bluuebunny/crossref_metadata_2025 huggingface dataset:
The use of myocardial perfusion scintigraphy to screen for asymptomatic coronary artery disease prior to kidney transplantation
Authors: Dirir O , Khwaja A
Published: October 2024

Background and Objectives

Advanced chronic kidney disease (CKD) is associated with an increased risk of cardiovascular disease (CVD), including significant asymptomatic coronary artery disease (CAD) [1], compared to the general general public. Additionally, CVD is the leading cause of mortality in kidney transplant recipients [2].

Given the relative scarcity of available organs, individuals are commonly screened for CAD with non-invasive cardiac testing such as Myocardial Perfusion Scintigraphy (MPS). However, the benefits of screening for asymptomatic CAD are unproven and in the absence of an established screening protocol, investigations vary centre to centre and can result in uncertain interpretation of results and unnecessary delays in transplantation.

The objective of this study was to assess the benefits of asymptomatic CVD screening of potential kidney transplant recipients, and its impact on transplantation outcomes.

Methods

This retrospective analysis included all MPS requested by the transplant team during patients’ assessment process between 2015 and 2023. Any resultant coronary angiograms (CA) were reviewed for evidence of significant CAD. Transplant decisions were reviewed to assess the impact of CVD screening on individuals’ transplant status.

Results

689 individuals underwent MPS. Of these, 90% required no further cardiovascular investigations. 6% (42 individuals) had subsequent CA. <1% (5) required percutaneous intervention (PCI) whilst the rest (37) were deemed to have no significant CAD. A further 4% (29) required coronary angiography at a later date (>2 years after their MPS), with similar rates of PCI (1%). All three outcome groups (negative MPS, CA referral, CA in the future) had similar rates of diabetes (40%) and previous diagnoses of CAD (14%). The average wait for CA was 283 days post-MPS. Transplant decisions took a further 286 days after CA, which in combination with the delays associated with CA resulted in average delays of 1.5 years.

Conclusions

The use of MPS to screen for significant asymptomatic CAD identifies only a small proportion of individuals requiring intervention prior to kidney transplantation and significantly delays transplant decisions. These results suggest transplant centres should review their use of CVD screening prior to listing.
Comprehensive risk factor analysis for sick sinus syndrome: an analysis of genetic, sociodemographic, clinical and laboratory data from the UK Biobank
Authors: Kim H J , Yang P S , Kim D H , Sung J H , Jang E S , Yu H T , Pak H N , Lee M H , Joung B Y , Lee C H
Published: October 2024

Background

Sick sinus syndrome (SSS) and atrial fibrillation (AF) frequently coexist and interact bidirectionally, often to initiate and perpetuate each other. The polygenic risk score (PRS) assesses the cumulative risk of disease onset based on variations at multiple genetic loci. To date, no specific PRS has been established for SSS. This study investigates the impact of clinical, sociodemographic, laboratory, and genetic factors, which were represented by PRS for AF due to the absence of a specific PRS for SSS on predicting the incidence of SSS.

Methods

The UK biobank enrolled 502,421 individuals, aged 38 to 73, across 22 centres in the UK locations, from 2006 to 2010. After excluding cases with incomplete data, prior history of AF, and valvular heart disease, 405,869 participants without AF (median age, 58.0 [interquartile range (IQR), 50.0–64.0] years; 213,684 [45.2%] male) were analyzed. Participants were categorized into three groups according to a validated PRS for AF: the first quintile the middle three quintiles, and the fifth quintile. Throughout the observation period, the incidence of SSS event was documented.

Results

During a follow-up period of 11.9 (IQR 11.1-12.6) years, a total of 769 cases of Sick sinus syndrome were identified. The Kaplan-Meier analysis demonstrated a progressive increase in the incidence of SSS as the quintiles of AF-related PRS increased. (Log-rank: P <0.001) Among 24 variables, statistically significant hazard ratios were observed with age, male sex, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), previous myocardial infarction (MI), history of malignant neoplasm, hypertension, diabetes mellitus, cystatin C, and AF PRS. In the prediction model for Sick Sinus Syndrome, the C-index for the sociodemographic model was 0.753. This increased to 0.764 with the addition of clinical factors, to 0.765 with the inclusion of biomarkers, and further to 0.769 upon adding genetic factors.

Conclusion

Our study found significant associations between the incidence of SSS and a range of sociodemographic, clinical, laboratory, and genetic factors, including age, male sex, BMI, blood pressure, and medical history. Notably, the AF PRS also showed relevance, suggesting its potential utility in developing one for SSS in the absence of a dedicated PRS for SSS.
Medication adherence and antithrombotic therapy outcomes: insights from a post-hoc analysis of the AFIRE trial
Authors: Chiba N , Noda T , Nochioka K , Kaikita K , Akao M , Ako J , Matoba T , Nakamura M , Miyauchi K , Hagiwara N , Kimura K , Hirayama A , Matsui K , Ogawa H , Yasuda S
Published: October 2024

Background

The AFIRE (Atrial Fibrillation and Ischemic Events With Rivaroxaban in Patients With Stable Coronary Artery Disease) trial established noninferiority in efficacy and superiority in safety endpoints of rivaroxaban monotherapy over rivaroxaban plus antiplatelet therapy (combination therapy) in patients with atrial fibrillation (AF) and stable coronary artery disease (CAD). However, the impact of medication adherence to rivaroxaban on AFIRE study outcomes remains unclear.

