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Esmaeili P, Roshanravan N, Ghaffari S, Mesri Alamdari N, Asghari-Jafarabadi M. Unraveling atherosclerotic cardiovascular disease risk factors through conditional probability analysis with Bayesian networks: insights from the AZAR cohort study. Sci Rep 2024; 14:4361. [PMID: 38388574 PMCID: PMC10883955 DOI: 10.1038/s41598-024-55141-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 02/20/2024] [Indexed: 02/24/2024] Open
Abstract
This study aimed at modelling the underlying predictor of ASCVD through the Bayesian network (BN). Data for the AZAR Cohort Study, which evaluated 500 healthcare providers in Iran, was collected through examinations, and blood samples. Two BNs were used to explore a suitable causal model for analysing the underlying predictor of ASCVD; Bayesian search through an algorithmic approach and knowledge-based BNs. Results showed significant differences in ASCVD risk factors across background variables' levels. The diagnostic indices showed better performance for the knowledge-based BN (Area under ROC curve (AUC) = 0.78, Accuracy = 76.6, Sensitivity = 62.5, Negative predictive value (NPV) = 96.0, Negative Likelihood Ratio (LR-) = 0.48) compared to Bayesian search (AUC = 0.76, Accuracy = 72.4, Sensitivity = 17.5, NPV = 93.2, LR- = 0.83). In addition, we decided on knowledge-based BN because of the interpretability of the relationships. Based on this BN, being male (conditional probability = 63.7), age over 45 (36.3), overweight (51.5), Mets (23.8), diabetes (8.3), smoking (10.6), hypertension (12.1), high T-C (28.5), high LDL-C (23.9), FBS (12.1), and TG (25.9) levels were associated with higher ASCVD risk. Low and normal HDL-C levels also had higher ASCVD risk (35.3 and 37.4), while high HDL-C levels had lower risk (27.3). In conclusion, BN demonstrated that ASCVD was significantly associated with certain risk factors including being older and overweight male, having a history of Mets, diabetes, hypertension, having high levels of T-C, LDL-C, FBS, and TG, but Low and normal HDL-C and being a smoker. The study may provide valuable insights for developing effective prevention strategies for ASCVD in Iran.
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Affiliation(s)
- Parya Esmaeili
- Liver and Gastrointestinal Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Epidemiology and Biostatistics, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Neda Roshanravan
- Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Samad Ghaffari
- Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | - Mohammad Asghari-Jafarabadi
- Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
- Cabrini Research, Cabrini Health, Malvern, VIC, 3144, Australia.
- School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3004, Australia.
- Department of Psychiatry, School of Clinical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, 3168, Australia.
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Megna R, Petretta M, Nappi C, Assante R, Zampella E, Gaudieri V, Mannarino T, D’Antonio A, Green R, Cantoni V, Panico M, Acampa W, Cuocolo A. Age-Specific Cardiovascular Risk Factors for Major Adverse Cardiac Events in Patients Undergoing Myocardial Perfusion Imaging. J Cardiovasc Dev Dis 2023; 10:395. [PMID: 37754824 PMCID: PMC10531606 DOI: 10.3390/jcdd10090395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/07/2023] [Accepted: 08/18/2023] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND The prevalence of traditional cardiovascular risk factors shows different age-specific patterns. It is not known whether the prognostic impact of risk factors is similarly age-specific. We evaluated the profiles of cardiovascular risk factors and their prognostic impact on coronary artery disease (CAD) in relation to age. METHODS We included 3667 patients with suspected or known CAD undergoing stress myocardial perfusion imaging (MPI). We evaluated the risk for major adverse cardiac events (MACE) within three years from the index MPI in patients belonging to three groups according to age tertile distribution: <59, 59-68, and >68 years. Gender, body mass index, diabetes, hypertension, dyslipidemia, family history of CAD, smoking, angina, dyspnea, previous CAD, and MPI outcome were assessed as risk factors by a multivariable Cox's regression. RESULTS The three-year risk of MACE increased progressively with age and was 9%, 13%, and 18% for each group, respectively (p < 0.0001). Dyspnea and abnormal MPI outcome were significant risk factors for all age groups. Diabetes and smoking were significant from the age of 59 onwards, while hypertension resulted significant for patients older than 68 years. CONCLUSIONS The number of risk factors was significantly associated with the occurrence of MACE increase with age. It is noteworthy that a personal history of CAD was not useful for risk stratification, while MPI results were.
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Affiliation(s)
- Rosario Megna
- Institute of Biostructure and Bioimaging, National Council of Research, via T. De Amicis 95, 80145 Naples, Italy;
| | - Mario Petretta
- IRCCS Synlab SDN, via Gianturco 113, 80143 Naples, Italy;
| | - Carmela Nappi
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Roberta Assante
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Emilia Zampella
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Valeria Gaudieri
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Teresa Mannarino
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Adriana D’Antonio
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Roberta Green
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Valeria Cantoni
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Mariarosaria Panico
- Institute of Biostructure and Bioimaging, National Council of Research, via T. De Amicis 95, 80145 Naples, Italy;
| | - Wanda Acampa
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University Federico II, via Pansini 5, 80131 Naples, Italy; (C.N.); (R.A.); (E.Z.); (V.G.); (T.M.); (A.D.); (R.G.); (V.C.); (W.A.); (A.C.)
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