Contemporary Chest Pain Evaluation: The Australian Case for Cardiac CT

Comparison of cardiovascular risk prediction in type 1 diabetes: an Australian viewpoint

Cardiovascular disease (CVD) is a significant burden in individuals with type 1 diabetes mellitus (T1DM). Yet the optimal method of CVD risk stratification remains uncertain. We found that the new Australian CVD risk calculator could overestimate risk category compared with the Steno Type 1 Risk Engine and underestimate risk category compared with the new Swedish/Scottish prediction tool, both of which were validated for T1DM. More research is needed to derive a CVD risk assessment pathway for individuals with T1DM in Australia.

Unravelling the cardio-renal-metabolic-foot connection in people with diabetes-related foot ulceration: a narrative review

Diabetes-related foot ulceration (DFU), a serious but preventable complication of diabetes, is a leading cause of hospitalisation, lower extremity amputation and disability worldwide. People with DFU have a greater burden of cardiovascular risk factors, heart failure and chronic kidney disease, resulting in over two-fold higher risk of cardiovascular death compared with people with diabetes without DFU. Here, we propose a "cardio-renal-metabolic-foot" connection in people with diabetes based on shared pathophysiological mechanisms linking DFU with cardiovascular and renal disease. Whilst these mechanistic links remain to be fully elucidated, systemic inflammation and infection in the context of DFU are postulated as key mediators in the development, and progression of, cardiovascular and renal disease. However, cardiovascular and renal disease are also implicated in the pathogenesis of DFU, highlighting the multi-directional interplay between conditions. The impact of screening, prevention, and early management of cardiovascular complications associated with DFU requires further research. Multi-modality cardiac imaging could play a role in unravelling disease mechanisms leading to novel therapeutic strategies, as well as facilitating personalised risk assessment and management. Recent clinical trials have transformed the therapeutic landscape for people with type 2 diabetes, by demonstrating that sodium glucose co-transporter 2 inhibitors, glucagon-like peptide-1 agonists and non-steroidal mineralocorticoid receptor antagonists improve cardiovascular and renal outcomes. Although dedicated research in people with DFU is warranted, these therapies could target multiple facets of the "cardio-renal-metabolic-foot" connection. The holistic, person-centred approach to managing DFU should incorporate new multidisciplinary models of care focusing on the prevention and management of cardiovascular and kidney disease.

Coronary Artery Stenosis and High-Risk Plaque Assessed With an Unsupervised Fully Automated Deep Learning Technique

Background

Coronary computed tomography angiography (CCTA) has emerged as a reliable noninvasive modality to assess coronary artery stenosis and high-risk plaque (HRP). However, CCTA assessment of stenosis and HRP is time-consuming and requires specialized training, limiting its clinical translation.

Objectives

The aim of this study is to develop and validate a fully automated deep learning system capable of characterizing stenosis severity and HRP on CCTA.

Methods

A deep learning system was trained to assess stenosis and HRP on CCTA scans from 570 patients in multiple centers. Stenosis severity was categorized as >0%, 1 to 49%, ≥50%, and ≥70%. HRP was defined as low attenuation plaque (≤30 HU), positive remodeling (≥10% diameter), and spotty calcification (<3 mm). The model was then tested on 769 patients (3,012 vessels) for stenosis severity and 45 patients (325 vessels) for HRP.

Results

Our deep learning system achieved 93.5% per-vessel agreement within 1 Coronary Artery Disease-Reporting and Data System (CAD-RADS) category for stenosis. Diagnostic performance for per-vessel stenosis was very good for sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve with: >0% stenosis: 90.6%, 88.8%, 83.4%, 93.9%, 89.7%, respectively; ≥50% stenosis: 87.1%, 92.3%, 60.9%, 98.1%, 89.7%, respectively. Similarly, the per-vessel HRP feature achieved very good diagnostic performance with an area under the curve of 0.80, 0.79, and 0.77 for low attenuation plaque, spotty calcification, and positive remodeling, respectively.

Conclusions

A fully automated unsupervised deep learning system can rapidly evaluate stenosis severity and characterize HRP with very good diagnostic performance on CCTA.

Low-level elevations in high-sensitivity cardiac troponin predict obstructive coronary artery disease and revascularisation in rural patients with non-ST-elevation myocardial infarction referred for coronary angiography

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.

Evaluation of stable chest pain following emergency department presentation: Impact of first-line cardiac computed tomography diagnostic strategy in an Australian setting

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.

Enhancing Risk Stratification on Coronary Computed Tomography Angiography: The Role of Artificial Intelligence

PURPOSE

To describe and outline the role of artificial intelligence (AI) in assisting coronary computed tomography angiography (CCTA) in enhancing risk stratification.

METHODS

A comprehensive review of the literature was performed to identify published work investigating the utility of applying AI to CCTA.