Purpose

This post-hoc analysis aimed to explore the influence of medication adherence on AFIRE trial results.

Methods

Among 2,120 patients, participants were classified into adherent and non-adherent groups based on self-reported measures, which were further verified through on-site visits to the facilities. Adherent patients were defined as those who reported consistently taking their medication as prescribed. The primary efficacy endpoint comprised stroke, systemic embolism, myocardial infarction, unstable angina requiring revascularization, or all-cause death, including cerebral events. Analysis also examined differences in the primary efficacy endpoint between adherent and non-adherent patients.

Results

Of the 2,120 patients, 2,012 (94.9%) were adherent to rivaroxaban, while 108 (5.1%) were non-adherent. Among adherent patients, rivaroxaban monotherapy showed significantly better efficacy outcomes compared to combination therapy (hazard ratio [HR] 0.73; 95% confidence interval [CI] 0.54–0.98; p=0.04, Figure 1A). However, primary efficacy outcomes did not significantly differ among non-adherent patients (HR 0.64, 95% CI 0.23–1.81, p=0.40, Figure 1B). Adherent patients exhibited improved outcomes relative to non-adherent patients, though this difference was not statistically significant (HR 1.68; 95% CI 0.99–2.85; p=0.05, Figure 2A). In clinically high-risk patients with a history of angina pectoris, those who demonstrated adherence to medication (n=1281) exhibited significantly better efficacy outcomes compared to non-adherent patients (n=68) (HR 1.97; 95% CI 1.09–3.56; p=0.03, Figure 2B).

Conclusions

Rivaroxaban monotherapy versus combination therapy showed favorable efficacy outcomes in patients with good adherence, consistent with the overall AFIRE trial. However, these benefits were not observed in non-adherent patients. Adherence to rivaroxaban is crucial for achieving its maximum therapeutic effect as monotherapy.Figure1Figure2
Effect of sodium-glucose cotransporter-2 inhibitor (SGLT2-i) in patients with LVAD: a systematic review and meta-analysis
Authors: Hasabo E A , Isik B , Elgadi A , Eljack M M F , Yacuob M S , Alzomor H , Sawabi R , Sultan S , Caliskan K , Soliman O
Published: October 2024

Introduction

Sodium-glucose cotransporter-2 inhibitor (SGLT2-i) have been shown to reduce risks of clinical events in patients with heart failure (HF). However, data on the use of SGLT2-i in patients with left ventricular assist devices (LVAD) are scarce. We thought to assess the efficacy and safety of SGLT2-i in patients with LVAD

Methods

A systematic search was done in PubMed, Scopus, Web of Science, Embase, and Cochrane from inception to December 2023. We used all relevant words for "SGLT2-i" and "LVAD" to search in databases and we included studies and published abstracts in peer-reviewed journals of studies assessed SGLT2-i in patients with LVAD. The efficacy and safety data were extracted across the studies. RevMan 5.4.1 was used for meta-analysis.

Results

Three studies and eight abstracts totaling 209 patients using SGLT2-i were included. Empagliflozin, Dapagliflozin, and Canagliflozin were the used SGLT2-i across the included studies. SGLT2-i effectively decreased hemoglobin A1c (HbA1c) (Mean = -0.44, 95% CI [-0.79, -0.09], p = 0.01) and diuretic dose (Mean=-2.54, 95% CI [-3.56, 1.51], p< 0.00001) from baseline. No significant improvement was found for glomerular filtration rate (GFR), B-type natriuretic peptide (BNP), or mean pulmonary artery pressure (MPAP). Regarding safety, the pooled percentage of people with driveline infection was 9.33%, 95% CI [2.05, 16.60], p=0.01.

Conclusion

SGLT2-i effectively improves HbA1c and diuretic dose in patients using LVAD. Further randomized studies with a large number of participants may be warranted.
Torsemide versus furosemide in patients with heart failure: a systematic review and meta-analysis
Authors: Mohamed A E , Ramadan S , Afify R , Ellaban M , Ishak J , Shafiek F A M , Abdelwahab A , Abdelaziz A , Elnady M I , Abdelazeem B , Lavie C J , Slipczuck L
Published: October 2024

Introduction

Loop diuretics are essential agents in the management of fluid overload conditions, heart failure and renal dysfunction. Despite their widespread use, there is ongoing debate regarding the relative efficacy, safety, and clinical outcomes associated with furosemide and torsemide. By systematically analyzing existing literature, this study seeks to provide a comprehensive evaluation of the comparative effectiveness and safety profiles of these two medications , Helping to inform clinical decision-making and contribute to the optimization of diuretic therapy in patients with heart and kidney diseases.

Methods

We searched PubMed, Scopus, WOS, and Cochrane until February 2024 for relevant studies comparing the torsemide and furosemide in Heart failure patients. Outcomes of interest were all-cause mortality, cardiovascular mortality, all-cause hospitalization, hospitalization for HF, and improvement of ≥ 1 in NYHA functional class.

Results

16 studies were included in this meta-analysis with a total of 12545 patients, There were no significant results between the two drugs in all-cause mortality, cardiovascular mortality or all-cause hospitalization, torsemide showed a reduction in hospitalization from heart failure (RR 0.85, 95% CI [0.71 to 1.02]), torsemide showed a significant improvement of ≥ 1 in NYHA functional class (OR 1.60, 95% CI [1.18, 2.17]).

