scholarly journals Risk factors of premature coronary artery disease in Iran: A systematic review and meta‐analysis

2019 ◽  
Vol 49 (7) ◽  
Author(s):  
Hoorak Poorzand ◽  
Konstantinos Tsarouhas ◽  
Seyyed Amin Hozhabrossadati ◽  
Nastaran Khorrampazhouh ◽  
Yones Bondarsahebi ◽  
...  
2021 ◽  
Vol 16 ◽  
Author(s):  
Farahnaz Rohani ◽  
Arash Akhavan Rezayat ◽  
Ahmadreza Zarifian ◽  
Mohammad Ghasemi Nour ◽  
Farveh Vakilian ◽  
...  

Background: Coronary artery disease is a major cause of morbidity and mortality worldwide. A major health concern in developing countries is opioid addiction, which has controversial cardiovascular side effects. We aimed to investigate whether myocardial infarction (MI) and its risk factors are associated with morphine dependency in the Iranian population. Methods: Electronic databases, including PubMed, Medline, Scopus, SID, Elmnet, and Magiran were searched to find published articles including the keywords morphine, coronary artery disease, hypertension, hyperlipidemia, and diabetes mellitus. Results: Twelve studies involving 25,800 people were included in the systematic review and meta-analysis. Morphine dependency was significantly associated with MI with an adjusted odds ratio (AOR) of 2.28 (95%CI=1.26-4.11). It didn’t have significant associations with hypertension (AOR=0.952; 95%CI=0.696-1.301) nor diabetes (AOR=0.895; 95%CI=0.644-1.246). Morphine dependency also had no significant association with hyperlipidemia with a crude odds ratio (COR) of 0.906 (95%CI=0.786-1.045). Conclusion: Morphine dependency was significantly related to MI, but its risk factors were not significantly associated with morphine dependency. The increasing prevalence of opioid abuse in developing countries may be a reason for the growing incidence of MI in younger ages and individuals with no risk factors. Besides, physicians should consider the presence of impurities in morphine-based opioids and its possible effects on health.


BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e047677
Author(s):  
Pierpaolo Mincarone ◽  
Antonella Bodini ◽  
Maria Rosaria Tumolo ◽  
Federico Vozzi ◽  
Silvia Rocchiccioli ◽  
...  

ObjectiveExternally validated pretest probability models for risk stratification of subjects with chest pain and suspected stable coronary artery disease (CAD), determined through invasive coronary angiography or coronary CT angiography, are analysed to characterise the best validation procedures in terms of discriminatory ability, predictive variables and method completeness.DesignSystematic review and meta-analysis.Data sourcesGlobal Health (Ovid), Healthstar (Ovid) and MEDLINE (Ovid) searched on 22 April 2020.Eligibility criteriaWe included studies validating pretest models for the first-line assessment of patients with chest pain and suspected stable CAD. Reasons for exclusion: acute coronary syndrome, unstable chest pain, a history of myocardial infarction or previous revascularisation; models referring to diagnostic procedures different from the usual practices of the first-line assessment; univariable models; lack of quantitative discrimination capability.MethodsEligibility screening and review were performed independently by all the authors. Disagreements were resolved by consensus among all the authors. The quality assessment of studies conforms to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A random effects meta-analysis of area under the receiver operating characteristic curve (AUC) values for each validated model was performed.Results27 studies were included for a total of 15 models. Besides age, sex and symptom typicality, other risk factors are smoking, hypertension, diabetes mellitus and dyslipidaemia. Only one model considers genetic profile. AUC values range from 0.51 to 0.81. Significant heterogeneity (p<0.003) was found in all but two cases (p>0.12). Values of I2 >90% for most analyses and not significant meta-regression results undermined relevant interpretations. A detailed discussion of individual results was then carried out.ConclusionsWe recommend a clearer statement of endpoints, their consistent measurement both in the derivation and validation phases, more comprehensive validation analyses and the enhancement of threshold validations to assess the effects of pretest models on clinical management.PROSPERO registration numberCRD42019139388.


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