical records through blockchain technology. The work states that the healthcare sector has a wide range of use cases on blockchain, such as maintaining electronic medical records, pharmaceutical supply chain, remote patient monitoring, and health insurance claims. This work helps us to understand the multiple applications available in the healthcare sector through blockchain security. Table 1 gives the information about comparison and contrast between existing works to the proposed system.

    Table 1.  Related works overview.
    Authors Properties
    Admin BCT type Tool Integrity check Access control Application
    Sudeep [13] Existed Private Hyper
    ledger caliper
    Yes Yes Health care
    Emeka Chukwu [14] No exist Public Not specified No No Health care
    Ben Fekih R [15] No exist Public Not specified No No Medical records
    W. Lin [16] Exist Consortium DSSCB and VANET Yes Yes Agriculture
    Rakesh Shrestha [17] Existed Consortium Not specified Yes Yes Ad-hoc network
    Chun Ta Li [18] No exist Public Ethereum and Amazon Cloud No No Medical data
    M. Al Baqari[19] No exist Public Not specified No No EHR
    M. Tabrez Quasim [20] No exist Public Not specified Yes No Health care App
    Hasselgren A
    [23]
    Study work Study work Study work Yes Yes Health
    care
    Hasselgren A [25] Study work Study work Study work Study work Study work Health
    care
    Jens-Andreas H
    [26]
    Existed Public Ethereum Yes Yes Health
    care
    Proposed Methodology Existed Public Remix and
    text RPC
    Yes Yes Medical certificate

     | Show Table
    DownLoad: CSV

    Blockchain technology is a disruptive technology. Currently, so many real-time applications are being designed using this advanced mechanism. This paper proposes a distributed application-based mechanism for maintaining official medical certificates under Industry 5.0 technology. It uses blockchain technology and users as knowledge agents. Initially, the Remix Etherum platform was used with Metamask wallet to deploy the proposed framework to generate medical certificates like birth, death, and sick.

    Furthermore, the system is implemented with a test RPC, Web, and Metamask to design and deploy the distributed application to maintain the new medical certificates and existing certificates that are available as physical copies. Logistic Map Encryption function [21] is used to generate cipher medical certificate of existing physical copies to maintain over a blockchain. So many applications have been proposed in the health sectors using blockchain. Some of the lapses existing in the proposed work are lack of implementation results, platform details, etc.

    The proposed system's main ingredients are authorized health centers as domain experts, users, blockchain as intelligent agents, and local database to maintain the Electronic Health Care Certificates (EHCC), as shown in Figure 1.

    Figure 1.  Industry 5.0 based proposed system.

    At first, all the health care centers have to get recognition from the hospital's regulatory authority (HRA) by submitting the required documents. HRA issues a unique ID to a healthcare center to give treatment to the patients and issue medical certificates to the users.

    We have mainly focused on issuing and maintaining a blockchain-based medical certificate such as birth, death, or sick in the proposed system. Figure 2 shows the process of ethereum blockchain-based medical certificate generation and maintenance.

    Figure 2.  Proposed system methodology.

    a) Smart contract

    The smart contract is lines of code using solidity programming. Each operation in the proposed system is executed through smart contracts consisting of solidity programming lines [21]. This system is implemented in two ways i.e., using a Web-based distributed Application and a system-based application. Both the applications use solidity programming to write smart contacts for performing the system operations like Cert_issue (), Cert_revoke () and Cert_verify (). The attributes of the certificates are Hospital Name, Hospital ID, Hospital address, Doctor Name, Certificate type, Recipient Name and address, a unique ID of the certificate in terms of a hash value. The structure of the main attributes of the medical certificate are as follows.

    Struct Medical_certificate
    String Hospital_ID
    String Hospital_name
    String Hosipital_Address
    String Recipient_ Name
    String Rec_Address

     | Show Table
    DownLoad: CSV

    1) Hospital_Name: A name of a hospital that has ready to issue the medical certificate.

    2) Hospital_ID: A hospital unique identity number (ID) that is issued by the central health care centers regulatory authority.

    3) Recipient_Name: A name of the receiver who has approached the hospital and requested a medical certificate.

    4) Recipient_Address: Complete details of the receiver like address, phone number, purpose. etc

    5) Certificate_Type: This field refers to the type of certificates such as birth, death, or a sick medical document.