Conclusion

There was no difference between torsemide and furosemide when it comes to all-cause and cardiovascular mortality, but torsemide showed better results in reducing hospitalization rates and and improving quality of life.Hospitalization from heart failureImprovement ≥ 1 in NYHA class
Differences in symptoms of anxiety and depression among out-of-hospital cardiac arrest survivors and their relatives, paired results from the DANCAS survey
Authors: Bekker-Jensen D , Sofie Hermansen A , Moesgaard Bruvik S , Joshi V , Wieghorst A , Zwisler A , Borregaard B
Published: October 2024

Background

It is well known that out-of-hospital cardiac arrest (OHCA) survivors, as well as their relatives, struggle with symptoms of anxiety and depression, but less is known about the potential differences in paired outcomes.

Purpose

To describe differences in symptoms of anxiety and depression among OHCA survivors and their relatives (paired) and to investigate characteristics associated with these symptoms among both groups.

Methods

A national cross-sectional survey (DANCAS) was conducted with OHCA survivors combined with a survey for their closest relatives. The Hospital Anxiety and Depression Scale (HADS) was included in both surveys. Paired t-tests were used to examine potential differences in HADS mean scores among survivors and relatives. Associations between characteristics (demographic and other self-reported outcomes) and symptoms of anxiety (HADS-A ≥8) and depression (HADS-D ≥8) were examined using multivariable logistic regression models, presented as odds ratios (OR) with 95% confidence intervals (CI), adjusted for potential confounders.

Results

In total, 526 pairs of OHCA survivors and their relatives both responded, with 447 (85%) of the survivors being men, a median age of 67 years (IQR 59-75) and 462 (88%) of the relatives being women with a median age of 64 years (IQR 55-70). Most relatives (85%) were spouses or unmarried partners. In the paired analyses, relatives had significantly higher scores of anxiety compared to survivors (mean 5.6 SD 4.0 vs 3.5 SD 3.8; p<0.001). On the contrary, survivors had significantly worse scores of depression (mean 3.1 SD 2.8 vs 2.4 SD 3.2; p>0.001). Several characteristics (demographic and self-reported) were associated with symptoms of anxiety and depression among both survivors and relatives, Table 1 & 2.

Conclusion

Following OHCA, relatives report worse scores of anxiety while, in contrast, survivors report worse scores of depression, indicating psychological interventions should be tailored differently for the two groups. Further investigation of the reasons for these findings are needed, including whether fatigue might be a symptom of depression or a confounder.
Determinants of adherence among patients with hypertension
Authors: Lomper K , Wleklik M , Chudiak A , Mazur G , Uchmanowicz I
Published: October 2024

Background

Poor adherence to pharmacological treatment among patients with hypertension (HTN) is common. Approximately half of HTN patients do not use their medications as prescribed. Multiple barriers can influence adherence to antihypertensive medications. HTN patients may be characterized by the presence of frailty syndrome (FS) and cognitive impairment (CI). FS and CI may adversely affect the course of the disease and adherence to therapeutic recommendations.

Purpose

To assess the adherence and its determinants among patients with hypertension.

Methods

The study included 129 patients diagnosed with hypertension (81 men, 48 women; mean age M±SD=69.98±11.67) hospitalized in the Department of Occupational Diseases and Hypertension. Medical record analysis, the author's sociodemographic questionnaire, the Tilburg Frailty Idicator (TFI) to determine the presence of frailty syndrome, the Montreal Cognitive Assesment (MoCa) questionnaire to assess cognitive function, and the Adherence to Medication Scale (ARMS) to assess adherence were used.

Results

The majority of respondents were male (62.79%), living in large cities (31.78%), in a relationship (61.24%), with a high school education (68.22%), and retired (67.44%). Analysis of medical records among comorbidities showed diabetes (59.69%) and other cardiovascular diseases (58.91%) to be the most common. Hospitalizations due to hypertension within the past year in the range of 1-2 were reported in 72.09% of the subjects, 3-5 hospitalizations in 17.05%, and more than 5 hospitalizations in 10.85% subjects. The surveyed patients mostly kept self-monitoring diaries (61.24%), measured their blood pressure values 2-3 times a day (58.15%) with an upper arm blood pressure monitor (64.34%). In terms of self-care behaviors, respondents most often indicated following a diet with a restriction of unhealthy fats (52.71%), following a low-sodium diet (44.19%) and being physically active (33.33%). The mean blood pressure values in the study group were M±SD=139.73±16.73 mmHg for SBP and M±SD=81.48±13.25 mmHg for DBP, respectively. On the basis of the TFI, 99.22% of patients showed the presence of FS (M±SD =10.66±2.82), the MoCa questionnaire indicated abnormal values in cognitive function in 79.07% (M±SD =18.16±8.3). The average adherence ARMS score was M±SD 17,6±6,72 pcts. (higher the ARMS score the worse adherence).

Univariate analysis as determinants of adherence showed unemployment (b=9.391;p=0.001), smoking (b=6.701;p=0.001), duration of illness (b=-0.153;p=0.003), 3-5 hospitalizations in the past year (b=3.891;p=0.014). Multivariate analysis among determinants of adherence showed unemployment (b=7.556;p=0.022), duration of illness (b=-0.167;p=0.002) and 3-5 hospitalizations (b=5.011;p=0.001).

