Enhancing coronary artery diseases screening:A comprehensive assessment of machine learning approaches using routine clinical and laboratory data

Introduction: Coronary artery disease (CAD) stands among the leading global causes of mortality, underscoring the critical necessity for early detection to facilitate effective treatment. Although Coronary Angiography (CA) serves as the gold standard for diagnosis, its limitations for screening, including side effects and cost, necessitate alternative approaches. This study focuses on the development and comparison of machine learning techniques as substitutes for CA in CAD screening, leveraging routine clinical and laboratory data. Material and Methods: Various machine learning classification algorithms—decision tree, k-nearest neighbor, artificial neural network, support vector machine, logistic regression, and stacked ensemble learning were employed to differentiate CAD and healthy subjects. Feature selection algorithms, namely LASSO and ReliefF, were utilized to prioritize relevant features. A range of evaluation metrics, including accuracy, precision, sensitivity, specificity, AUC, F1 score, ROC curve, and NPV, were applied. The SHAP technique was employed to elucidate and interpret the artificial neural network model. Results: The artificial neural network, support vector machine, and stacked ensemble learning models demonstrated excellent results in a 10-fold cross-validation evaluation using features selected by LASSO and ReliefF. With the LASSO feature selection algorithm, these models achieved accuracies of 90.38%, 90.07%, and 90.39%, sensitivities of 94.43%, 93.03%, and 93.96%, and specificities of 80.27%, 82.77%, and 81.52%, respectively. Using ReliefF, the accuracies were 88.79%, 88.77%, and 90.06%, sensitivities were 92.12%, 91.66%, and 93.98%, and specificities were 80.13%, 81.38%, and 80.13%, respectively. The SHAP technique revealed that typical and atypical chest pain, hypertension, diabetes mellitus, T inversion, and age were the most influential features in the neural network model. Conclusion: The machine learning models developed in this study exhibit high potential for non-invasive screening and diagnosis of CAD in the Z-Alizadeh Sani dataset. However, further studies are essential to validate and apply these models in real-world and clinical settings.</p

Toxoplasmosis in Patients with Cardiac Disorders: a Systematic Review and Meta-Analysis

Toxoplasmosis is a common and serious infection caused by an obligatory intracellular protozoan, Toxoplasma gondii. This study investigated the possible association between heart failure and toxoplasmosis. We searched for toxoplasmosis and heart failure patients in English databases including PubMed, Scopus, ISI Web of Sciences, Science Direct, EMBASE, and Google Scholar up to June 2018. A total of 6 studies and 1,795 participants, comprising 934 cases and 861 controls, had acceptable criteria for entering the study. Im­munoglobulin G (IgG) antibodies against T. gondii were found in 53% (22 to 83) of patients with heart diseases and 26% (11 to 42) of healthy controls. In comparison, immunoglobulin M (IgM) antibodies were found in 0.5% (0.1 to 1) in patients with heart diseases and 0.3% (0 to 0.7) of healthy controls. The patients suffering from cardiac disorders were more significantly correlated to anti-T. gondii IgG (OR: 3.53; 95% CI, 2.27 to 5.47; P = 0.014) and IgM (OR: 1.80; 95% CI, 0.31 to 10.4; P = 0.028) seropositivity than healthy controls. Despite limitations such as the low number of studies, our research showed a high association between toxoplasmosis and cardiac disorders. Therefore, toxoplasmosis may be a risk factor in cardiac patients, and more studies are being done

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

The effect of written material and verbal method education on anxiety and depression in patients with myocardial infarction in selected hospitals in iran

Introduction: Myocardial infarction (MI) is the damage to the heart muscle, or myocardium, resulting from the lack of blood flow to the heart. MI patients experience mental and emotional problems such as depression and anxiety. These complications could cause delay in resuming work, decreased quality of life and increased risk of death. The role of education in facilitating adaptation is very important in these patients. The purpose of this study was to determine the effect of written material and verbal method education on anxiety and depression in patients with myocardial infarction in Urmia hospital in 2009. Methods: This study was a quasi-experimental study, comparing the effect of education on anxiety and depression in patients with myocardial infarction in hospitals affiliated to Urmia University of Medical Science. 124 patients were selected randomly and divided into two groups. The experimental group was educated through face to face training and an educational booklet (Written Material and Verbal Method). The control group did not receive any intervention. The level of anxiety and depression was evaluated, using HADS questionnaire at 3 intervals: after 48 hours of admission, the discharge day and 2 months after discharge. Results: The findings suggested that MI patients were worried about their social role, interpersonal relations and personal health. Such problems can aggravate symptoms and complicate the future care. There was no significant difference between the control and experimental groups before the intervention, but after the intervention, anxiety and depression in the experimental group was significantly less than that in the control group (p<0.05). Conclusion: Considering the beneficial results obtained from written materials and verbal method education on reducing anxiety and depression in cases with myocardial infarction, this may be one of the health care goals. More research on more patients is required to achieve more conclusive results

Evaluation of Factors Affecting the Efficacy of Nitroglycerin Infusion in Patients with Hypertensive Crisis: Effects of nitroglycerin in hypertensive crisis

