Clinical Trials Arena lists five top tweets on cardiology in Q2 2022 based on data from GlobalData’s Pharmaceuticals Influencer Platform.
The top tweets are based on total engagements (likes and retweets) received on tweets from more than 249 cardiology experts tracked by GlobalData’s Pharmaceuticals Influencer platform during the second quarter (Q2) of 2022.
The most popular tweets on cardiology in Q2 2022: Top five
1. Pradeep Natarajan’s tweet on South Asians’ increased risk for cardiovascular disease and diabetes
Pradeep Natarajan, an associate professor at the Harvard Medical School, shared a research study on heart disease and diabetes disproportionately affecting individuals of South Asian ancestry. According to Natarajan, South Asians are markedly underrepresented in most human genetic studies that yield both population-specific and general insights. The study highlighted that South Asians remained one of the fastest growing subgroups in the US, with an estimated 5.4 million living in the country. However, they were found to consistently at a two-to-three-fold increased risk for cardiovascular disease and up to four-fold increased risk for diabetes, especially if it occurred in the absence of obesity.
The study further detailed that South Asian ancestry was considered a risk-enhancing factor for cardiovascular disease, with South Asians reporting twice (20%) the risk of cardiovascular disease compared to Europeans (11%). Experts claim that it is not conclusive why South Asians are at a higher risk as there have been very few studies on them, with a subsequent lack of data especially on those living in the US, the article noted. Another study on atherosclerotic cardiovascular disease (ASCVD) in South Asians living in the US, found that the group had higher proportional mortality rates caused by ASCVD compared to other Asian groups and non-Hispanic whites.
Username: Pradeep Natarajan
Twitter handle: @pnatarajanmd
2. Salvatore Brugaletta’s tweet on transcatheter closure being used to treat atrial and ventricular septal defects
Salvatore Brugaletta, an interventional cardiologist, shared a research about transcatheter closure of atrial septal defects (ASDs) and ventricular septal defects (VSDs). The research described the present status of transcatheter closure of ASDs and VSDs in children and adults, including patient selection, the methods used, and outcomes.
Highlights of the study revealed that transcatheter device closure was the most preferred method for most secundum ASDs. The research also found that VSDs were typically treated surgically, but transcatheter closure was used in certain cases. Experts believe that catheter-based methods can close the defects in cardiac septation than novel devices and technologies can increase the range of these defects.
Username: Salvatore Brugaletta
Twitter handle: @sbrugaletta
3. Christie Ballantyne’s tweet on combination lipid-lowering therapy for treating elevated LDL-C for CV risk reduction
Christie Ballantyne, a cardiologist, shared a study on why combination lipid-lowering therapy should be considered in treating elevated low-density lipoprotein cholesterol (LDL-C) for reducing cardiovascular (CV) risk. The research found that a combination therapy with statin and a non-statin LDL-C-lowering agent was safe and effective in lowering LDL-C and CV risk in clinical outcome trials. It also revealed that an increased statin dose is not as effective than adding a second agent to lower LDL-C levels, with several choices being available to personalise the therapy, including ezetimibe, evolocumab, alirocumab, bempedoic acid, inclisiran.
Several clinical studies and meta-analyses have shown that reducing LDL-C is critical to preventing atherosclerotic cardiovascular disease (ASCVD) outcomes. For example, 1.0-mmol/L (38.7-mg/dL) reduction in LDL-C was related to a 23% relative risk reduction in major ASCVD events. In the Improved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT), ezetimibe added to moderate-intensity statin led to a reduction in LDL-C and ASCVD endpoints compared with statin monotherapy in patients with recent acute coronary syndromes (ACS). This was the first randomised controlled trial that showed a reduction in ASCVD outcomes when a non-statin agent was combined with a statin in extremely-high-risk patients.
Username: Christie Ballantyne
Twitter handle: @CBallantyneMD
4. Eric Topol’s tweet on height being a biologically plausible risk factor for several common conditions in adults
Eric Topol, a physician and scientist, shared an article on adult height being related to several clinical traits, such as increased risk of atrial fibrillation and reduced risk of cardiovascular disease. Using data from VA Million Veteran Programme that included genetic data linked to clinical data in more than 200,000 non-Hispanic White (NHW) adults and more 50,000 non-Hispanic Black adults, the researchers examined the link between measured height and genetically-predicted height with clinical traits phenome-wide, the study revealed.
Findings revealed that among the approximately 350 traits, 127 were connected to genetically-predicted height in NHW individuals. In addition, while only two were statistically significant in non-Hispanic Black individuals, there were consistent evidence of effect of relatedness of traits with genetically-predicted height in non-Hispanic Black and White individuals. As a result, the study concluded that height maybe an unrecognisable, non-modifiable risk factor for many conditions in adults.
Username: Eric Topol
Twitter handle: @EricTopol
5. Prof Chris P Gale’s tweet on efficient screening of severe aortic valve stenosis using understandable AI
Prof Chris P Gale, a professor of cardiovascular medicine, tweeted on how a smartphone app using artificial intelligence (AI) detected severe aortic valve stenosis (AS) from electronic heart sounds, achieving a sensitivity, specificity, accuracy, and F1 value of 97.6%, 94.4%, 95.7%, and 0.93 respectively. This was much higher than agreed by cardiologists, the research highlighted. Multiple convolutional neural networks (CNNs) were developed in this diagnostic accuracy study, using an altered stratified five-fold cross-validation to identify severe AS in electronic heart sound data documented at three auscultation locations.
Clinical validation was carried out with the developed smartphone application in an independent cohort. The results of the study found the technology to be effective in screening severe AS based on heart sounds. The visual explanations of AI decisions for the heart sounds were explainable, suggesting that such technologies could help in remote consultations and medical training, the research noted.
Username: Prof Chris P Gale
Twitter handle: @cpgale3