Conclusion

Hypertensive patients are characterized by optimal adherence. Despite expectations, cognitive impairment and frailty syndrome did not determine adherence to medications.
Differential effects of heat-not-burn, electronic cigarettes and conventional cigarettes on endothelial glycocalyx
Authors: Ikonomidis I , Katogiannis Κ , Kourea K , Kostelli G , Pavlidis G , Thymis J , Katsanaki H , Vlachomitros D , Maratou E , Vlastos D , Lambadiari V
Published: October 2024

Background

Heat-not-burn cigarette (HNBC) and electronic cigarette (Ecig) constitute non-combustible smoke products. Their effect on endothelial glycocalyx has not been investigated so far.

Patients and Methods: Out of 100 subjects attending smoking cessation clinic: α) 50 smokers were randomized to usage of HNBC (n=25) or Ecig (n=25) and β) 50 smokers were used as control group. Participants randomized to the newer tobacco products had similar clinical and demographic characteristics to the control group. Smoking status was verified by measuring the concentration of exhaled carbon monoxide [(e CO) (ppm), Bedfont Scientific, Maidstone, Kent UK]. Perfused Boundary Region (PBR), which is inversely related to endothelial glycocalyx thickness in sublingual arterioles (range 5–25 μm) and blood levels of cotinine, a stable metabolite of nicotine, was assessed in all participants. Exhaled CO, endothelial glycocalyx, and blood cotinine were assessed at baseline and after 1 month.

Results

Conventional cigarette smokers were aged: 48 ± 5 years, 53% female and used 27 ± 9 cigarettes/day, 29 ± 9 pack-years. HNBC users were aged: 46 ± 14 years, 55% female and used 26 ± 8 cigarettes/day, 30 ± 8 pack-years. Ecig users were aged: 45 ± 8 years, 51% female and used 27 ± 10 cigarettes/day, 28 ± 10 pack-years. Compared to baseline, switching to HNBC for 1 month improved only PBR20-25 (2.55±0.49 vs 2.34±0.34 μm, p=0.002). Ecig use did not alter endothelial glycocalyx in any range of microvessels throughout the study (p>0.05). In contrast, Tcig smoking for one month further worsened endothelial glycocalyx in all microvessels ranges compared to baseline (p<0.05). Blood cotinine levels were similar at baseline and after 1 month using HNBC (p=0.432), Ecig (p=0.535) or conventional cigarette (p=0.489). Compared to baseline, exhaled CO decreased in HNBC or Ecig users (mean percent change: -55% and -58% respectively p<0.001), while remained unchanged in Tcig smokers (p=0.312) at 1 month. Thus, Tcig smokers had higher CO than those who switched to HNBC or E-cig after one month (p<0.01).

Conclusion

Conventional cigarette users further worsened endothelial glycocalyx after continuing to smoke for one month. In contrast, smokers who switched to Ecig maintained glycocalyx integrity, while those who switched to HNBC showed modest improvement in glycocalyx integrity in microvessels ranging from 20 to 25 μm. Cotinine levels, which reflect nicotine exposure, were similar between the Tcig, HNBC and Ecig groups. Thus, endothelial glycocalyx impairment in the conventional cigarette group was independent of nicotine consumption and possibly related to greater exposure to toxic emissions, such as CO, after Tcig use than after switching to HNBC or Ecig.
The introduction of a dedicated cardiology clinic including a clinical scientist led pathway for women with turner's syndrome
Authors: Macrae R , Von Klemperer K , Zemrak F , Wong H Y C , Stoicescu C N
Published: October 2024

Background

There are more than 15,000 women living with Turner’s Syndrome (TS) in the UK, over 700 of whom are cared for within our linked Endocrinology services. Mortality is predominantly related to cardiovascular disease therefore close cardiology review with a focus on aortopathy is essential (1). However appropriate surveillance is challenging with growing pressures on all aortopathy services across the United Kingdom.

Purpose

To audit our current practise according to current international guidelines (2) and seek methods to improve the pathway for our growing population of TS patients including the feasibility of a Clinical Scientist led clinic, aiming to improve capacity and efficiency of our service.

Methods

A quality improvement project was conducted over a three-year period, piloting a dedicated clinical scientist-led clinic under close Cardiology Consultant supervision. Patients selected were deemed lower risk for cardiovascular complications according to American Heart Association (AHA) recommendations (2) (figure 1). Follow-up intervals of patients under both consultant-led and clinical scientist led pathways were analysed.

Results

Among a total of 226 patients analysed, 103 (46%) fell into the lowest risk category and therefore deemed suitable for prospective Clinical Scientist led pathway (figure 2).

Analysis of all patients demonstrated that 60% had appropriate follow-up intervals according to guidelines, while 37% were too short and 3% were too long. A five-year projection indicated a consequential 96 unnecessary additional appointments for patients that were being seen too frequently. Further analysis showed that the time frame for follow up was too short in 25% of patients seen in the clinical scientist led clinic compared to 41% in the Consultant-led clinic.

There were no aortic dissections in patients under surveillance during this period. In the last 10 years 1 patient on the waiting list for surgery (having presented with a type B dissection but requiring workup for liver cirrhosis) had a retrograde type A dissection (indexed aortic root dimension 2.4cm/m²). No other adverse events were recorded.

