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Sarcoidosis embodies a complex inflammatory disorder spanning multiple systems, with its origin remaining elusive. It manifests as the infiltration of inflammatory cells that coalesce into distinctive noncaseous granulomas within afflicted organs. Unraveling this disease necessitates the utilization of cellular or tissue-based imaging methods to both visualize and characterize the biochemistry of these sarcoid granulomas. Although hematoxylin and eosin stain, standard in routine use alongside cytological stains have found utility in diagnosis within clinical contexts, special stains such as Masson's trichrome, reticulin, methenamine silver, and Ziehl-Neelsen provide additional varied perspectives of sarcoid granuloma imaging. Immunohistochemistry aids in pinpointing specific proteins and gene expressions further characterizing these granulomas. Finally, recent advances in spatial transcriptomics promise to divulge profound insights into their spatial orientation and three-dimensional (3-D) molecular mapping. This review focuses on a range of preexisting imaging methods employed for visualizing sarcoid granulomas at the cellular level while also exploring the potential of the latest cutting-edge approaches like spatial transcriptomics and matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), with the overarching goal of shedding light on the trajectory of sarcoidosis research. [ABSTRACT FROM AUTHOR]

The relationship between testosterone and related hormones and cardiovascular and mortality outcomes is debated. The authors of this study obtained individual patient–level data from 9 cohort studies and aggregate data from 11 studies in total. These data enabled them to describe the associations of testosterone, sex hormone–binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone (DHT), and estradiol with all-cause mortality, cardiovascular death, and incident cardiovascular events while accounting for other cardiac risk factors. Background: Whether circulating sex hormones modulate mortality and cardiovascular disease (CVD) risk in aging men is controversial. Purpose: To clarify associations of sex hormones with these outcomes. Data Sources: Systematic literature review to July 2019, with bridge searches to March 2024. Study Selection: Prospective cohort studies of community-dwelling men with sex steroids measured using mass spectrometry and at least 5 years of follow-up. Data Extraction: Independent variables were testosterone, sex hormone–binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone (DHT), and estradiol concentrations. Primary outcomes were all-cause mortality, CVD death, and incident CVD events. Covariates included age, body mass index, marital status, alcohol consumption, smoking, physical activity, hypertension, diabetes, creatinine concentration, ratio of total to high-density lipoprotein cholesterol, and lipid medication use. Data Synthesis: Nine studies provided individual participant data (IPD) (255 830 participant-years). Eleven studies provided summary estimates (n = 24 109). Two-stage random-effects IPD meta-analyses found that men with baseline testosterone concentrations below 7.4 nmol/L (<213 ng/dL), LH concentrations above 10 IU/L, or estradiol concentrations below 5.1 pmol/L had higher all-cause mortality, and those with testosterone concentrations below 5.3 nmol/L (<153 ng/dL) had higher CVD mortality risk. Lower SHBG concentration was associated with lower all-cause mortality (median for quintile 1 [Q1] vs. Q5, 20.6 vs. 68.3 nmol/L; adjusted hazard ratio [HR], 0.85 [95% CI, 0.77 to 0.95]) and lower CVD mortality (adjusted HR, 0.81 [CI, 0.65 to 1.00]). Men with lower baseline DHT concentrations had higher risk for all-cause mortality (median for Q1 vs. Q5, 0.69 vs. 2.45 nmol/L; adjusted HR, 1.19 [CI, 1.08 to 1.30]) and CVD mortality (adjusted HR, 1.29 [CI, 1.03 to 1.61]), and risk also increased with DHT concentrations above 2.45 nmol/L. Men with DHT concentrations below 0.59 nmol/L had increased risk for incident CVD events. Limitations: Observational study design, heterogeneity among studies, and imputation of missing data. Conclusion: Men with low testosterone, high LH, or very low estradiol concentrations had increased all-cause mortality. SHBG concentration was positively associated and DHT concentration was nonlinearly associated with all-cause and CVD mortality. Primary Funding Source: Medical Research Future Fund, Government of Western Australia, and Lawley Pharmaceuticals. (PROSPERO: CRD42019139668) [ABSTRACT FROM AUTHOR]

Rural patients with non‐ST‐elevation myocardial infarction (NSTEMI) are transferred to metropolitan hospitals for invasive coronary angiography (ICA). Yet, many do not have obstructive coronary artery disease (CAD). In this analysis of rural Western Australian patients transferred for ICA for NSTEMI, low‐level elevations in high‐sensitivity cardiac troponin (≤5× upper reference limit) were associated with less obstructive CAD and revascularisation. Along with other factors, this may help identify rural patients not requiring transfer for ICA. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is the leading cause of death worldwide. The human body is populated by a diverse community of microbes, dominated by bacteria, but also including viruses and fungi. The largest and most complex of these communities is located in the gastrointestinal system and, with its associated genome, is known as the gut microbiome. Gut microbiome perturbations and related dysbiosis have been implicated in the progression and pathogenesis of CVD, including atherosclerosis, hypertension, and heart failure. Although there have been advances in the characterization and analysis of the gut microbiota and associated bacterial metabolites, the exact mechanisms through which they exert their action are not well understood. This review will focus on the role of the gut microbiome and associated functional components in the development and progression of atherosclerosis. Potential treatments to alter the gut microbiome to prevent or treat atherosclerosis and CVD are also discussed. [ABSTRACT FROM AUTHOR]

• A novel 3D Split&Shuffle-GAN model for 3D medical image generation is proposed, and new inflation strategies are developed to facilitate training of 3D medical generation models. The proposed model significantly improves image generation quality: 14.7 improvements on Frechet Inception Distance with only 48.5% parameters of the baseline. • We conducted comprehensive experiments on both the Heart Coronary CT and Brain MRI images, which verifies the effectives and wide applicability to multiple organs. • Real-world test data has been utilized in this paper: Stanford AIMI Coronary Calcium and Alzheimer's Disease Neuroimaging Initiative. This collaborates the real-world application potential of our technical solution. Background and Objective : The generation of three-dimensional (3D) medical images has great application potential since it takes into account the 3D anatomical structure. Two problems prevent effective training of a 3D medical generative model: (1) 3D medical images are expensive to acquire and annotate, resulting in an insufficient number of training images, and (2) a large number of parameters are involved in 3D convolution. Methods : We propose a novel GAN model called 3D Split&Shuffle-GAN. To address the 3D data scarcity issue, we first pre-train a two-dimensional (2D) GAN model using abundant image slices and inflate the 2D convolution weights to improve the initialization of the 3D GAN. Novel 3D network architectures are proposed for both the generator and discriminator of the GAN model to significantly reduce the number of parameters while maintaining the quality of image generation. Several weight inflation strategies and parameter-efficient 3D architectures are investigated. Results : Experiments on both heart (Stanford AIMI Coronary Calcium) and brain (Alzheimer's Disease Neuroimaging Initiative) datasets show that our method leads to improved 3D image generation quality (14.7 improvements on Frchet inception distance) with significantly fewer parameters (only 48.5% of the baseline method). Conclusions : We built a parameter-efficient 3D medical image generation model. Due to the efficiency and effectiveness, it has the potential to generate high-quality 3D brain and heart images for real use cases. [ABSTRACT FROM AUTHOR]

