Which risk factor best predicts coronary artery disease using artificial neural network method?

BACKGROUND: Coronary artery disease (CAD) is recognized as the leading cause of death worldwide. This study analyses CAD risk factors using an artificial neural network (ANN) to predict CAD. METHODS: The research data were obtained from a multi-center study, namely the Iran-premature coronary artery disease (I-PAD). The current study used the medical records of 415 patients with CAD hospitalized in Razi Hospital, Birjand, Iran, between May 2016 and June 2019. A total of 43 variables that affect CAD were selected, and the relevant data was extracted. Once the data were cleaned and normalized, they were imported into SPSS (V26) for analysis. The present study used the ANN technique. RESULTS: The study revealed that 48% of the study population had a history of CAD, including 9.4% with premature CAD and 38.8% with CAD. The variables of age, sex, occupation, smoking, opium use, pesticide exposure, anxiety, sexual activity, and high fasting blood sugar were found to be significantly different among the three groups of CAD, premature CAD, and non-CAD individuals. The neural network achieved success with five hidden fitted layers and an accuracy of 81% in non-CAD diagnosis, 79% in premature diagnosis, and 78% in CAD diagnosis. Anxiety, acceptance, eduction and gender were the four most important factors in the ANN model. CONCLUSIONS: The current study shows that anxiety is a high-prevalence risk factor for CAD in the hospitalized population. There is a need to implement measures to increase awareness about the psychological factors that can be managed in individuals at high risk for future CAD.

De Winter's pattern: an uncommon but very important electrocardiographic sign in the prompt recognition of spontaneous occlusive coronary artery dissection in young patients with chest pain (a case report).

Chest pain is a clinical symptom for immediate consultation, and electrocardiogram (ECG) is a valuable diagnostic tool for use in the emergency room. Although the ST- elevation myocardial infarction (STEMI) requires urgent management, there are other ECG high-risk findings which are associated with adverse outcomes or imminent acute myocardial infarction (AMI). This is a case of STEMI equivalent pattern such as de Winter. As this ECG pattern is uncommon, it may be misinterpreted in the emergency department. We report a misinterpretation of de Winter's pattern (dWp) in a young woman referred to the emergency department for chest pain, feeling of suffocation and hemodynamic instability who undergone reteplase treatment with the suspicion of acute massive pulmonary embolism but developed cardiogenic shock as a result of extensive myocardial infarction due to spontaneous dissection of the left anterior descending coronary artery. A prompt diagnosis of de Winter's pattern and early angiography to detect the underlying cause of clinical manifestation can be lifesaving.

One-year survival cohort of patients with reduced ejection fraction heart failure in Iranian population: A single center study.

BACKGROUND: Cardiovascular diseases (CVDs) are one of the main concerns of health care systems. The aim of this study was to investigate the most important prognostic factors of heart failure (HF) and their survival outcomes in patients in Birjand, East of Iran. METHODS: A total of 194 systolic HF patients hospitalized in Birjand Valiasr hospital were followed up for 12 months in 2016, and those with reduced left ventricle ejection fraction (LVEF < 50%) were included in this study. Kaplan-Meier and Cox proportional hazard analysis were used to determine the association of each factor with events. RESULTS: The mean age of patients was 68.23 ± 13.40 (27-95) years, and 57.2% (111 out of 194) were women. Mean survival time was 294.7 ± 9.924 days. Pervious history of myocardial infarction (MI) [2.141 (1.101-4.161)] increased the risk of cardiovascular hospitalization. Elevated blood levels of potassium [2.264 (1.438-3.564)] was found to be a risk factor for all-cause and cardiovascular mortality. Moreover, there was a reverse relationship between body height [0.942 (0.888-0.999)] and cardiovascular death. Patients with opium addiction [4.049 (1.310-12.516)] are at a higher risk of cardiovascular mortality. Lower levels of LDL-C [0.977 (0.960-0.996)] and living in rural areas [3.052 (1.039-8.964)] increased all-cause mortality levels. Lack of pervious history of chronic obstructive pulmonary disease (COPD) decreased cardiovascular hospitalization [0.265 (0.062-1.122)]. CONCLUSION: In our study, serum potassium, LDL-C, and uric acid levels in patients with HF were identified as prognostic factors. The height of patients, which can be an indicator of the functional state of their respiratory system, and the history of COPD were also recognized as prognostic factors. Opium use and rural living were identified as social factors influencing patients' prognosis.

Surveying the Effect of Opioid Abuse on the Extent of Coronary Artery Diseases in Diabetic Patients.

BACKGROUND: Diabetes mellitus is recognized as one of the most common, serious, and costly chronic diseases. Opium addiction is also a common health problem in Iran. Given the high prevalence of opium use in South Khorasan Province and the increasing prevalence of opioid abuse in the community, this study was performed to investigate the effect of opioid abuse on the extent of disease in diabetic patients undergoing coronary angiography in the cardiology department of Vali-e-Asr Hospital in Birjand city, South Khorasan Province, Iran. METHODS: This study recruited a total of 1051 diabetic patients who underwent coronary angiography in the cardiology department of Vali-e-Asr Hospital of Birjand city from 2011 to 2015. The collected data were analyzed using SPSS version 22.0 with the chi-square test and univariate regression analysis. P value <0.05 was considered as statistically significant. RESULTS: Among opiate-addicted diabetics, the risk of coronary artery disease was 0.44 times higher than among nonaddicted diabetics (range 0.24-0.77, P=0.004). The extent of coronary vessel involvement, when present, was not different between the two groups. CONCLUSION: Opiate-addicted diabetics appear to be more susceptible to CAD than their nonaddicted counterparts. The determinants and correlates of this interaction must be the subject of further study.