Conclusion

Auditing our service revealed safe management and improved adherence to guidelines in the clinical scientist-led clinic, identifying opportunities to optimize follow-up and enable physicians to focus upon high-risk patients. This pilot demonstrates the feasibility of a clinical scientist-led clinic in managing low risk TS patients, suggesting scalability to other conditions involving aortopathy to address capacity issues and improve pathways.
Fully automated detection of anomalous aortic origin of the coronary arteries in coronary CT images: a novel artificial intelligence-based screening tool
Authors: Shiri I , Mohammadi Kazaj P , Bigler M , Stark A , Kakizaki R , Siepe M , Valenzuela W , Raber L , Giannopoulos A , Ralf Buechel R , Graeni C
Published: October 2024

Background

Anomalous Aortic Origin of the Coronary Artery (AAOCA) is a rare congenital disease that can be easily overlooked during contrast-enhanced Coronary Computed Tomography Angiography (CCTA) image analysis.

Objective

In this study, we aimed to develop a novel artificial intelligence-based screening tool to automate the detection of AAOCA in CCTA images.

Method

We enrolled 127 patients from the coronary artery anomaly registry from two centers with AAOCA diagnosis based on CCTA as well as 413 normal cases. A deep learning model was developed to automatically segment the aorta and the left ventricle (LV), after which the images were automatically cropped to the aortic root and LV intersection with a box size of 6 cm3. The images were then clipped to Hounsfield Units ranging from -400 to 750 and normalized to -1 to1. These cropped regions were fed into different residual convolutional neural networks (ResNet, with different depths 10, 18, 34 and 50) to detect AAOCA. Model development (parameter and hyperparameters optimization) was performed on the training and validation sets (70/10%), and finally, it was tested on the 20% untouched test set. Various classification metrics were reported for the detection of AAOCA.

Results

ResNet-10 achieved an AUC of 0.91 (sensitivity: 0.89, specificity: 0.86), while ResNet-18 showed improved performance with an AUC of 0.95 (sensitivity: 0.89, specificity: 0.95). ResNet-34 achieved an AUC of 0.94 (sensitivity: 0.83, specificity: 0.96), and ResNet-50 excelled with the highest AUC of 0.96 (sensitivity: 0.89, specificity: 0.95), indicating its superior capability in accurately identifying AAOCA.

Conclusion

We developed a high-performance AI tool for the fully automated detection of AAOCA using CCTA images. This tool can be used to evaluate large patient cohorts and detect AAOCA in extensive databases. Moreover, it can operate seamlessly alongside clinical assessments of CCTA scans, providing real-time alerts to medical personnel about potential AAOCA findings. This enhances diagnostic efficiency and supports early intervention in cardiovascular care.
Using deep learning to detect atherosclerotic plaques on carotid ultrasound images in the UK Biobank
Authors: Omarov M , Jorshery S D , Malik R , Raghu V K , Dichgans M , Anderson C D , Georgakis M K
Published: October 2024

Background

Atherosclerosis is the main underlying cause of cardiovascular disease (CVD). Existing CVD risk assessment tools do not consider the burden of subclinical atherosclerosis. The presence of carotid plaques on carotid ultrasound is a well-known marker of subclinical atherosclerosis. The accumulation of population-scale data on the presence of atherosclerotic plaques, along with deep phenotyping, can allow not only to address the effectiveness of carotid ultrasound in routine clinical practice, but to shed light on the biology of atherosclerosis development.

Purpose

To develop an effective deep learning model for plaque detection in carotid ultrasound images in the UK Biobank.

Methods

We used 680 carotid ultrasound images with manually annotated plaques to train a deep learning model employing the YOLOv8 architecture. Different augmentation techniques were used to increase the generalizability of the model. The developed model was applied to automatically detect plaques in raw ultrasound images from 19,507 UK Biobank participants. Logistic and Cox regression were used to explore the associations of plaque presence and number as predicted by the model with conventional CVD risk factors and the risk of future CVD events over follow-up. To explore the genetic architecture of subclinical atherosclerosis, we conducted a genome-wide association study (GWAS) on plaque presence, followed by meta-analysis with data from the CHARGE Consortium.

Results

Our plaque detection model achieved high classification metrics of accuracy, sensitivity, and specificity (89.3%, 89.5%, and 89.2%, respectively) and detected atherosclerotic plaques in 44% of UK Biobank participants. As expected, plaques were more common among men than women and their prevalence increased linearly with age. Both plaque presence and number of plaques were correlated with conventional CVD risk factors including diabetes, hypertension, and hyperlipidemia, and showed strong associations with future risk of incident CVD events (Hazard Ratio for plaque presence: 1.48 [95%CI: 1.21-1.82], for 2 plaques or more: 1.65, [95% CI: 1.28-2.13]). Incorporating plaque-derived phenotypes minimally altered the C-index of the time-to-event model. GWAS meta-analysis of carotid plaque presence revealed 5 previously known loci, as well as a significant locus including the LPA gene that had not previously been associated with carotid plaque.

Conclusion

We have developed and implemented an efficient plaque detection model to data from the UK Biobank, which holds significant promise for studying atherosclerosis at a population-wide scale through integration with multiomics data and electronic health records.
AI-ECG sex-estimation discordances predict cardiovascular events
Authors: Multinu G , Rajai N , Ozcan I , Medina-Inojosa B , Medina-Inojosa J , Attia Z , Lerman L O , Lopez-Jimenez F , Friedman P , Lerman A
Published: October 2024

Background

Cardiovascular disease remains the leading cause of death and burden globally, warranting the need to explore novel predictors of major adverse cardiovascular events (MACE) using new technologies. Artificial Intelligence (AI)-enhanced ECG (AI-ECG) algorithms can provide information on cardiovascular health of individuals, independent of conventional risk factors.

