Telehealth during COVID-19 restrictions in patients with cardiovascular disease: impact on medication prescriptions and patient satisfaction.

BACKGROUND AND AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Western Australian medical students' attitudes towards artificial intelligence in healthcare.

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.

Transfer learning artificial intelligence for automated detection of atrial fibrillation in patients undergoing evaluation for suspected obstructive sleep apnoea: a feasibility study.

BACKGROUND: Individuals with obstructive sleep apnoea (OSA) experience a higher burden of atrial fibrillation (AF) than the general population, and many cases of AF remain undetected. We tested the feasibility of an artificial intelligence (AI) approach to opportunistic detection of AF from single-lead electrocardiograms (ECGs) which are routinely recorded during in-laboratory polysomnographic sleep studies. METHODS: Using transfer learning, an existing ECG AI model was applied to 1839 single-lead ECG traces recorded during in-laboratory sleep studies without any training of the algorithm. Manual review of all traces was performed by two trained clinicians who were blinded to each other's review. Discrepancies between the two investigators were resolved by two cardiologists who were also unaware of each other's scoring. The diagnostic accuracy of the AI algorithm was calculated against the results of the manual ECG review which were considered gold standard. RESULTS: Manual review identified AF in 144 of the 1839 single-lead ECGs (7.8%). The AI detected all cases of manually confirmed AF (sensitivity = 100%, 95% CI: 97.5-100.0). The AI model misclassified many ECGs with artefacts as AF, resulting in a specificity of 76.0 (95% CI: 73.9-78.0), and an overall diagnostic accuracy of 77.9% (95% CI: 75.9%-97.8%). CONCLUSION: Transfer learning AI, without additional training, can be successfully applied to disparate ECG signals, with excellent negative predictive values, and can exclude AF among patients undergoing evaluation for suspected OSA. Further signal-specific training is likely to improve the AI's specificity and decrease the need for manual verification.

Combined effects of one 8-hydroxyquinoline/picolinate and "CH"/N substitutions on the geometry, electronic structure and optical properties of mer-Alq(3).

With the aim of evaluating the combined effect of one 8-hydroxyquinoline (q)/picolinate (p) and "CH"/N substitutions on the molecular geometry, electronic structure, and optical properties of tris-(8-hydroxyquinoline)aluminum [Alq(3)], the density functional theory (B3LYP) and time-dependent density functional theory (TD-B3LYP), using the 6-31G(d) and 3-21+G(d,p) basis sets were applied on Alq(3), Alq(2)p, and its "CH"/N-substitution derivatives. A comparison of the optimized ground-state (S(0)) geometries has shown that the molecular shape is conserved upon such a substitution. On the basis of the frontier molecular orbital and gap energy (E(g)) calculations, it was shown that, comparatively to the pristine Alq(2)p (and to the original parent Alq(3)), the HOMO and LUMO are stabilized, the net effect being an increasing or a decreasing E(g), depending on the position of the substituted group. The substitution of q(B) by p (from Alq(3) to Alq(2)p) was also found to induce the same feature. Starting from the S(0) and S(1) (first excited state) geometries, the effect of the substitution on the absorption (and emission) spectra was evaluated. It was found that the "CH"/N substitution in different positions on the two 8-hydroxyquinoline ligands may also constitute an efficient approach of tuning the Alq(2)p emitting color. In comparison with both Alq(3) and Alq(2)p, an important blue shift was predicted for the 5-substituted derivative, an important red shift being observed for the 4-substituted one. Also, relatively significant blue and red shifts were predicted for the 7- and 2-substituted derivatives. Finally, revisiting the correlation between the spectrum shifts and the metal-ligand bonding, our recent findings (2) were confirmed.

Quantified coronary plaque characteristics between Caucasian and Morise score-matched South Asian populations.

