Background: Various predictive models have been developed for predicting the incidence of coronary heart disease (CHD), but none of them has had optimal predictive value. Although these models consider diabetes as an important CHD risk factor, they do not consider insulin resistance or triglyceride (TG). The unsatisfactory performance of these prediction models may be attributed to the ignoring of these factors despite their proven effects on CHD. We decided to modify standard CHD predictive models through machine learning to determine whether the triglyceride-glucose index (TyG-index, a logarithmized combination of fasting blood sugar (FBS) and TG that demonstrates insulin resistance) functions better than diabetes as a CHD predictor. Methods: Two-thousand participants of a community-based Iranian population, aged 20–74 years, were investigated with a mean follow-up of 9.9 years (range: 7.6–12.2). The association between the TyG-index and CHD was investigated using multivariate Cox proportional hazard models. By selecting common components of previously validated CHD risk scores, we developed machine learning models for predicting CHD. The TyG-index was substituted for diabetes in CHD prediction models. All components of machine learning models were explained in terms of how they affect CHD prediction. CHD-predicting TyG-index cut-off points were calculated. Results: The incidence of CHD was 14.5%. Compared to the lowest quartile of the TyG-index, the fourth quartile had a fully adjusted hazard ratio of 2.32 (confidence interval [CI] 1.16–4.68, p-trend 0.04). A TyG-index > 8.42 had the highest negative predictive value for CHD. The TyG-index-based support vector machine (SVM) performed significantly better than diabetes-based SVM for predicting CHD. The TyG-index was not only more important than diabetes in predicting CHD; it was the most important factor after age in machine learning models. Conclusion: We recommend using the TyG-index in clinical practice and predictive models to identify individuals at risk of developing CHD and to aid in its prevention.

Background: There is a substantial disparity in coronary artery disease (CAD) burden between Iran and other nations that place a strong emphasis on the assessment of CAD risk factors and individuals’ awareness and ability to control them. Methods: Two thousand participants of a community-based Iranian population aged 20–74 years were investigated with a mean follow-up of 9.9 years (range: 7.6 to 12.2). An analysis of Cox regression was conducted to determine the association between CAD development and classic risk factors such as age, sex, smoking, physical activity, education, obesity, dyslipidemia, hypertension, and diabetes mellitus. Furthermore, we computed the population attributable fraction for these risk factors. Results: After a follow-up period of nearly 10 years, 225 CAD events were reported, constituting 14.5% of the overall incidence. Nighty three percent of participants had more than one risk factor. Age was the most predictive risk factor, with a hazard ratio (HR) and confidence interval (CI) of 5.56 (3.87–7.97, p < 0.001) in men older than 45 and females older than 55 compared to lower ages. In comparison to females, males had an HR of 1.45 (CI: 1.11–1.90, p value = 0.006) for developing CAD. Nearly 80% of the patients had dyslipidemia, with a hazard ratio of 2.19 (CI: 1.40–3.44, p = 0.01). Among the participants, 28.9% had hypertension, and 52% had prehypertension, which had HRs of 4.1 (2.4–7.2, p < 0.001) and 2.4 (1.4–4.2, p < 0.001), respectively. Diabetes, with a prevalence of 17%, had an HR of 2.63 (CI: 2 -3.47, p < 0.001), but prediabetes was not significantly associated with CAD. Awareness of diabetes, dyslipidemia, and hypertension was 81%, 27.9%, and 48.1%, respectively. Regarding medication usage, the corresponding percentages were 51% for diabetes, 13.2% for dyslipidemia, and 41% for hypertension. Conclusions: Compared to previous studies in Iran and neighboring countries, the current study found a higher incidence of CAD, more prevalent risk factors, and a lower awareness and ability to control these risk factors. Thus, an effective preventive strategy is needed to reduce the CAD burden in Iran.

Background: Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as well as anthropometric features. However, there is still no agreement on the most suitable one for predicting CAD. Methods: We followed a cohort of 2,000 individuals, ranging in age from 20 to 74, for a duration of 9.9 years. We utilized multivariate Cox proportional hazard models to investigate the association between TyG-index, TyG-BMI, TyG-WC, TG/HDL, plus METS-IR and the occurrence of CAD. The receiver operating curve (ROC) was employed to compare the predictive efficacy of these indices and their corresponding cutoff values for predicting CAD. We also used three distinct embedded feature selection methods: LASSO, Random Forest feature selection, and the Boruta algorithm, to evaluate and compare surrogate markers of insulin resistance in predicting CAD. In addition, we utilized the ceteris paribus profile on the Random Forest model to illustrate how the model’s predictive performance is affected by variations in individual surrogate markers, while keeping all other factors consistent in a diagram. Results: The TyG-index was the only surrogate marker of insulin resistance that demonstrated an association with CAD in fully adjusted model (HR: 2.54, CI: 1.34–4.81). The association was more prominent in females. Moreover, it demonstrated the highest area under the ROC curve (0.67 [0.63–0.7]) in comparison to other surrogate indices for insulin resistance. All feature selection approaches concur that the TyG-index is the most reliable surrogate insulin resistance marker for predicting CAD. Based on the Ceteris paribus profile of Random Forest the predictive ability of the TyG-index increased steadily after 9 with a positive slope, without any decline or leveling off. Conclusion: Due to the simplicity of assessing the TyG-index with routine biochemical assays and given that the TyG-index was the most effective surrogate insulin resistance index for predicting CAD based on our results, it seems suitable for inclusion in future CAD prevention strategies.