Purpose

The current study aimed to understand whether a previously described AI-ECG sex estimation algorithm could be applied for risk stratification of major adverse cardiovascular events (MACE), with a focus on a population without previous history of MACE.

Methods

Patients having 12-lead ECGs between 2018-2019 were included and followed up until August 2023. Exclusion criterion was a prior history of MACE. AI-ECG sex estimation was determined using a previously described algorithm predicting sex based on 12-lead ECGs. The algorithm generates outputs ranging from 0 to 1, representing the estimated probability of being male. Outputs above 0.5 were considered as AI-ECG-estimated male, and below as AI-ECG-estimated female. This was compared with biological sex to determine whether the two matched. Inconsistency between AI-ECG estimated sex and biological sex was defined as discordance. MACE was defined as myocardial infarction, coronary revascularization, non-fatal stroke, and all-cause death.

Results

Among 80,578 subjects (mean age 59.1 ± 16.1 years, 52.4% female), 9.7% exhibited sex discordance in AI-ECG estimation. Discordance was associated with a 56% higher risk of MACE (HR, 1.56, 95% CI 1.46-1.65, p <0.001), and remained significant in multivariable analysis with traditional risk factors (HR 1.35, 95% CI 1.27-1.43, p <0.001) (Figure 1). Sex-specific analysis showed increased MACE risk in both discordant males and females (Figure 2).

Conclusion

In patients with no history of MACE, discordance in AI-ECG sex estimation is associated with increased risk of MACE. These findings suggest the potential of AI-ECG sex estimation algorithm for risk assessment, especially in patients with no history of MACE.Figure 1.Cox proportional hazard modelFigure 2.Kaplan-Meier of MACE by sex
Predicting physical fitness levels from resting ECG data: a machine learning approach in cardiovascular assessment
Authors: Cohen-Shelly M , Cohen J , Zimlichman E , Rahman N , Klempfner R , Maor E , Segev A , Raanani E , Sabbag A , Masalha E
Published: October 2024

Background

Exercise Stress Testing (EST), an inexpensive noninvasive modality, is widely used for preliminary cardiovascular evaluation and ongoing monitoring of cardiac patients. The MET (Metabolic Equivalent of Task) score from EST, indicating physical fitness, is associated with overall mortality risk and is extremely helpful for preoperative evaluation. Artificial Intelligence (AI) advances, particularly Deep Learning (DL) for resting ECG analysis, have significantly improved cardiac diagnostic accuracy.

Objectives

This study explores AI's ability to predict MET scores from resting ECGs, aiming to streamline fitness assessments and detect early changes in fitness levels.

Methods

The current analysis encompasses 45,518 consecutive EST evaluations from 31,532 individual patients from 2017 to 2023. MET scores were automatically computed using an established formula, while interpretations by certified cardiologists provided a benchmark for the AI model. Poor fitness was defined as being within the lowest quartile of MET scores, adjusted for sex and age. A deep learning framework was developed to process a 10-second snippet of resting phase ECG in raw waveform, predicting the likelihood of diminished fitness and thus acting as a binary classifier. The efficacy of this Poor Fitness AI model (PF-AI model) was assessed through metrics such as the area under the receiver operating characteristic curve (AUROC), along with sensitivity, specificity, and accuracy rates.

Results

The average age of the study group was 55±10 years, predominantly male (68.8%, n = 31,337). Among them, 1,152 were identified as having poor fitness. Applying the model to the entire cohort through 5-fold cross-validation yielded a sensitivity of 78%, a specificity of 81%, and an AUROC of 0.87 in predicting poor fitness.

Conclusions

Leveraging merely 10 seconds of resting ECG data, the PF-AI model proves to be a robust tool in predicting poor fitness levels, comparable to the outcomes of comprehensive stress testing.
Revolutionising patient care: the role of AI-generated avatars in healthcare consultations
Authors: Loh B C S , Fong A Y Y , Ong T K , Then P H H
Published: October 2024

Background/Introduction

The healthcare sector faces an unprecedented challenge with the surging demand in both public and private settings, pushing them towards the brink of overload. This scenario underscores a critical knowledge gap in leveraging technology to alleviate the burden on healthcare services. Our study introduces an innovative solution through the development of avatars generated with artificial intelligence (AI) technologies, that replicate the likeness and expertise of healthcare professionals. These AI-generated avatars aim to bridge the gap in patient consultations, offering a scalable and efficient alternative to traditional care models.

Purpose

The primary objective of our study was to design and implement a virtual assistant capable of conducting patient consultations with the same reliability and personal touch as a trusted human medical professional. This was carried out through the integration of diverse AI technologies including generative models, large language models (LLMs), speech-to-text, and text-to-speech algorithms.

Methods

Our methodology encompassed the creation of three-components, the visual and auditory representation of the healthcare professional (avatar), the capability to process and generate speech (brain functions), and a database of information sourced from medical repositories as well as expert inputs (compiled knowledge). The development process involved capturing and generating the likeness and voice of a medical expert, training LLMs with the compiled knowledge, and engineering the system to function in real-time. This multifaceted approach ensured the AI-generated avatars were not only personalised but also intelligent and interactive.