Low-attenuation plaques (LAPs) are associated with an increased risk of cardiovascular mortality and morbidity. South Asians experience poorer cardiovascular outcomes compared to Caucasian populations. We hypothesised that South Asian population has a higher prevalence of LAP compared to Caucasians and this difference predicts major adverse cardiovascular events. 72 Caucasian and 72 Morise score-matched South Asian patients were identified from a cardiac computed tomography angiography (CCTA) registry. Coronary artery plaque subtypes in proximal major epicardial and left main arteries were analysed from CCTA images using pre-determined attenuation ranges in Hounsfield units (HUs): 1 to 30 HU (low attenuation), 31 to 70 HU (intermediate attenuation), 71 to 150 HU (high attenuation), and mean coronary lumen + 2 standard deviations to 1000 HU (calcified). For each analysis, data comparison was performed for plaque volumes after normalising for the corresponding coronary artery outer vessel wall volume. The baseline characteristics and total plaque score of the two cohorts were similar. There were no statistically significant differences in low, intermediate, and high- attenuation, or calcified normalised plaque volumes between Caucasian and Morise score-matched South Asian cohorts. After a mean follow up of 32 months, major adverse cardiovascular events were similar between Caucasians and South Asians. In a Morise score-matched ethnicity study, we found no significant differences in plaque subtypes including LAP in South Asians compared to a Caucasian cohort. Other factors accounting for poor outcomes in South Asians should be investigated.

Advances in screening for undiagnosed atrial fibrillation for stroke prevention and implications for patients with obstructive sleep apnoea: a literature review and research agenda.

Atrial fibrillation (AF) is the most common type of sustained cardiac arrhythmia encountered in clinical practice, and its burden is expected to increase in most developed countries over the next few decades. Because AF can be silent, it is often not diagnosed until an AF-related complication occurs, such as stroke. AF is also associated with increased risk of heart failure, lower quality of life, and death. Anticoagulation has been shown to dramatically decrease embolic risk in the setting of atrial fibrillation, resulting in growing interest in early detection of previously undiagnosed AF. Newly developed monitoring devices have improved the detection of AF and have been recommended in guidelines for screening of AF in individuals aged 65 years and over. While screening is currently targeted to these older individuals, younger patients with obstructive sleep apnoea (OSA) are at higher risk of AF and stroke than the general population, indicating a need for targeted early detection of AF in this group. Compared to individuals without OSA, those with OSA are four times more likely to develop AF, and the risk of AF is strongly associated with OSA severity. The overall prevalence of AF among individuals with OSA remains unknown because of limitations related to study design and to the conventional methods previously used for AF detection. Recent and emerging technological advances may improve the detection of undiagnosed AF in high-risk population groups, such as those with OSA. In this clinical review, we discuss the methods of screening for AF and the applications of newer technologies for AF detection in patients with OSA. We conclude the review with a brief description of our research agenda in this area.

Noninvasive Cardiovascular Imaging: Emergence of a Powerful Tool for Early Identification of Cardiovascular Risk in People Living With HIV.

Antiretroviral therapy (ART) has been pivotal in prolonging the lifespan of people living with HIV (PLWH). However, this also simultaneously increases their risk of cardiovascular disease (CVD) either related to ART, aging, hypertension, immunosenescence, inflammation, immune activation, or other comorbidities. Although the use of risk markers has greatly enhanced the field of cardiovascular (CV) medicine and improved the prognosis and early diagnosis in the general population, this strategy has not been clearly elucidated in PLWH. Developing accurate risk algorithms for PLWH requires an innate understanding of mechanistic factors influencing their risks. Early identification of CV risk will significantly enhance the prospects of PLWH living longer and relatively healthily. Herein, we discuss the use of multimodality noninvasive CV imaging as robust markers for ameliorating CV risk. The ability to prognosticate CV risk and hence prevent CV events in PLWH would represent an important advance in CV medicine, allowing precise detection and early institution of preventative strategies. Using novel CV imaging modalities and strategies would have a positive impact on precision medicine in this patient cohort.