    6) Doctor_Name: It gives information about the physician who has approved the certificate to the user.

    7) _Date: On which date the certificate was generated and issued.

    8) Cert_hash: It is a unique ID of the certificate that will be generated based on the certificate's contents. And also, that will be used to refer to a specific certification that was issued by a central authority.

    b) Ethereum blockchain-based system Implementation

    Ethereum blockchain-based medical certificate maintenance is implemented in two ways, i.e., DApp using Web and test RPC, a system-based application using Remix. Both test PC and Remix run on the ethereum public blockchain network. Metamask wallet is a browser extension is used to get Eth. Eth is a cryptocurrency unit that is required to perform any operations over a blockchain network. Remix platform-based smart contract is deployed on Ropstern network-based ethereum blockchain. Test RPC-based DApp smart contract is deployed on localhost 8545. Algorithm 1 shows the health care centers recognition from regulatory authority assumed as a prerequisite in the proposed system.

    Algorithm 1: HCC_ enroll ()
    Input: HCC_Name, HCC_address, regulatory authority name
    Output: Unique ID to the HCC
    Step 1: Submit the details of health care centers such as Name
      address, infrastructures, Authority Name.
    Step 2: HCC_application = Name (HCC) || Addr(HCC) ||
    Infra_details (HCC) || Experts (HCC) || Auth (HCC)
    Step 3: Validate the details by Central regulatory authority (CA)
    If (Integrity (HCC_Application) = = True) then
      issue unique ID otherwise reject the request
        HCCi = IDi

     | Show Table
    DownLoad: CSV

    The process of medical certificate issued to the user by the HCCs on both the proposed ways is shown in Algorithm 2. The user initially needs to submit the details about the required certifications such as a type of certificate (Birth, death, and sick), Name of a recipient, and address to the health care centers. Furthermore, a physician or authorized person from the health care centers verifies the details by saving them in the healthcare centers' local database. Create a blockchain-based ID by successfully sending the certificate into ethereum based blockchain after going through the verification process. Metamask Wallet balance is required to perform any operation over a blockchain.

    Algorithm 2: Cert_issue ()
    Input: Certificate type, User name, user address, Date
    Output: Blockchain (BCT) based a unique ID
    Step 1: Verify the details given by the user
      if ((Valid (details) = = True)) & & Exist_ application)
        Cipher Certificate = E LMF (Exist(certificate))
      if ((Valid (details) = = True)) & & New_application)
          Stores in HCC_local database.
            Process on blockchain network.
    Step 2: Enroll the credentials using Web based DApp or
        system App.
    Step 3: Connect to Metamsk.
      Ask confirmation to establish a connection between application to blockchain environment over a Ropestern or localhost 8545 Network.
    Step 4: If confirms the metamask request
          Connection established and go to Step 5
    otherwise not established
    Step 5: If (Eth_balance > = Operation required balance) then
      Set the credentials over a blockchain
      BCT based Certificate generates
      Unique BCT _ID allotted to the certificate
    Step 6: If Step 5 fails then shows as
      Not enough Eth balance unable generate a BCT-based
      certificate.

     | Show Table
    DownLoad: CSV

    Algorithm 3 shows the process of encryption algorithm LMF that is used to encrypt the existing medical certificate document image before processing over a blockchain. LME based cipher medical certificate is uploaded through proposed Dapp from a system and is maintained over an ethereum based blockchain.

    Algorithm 4 shows the validation process after authority issues an authority to the user or any authorized person. This application helps to prove their identity regarding their birth or death or sick by presenting a unique BCT_ID without showing any physical identity proofs. Anywhere and anytime, the user's claim can be proved by presenting his/her BCT_ID. An authorized person enters the user ID in the application and verifies the credentials, whether if they exist in the blockchain or not. Figure 4 shows a metamask screen with a confirmation request to connect distributed application to a blockchain environment on the Test RPC based localhost 8545 network.