Background: Epidemiological analyses demonstrate that pneumonia survivors have a higher risk of myocardial infarction than people with similar load of risk factors for atherosclerotic cardiovascular disease (ASCVD) but without pneumonia. This may be due to a higher baseline burden of ASCVD in patients with pneumonia that is not captured by the accounting of known ASCVD risk factors in epidemiological analyses or to unfavorable accelerating effects of pneumonia on atherosclerosis. Methods: We analyzed data from the Multi-Ethnic Study of Atherosclerosis. We identified 54 participants that were hospitalized for pneumonia during study follow-up and that also had assessment of coronary artery calcium (CAC, an objective marker of coronary atherosclerotic burden) before and after this hospitalization. We matched them to 54 participants who were not hospitalized for pneumonia but that had CAC assessments at the same study visits as the pneumonia cases. We compared baseline CAC scores and their progression between groups. Results: Baseline CAC scores were similar in both groups (median [IQR]; 6.3 [0–356.8] in pneumonia participants vs. 10.8 [0–178.3] in controls; p = 0.25). After a median of 4.8 years, the direction and magnitude of CAC score change, and the slope of CAC score progression between groups was also similar (median change [IQR], 21.8 [0 to 287.29] in participants with pneumonia versus 15.8 [0 to 140.94] in controls, p = 0.28; difference in slope, 7.7, 95% CI -9.0 to 24.6, p = 0.18). However, among participants with high baseline ASCVD risk (i.e. ACC/AHA 10-year risk estimate ≥7.5%), participants with pneumonia showed a larger increase in CAC scores (median change [IQR]; 159.10 [38.55–407.34] versus 48.72 [0.97–246.99] in controls; p = 0.02) and a trend towards a steeper slope of CAC score progression (difference in slope, 19.7, 95% CI -6.6 to 45.6, p = 0.07). Conclusion: Pneumonia may accelerate the progression of atherosclerosis in people with high baseline ASCVD risk. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) FDG PET is an established metabolic imaging technique to assess myocardial viability. Delayed iodinated contrast enhancement (DE) of myocardium on computed tomography (CT) has also been shown to be an anatomical marker of nonviable myocardium. A pilot study was undertaken to determine quantitative and qualitative agreement between metabolic viability imaging and scar imaging using FDG PET and multislice CT respectively. Methods: Fifteen patients with coronary artery disease and left ventricular dysfunction were recruited in the study. All patients underwent same day FDG PET and DECT to evaluate myocardial viability. The images were analyzed quantitatively and qualitatively using a 17 segment model. Results: DECT diagnosed viability in 57% (146/255) whilst PET in 51% (129/255) of segments. The per-segment agreement between DECT and FDG PET on qualitative analysis was 70% (Kappa: 0.40). The agreement in quantitative measurements between the two techniques for viability showed modest correlation [Pearson ρ: 0.63; P<0.0001] on scatter plot and the Passing–Bablok regression analysis. Higher agreement (70 vs 77%; P=0.051; Kappa: 0.40 vs 0.53) was obtained with quantitative compared to qualitative DECT. Conclusions: DECT may be useful in characterizing myocardial scar, and preliminary results correlate modestly with metabolic FDG PET, both qualitatively and quantitatively. Although in our study quantitative analysis offered superior agreement compared to qualitative with DECT, further studies are needed to determine its incremental value. [Copyright &y& Elsevier]

Abstract: Background: Previous studies have confirmed that cardiac structural and functional abnormalities exist in patients with malignant hypertension (MHT). The effect of long-term blood pressure control in MHT patients on cardiac structure and function is still unknown. Methods: We performed detailed left ventricle (LV) assessment using two-dimensional (2DE) and three-dimensional (3DE) echocardiography, and tissue Doppler imaging (TDI) in patients with previous MHT (but now in stable phase) who were compared with patients with treated ‘high risk’ hypertension (HHT, but non-MHT) and healthy controls (HC). Vasodilator stress myocardial contrast echocardiography (in addition to wall motion analysis) was used to exclude significant coronary artery disease, as part of our comprehensive echocardiographic assessment. Septal and posterior wall thickness, LV mass index, LV volumes and ejection fraction, mitral valve inflow indices (E, A) mitral annular velocity (S, E′) and left atrial volume index (LAVI), were calculated using 2DE, 3DE, and TDI. MHT patients had good blood pressure control for an average of 144months. Results: A total of 95 subjects (MHT=15; HHT and HC=40 each) were studied. Both posterior and septal wall thickness were significantly higher in the MHT and hypertensive groups compared to normal controls with no difference between MHT and HHT. No significant difference in LV ejection fraction was found between the 3 groups. Increased LAVI (p<0.05 MHT vs. HC and HHT vs. HC), reduced ‘S’ velocity on TDI (p=0.05 MHT vs. HC and vs.HHT, p<0.001 HHT vs. HC) and higher E/E′ (p=0.029 HHT vs. HC) and lower E/A ratio (p=0.001 MHT vs. HC, p<0.001 HHT vs. HC) values were detected in the two hypertensive groups. Conclusion: Despite long-term good blood pressure control, MHT patients have persistent structural and functional changes in LV function on echocardiography, comparable to that seen in HHT. [Copyright &y& Elsevier]

Patients with chronic kidney disease have a worse cardiovascular prognosis than those without. The aim of this study was to determine the incremental prognostic value of coronary computed tomographic angiography in predicting mortality across the entire spectrum of renal function in patients with known or suspected coronary artery disease (CAD). A large international multicenter registry was queried, and patients with left ventricular ejection fraction (LVEF) and creatinine data were screened. National Cholesterol Education Program Adult Treatment Panel III risk was calculated. Coronary computed tomographic angiographic results were evaluated for CAD severity (normal, nonobstructive, or obstructive) and an LVEF <50%. Patients were followed for the end point of all-cause mortality. Among 5,655 patients meeting the study criteria, follow-up was available for 5,572 (98.9%; median follow-up duration 18.6 months). All-cause mortality (66 deaths) significantly increased with every 10-unit decrease in renal function (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.07 to 1.41). All-cause mortality occurred in 0.33% of patients without coronary atherosclerosis, 1.82% of patients with nonobstructive CAD, and 2.43% of patients with obstructive CAD. Multivariate Cox proportional-hazards models revealed that impaired renal function (HR 2.29, 95% CI 1.65 to 3.18), CAD severity (HR 1.81, 95% CI 1.31 to 2.51), and an abnormal LVEF (HR 4.16, 95% CI 2.45 to 7.08) were independent predictors of all-cause mortality. In conclusion, coronary computed tomographic angiographic measures of CAD severity and the LVEF provide effective risk stratification across a wide spectrum of renal function. Furthermore, renal dysfunction, CAD severity, and the LVEF have additive value for predicting all-cause death in patients with suspected obstructive CAD. [ABSTRACT FROM AUTHOR]