Results

The successful execution of each component confirmed its feasibility, with the AI-generated avatars resembling their human counterparts in appearance and voice, effectively processing spoken inputs, and providing medical advice based on the compiled knowledge. The primary challenge identified was the integration of these components to operate seamlessly in real-time, indicating the need for further refinement in synchronisation and response speed.

Conclusion

This study has laid a foundational step towards revolutionising patient care through AI technologies. Our results demonstrate the potential of AI-generated avatars to alleviate workloads by providing personalised and efficient patient consultation services. Future work will focus on enhancing the real-time integration of system components, improving the scalability of the solution, and further personalising the patient experience. This direction not only intends to expand the capabilities of healthcare providers but also opens new avenues for patient engagement and care delivery.
Exploring the role of AI-driven chatbots in patient care: a critical evaluation amidst healthcare staff shortages
Authors: Olszewski R , Brzezinski J , Watros K , Manczak M , Owoc J , Jeziorski K
Published: October 2024

Background

Amidst the backdrop of staff shortages in healthcare systems, patients and their families are increasingly turning to chatbots, powered by Large Language Models (LLMs), for information about their medical conditions. These AI-driven chatbots, capable of generating human-like responses across a broad range of topics, have become a prevalent tool in the healthcare landscape. Given the proliferation of these chatbots, it is crucial to evaluate the quality and accuracy of the responses they provide.

Methods

We selected five freely accessible chatbots (Bard, Microsoft Copilot, PiAI, ChatGPT, and ChatSpot) for our study. These chatbots were posed questions spanning three medical fields: cardiology, cardio-oncology, and cardio-rheumatology. The responses generated by the chatbots were then compared against established guidelines from the European Society of Cardiology, American Academy of Dermatology, and American Society of Clinical Oncology. In addition to the content, the readability of the responses was evaluated using four different readability scales: the Flesch Reading Scale, Gunning Fog Scale Level, Flesch-Kincaid Grade Level, and Dale-Chall Score. To assess the accuracy of the responses in accordance with the medical guidelines, two independent medical professionals rated them on a 3-point Likert scale (0 - incorrect, 1 - partially correct or incomplete, 2 - correct). This allowed us to gauge the compliance of the chatbot responses with the medical guidelines.

Results

Results: In our study, we posed a total of 45 questions to each of the chatbots. Out of the five chatbots, Microsoft Copilot, PiAI, and ChatGPT were able to respond to all the questions. The length of the responses varied, with PiAI providing the shortest average response length of 7.26 words, and Bard providing the longest at 18.9 words. In terms of readability, the Flesch Reading Ease Scale scores ranged from 17.67 (ChatGPT) to 39.34 (Bard), indicating the relative complexity of the responses. The Flesch-Kincaid Grade Level, which reflects the academic grade level required to comprehend the text, ranged from 14.02 (PiAI) to 15.97 (ChatGPT). The Gunning Fog Scale Level, another measure of readability, varied from 15.77 (Bard) to 19.73 (ChatGPT). Lastly, the Dale-Chall Score, which assesses the understandability of the text, ranged from 10.24 (Bard) to 11.87 (ChatGPT). These results highlight the variability in the readability and complexity of responses generated by different chatbots.

Readability analysis is presented in table 1.

Conclusion

This study indicates that chatbots vary in length, quality and readability. They answer each question in their way, based on data they have pulled from the network. Our data suggests that people who want information from a chatbot need to be careful and verify the answers they get.
"I don't want hear about that": Treatment wishes/preferences of elderly patients regarding possible treatment goals in acute life-threatening illness or acute organ failure
Authors: Richter S , Filo J , Boukadida M , Winterhalter M , Krabs R , Ohlow M A
Published: October 2024

Background

In many people with acutely life-threatening illnesses, the will to undergo treatment is not known with sufficient precision. It is often unclear whether the person concerned would have consented to life-sustaining measures or would have preferred to die with palliative care. This applies in particular to the vulnerable group of elderly, chronically ill/fragile people. It is not uncommon for people to reject the risks/burdens of medical treatment, even if there is a chance of success. On the other hand, there are many people who fight to continue living, even if this can be associated with great burdens and the outcome is rather uncertain.

Aim of the study is to determine the characteristics of cardiologic patients who refuse to discuss treatment wishes/preferences in case of acute emergencies, temporary (e.g. in the context of intensive care unit (ICU) treatment), or permanent (vegetative state) inability to consent.

Methods

Prospective, questionnaire-based cross-sectional study including Hospital Anxiety and Depression Scale (HADS) and assessment of quality of life using the 12-item Short Form Health Survey (SF-12) on normal cardiology wards.

Results

455 cardiologic patients were interviewed (mean age 71.2 ± 12.9 years, 39.6% female), 76.1% had moderate-severe concomitant diseases according to the Carlsson Comorbidity Index (4.3 ± 2.4 points) (see Table I). 23.5 % of respondents did not wish to address the above-mentioned question, they were significantly older (74.6 ± 13.1 vs. 69.9 ± 12.8 years; p=0.0009), had more comorbidities, were less likely to have a high level of education (university degree: 13.0 % vs. 30.6 %; p=0.0021) and were less likely to be employed (11.7 % vs. 25.8 %; p=0.0026). Furthermore, these patients live alone more frequently (45.8% vs. 30.6%; p=0.0048) and are less likely to live in a partnership (52.0% vs. 68.0%; p=0.0043). Refusal of an advance directive was also more common (22.5% vs. 10.7%; p=0.05), quality of life was impaired (42.4 ± 9.8 vs. 45.9 ± 10.5 points; p=0.0022), and the HADS-score levels were higher (15.6 ± 7.3 vs. 12.7 ± 7.8 points; p=0.0007).