Adherence to fluid restrictions and dietary and medication guidelines is important for adequate management of hemodialysis (HD) patients. This study aimed at assessing the factors suggestive of adherence in uremic patients on HD. Two hundred HD patients were recruited by census method. Data on blood urea nitrogen (BUN), serum potassium and phosphate levels, and interdialytic weight gain (IWG) were collected from medical records and analyzed. Most of the patients (56%) did not adhere to fluid restrictions. Nonadherence to phosphate, potassium, and BUN levels was 25.5%, 5.5%, and 4.5%, respectively. In addition, there was a relationship between BUN, serum potassium and phosphate levels, and IWG with educational status (p ≤ .05). However, there was no correlation between BUN, serum potassium and phosphate levels, and IWG with sex, age, financial status, marital status, and duration of dialysis (p > .05). Based on the results, most of the patients adhered to dietary and medication regimens. Educational level of the patients was associated with adherence to fluid restriction. It was concluded that dietary compliance may be improved by using dietary counseling techniques and that education motivates patients to change and comply with dietary recommendations.

Restoring patient homeostasis after coronary angiography, the gold standard diagnostic test for coronary heart disease is usually achieved by manual compression of the puncture site using a sandbag and prolonged bed rest. However, this process frequently results in patient complaints of back pain and discomfort. The aim of study was to assess the effect of positioning on patient outcomes after coronary angiography. This study used a single-blind randomized control trial approach. The sample consisted of 80 patients who had undergone a nonemergency coronary angiography via the femoral artery. Balanced block randomization was used to allocate participants into intervention and control groups. Routine care for the intervention group (n = 40) was adjusted to include the following: (1) intermittent changes to patient body and head position in bed during first 6 hours after catheterization, (2) reduction of sandbag compression time on the puncture site to 1 hour, and (3) regular examination for bleeding during the first 6 hours after catheterization. Intervention group participants were allowed to ambulate without restriction 6 hours after catheterization. Patients in the control group (n = 40) received routine care, consisting of (1) 6-24 hours of bed rest in the supine position with the affected leg fixed straight and immobilized and (2) sandbag compression on the puncture site for 6 hours. The main outcomes used in this study were level of back pain, discomfort, foot pain, bleeding, and hematoma. Intervention group patients had significantly less back pain and foot pain and higher comfort than the control group at the second, third, and sixth hour after catheterization (p = .00). There was no significant difference between the two groups in terms of amount of bleeding and hematoma (p > .05). Findings suggest that changes in patient position may be safer in the early period of postcatheterization bed rest than currently indicated in standard practice protocols. Furthermore, limiting sandbag compression to 1 hour has no measurable effect on the incidence and severity of vascular complications.

Background: Atrial septal defect (ASD) is a common congenital heart disease. Objectives: The aim of this study was to assess the clinical course of ASD, as well as its frequency of spontaneous closure and regression of diameter. Methods: In a study conducted from 2000 to 2011, 192 consecutive patients with an isolated ASD were followed up regularly with periodic echocardiographic evaluations according to a standardized protocol. The study was conducted in two series of patients: infants and children and adults. Infants were classified into three groups based on ASD diameter: small (≤ 5 mm), medium (6 - 9 mm), and large (> 9 mm). In the same manner, the ASD size in children and adults was categorized into three groups: small (≤ 10), medium (10 - 20 mm), and large (> 20 mm). Results: The patients consisted of 76 (39.6%) males and 116 (60.4%) females. The mean age of patients at diagnosis was 16.12 ± 15.66 years (range 1 week - 75 years). The mean follow-up duration was 70 ± 9 months (range: 25 - 119 months). The most prevalent age group was adult patients (> 20 years), and most ASDs were of medium size (1 - 2 cm). The most common complication was mild pulmonary hypertension (31 cases, 16.2%), and Eisenmenger phenomenon was the rarest complication (2 cases, 1%). Overall spontaneous closure of ASD occurred in 42 (21.9%) cases. Spontaneous closure in cases with small defects occurred in 18 of 22 (81%) infants and 24 of 81 children > 1 years of age. Regression of ASD size occurred in 2 (9.5%) infants and 3 (3.7%) children. No spontaneous closure was observed in cases with a defect size > 10 mm, and no spontaneous occlusion was detected in adolescents or adults. Seventy-two percent (n = 139) of patients needed surgical repair or transcatheter closure of the ASD. Conclusions: It is concluded that atrial septal defects < 6 mm typically close spontaneously, and ASDs measuring 6 - 9 mm may regress in infants and children. An ASD > 1 cm has little chance of spontaneous closure and may need surgical or device closure. ASD diameter and age at diagnosis are the most important predictors of spontaneous closure and the need for possible surgical or device closure. Keywords: Atrial Septal Defect; Natural Course; Clinical Course; Spontaneous Closure