    Algorithm 3: Logistic Map Encryption Cipher
    Input: Medical Certificate image – Existed/Older version
    Output: Cipher Medical certificate
    Step 1: Read a random number i.e., 'x' and plain medical
      certificate (MI)
        Where x ϵ (0, 1) and MI_size ← size (MI)
    Step 2: Apply chaotic logistic map.
    Step 3: For i ←1 to MI_size do
        µ ← random number where µ ϵ (3.5, 4)
        xi ← µ x(1-x)
        x ← ni
      k1[] ← xn
    Step 4: Generate a pseudo random sequence using a rightshift
        operation.
          for j ←1 to MI_size do
        µ ← random number where µ ϵ (3.5, 4)
          xj ← µ x(1-x)
        x ← xj
      k2[] ← RSR (xn*255)
    Step 5: Generates a key matrix
        key[][] ← (k1[]) ⊕ (k2[])
    Step 6: Generates a Cipher Certificate
        Enccertificate⟵ MI[][] ⊕ Key[][]

     | Show Table
    DownLoad: CSV
    Algorithm 4: Cert_verify ()
    Input: BCT_ID
    Output: Existed or not
    Step 1: Enter BCT_ID into the Web based Distributed application (DApp) or System application
    Step 2: If (BCT_ID == Existed) then go to Step 3 otherwise go to Step 4.
    Step 3: Successfully verified
    Step 4: Unsuccessful Entry
      Revoke the user request

     | Show Table
    DownLoad: CSV
    Figure 3.  Metamask connection confirmation to process the smart contract over Remix platform.
    Figure 4.  Metamask connection confirmation to process the smart contract over the DApp platform.

    Blockchain technology is raised as an essential technology in Industry 5.0. Although highly well securely designed technology for resilience, some attacks are undertaking in it. The main elements of a blockchain that can suffer from vulnerabilities are Smart Contracts, blockchain nodes, Wallets, and consensus mechanisms. Generally, blockchain attacks are categorized into four ways based on peer-to-peer network, wallet, smart contract, and consensus & ledger [27]. The lists of attacks under these categories are as follows.

    a. 51% attack

    The fundamental assumption in the blockchain mechanism design is that only the trusted nodes with the maximum computational power control system work on the blockchain network. If the unauthorized nodes with the collective power control system are more than the trusted or authorized nodes, then the risk of 51% will have occurred. Beikverdi et al. [28] discussed 51% attacks possibilities over a blockchain, although it is decentralized. In the proposed application, all the parties participate in the network using the allotted unique ID. Hence, every user must prove them as an authorized entity like the Zero-knowledge (ZK) protocol mechanism.

    b. Eclipse attack

    It refers to that attack on a specific user rather than a whole network on a decentralized network. It is a known attack in which the attacker seeks to isolate the victim user by flooding with false data then exploits them. The proposed knowledge engineering-based BCT application allocated a unique ID to the user and authorized parties for making transactions and communication. Allow only the parties who are participating in the network through the allotted unique ID. Each user sends a request to the health care centers, using an assigned unique ID to get their official health documents.

    c. Finney attack

    It is a type of double-spending attack that creates a chain to support fraud transactions. The attacker needs to spend a lot of time and patience to perform this type of attack because mining participation is required. In response to this, the attacker creates two transactions with the same amount. An initial transaction includes a valid block, and mining will start without broadcasting it to the network by an attacker. This meanwhile, the attacker creates a second transaction with the vendor by spending the same amount.

    If the vendor accepts the attacker transaction without confirmation from the network and serves the good, immediately an attacker transmits the mined block that includes the first transaction. The network takes valid blocks and rejects the vendor transaction. The vendor should wait to receive at least six confirmations before serving goods to mitigate this attack.

    In a Finney attack, the time to transfer the amount by an attacker and the time for merchant acceptance is 't'. The average time to find a block is 'T.' The probability of another block to be found on the same network simultaneously is 't/T. 'Generally, the attack will fail in this case, and the attacker will lose the reward of 'B.' The average cost of attempting the attack is = (t/T) × B. As a rule of thumb, the merchant should wait at least t = V x (T/B), Where V = value of the transaction

    d. Race attack

    Pre-mining the block before making a transaction doesn't require here as requires in the Finney attack [29,30,31,32,33]. Instead, the attacker sends the same amount to more than one vendor within a short period. In addition, the vendor receives a message about transaction rejection during mining when he provides service without receiving the block confirmation. Therefore, the vendor should wait for at least one confirmation block before delivering the goods to avoid this attack.