FINDINGS

CCTA is an excellent diagnostic tool for the detection of atherosclerotic cardiovascular disease. The noninvasive nature and high diagnostic accuracy have made CCTA a viable alternative to invasive coronary angiography to detect luminal stenosis. However, it is now understood that stenosis is just one factor that predicts cardiac risk and other factors need to be considered. CCTA-derived plaque biomarkers have since emerged as established predictors of cardiac events to improve risk stratification. Despite awareness of these biomarkers, they are still yet to be incorporated into routine clinical practice. The major barriers to implementation include the specialized skills required for image evaluation and the time intensive nature of analysis. With the many recent advancements in the technology, AI presents itself as a promising solution. AI is attractive because it has the potential to rapidly automate technically challenging tasks with exceptional accuracy.

IMPLICATIONS

Developments in the field of AI are occurring at a rapid rate. There is already increasing evidence of the potential AI has to greatly improve the utility of CCTA by improving analysis time and extracting additional prognostic data from new plaque biomarkers. There are, however, technical and ethical challenges that need to be considered before implementing such technology into routine clinical practice.

Determinants and Outcomes of Invasive Coronary Angiography in Unselected Patients Presenting With Chest Pain to Emergency Departments in Western Australian Teaching Hospitals

BACKGROUND

Chest pain is a common cause of presentation to the emergency department (ED), and its outcomes are affected by various diagnostic tests and timely management. Our aim was to identify determinants of invasive coronary angiography (ICA) in a chest pain cohort following ED presentation, and to compare outcomes by time to ICA.

METHODS

We identified all adults aged ≥20 years presenting with chest pain to public teaching hospital EDs in Perth, Western Australia, from 1 January 2016 to 31 March 2017. Data were obtained from linked administrative ED, hospitalisation, pathology, and death records. Multivariable logistic regression was used to identify determinants of ICA within 90 days of ED presentation. Restricted cubic splines fitted in multivariable Cox regression models showed the relationship between time to ICA and outcomes of death and major cardiovascular events.

RESULTS

The cohort comprised 16,974 people, with 8,609 (51%) male patients and a mean age of 56 years; 986 (5.8%) patients had ICA within 1 day of presentation, 394 (2.3%) within 2-3 days, 543 (3.2%) within 4-90 days, and 15,051 (88.7%) had no ICA or had ICA after 90 days. Age, sex, residential area, triage code, troponin classification, ED diagnosis, and medical history were all significantly associated with 90-day ICA. The adjusted odds ratio of women receiving ICA was 0.53 (95% confidence interval 0.47-0.61) in comparison with men. Restricted cubic splines showed a biphasic relationship between time to ICA and death.

CONCLUSIONS

The determinants of ICA reflect clinical practice guidelines, although ICA remains less likely in women than in men. Early ICA is associated with lower risk of death but may not affect myocardial infarction or composite outcomes after adjusting for cofactors.

Clinical outcomes and health care costs of transferring rural Western Australians for invasive coronary angiography, and a cost-effective alternative care model: a retrospective cross-sectional study

OBJECTIVES

To examine the severity of coronary artery disease (CAD) in people from rural or remote Western Australia referred for invasive coronary angiography (ICA) in Perth and their subsequent management; to estimate the cost savings were computed tomography coronary angiography (CTCA) offered in rural centres as a first line investigation for people with suspected CAD.

DESIGN

Retrospective cohort study.

SETTING, PARTICIPANTS

Adults with stable symptoms in rural and remote WA referred to Perth public tertiary hospitals for ICA evaluation during the 2019 calendar year.

MAIN OUTCOME MEASURES

Severity and management of CAD (medical management or revascularisation); health care costs by care model (standard care or a proposed alternative model with local CTCA assessment).

RESULTS

The mean age of the 1017 people from rural and remote WA who underwent ICA in Perth was 62 years (standard deviation, 13 years); 680 were men (66.9%), 245 were Indigenous people (24.1%). Indications for referral were non-ST elevation myocardial infarction (438, 43.1%), chest pain with normal troponin level (394, 38.7%), and other (185, 18.2%). After ICA assessment, 619 people were medically managed (60.9%) and 398 underwent revascularisation (39.1%). None of the 365 patients (35.9%) without obstructed coronaries (< 50% stenosis) underwent revascularisation; nine patients with moderate CAD (50-69% stenosis; 7%) and 389 with severe CAD (≥ 70% stenosis or occluded vessel; 75.5%) underwent revascularisation. Were CTCA used locally to determine the need for referral, 527 referrals could have been averted (53%), the ICA:revascularisation ratio would have improved from 2.6 to 1.6, and 1757 metropolitan hospital bed-days (43% reduction) and $7.3 million in health care costs (36% reduction) would have been saved.

CONCLUSION

Many rural and remote Western Australians transferred for ICA in Perth have non-obstructive CAD and are medically managed. Providing CTCA as a first line investigation in rural centres could avert half of these transfers and be a cost-effective strategy for risk stratification of people with suspected CAD.