Aims Despite major advances in our understanding of ‘systolic’ heart failure, at present the epidemiology, pathophysiology, and therapy of heart failure with preserved left ventricular ejection fraction (HFpEF) is poorly understood, in large part because of the lack of robust and widely accepted diagnostic criteria. Although there is a good evidence base for the treatment of systolic heart failure, similar data are lacking for the treatment of HFpEF. Methods In our study, we will screen a consecutive series of 5000 subjects aged ≥60 from the community. Following symptom questionnaire and echocardiography, metabolic exercise testing will be used to confirm whether or not patients thought clinically to have HFpEF are in fact exercise limited and that this limitation is cardiac in origin. Blood samples for plasma brain natriuretic peptide (BNP) will be taken at rest and following exercise in symptomatic patients and matching controls. Conclusions At the end of our study we will establish community prevalence and population characteristics of HFpEF, and also evaluate the diagnostic accuracy of current echocardiography parameters and BNP for the diagnosis of the condition. [ABSTRACT FROM AUTHOR]

Unlabelled: Introduction: Fulminant hepatic failure is a serious disease with significant mortality and morbidity. Identifying the exact cause of hepatic failure and predicting prognosis is of paramount importance in managing such patients. Drug-induced liver injury is a common but challenging entity to treat. The use of newer drugs and medications with previously unknown hepatotoxicity add to the challenges faced by treating physicians. Quetiapine is an antipsychotic that has rarely been linked to acute liver injury. In the present work we describe a case of fulminant hepatic failure secondary to use of quetiapine.Case Presentation: A 59-year-old Caucasian woman with known Parkinson's disease was being treated with quetiapine for hallucinations. She was referred to our hospital with yellow discoloration of the sclera and later on developed clinical features suggestive of hepatic encephalopathy. A diagnosis of fulminant hepatic failure was made following her admission to the intensive care unit. Her condition improved after discontinuing the drug and providing the standard supportive treatment.Conclusions: Our findings in the present report emphasize the importance of keeping an open mind in cases of fulminant hepatic failure. As drug-induced hepatotoxicity is the most common cause of fulminant hepatic failure in many parts of the world, consideration should be given to the medication(s) patients receive as the potential cause and a review of this list should be part of the clinical care given. [ABSTRACT FROM AUTHOR]

Abstract: Background: Following ST elevation acute myocardial infarction (STEMI) and reperfusion therapy, there are often persistent wall thickening (WT) abnormalities and perfusion defects due to variable degree of myocardial stunning and necrosis. We hypothesised that following STEMI and reperfusion therapy, the extent of residual perfusion assessed by myocardial contrast echocardiography (MCE) and not the extent of WT abnormalities would predict subsequent global recovery of left ventricular (LV) function. Methods: Accordingly, 112 patients with STEMI underwent simultaneous assessment of WT abnormality and perfusion using MCE 7±2 days after AMI and reperfusion therapy. Both WT and perfusion were scored on a 16 segment LV model. Contrast perfusion index (CPI), and global LV function were calculated. Echocardiography was repeated 12 weeks after reperfusion to assess recovery of LV function. Results: Of the 112 patients recruited, follow up echocardiography 12 weeks after reperfusion was available in 98 patients. CPI was significantly higher (p <0.0001) in the 66 patients, who showed late recovery of LV function (1.67±0.27) compared to those who did not show recovery of function (1.25±0.04). No significant difference was noted in the indices of baseline LV function in patients with (1.67±0.32) and without (1.80±0.36) recovery of LV function. The multivariable predictors of late recovery of function were MCE (p =0.02), absence of diabetes (p =0.02) and lower peak creatine kinase (p =0.01). Conclusion: The extent of residual contrast perfusion and not WT abnormalities predicts late recovery of global LV function after acute myocardial infarction and reperfusion therapy. [Copyright &y& Elsevier]

Abstract: Obstructive sleep apnea (OSA) is a common yet an under-diagnosed sleep related breathing disorder affecting predominantly middle-aged men. OSA is associated with many adverse health outcomes, including cardiovascular disease. Common OSA associated/induced cardiovascular disorders include coronary artery disease, heart failure, hypertension, cardiac arrhythmias and stroke, which further increase morbidity and mortality in the OSA population. Endothelial dysfunction, coagulopathy, impaired sympathetic drive, oxidative and inflammatory stress are the pathophysiological pathways suggested for the development of cardiovascular disease in OSA. The evidence would suggest that OSA should be considered as a cardiovascular risk factor, and is a treatable condition. Multiple studies using Continuous Positive Airway Pressure (CPAP) have shown improvements in the clinical state as well as retardation of disease progression. Therefore, patients with cardiovascular disease should be proactively screened for OSA and vice versa. [Copyright &y& Elsevier]

The extent of residual myocardial viability (MV) after acute myocardial infarction (AMI) is an important determinant of the outcome. Single photon emission computed tomography (SPECT) is widely used to assess MV after an AMI. However, myocardial contrast echocardiography (MCE), a relatively new technique for the assessment of MV, has better spatial and temporal resolution than SPECT. The present study evaluated whether MV determined by MCE is comparable to that determined using SPECT for the prediction of hard cardiac events after an AMI. Accordingly, 99 patients who had undergone simultaneous rest low-power MCE and nitrate-enhanced SPECT 7 days after an AMI were followed up for cardiac death and AMIs. Both MCE perfusion (1 = normal; 2 = reduced; and 3 = absent) and SPECT tracer uptake (0 = normal; 1 = mildly reduced; 2 = moderately reduced; 3 = severely reduced; and 4 = absent) were scored on a 16-segment left ventricular model. The contrast perfusion index and SPECT perfusion index were calculated by adding the respective scores in the 16 segments and dividing by 16. The contrast perfusion index and SPECT perfusion index were used as a measure of the residual MV on MCE and SPECT, respectively. Of the 99 patients recruited, 95 were available for the follow-up examination (follow-up 46 ± 16 months). A total of 15 events (16%) occurred (8 cardiac deaths and 7 AMIs). Of the clinical, biochemical, echocardiographic, and SPECT markers of prognosis, the only independent predictors of cardiac death and cardiac death or AMI were age and MV as determined by MCE (p = 0.01 and p = 0.002, respectively). In conclusion, MV determined by MCE at rest was superior to nitrate-enhanced SPECT for the prediction of hard cardiac events after AMI. [Copyright &y& Elsevier]

