Transition in public knowledge of risk factors of cardiovascular disease in an Iranian general population: A latent transition analysis (LTA) on a longitudinal large community-based educational prevention program

BACKGROUND: Cardiovascular diseases (CVD) are the second leading cause of death, after accidents, in Iran. This study was performed to assess the change in levels of knowledge about 8 risk factors of CVD and its associated determinants the Iranian general population. METHODS: The current repeated cross-sectional study included 3014 people in 2004, 3012 in 2005, and 4719 in 2007, aged older than 19 years. Knowledge about 8 risk factors (high blood pressure, nutrition, physical inactivity, smoking, diabetes, heredity, stress, and obesity) as the major causes of CVD was evaluated using latent transition analysis (LTA). RESULTS: The most widely known CVD risk factors were nutrition and physical inactivity followed by stress. In addition, old age, low level of education, male gender and low socioeconomic status (SES) level were the significant determinants of low knowledge levels of CVD risk factors. Besides, individuals' knowledge of CVD risk factors increased across the time. CONCLUSION: Public knowledge of CVD risk factors has increased; however significant gaps continue to exist, particularly among the elderly, less-educated people, people in low socioeconomic status level and men. Future intensified educational efforts by policymakers are necessary for improving knowledge of CVD, particularly among high-risk groups

Prevalence of Extracardiac Anomalies in Patients With Congenital Heart Defects

Background: Various extracardiac disorders are associated with congenital heart defect (CHD) at varying prevalence rates (7-50). - 50). Over the years, numerous studies worldwide have investigated these associations. This study aimed to examine the prevalence of extracardiac anomalies in children with CHD in Isfahan, one of Iran's largest cities. Methods: This cross-sectional study was conducted in Isfahan, Iran, from 2020 through 2022, involving 750 infants under 1 year old diagnosed with CHD. Pediatric cardiologists performed echocardiography to evaluate the cardiovascular system and detect CHD. Most participants were referred for cardiac examinations due to abnormalities detected during physical examinations of skin, cerebral, spinal cord, abdominal, and urinary tract regions. Patients exhibiting signs of a syndromic disorder were also referred for CHD evaluation. Results: Out of 750 infants with confirmed CHD, 241 (32.13) presented at least 1 extracardiac malformation. Ninety (37.7) had craniofacial malformations, with 66.7 having cleft palate with or without cleft lip. Forty-eight patients (19.9) had genetic syndromes, most commonly Down syndrome (56.5), and 46 (19.8) had gastrointestinal abnormalities, including intestinal or esophageal atresia. Conclusions: The prevalence of extracardiac anomalies in patients with CHD is significant, and these patients are at an increased risk of mortality and morbidity throughout their lives. Implementing a screening program could effectively prevent further complications associated with the late diagnosis of these anomalies. (Iranian Heart Journal 2024; 25(3): 6-12

Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.</jats:p

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population