Hypertensive crisis is a severe elevation in blood pressure (BP) that requires urgent reduction in BP to prevent or reduce target organ damage. The antihypertensive effects of nitroglycerin have been proven, but there are limited reports on the effects of various factors on the effectiveness of nitroglycerin in the treatment of hypertensive crisis. The purpose of this study was to evaluate the effects of diabetes, history of hypertension and age as well as gender differences in the effectiveness of nitroglycerin in patients with hypertensive crisis. This study included 76 patients with hypertensive crisis. For management, nitroglycerin initially started at 5 μg/min by intravenous infusion and, if needed, every 3 to 5 min, 5 μg/min was added to the above dose to a maximum of 20 μg/min as long as the blood pressure level reaches to the desired level. The results showed that the mean time of reduction of BP to the desired level in patients with history of hypertension and diabetes alone or both diseases, increased significantly in comparison to patients without these underlying diseases (P&lt;0.01, P&lt;0.01 and P&lt;0.05 respectively). The results also demonstrated that there is a significant difference between patients younger than 45 and over 65 years with patients aged 45-65 (P&lt;0.05). There is no difference between two genders in each group (P&gt;0.05). In conclusion, patients with diabetes and/or history of hypertension are more resistant to pressure lowering effect of nitroglycerin in hypertensive crisis. Patients under 45 years of age as well as the elderly are also resistant. Therefore, it is advisable for physicians to choose the appropriate treatment for the desired outcome, considering the patient's condition

Inter-relationships between inflammatory biomarkers and severity of angiographically verified coronary artery occlusion

Background and Aim: Growing clinical evidence suggests that inflammation is the hallmark of the initiation, progression and extent of occlusion by atherosclerosis plaques, but biochemical data are still controversial. The aim of the present cross-sectional investigation was to evaluate the relationship between the severity of coronary artery occlusion (CAO), serum amyloid A (SAA), and interleukin -6 (IL-6) Materials and Methods: The subjects assessed were165 having stable coronary artery disease, but without left main artery lesion. Angiographic examination revealed that 37 subjects had minimal CAO (control group), 41 one CAO, 41 two CAO , and 47 three CAO. The Subjects’ SAA and IL-6 were assessed by means of ELISA.The level of fibrinogen was estimated using coaglumetry. The obtained data was analysed by means of SPSS (v: 13). Results: Fibrinogen concentrations were significantly higher in subjects with 1, 2 or 3 CAO compared to the controls. SAA levels in the subjects were higher than those in the controls, but the differences were not statistically significant. On the other hand, IL6- concentrations in patients with a varying degree of CAO were similar but slightly lower than those in the controls. Significant correlations were distinguished between SAA, IL-6, and fibrinogen in the patients as a whole (p=0.05). Fibrinogen levels in the patients were significantly correlated with HDL and LDL. Conclusion: It was found that fibrinogen estimation is .superior to IL-6 and SAA in examining the interrelationship between inflammation and progression of CAO

Correlation between serum levels of cystatin C and coronary slow flow and body mass index in men

Background: Cystatin C (Cys C) as a cysteine protease inhibitor is produced in a constant level from all nucleated cells. The purpose of this study was to investigate the correlation between serum levels of Cys C and coronary slow flow (CSF) and body mass index (BMI) in men. Methods: This investigation is in the form of a descriptive-analytical study. The statistical population was all non-active male aged 34-73 years with CSF candidate for angiography referring to Seyedoshohada University Hospital, Urmia, Iran, from March 2015 to February 2017. After obtaining an inform consent, 74 male patients (mean age 54.77±9.00 years, height 1.74±0.12 cm, weight 73.13±6.85 kg, and BMI 26.98±3.83 kg/m2) were selected by convenience non-random sampling as the sample size (patients were eligible for diagnostic coronary artery angiography for the first time and referring to Seyedoshohada University Hospital in Urmia). Then all the patients were placed under angiography with one mobile angiography system. Patients were assessed for coronary blood flow with a quantitative method using corrected thrombolysis frame count in myocardial infarction (CTFC). All the patients with TFC larger than two standard deviation pre-published area for a specific vessel were counted as CSF. Demographic characteristics of age, height, weight, and BMI in male patients were measured by wall-meter with an accuracy of one millimeter, digital scale with precision of 100 g, and weight/hieght2 formula, respectively. The traditional risk factors including smoking, diabetes mellitus (DM), high blood pressure (HBP), dyslipidemia, and family history were also assessed using a checklist. Serum levels of Cys C were measured by ELISA machine. Results: The mean demographic and physiological variables of subjects were: age 54.77±9.00 yr, height 1.74±0.12 cm, weight 73.13±6.85 kg, and BMI 26.98±3.83 kg/m2. Also, the results of this study showed that there were no significant correlations between serum levels of Cys C with CSF and BMI in male patients’ candidate for angiography referring to Seyedoshohada University Hospital (P=0.871 and P=0.494, respectively). Conclusion: The results of this study suggest that serum levels of Cys C had no significant correlations with the CSF and BMI in male patients’ candidate for angiography aged 34-73 years

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

BackgroundFuture trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.MethodsUsing forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline.FindingsIn the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]).InterpretationGlobally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions.FundingBill & Melinda Gates Foundation.</p