Objectives: This study sought to determine whether residual myocardial viability determined by myocardial contrast echocardiography (MCE) after acute myocardial infarction (AMI) can predict hard cardiac events. Background: Myocardial viability detected by MCE has been shown to predict recovery of left ventricular (LV) function in patients with AMI. However, to date no study has shown its value in predicting major adverse outcomes in AMI patients after thrombolysis. Methods: Accordingly, 99 stable patients underwent low-power MCE at 7 ± 2 days after AMI. Contrast defect index (CDI) was obtained by adding contrast scores (1 = homogenous; 2 = reduced; 3 = minimal/absent opacification) in all 16 LV segments divided by 16. At discharge, 65 (68%) patients had either undergone or were scheduled for revascularization independent of the MCE result. The patients were subsequently followed up for cardiac death and nonfatal AMI. Results: Of the 99 patients, 95 were available for follow-up. Of these, 86 (87%) underwent thrombolysis. During the follow-up time of 46 ± 16 months, there were 15 (16%) events (8 cardiac deaths and 7 nonfatal AMIs). Among the clinical, biochemical, electrocardiographic, echocardiographic, and coronary arteriographic markers of prognosis, the extent of residual myocardial viability was an independent predictor of cardiac death (p = 0.01) and cardiac death or AMI (p = 0.002). A CDI of ≤1.86 and ≤1.67 predicted survival and survival or absence of recurrent AMI in 99% and 95% of the patients, respectively. Conclusions: The extent of residual myocardial viability predicted by MCE is a powerful independent predictor of hard cardiac events in patients after AMI. [Copyright &y& Elsevier]

To analyze the cost efficiency of guidelines proposed by the European Society of Cardiology for investigation of patients in the community with suspected heart failure (HF). The guidelines recommend electrocardiography (ECG) and/or measurement of N-terminal pro B type natriuretic peptide (NTproBNP) prior to referral for echocardiography. Portable echocardiography is a new but validated technique for the evaluation of HF. Accordingly, 137 suspected HF patients (mean age 71±13 years) from the community underwent ECG and NTproBNP estimation prior to portable echocardiography. Cost effective analysis for ECG, NTproBNP, portable echocardiography and a combination of these; to define valvular heart disease, right ventricular dysfunction and left ventricular systolic and diastolic dysfunction were compared. The cost of abnormal NTproBNP followed by portable echocardiography, abnormal ECG followed by portable echocardiography and portable echocardiography alone for the detection per case of left ventricular systolic dysfunction were €313, €310, and €296 respectively and that for detection per case of any of the aforementioned cardiac abnormalities were €198, €223, and €170 respectively. Portable echocardiography alone for the assessment of suspected HF patients resulted in a cost reduction of up to €1083 for the detection per case of cardiac abnormality. While a strategy where initial NTproBNP estimation is cost effective in detecting any causes of heart failure, portable echocardiography remains the most costeffective strategy to assess patients from the community with suspected heart failure. [ABSTRACT FROM AUTHOR]

The article presents a study of myocardial perfusion assessment after myocardial infarction through a case study of acute myocardial infarction. The article begins with describing the case like symptoms of the patient at the time of admission in the emergency department, clinical diagnosis with electrocardiograph, and treatment involving various drugs. The article discusses myocardial contrast echocardiography (MCH) technique as effective modality for assessing myocardial perfusion.

Objectives Methods Results Conclusion To investigate health consumers' ethical concerns towards the use of artificial intelligence (AI) in EDs.Qualitative semi‐structured interviews with health consumers, recruited via health consumer networks and community groups, interviews conducted between January and August 2022.We interviewed 28 health consumers about their perceptions towards the ethical use of AI in EDs. The results discussed in this paper highlight the challenges and barriers for the effective and ethical implementation of AI from the perspective of Australian health consumers. Most health consumers are more likely to support AI health tools in EDs if they continue to be involved in the decision‐making process. There is considerably more approval of AI tools that support clinical decision‐making, as opposed to replacing it. There is mixed sentiment about the acceptability of AI tools influencing clinical decision‐making and judgement. Health consumers are mostly supportive of the use of their data to train and develop AI tools but are concerned with who has access. Addressing bias and discrimination in AI is an important consideration for some health consumers. Robust regulation and governance are critical for health consumers to trust and accept the use of AI.Health consumers view AI as an emerging technology that they want to see comprehensively regulated to ensure it functions safely and securely with EDs. Without considerations made for the ethical design, implementation and use of AI technologies, health consumer trust and acceptance in the use of these tools will be limited. [ABSTRACT FROM AUTHOR]

Atherosclerosis is the commonest cause of death in Australia. Cardiovascular (CV) risk calculators have an important role in preventative cardiology, although they are are strongly age-dependent and designed to identify individuals at high risk of an imminent event. The imprecision around "intermediate" or "low" risk generates therapeutic uncertainty, and a significant proportion of patients presenting with myocardial infarction come from these groups, often with no warning. This highlights a conundrum: "Low" risk does not mean "no" risk. A fresh approach may be required to address the clinical conundrum around CV preventative approaches in non-high-risk individuals. While probabilistic calculators do not measure atherosclerosis, calculation of Coronary Artery Calcium (CAC) scores by low-dose computed tomography (CT) can provide a snapshot of atherosclerotic burden. In intermediate-risk individuals, CAC is well-established as an aid to CV risk prediction. Although CAC scoring in low-risk asymptomatic people may be considered controversial, CAC has emerged as the single best predictor of CV events in asymptomatic individuals, independent of traditional risk factor calculators. Therefore, apart from the contribution of age and sex, the somewhat arbitrary distinction between "intermediate" and "low" CV risk using probabilistic calculators may need to be reconsidered. A zero CAC score has a very low future event rate and non-zero CAC scores are associated with a progressive, graded increase in risk as the CAC score rises. In this review, we examine the evidence for CAC screening in low-risk individuals, and propose more widespread use of CAC using simple new model intended to enhance established CV risk prediction equations. [ABSTRACT FROM AUTHOR]

Objective: To assess Australian and New Zealand emergency clinicians' attitudes towards the use of artificial intelligence (AI) in emergency medicine. Methods: We undertook a qualitative interview‐based study based on grounded theory. Participants were recruited through ED internal mailing lists, the Australasian College for Emergency Medicine Bulletin, and the research teams' personal networks. Interviews were transcribed, coded and themes presented. Results: Twenty‐five interviews were conducted between July 2021 and May 2022. Thematic saturation was achieved after 22 interviews. Most participants were from either Western Australia (52%) or Victoria (16%) and were consultants (96%). More participants reported feeling optimistic (10/25) than neutral (6/25), pessimistic (2/25) or mixed (7/25) towards the use of AI in the ED. A minority expressed scepticism regarding the feasibility or value of implementing AI into the ED. Multiple potential risks and ethical issues were discussed by participants including skill loss from overreliance on AI, algorithmic bias, patient privacy and concerns over liability. Participants also discussed perceived inadequacies in existing information technology systems. Participants felt that AI technologies would be used as decision support tools and not replace the roles of emergency clinicians. Participants were not concerned about the impact of AI on their job security. Most (17/25) participants thought that AI would impact emergency medicine within the next 10 years. Conclusions: Emergency clinicians interviewed were generally optimistic about the use of AI in emergency medicine, so long as it is used as a decision support tool and they maintain the ability to override its recommendations. This qualitative study found that emergency clinicians in Australia and New Zealand were generally optimistic about the use of artificial intelligence (AI)‐enabled decision support tools in EDs. A number of issues were raised that require attention before full acceptance. AI‐enabled tools must operate as decision support only, be locally validated, be effectively integrated into existing workflows and take ethical concerns into consideration. [ABSTRACT FROM AUTHOR]