    We have implemented the proposed system using the remix platform and also tested it using the test RPC platform. Ethereum blockchain [32,34,35,36,37,38,39] network is used in these platforms. Moreover, this system used a browser extension, Metamask cryptocurrency wallet, to deploy the system operations over a blockchain network. An open-source, public blockchain-based application, Remix is used here to write the smart contracts using solidity programming for the functions performed by the proposed system such as issue_certificate () and verify_certificate (). Furthermore, we have deployed the proposed system operations using a decentralized application designed using Web, Test RPC node, and solidity programming based smart contracts.

    Figure 3 shows a metamask screen with a confirmation request to establish a connection between the Remix platform to the etherum blockchain running on the Ropstern network.

    We have to pay a crypto balance to operate any function over a blockchain network. Figures 3 and 4. show the confirmation request screens to establish a connection with the operating costs. The credentials enter on the webpage verified with the details in the Google Firebase at administration side. From Figure 2, we came to know that the connection establishment between a Remix-based medical certificate smart contract to the Ropstern based blockchain network cost is 0.000761 Gas. Figure 3 shows that the connection between the proposed application and the Test RPC (Localhost 8545) based blockchain cost is 0.001995 Gas.

    After successfully establishing the connections, medical certificates' attributes are used to issue the certificate to the user after deploying the certificates details in cipher format using LME algorithm over blockchain at administration side. Figure 5. shows the set () function's operating cost to deploy the attributes of the user-required medical certificates.

    Figure 5.  Set () operational cost over a remix platform.

    Figure 6 shows the cost of operation on an etherum blockchain-based distributed application. This certificate consists of a hospital registered ID, doctor name, hospital name, a required certificate type, i.e., death, birth or sick, date of issue, etc. The results regarding the verification of the generated medical certificate is shown in Figure 7. The proposed method's operational cost over an etherum based blockchain network is shown in Table II. This table shows the cost of deployed functions of the system such as set_credentials (), issue_certificate () and verify_certificate ().

    Figure 6.  Set () operational cost over a distributed application.
    Figure 7.  Verification of a medical certificate on Remix platform.

    Figure 8 shows Gas's consumption to generate medical certificates on both the platforms such as Remix Ethereum blockchain and test RPC etherum blockchain using Metamask Wallet. Gas consumption is measured in the units of Eths and GWei. Here we tested the application by generating up to 100 certificates.

    Figure 8.  Gas cost to set the medical certificates credentials on various platforms.

    Figure 9 shows the details of the proposed system's operational cost on the Ropstern network and the localhost 8545 network by Web-based distributed application and remix-based system application.

    Figure 9.  Consumption of total Eth for certificates generation.

    Figure 10 shows the details of transaction hash, block number, from address, to address, the value of the transaction interms of Ether, Txn Fee, Nonce, etc. The proposed system performance analyzed by considering the existing systems by considering the non functional operations such as latency and processing time. Here considered 100 certificates to process over a blockchain to investigate the system's latency and processing time. The processing time increases as the number of users increase to process their request over a system. Figures 11 and 12 show the comparison results with the existed systems which have implementation results.

    Figure 10.  Proof of Etherscan to the certificate maintains over a blockchain.
    Figure 11.  Latency time for different transactions.
    Figure 12.  Processing time for different transactions.

    Blockchain technology can help reduce fraud in the distribution and management of medical certificates. The proposed system will automate the certificate generation and certification process and maintenance and make it an attack resistance system using Ethereum based public blockchain technology. A single point and Central Authority failure affect the reliability of the system. The proposed approach reduces these kinds of problems with the immutable feature of the blockchain. Due to its transparent feature, every node in the system gets information about creating a new medical certificate in a block as a transaction. Here Mata mask wallet is used for cryptocurrency balance in terms of Eths to operate system functionalities over a blockchain. The proposed system is a user-friendly application to issue or verify medical certificates from anywhere at any time.

    Authors would like to acknowledge to the Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Lincoln University College, Malaysia, and Taif University Saudi Arabia for supporting this work.

    This research was supported by Taif University Researchers Supporting Project number (TURSP-2020/216), Taif University, Taif, Saudi Arabia.

    Authors declare that they have no conflict of interest.