Conclusions

A relevant proportion of our patients refuse to discuss treatment wishes/preferences in case of acute emergencies, temporary or permanent inability to consent. Paradoxically, these were patients for whom it would make particular sense (older, sicker, and more socially isolated patients). Those patients are also prone to anxiety and depression, and have a reduced quality of life.
Distinguishing factors in regional variations of TAVI in Japan: the unique role of administrative facility standards compared to other procedures in a high-cost medical care subsidy system
Authors: Kanda M , Kuwabara H , Kobayashi Y , Inoue T
Published: October 2024

Background

Transcatheter aortic valve implantation (TAVI) is less invasive than surgical aortic valve replacement and is becoming increasingly popular worldwide, particularly among patients with aortic valve stenosis (AS) due to aging. However, regional differences are expected to exist not only between countries but also within a single country. Reports from Western countries indicate the presence of regional differences in TAVI and the reasons for these differences, which include differences in medical infrastructure, economic resources, health insurance systems and policies, geographic factors, and availability of specialized medical personnel. TAVI is expensive, but in Japan, the economic aspect is relatively unimportant due to the high-cost medical assistance system. Furthermore, there is little socioeconomic disparity between regions. In such a society, we have reported that the number of specialists and resources for PCI can explain regional differences in ablation and endovascular treatment (EVT). However, unlike those other cardiovascular procedures, there are specific requirements for facilities to perform TAVI, such as the number of transesophageal echocardiographies, as well as cardiologists and cardiovascular surgeons, and the equipment itself, such as hybrid operating rooms. We examined how these facility requirements, which are thought to be controlled by the government, are related to regional differences in TAVI implementation.

Methods and Results

We used the Japanese Ministry of Health, Labour and Welfare national database to determine the rate of TAVI for patients with AS performed per 100,000 population aged ≥40 years in all 47 prefectures in 2022. A linear regression model was developed to assess factors contributing to the regional medical supply, including the rates of PCI per 100,000 population aged ≥40 years and the numbers of cardiologists, cardiovascular surgeons, cardiovascular intervention and therapy training facilities, cardiovascular surgery base facilities, and TAVI facilities. The numbers in the highest and lowest regions were 26.6 and 3.9 (a 6.8-fold difference) for TAVI number. The number of TAVI facilities contributed most significantly to the TAVI volumes (P = 0.0105), while the rates of PCI and other factors did not contribute significantly. The number of TAVI facilities was positively correlated with the number of transesophageal echocardiographies the most (r = 0.353).

Conclusion

This study revealed large regional variations in TAVI volumes in Japan, of which administrative facility standards were a major determinant.
Association of ticagrelor vs clopidogrel with net adverse clinical events in NSTEMI patients with mild thrombocytopenia
Authors: Jiang C , Zhang Y K , Gu T S , Hu S T , Zhang J K , Wu X , Liu X , Liu T , Chen K Y
Published: October 2024

Backgrounds: Guidelines currently recommend aspirin plus ticagrelor as the preferred dual antiplatelet therapy (ADPT) for non-ST-elevation myocardial infarction (NSTEMI). However, there are no established recommendations for managing NSTEMI patients with mild thrombocytopenia, defined as a platelet count of 100~150×109/L.

Purpose

This study aims to investigate the association between ticagrelor and clopidogrel with ischemic and hemorrhagic events in NSTEMI patients with a platelet count of 100~150×109/L.

Methods

A retrospective cohort study was conducted using data from the Health and Medical Big Data Super Platform from January 2010 to June 2023. The study included NSTEMI patients with a platelet count of 100~150×109/L who received DAPT consisting of aspirin and a P2Y12 receptor antagonist (eithor clopidogrel or ticagrelor). Patients were followed up for at least one year. The inverse probability of treatment weighting (IPTW) approach based on propensity score was used to balance the observed confounders between treatments. The primary endpoint was net adverse events (NACE) at 1 year, composed of ischemic events (recurrent myocardial infarction or ischemic stroke), Bleeding Academic Research Consortium (BARC) classification ≥ 3, and cardiac death. Secondary outcomes included cardiac death, recurrent myocardial infarction and, ischemic stroke.

Results

The study cohort comprised 2969 participants, with a median age of 72 years and 29.2.0% female. After adjustment using inverse probability of treatment weighting, ticagrelor and clopidogrel showed similar rates of NACE (aHR, 0.84; 95%Cl, 0.58-1.21). Cardiac death (aHR, 0.99; 95%Cl, 0.54-1.83) and ischemic stroke (aHR, 0.94; 95%Cl, 0.49-1.81) did not significantly differ between the two groups. However, ticagrelor was associated with a lower rate of recurrent myocardial infarction (aHR, 0.44; 95%Cl, 0.21-0.93).

Conclusion

In routine clinical practice, among NSTEMI patients with a platelet count of 100~150×109/L, ticagrelor, did not showed a significant difference in the risk of NACE at 1 year compared with clopidogrel. However, ticagrelor was associated with a lower rate of recurrent myocardial infarction. Further research is warranted to confirm the this conclusion.