Background and Aims Methods Results Conclusion Telehealth plays an integral part in healthcare delivery. The impact of telehealth and the COVID‐19 pandemic on medication prescribing and patient satisfaction with telehealth in cardiology clinics remains unknown.A retrospective study of cardiology clinic patients at an Australian tertiary hospital was conducted; 630 patients seen before the COVID‐19 pandemic (0.6% telehealth) and 678 during the pandemic (91.2% telehealth) were included. Medication changes, new prescriptions and time to obtaining prescriptions after clinic were compared. To evaluate patients' experiences, cardiology clinic patients reviewed during the pandemic were prospectively invited to participate in an electronic survey sent to their mobile phones.The overall rates of medication changes made in the clinic between the prepandemic and the pandemic periods did not differ significantly (26.9% vs 25.8%). Compared with prepandemic, new cardiac medication prescriptions during clinic were significantly less (9.3% vs 2.5%; P < 0.0001) and recommendations to general practitioners (GP) to initiate cardiac medications were significantly more (2.6% vs 9.1%; P < 0.0001). Time to obtaining new prescriptions was significantly longer in the pandemic cohort (median 0 days (range: 0–32) vs 10.5 days (range: 0–231); P < 0.0001). Two hundred forty‐three (32.7%) patients participated in the survey; 50% reported that telehealth was at least as good as face‐to‐face consultations. Most patients (61.5%) were satisfied with telehealth and most (62.9%) wished to see telehealth continued postpandemic.Telehealth during the COVID‐19 pandemic was associated with greater reliance on GP to prescribe cardiac medications and delays in obtaining prescriptions among cardiology clinic patients. Although most patients were satisfied with telehealth services, nearly half of the cardiac patients expressed preference towards traditional face‐to‐face consultations. [ABSTRACT FROM AUTHOR]

This study explores the effectiveness of Explainable Artificial Intelligence (XAI) for predicting suicide risk from medical tabular data. Given the common challenge of limited datasets in health-related Machine Learning (ML) applications, we use data augmentation in tandem with ML to enhance the identification of individuals at high risk of suicide. We use SHapley Additive exPlanations (SHAP) for XAI and traditional correlation analysis to rank feature importance, pinpointing primary factors influencing suicide risk and preventive measures. Experimental results show the Random Forest (RF) model is excelling in accuracy, F1 score, and AUC (>97% across metrics). According to SHAP, anger issues, depression, and social isolation emerge as top predictors of suicide risk, while individuals with high incomes, esteemed professions, and higher education present the lowest risk. Our findings underscore the effectiveness of ML and XAI in suicide risk assessment, offering valuable insights for psychiatrists and facilitating informed clinical decisions. [ABSTRACT FROM AUTHOR]

Atherosclerosis is the leading cause of death worldwide, and the predominant risk factors are advanced age and high-circulating low-density lipoprotein cholesterol (LDL-C). However, the findings of atherosclerosis in relatively young mummified remains and a lack of atherosclerosis in chimpanzees despite high LDL-C call into question the role of traditional cardiovascular risk factors. The inflammatory theory of atherosclerosis may explain the discrepancies between traditional risk factors and observed phenomena in current literature. Following the divergence from chimpanzees several millennia ago, loss of function mutations in immune regulatory genes and changes in gene expression have resulted in an overactive human immune system. The ubiquity of atherosclerosis in the modern era may reflect a selective pressure that enhanced the innate immune response at the cost of atherogenesis and other chronic disease states. Evidence provided from the fields of genetics, evolutionary biology, and paleoanthropology demonstrates a sort of circular dependency between inflammation, immune system functioning, and evolution at both a species and cellular level. More recently, the role of proinflammatory stimuli, somatic mutations, and the gene-environment effect appear to be underappreciated elements in the development and progression of atherosclerosis. Neurobiological stress, metabolic syndrome, and traditional cardiovascular risk factors may instead function as intermediary links between inflammation and atherosclerosis. Therefore, considering evolution as a mechanistic process and atherosclerosis as part of the inertia of evolution, greater insight into future preventative and therapeutic interventions for atherosclerosis can be gained by examining the past. [ABSTRACT FROM AUTHOR]

Objective: International guidelines provide increasing support for computed tomography coronary angiography (CTCA) in investigating chest pain. A pathway utilising CTCA first‐line for outpatient stable chest pain evaluation was implemented in an Australian ED. Methods: In pre‐post design, the impact of the pathway was prospectively assessed over 6 months (August 2021 to January 2022) and compared with a 6‐month pre‐implementation group (February 2021 to July 2021). CTCA was recommended first‐line in suspected stable cardiac chest pain, followed by chest pain clinic review. Predefined criteria were provided recommending functional testing in select patients. The impact of CTCA versus functional testing was evaluated. Data were obtained from digital medical records. Results: Three hundred and fifteen patients were included, 143 pre‐implementation and 172 post‐implementation. Characteristics were similar except age (pre‐implementation: 58.9 ± 12.0 vs post‐implementation: 62.8 ± 12.3 years, P = 0.004). Pathway‐guided management resulted in higher first‐line CTCA (73.3% vs 46.2%, P < 0.001), lower functional testing (30.2% vs 56.6%, P < 0.001) and lower proportion undergoing two non‐invasive tests (4.7% vs 10.5%, P = 0.047), without increasing investigation costs or invasive coronary angiography (ICA) (pre‐implementation: 13.3% vs post‐implementation: 9.3%, P = 0.263). In patients undergoing CTCA, 40.7% had normal coronaries and 36.2% minimal/mild disease, with no difference in disease burden post‐implementation. More medication changes occurred following CTCA compared with functional testing (aspirin: P = 0.005, statin: P < 0.001). In patients undergoing ICA, revascularisation to ICA ratio was higher following CTCA compared with functional testing (91.7% vs 18.2%, P < 0.001). No 30‐day myocardial infarction or death occurred. Conclusions: The pathway increased CTCA utilisation and reduced downstream investigations. CTCA was associated with medication changes and improved ICA efficiency. [ABSTRACT FROM AUTHOR]