    Acknowledgments



    Gratitude is given to the coordinator and psychosocial guides of the HIV outpatient clinic of the Yaoundé, Mvog Ada district health hospital for their assistance during recruitment, and to the personnel of the biochemistry laboratory of the Yaoundé Medical Diagnostic Centre for their assistance during biochemical measurements. The authors are also grateful to all those who have voluntarily accepted to take part in this study. All authors have taken responsibility for all aspects of the reliability and freedom-from-bias of the data presented, and they have all discussed its interpretation.

    Funding



    This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

    Ethics approval and consent to participate



    The study was approved by the Cameroon National Ethics Committee for Human Health Research (Ethical approval No. 2131/CRERSHC/2020). All participants signed a consent form.

    Conflict of interest



    The authors declare that they have no competing interests.

    [1] Fiche d'informationDernières statistiques sur l'état de l'épidémie de sida. UNAIDS (2021). Available from: http://www.unaids.org/fr/resources/fact-sheet
    [2] Fiche d'informationDernières statistiques sur l'état de l'épidémie de sida. UNAIDS (2019). Available from: http://www.unaids.org/fr/resources/fact-sheet
    [3] Smit M, Brinkman K, Geerlings S, et al. (2015) Future challenges for clinical care of an ageing population infected with HIV: A modelling study. Lancet Infect Dis 15: 810-818. https://doi.org/10.1016/S1473-3099(15)00056-0
    [4] Smith J, Flexner C (2017) The challenge of polypharmacy in an aging population and implications for future antiretroviral therapy development. AIDS 31: S173-S184. https://doi.org/10.1097/QAD.0000000000001401
    [5] Allavena C, Hanf M, Rey D, et al. (2018) Antiretroviral exposure and comorbidities in an aging HIV-infected population: The challenge of geriatric patients. PLoS One 13: e0203895. https://doi.org/10.1371/journal.pone.0203895
    [6] Marcus J, Chao C, Leyden W, et al. (2016) Narrowing the gap in life expectancy between HIV-Infected and HIV-uninfected individuals with access to care. J Acquir Immune Defic Syndr 73: 39-46. https://doi.org/10.1097/QAI.0000000000001014
    [7] Liang Y, Ketchum NS, Turner BJ, et al. (2020) Cardiovascular risk assessment varies widely by calculator and race/ethnicity in a majority Latinx cohort living with HIV. J Immigr Minor Health 22: 323-335. https://doi.org/10.1007/s10903-019-00890-w
    [8] Damen JAAG, Hooft L, Schuit E, et al. (2016) Prediction models for cardiovascular disease risk in the general population: Systematic review. BMJ : 353. https://doi.org/10.1136/bmj.i2416
    [9] Khera R, Pandey A, Ayers CR, et al. (2020) Performance of the pooled cohort equations to estimate atherosclerotic cardiovascular disease risk by body mass index. JAMA Netw Open 3: e2023242. https://doi.org/10.1001/jamanetworkopen.2020.23242
    [10] D'Agostino RB, Pencina MJ, Massaro JM, et al. (2013) Cardiovascular disease risk assessment: Insights from Framingham. Glob Heart 8: 11-23. https://doi.org/10.1016/j.gheart.2013.01.001
    [11] Feinstein MJ, Hsue PY, Benjamin LA, et al. (2019) Characteristics, prevention, and management of cardiovascular disease in people living with HIV: A scientific statement from the American Heart Association. Circulation 140: e98-e124. https://doi.org/10.1161/CIR.0000000000000695
    [12] Achhra AC, Lyass A, Borowsky L, et al. (2021) Assessing cardiovascular risk in people living with HIV: Current tools and limitations. Curr HIV/AIDS Rep 18: 271-279. https://doi.org/10.1007/s11904-021-00567-w
    [13] Ricci J, Gagnon L (2011) Evaluation du niveau d'activité physique et de condition physique. Clin Prosport : 1-26.
    [14] National Cholesterol Education Program (US).Expert Panel on Detection, and Treatment of High Blood Cholesterol in Adults. Third report of the National Cholesterol Education Program on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III), The Program (2001) . https://doi.org/10.1001/jama.285.19.2486