Atherosclerosis is a multifactorial disease that is thought to be primarily inflammatory in origin. Given the contribution of inflammation to the development and progression of atherosclerosis, other conditions that are characterised by a dysregulated inflammatory response have also been proposed to play a role. The purpose of this review is to organise and present the various inflammatory processes that can affect atherosclerosis into two broad categories: extrinsic or host-independent and intrinsic or host-dependent. Within these two categories, we will discuss various processes that may contribute to the development and progression of atherosclerosis and the clinical studies describing these associations. Although the clinical trials investigating anti-inflammatory therapies have to date provided mixed results, further studies, particularly in conjunction with lipid-lowering and blood pressure lowering therapies should be considered. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is the leading cause of death worldwide. The gut microbiota and its associated metabolites may be involved in the development and progression of CVD, although the mechanisms and impact on clinical outcomes are not fully understood. This study investigated the gut microbiome profile and associated metabolites in patients with chronic stable angina (CSA) and acute coronary syndrome (ACS) compared with healthy controls. Bacterial alpha diversity in stool from patients with ACS or CSA was comparable to healthy controls at both baseline and follow-up visits. Differential abundance analysis identified operational taxonomic units (OTUs) assigned to commensal taxa differentiating patients with ACS from healthy controls at both baseline and follow-up. Patients with CSA and ACS had significantly higher levels of trimethylamine N-oxide compared with healthy controls (CSA: 0.032 ± 0.023 mmol/L, P < 0.01 vs. healthy, and ACS: 0.032 ± 0.023 mmol/L, P ¼ 0.02 vs. healthy, respectively). Patients with ACS had reduced levels of propionate and butyrate (119 ± 4 vs. 139 ± 5.1 lM, P ¼ 0.001, and 14 ± 4.3 vs. 23.5 ± 8.1 lM, P < 0.001, respectively), as well as elevated serum sCD14 (2245 ± 75.1 vs. 1834 ± 45.8 ng/mL, P < 0.0001) and sCD163 levels (457.3 ± 31.8 vs. 326.8 ± 20.7 ng/mL, P ¼ 0.001), compared with healthy controls at baseline. Furthermore, a modi- fied small molecule metabolomic and lipidomic signature was observed in patients with CSA and ACS compared with healthy controls. These findings provide evidence of a link between gut microbiome composition and gut bacterial metabolites with CVD. Future time course studies in patients to observe temporal changes and subsequent associations with gut microbiome composition are required to provide insight into how these are affected by transient changes following an acute coronary event. NEW & NOTEWORTHY The study found discriminative microorganisms differentiating patients with acute coronary syndrome (ACS) from healthy controls. In addition, reduced levels of certain bacterial metabolites and elevated sCD14 and sCD163 were observed in patients with ACS compared with healthy controls. Furthermore, modified small molecule metabolomic and lipidomic signatures were found in both patient groups. Although it is not known whether these differences in profiles are associated with disease development and/or progression, the findings provide exciting options for potential new disease-related mechanism(s) and associated therapeutic target(s). [ABSTRACT FROM AUTHOR]

Introduction: Natural language processing (NLP) uses various computational methods to analyse and understand human language, and has been applied to data acquired at Emergency Department (ED) triage to predict various outcomes. The objective of this scoping review is to evaluate how NLP has been applied to data acquired at ED triage, assess if NLP based models outperform humans or current risk stratification techniques when predicting outcomes, and assess if incorporating free-text improve predictive performance of models when compared to predictive models that use only structured data. Methods: All English language peer-reviewed research that applied an NLP technique to free-text obtained at ED triage was eligible for inclusion. We excluded studies focusing solely on disease surveillance, and studies that used information obtained after triage. We searched the electronic databases MEDLINE, Embase, Cochrane Database of Systematic Reviews, Web of Science, and Scopus for medical subject headings and text keywords related to NLP and triage. Databases were last searched on 01/01/2022. Risk of bias in studies was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST). Due to the high level of heterogeneity between studies and high risk of bias, a metanalysis was not conducted. Instead, a narrative synthesis is provided. Results: In total, 3730 studies were screened, and 20 studies were included. The population size varied greatly between studies ranging from 1.8 million patients to 598 triage notes. The most common outcomes assessed were prediction of triage score, prediction of admission, and prediction of critical illness. NLP models achieved high accuracy in predicting need for admission, triage score, critical illness, and mapping free-text chief complaints to structured fields. Incorporating both structured data and free-text data improved results when compared to models that used only structured data. However, the majority of studies (80%) were assessed to have a high risk of bias, and only one study reported the deployment of an NLP model into clinical practice. Conclusion: Unstructured free-text triage notes have been used by NLP models to predict clinically relevant outcomes. However, the majority of studies have a high risk of bias, most research is retrospective, and there are few examples of implementation into clinical practice. Future work is needed to prospectively assess if applying NLP to data acquired at ED triage improves ED outcomes when compared to usual clinical practice. [ABSTRACT FROM AUTHOR]

Heart failure (HF) is the end stage of most cardiovascular diseases and remains a significant health problem globally. We aimed to assess whether patients with left ventricular ejection fraction ≤45% had alterations in both the gut microbiome pro- file and production of associated metabolites when compared with a healthy cohort. We also examined the associated inflammatory, metabolomic, and lipidomic profiles of patients with HF. This single center, observational study, recruited 73 patients with HF and 59 healthy volunteers. Blood and stool samples were collected at baseline and 6-mo follow-up, along with anthropometric and clinical data. When compared with healthy controls, patients with HF had reduced gut bacterial alpha diversity at follow-up (P = 0.004) but not at baseline. The stool microbiota of patients with HF was characterized by a depletion of operational taxonomic units representing commensal Clostridia at both baseline and follow-up. Patients with HF also had significantly elevated baseline plasma acetate (P = 0.007), plasma trimethylamine-N-oxide (TMAO) (P = 0.003), serum soluble CD14 (sCD14; P = 0.005), and soluble CD163 (sCD163; P = 0.004) levels compared with healthy controls. Furthermore, patients with HF had a distinct metabolomic and lipidomic profile at baseline when compared with healthy controls. Differences in the composition of the gut microbiome and the levels of associated metabolites were observed in patients with HF when compared with a healthy cohort. This was also associated with an altered metabolomic and lipidomic profile. Our study identifies microorganisms and metabolites that could represent new therapeutic targets and diagnostic tools in the pathogenesis of HF. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is the leading cause of death worldwide. The gut microbiota and its associated metabolites may be involved in the development and progression of CVD, although the mechanisms and impact on clinical outcomes are not fully understood. This study investigated the gut microbiome profile and associated metabolites in patients with chronic stable angina (CSA) and acute coronary syndrome (ACS) compared with healthy controls. Bacterial alpha diversity in stool from patients with ACS or CSA was comparable to healthy controls at both baseline and follow-up visits. Differential abundance analysis identified operational taxonomic units (OTUs) assigned to commensal taxa differentiating patients with ACS from healthy controls at both baseline and follow-up. Patients with CSA and ACS had significantly higher levels of trimethylamine N-oxide compared with healthy controls (CSA: 0.032 ± 0.023 mmol/L, P < 0.01 vs. healthy, and ACS: 0.032 ± 0.023 mmol/L, P = 0.02 vs. healthy, respectively). Patients with ACS had reduced levels of propionate and butyrate (119 ± 4 vs. 139 ± 5.1 μM, P = 0.001, and 14 ± 4.3 vs. 23.5 ± 8.1 μM, P < 0.001, respectively), as well as elevated serum sCD14 (2245 ± 75.1 vs. 1834 ± 45.8 ng/mL, P < 0.0001) and sCD163 levels (457.3 ± 31.8 vs. 326.8 ± 20.7 ng/mL, P = 0.001), compared with healthy controls at baseline. Furthermore, a modified small molecule metabolomic and lipidomic signature was observed in patients with CSA and ACS compared with healthy controls. These findings provide evidence of a link between gut microbiome composition and gut bacterial metabolites with CVD. Future time course studies in patients to observe temporal changes and subsequent associations with gut microbiome composition are required to provide insight into how these are affected by transient changes following an acute coronary event. NEW & NOTEWORTHY The study found discriminative microorganisms differentiating patients with acute coronary syndrome (ACS) from healthy controls. In addition, reduced levels of certain bacterial metabolites and elevated sCD14 and sCD163 were observed in patients with ACS compared with healthy controls. Furthermore, modified small molecule metabolomic and lipidomic signatures were found in both patient groups. Although it is not known whether these differences in profiles are associated with disease development and/or progression, the findings provide exciting options for potential new disease-related mechanism(s) and associated therapeutic target(s). [ABSTRACT FROM AUTHOR]

Sarcoidosis is a complex inflammatory fibrotic disease that affects multiple organ systems. It is characterized by the infiltration of lymphocytes and mononuclear phagocytes, which form non-caseating granulomas in affected organs. The lungs and intrathoracic lymph nodes are the most commonly affected organs. The underlying cause of sarcoidosis is unknown, but it is believed to occur in genetically predisposed individuals who are exposed to pathogenic organisms, environmental contaminants, or self and non-self-antigens. Recent research has suggested that the microbiome may play a role in the development of respiratory conditions, including sarcoidosis. Additionally, metabolomic studies have identified potential biomarkers for monitoring sarcoidosis progression. This review will focus on recent microbiome and metabolomic findings in sarcoidosis, with the goal of shedding light on the pathogenesis and possible diagnostic and therapeutic approaches. [ABSTRACT FROM AUTHOR]

Atrial fibrillation arises mainly due to abnormalities in the cardiac conduction system and is associated with anatomical remodeling of the atria and the pulmonary veins. Cardiovascular imaging techniques, such as echocardiography, computed tomography, and magnetic resonance imaging, are crucial in the management of atrial fibrillation, as they not only provide anatomical context to evaluate structural alterations but also help in determining treatment strategies. However, interpreting these images requires significant human expertise. The potential of artificial intelligence in analyzing these images has been repeatedly suggested due to its ability to automate the process with precision comparable to human experts. This review summarizes the benefits of artificial intelligence in enhancing the clinical care of patients with atrial fibrillation through cardiovascular image analysis. It provides a detailed overview of the two most critical steps in image-guided AF management, namely, segmentation and classification. For segmentation, the state-of-the-art artificial intelligence methodologies and the factors influencing the segmentation performance are discussed. For classification, the applications of artificial intelligence in the diagnosis and prognosis of atrial fibrillation are provided. Finally, this review also scrutinizes the current challenges hindering the clinical applicability of these methods, with the aim of guiding future research toward more effective integration into clinical practice. [ABSTRACT FROM AUTHOR]

Introduction: Surveys conducted internationally have found widespread interest in artificial intelligence (AI) amongst medical students. No similar surveys have been conducted in Western Australia (WA) and it is not known how medical students in WA feel about the use of AI in healthcare or their understanding of AI. We aim to assess WA medical students' attitudes towards AI in general, AI in healthcare, and the inclusion of AI education in the medical curriculum. Methods: A digital survey instrument was developed based on a review of available literature and consultation with subject matter experts. The survey was piloted with a group of medical students and refined based on their feedback. We then sent this anonymous digital survey to all medical students in WA (approximately 1539 students). Responses were open from the 7th of September 2021 to the 7th of November 2021. Students' categorical responses were qualitatively analysed, and free text comments from the survey were qualitatively analysed using open coding techniques. Results: Overall, 134 students answered one or more questions (8.9% response rate). The majority of students (82.0%) were 20–29 years old, studying medicine as a postgraduate degree (77.6%), and had started clinical rotations (62.7%). Students were interested in AI (82.6%), self-reported having a basic understanding of AI (84.8%), but few agreed that they had an understanding of the basic computational principles of AI (33.3%) or the limitations of AI (46.2%). Most students (87.5%) had not received teaching in AI. The majority of students (58.6%) agreed that AI should be part of medical training and most (72.7%) wanted more teaching focusing on AI in medicine. Medical students appeared optimistic regarding the role of AI in medicine, with most (74.4%) agreeing with the statement that AI will improve medicine in general. The majority (56.6%) of medical students were not concerned about the impact of AI on their job security as a doctor. Students selected radiology (72.6%), pathology (58.2%), and medical administration (44.8%) as the specialties most likely to be impacted by AI, and psychiatry (61.2%), palliative care (48.5%), and obstetrics and gynaecology (41.0%) as the specialties least likely to be impacted by AI. Qualitative analysis of free text comments identified the use of AI as a tool, and that doctors will not be replaced as common themes. Conclusion: Medical students in WA appear to be interested in AI. However, they have not received education about AI and do not feel they understand its basic computational principles or limitations. AI appears to be a current deficit in the medical curriculum in WA, and most students surveyed were supportive of its introduction. These results are consistent with previous surveys conducted internationally. [ABSTRACT FROM AUTHOR]

Significant advances have been made in artificial intelligence technology in recent years. Many health care applications have been investigated to assist clinicians and the technology is close to being integrated into routine clinical practice. The high prevalence of cardiac disease in Australia places overwhelming demands on the existing health care system, challenging its capacity to provide quality patient care. Artificial intelligence has emerged as a promising solution. This discussion paper provides an Australian perspective on the current state of artificial intelligence in cardiology, including the benefits and challenges of implementation. This paper highlights some current artificial intelligence applications in cardiology, while also detailing challenges such as data privacy, ethical considerations, and integration within existing health infrastructures. Overall, this paper aims to provide insights into the potential benefits of artificial intelligence in cardiology, while also acknowledging the barriers that need to be addressed to ensure safe and effective implementation into an Australian health system. [ABSTRACT FROM AUTHOR]

Interest in artificial intelligence (AI) research has grown rapidly over the past few years, in part thanks to the numerous successes of modern machine learning techniques such as deep learning, the availability of large datasets and improvements in computing power. AI is proving to be increasingly applicable to healthcare and there is a growing list of tasks where algorithms have matched or surpassed physician performance. Despite the successes there remain significant concerns and challenges surrounding algorithm opacity, trust and patient data security. Notwithstanding these challenges, AI technologies will likely become increasingly integrated into emergency medicine in the coming years. This perspective presents an overview of current AI research relevant to emergency medicine. [ABSTRACT FROM AUTHOR]

The article presents a letter to the editor and a response regarding the article "Heparin Plus a glycoprotein llb/llla inhibitor versus bivalirudin monotherapy and paclitaxel-eluting stents versus bare-metal stents in acute myocardial infarction (HORIZONS-AMI): final 3-year results from a multicentre, randomised controlled trial," by Gregg Stone and colleagues in the 2011 issue.