    [15] Assman G, Cullen P, Schulte H (2002) Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Munster (PROCAM) study. Circulation 105: 310-315. https://doi.org/10.1161/hc0302.102575
    [16] De Backer G, Ambrosioni E, Borch-Johnsen K, et al. (2004) European guidelines on cardiovascular disease prevention in clinical practice. Third Joint Task Force of European and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of eight societies and by invited experts). Atherosclerosis 173: 381-391. https://doi.org/10.1016/j.atherosclerosis.2004.02.013
    [17] Melo S, Antonini M, Christefany R, et al. (2020) Evaluation of cardiovascular risk factors in people living with HIV in São Paulo, Brazil. J Infect Dev Ctries 14: 89-96. https://doi.org/10.3855/jidc.11326
    [18] Pinto N, Dias F, Bressan F, et al. (2017) Comparison of the ACC/AHA and Framingham algorithms to assess cardiovascular risk in HIV-infected patients. Braz J Infect Dis 21: 577-580. https://doi.org/10.1016/j.bjid.2017.06.007
    [19] Mosepele M, Hemphill L, Palai T, et al. (2017) Cardiovascular disease risk prediction by the American College of Cardiology (ACC)/American Heart Association (AHA) Atherosclerotic Cardiovascular Disease (ASCVD) risk score among HIV-infected patients in sub-Saharan Africa. PLoS One 12: e0172897. https://doi.org/10.1371/journal.pone.0172897
    [20] Noumegni SR, Ama VJM, Assah FK, et al. (2017) Assessment of the agreement between the Framingham and DAD risk equations for estimating cardiovascular risk in adult Africans living with HIV infection: A cross-sectional study. Trop Dis Travel Med Vaccines 3: 12. https://doi.org/10.1186/s40794-017-0055-z
    [21] D'Agostino RB, Vasan RS, Pencina MJ, et al. (2008) General cardiovascular risk profile for use in primary care: The Framingham Heart Study. Circulation 117: 743-753. https://doi.org/10.1161/CIRCULATIONAHA.107.699579
    [22] Zilbermint M, Hannah-Shmouni F, Stratakis CA (2019) Genetics of hypertension in African Americans and others of African descent. Int J Mol Sci 20: 1081. https://doi.org/10.3390/ijms20051081
    [23] Nyirenda M (2021) Assessment of cardiovascular disease risks using Framingham risk scores (FRS) in HIV-positive and HIV-negative older adults in South Africa. Prev Med Rep 22: 101352. https://doi.org/10.1016/j.pmedr.2021.101352
    [24] De Gaetano Donati K, Cauda R, Iacoviello L (2010) HIV infection, antiretroviral therapy and cardiovascular risk. Mediterr J Hematol Infect Dis 2: e2010034. https://doi.org/10.4084/mjhid.2010.034
    [25] Wu PY, Chen MY, Sheng WH, et al. (2019) Estimated risk of cardiovascular disease among the HIV-positive patients aged 40 years or older in Taiwan. J Microbiol Immunol Infect 52: 549-555. https://doi.org/10.1016/j.jmii.2019.03.006
    [26] Warren TY, Barry V, Hooker SP, et al. (2010) Sedentary behaviors increase risk of cardiovascular disease mortality in men. Med Sci Sports Exerc 42: 879-885. https://doi.org/10.1249/MSS.0b013e3181c3aa7e
    [27] Policarpo S, Rodrigues T, Moreira AC, et al. (2019) Cardiovascular risk in HIV-infected individuals: A comparison of three risk prediction algorithms. Rev Port Cardiol 38: 463-470. https://doi.org/10.1016/j.repc.2019.08.002
    [28] Esser S, Gelbrich G, Brockmeyer N, et al. (2013) Prevalence of cardiovascular diseases in HIV-infected outpatients: Results from a prospective, multicenter cohort study. Clin Res Cardiol 102: 203-213. https://doi.org/10.1007/s00392-012-0519-0
    [29] Peyracchia M, De Lio G, Montrucchio C, et al. (2018) Evaluation of coronary features of HIV patients presenting with ACS: The CUORE, a multicenter study. Atherosclerosis 274: 218-226. https://doi.org/10.1016/j.atherosclerosis.2018.05.001
    [30] Baker JV, Henry WK, Neaton JD (2009) The consequences of HIV infection and antiretroviral therapy use for cardiovascular disease risk: Shifting paradigms. Curr Opin HIV AIDS 4: 176-182. https://doi.org/10.1097/COH.0b013e328329c62f
    [31] Kelly Y AHA Offers CVD Guidance for Patients with HIV (2019).
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