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91–0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = −0.98 and PE.P 16:0/18:1, Cliff's delta = −0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages. [ABSTRACT FROM AUTHOR]

Background: Guidelines advocate for intensive lipid‐lowering in patients with atherosclerotic cardiovascular disease (ASCVD). In May 2020, evolocumab, a proprotein convertase subtilisin‐kexin type 9 (PCSK9) inhibitor, became government subsidised in Australia for patients with ASCVD requiring further low‐density lipoprotein cholesterol (LDL‐C) lowering. Aim: To identify barriers to prescribing PCSK9 inhibitors in hospitalised patients with ASCVD. Methods: A retrospective 3‐month, single‐site, observational analysis was conducted in consecutive patients undergoing percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) surgery. Lipid‐lowering therapy prescriptions, including PSCK9 inhibitors, were assessed using electronic medical records, compared against the Australian Pharmaceutical Benefits eligibility criteria, and barriers to PCSK9 inhibitor use identified. Results: Of 331 patients, 244 (73.7%) underwent PCI and 87 (26.3%) underwent CABG surgery. A lipid profile during or within 8 weeks of admission was measured for 202 (82.8%) patients undergoing PCI and 59 (67.8%) undergoing CABG surgery. In patients taking high‐intensity statins on admission (n = 109), LDL‐C ≥1.4, ≥1.8 and >2.6mmol/L was seen in 64 (58.7%), 44 (40.4%) and 19 (17.4%) patients respectively. High‐intensity statin prescribing at discharge was high (>80%); however, ezetimibe was initiated in zero patients with LDL‐C ≥1.4 mmol/L. There was variable advice given by clinicians for LDL‐C targets. No patients met the criteria for subsidised PSCK9 inhibitor therapy, largely due to lack of qualifying lipid levels following combined statin and ezetimibe therapy. Conclusion: Prescribing of non‐statin LDL‐C‐lowering therapies remains low in patients with ASCVD. Underprescribing of ezetimibe and suboptimal lipid testing rates are barriers to accessing subsidised PCSK9i therapy using current Australian eligibility criteria. [ABSTRACT FROM AUTHOR]

Computed tomography coronary angiography (CTCA) is a non-invasive diagnostic modality that provides a comprehensive anatomical assessment of the coronary arteries and coronary atherosclerosis, including plaque burden, composition and morphology. The past decade has witnessed an increase in the role of CTCA for evaluating patients with both stable and acute chest pain, and recent international guidelines have provided increasing support for a first line CTCA diagnostic strategy in select patients. CTCA offers some advantages over current functional tests in the detection of obstructive and non-obstructive coronary artery disease, as well as for ruling out obstructive coronary artery disease. Recent randomised trials have also shown that CTCA improves prognostication and guides the use of guideline-directed preventive therapies, leading to improved clinical outcomes. CTCA technology advances such as fractional flow reserve, plaque quantification and perivascular fat inflammation potentially allow for more personalised risk assessment and targeted therapies. Further studies evaluating demand, supply, and cost-effectiveness of CTCA for evaluating chest pain are required in Australia. This discussion paper revisits the evidence supporting the use of CTCA, provides an overview of its implications and limitations, and considers its potential role for chest pain evaluation pathways in Australia. [ABSTRACT FROM AUTHOR]

Chest pain is one of the most common presentations to emergency departments. However, only 5.1% will be diagnosed with an acute coronary syndrome, representing considerable time and expense in the diagnosis and investigation of the patients eventually found not to be suffering from an acute coronary syndrome. PubMed and Medline databases were searched with variations of the terms "chest pain", "emergency department", "computed tomography coronary angiography". After review, 52 articles were included. Computed tomography coronary angiography (CTCA) is a class I endorsement for investigating chest pain in major international societal guidelines. CTCA offers excellent sensitivity and negative predictive value in identifying patients with coronary disease, with prognostic data impacting patient management. If CTCA is to be applied to all comers, it is pertinent to discuss the advantages and potential pitfalls if use in the Australian system is to be increased. [ABSTRACT FROM AUTHOR]

Objectives: Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC. Methods: Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1–10, 11–100, 101–400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers). Results: Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman's r = 0.90, 95% confidence interval [CI] 0.89–0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98–0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland–Altman analysis demonstrated little difference (1.69, 95% limits of agreement: −41.22, 44.60) and there was almost excellent agreement (Cohen's κ = 0.90, 95% CI 0.88–0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan. Conclusions: This artificial intelligence–based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation. Key Points: • Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)–based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis. [ABSTRACT FROM AUTHOR]

Human cytomegalovirus (HCMV) infection has been shown to increase the risk of cardiovascular events and all-cause death among individuals with clinically apparent cardiovascular disease (CVD). Whether this association exists in individuals with no history of CVD remains unclear. Serum levels of HCMV IgG antibody were measured using an ELISA in 2050 participants aged 40–80 years from the 1994/1995 Busselton Health Survey who did not have CVD at baseline. Outcomes were all-cause death, cardiovascular death, acute coronary syndrome (ACS) and major adverse coronary and cerebrovascular events (MACCE, composite of all-cause death, ACS, stroke and coronary artery revascularisation procedures). Cox proportional hazards regression analysis was used to investigate HCMV antibody levels as a predictor of death and cardiovascular outcomes during follow-up periods of 5, 10 and 20 years. At baseline, participants had a mean age of 56 years and 57% were female. During the 20-year follow-up, there were 448 (21.9%) deaths (including 152 from CVD), 139 (6.8%) participants had ACS and 575 (28.0%) had MACCE. In the fully adjusted model, levels of HCMV antibody at 20 years was associated with all-cause death (HR 1.04; 95% CI 1.00, 1.07, p = 0.037) but not with CVD death, ACS or MACCE. Levels of HCMV antibody are associated with all-cause death but not with cardiovascular outcomes in adults without pre-existing CVD. [ABSTRACT FROM AUTHOR]

Coronary artery disease (CAD) remains the leading cause of adult mortality globally. Targeting known modifiable risk factors has had substantial benefit, but there remains a need for new approaches. Improvements in invasive and noninvasive imaging techniques have enabled an increasing recognition of distinct quantitative phenotypes of coronary atherosclerosis that are prognostically relevant. There are marked differences in plaque phenotype, from the high-risk, lipid-rich, thin-capped atheroma to the low-risk, quiescent, eccentric, nonobstructive calcified plaque. Such distinct phenotypes reflect different pathophysiologic pathways and are associated with different risks for acute ischemic events. Noninvasive coronary imaging techniques, such as computed tomography, positron emission tomography, and coronary magnetic resonance imaging, have major potential to accelerate cardiovascular drug development, which has been affected by the high costs and protracted timelines of cardiovascular outcome trials. This may be achieved through enrichment of high-risk phenotypes with higher event rates or as primary end points of drug efficacy, at least in phase 2 trials, in a manner historically performed through intravascular coronary imaging studies. Herein, we provide a comprehensive review of the current technology available and its application in clinical trials, including implications for sample size requirements, as well as potential limitations. In its effort to accelerate drug development, the US Food and Drug Administration has approved surrogate end points for 120 conditions, but not for CAD. There are robust data showing the beneficial effects of drugs, including statins, on CAD progression and plaque stabilization in a manner that correlates with established clinical end points of mortality and major adverse cardiovascular events. This, together with a clear mechanistic rationale for using imaging as a surrogate CAD end point, makes it timely for CAD imaging end points to be considered. We discuss the importance of global consensus on these imaging end points and protocols and partnership with regulatory bodies to build a more informed, sustainable staged pathway for novel therapies. [ABSTRACT FROM AUTHOR]