Risultati per: Screening della retinopatia diabetica

Circulation, Volume 150, Issue Suppl_1, Page A4138273-A4138273, November 12, 2024. Background:Rheumatic heart disease (RHD) causes 305,000 premature annual deaths, and education is one of the strategies to diminish disease burden. International RHD foundations aim do provide preventive and control efforts for RHD. We aimed to assess the acceptability and gain of knowledge of a series of education flipcharts presented during screening programs in high-burden areas of Brazil.Methods:Four flipcharts (“Introduction to rheumatic fever (RF) and RHD”, “RHD and pregnancy”, “RHD and surgery” and “RHD community awareness”) were developed over 3 years and taught during 36 months to patients, community, health and education professionals in Minas Gerais state. Training included in-person interactions and virtual workshops. Pre and post-training questionnaires were applied through an online and printed surveys in 2021 and 2022, and post-education evaluations were conducted from January 2023 to April, 2024.Results:Flipchart training was successfully delivered to 112 education professionals, 574 health providers and 598 community members (N=1284): 899 (70%) were enrolled in primary care, and 1109 (86%) responded the surveys. Among respondents of the survey for health and education professionals (N=589), 240 (41%) had been educated about RHD in the previous year. 569 (96%) learned any new information; the content was all new for 21 (4%). Nearly all professionals reported that flipcharts could improve patients’ lives (571, 97%) and felt confident to use the tool with someone with no knowledge about RHD (533, 91%); 86% of the teachers said they would use flipcharts as educational tools. In the survey for community / schoolchildren (N=520) only 128 (25%) respondents had previous education on RHD, 510 (98%) reported that learned new information, and content was completely new for 242 (47%). A total of 430 (83%) individuals reported that they will discuss RHD with families and community. All qualitative written reports were positive. In 2021/2022, 218/485 (45%) health and education professionals responded the pre/post questionnaire. Knowledge about RHD increased after training: RF as the cause of RHD (56% vs 86%), use of Benzathine Penicillin G (50% vs 97%), frequency of antibiotic prophylaxis (32% vs 90%) and overall moderate or expert understanding of RF or RHD (30% vs 82%).Conclusion:Flipchart educational sessions about RHD had a very positive acceptability in high-risk Brazilian populations, with remarkable gain of knowledge for health professionals.

Circulation, Volume 150, Issue Suppl_1, Page A4144973-A4144973, November 12, 2024. Background:Cardiac calcium, which includes coronary and extra-coronary calcification, is often incidentally found in chest CT scans performed for various reasons. Despite its prognostic value, manual quantification of cardiac calcium in non-gated chest CT images is labor-intensive.Goals:This retrospective study aims to perform automatic quantification and scoring of cardiac calcium in non-contrast-enhanced chest CTs. The objective is to determine associations between automatic calcium scoring and outcomes such as all-cause mortality, non-fatal myocardial infarction (MI), and non-fatal stroke.Methods:We conducted a nationwide cohort study using the Taiwan National Health Insurance Research Database (NHIRD) from 2016 to 2022. Patients under 20 years old, with a diagnosis of malignancy, or with outcome events before the CT acquisition were excluded. HeaortaNet 1.0, a validated AI model, was used for cardiac calcium scoring. Comorbidities were determined using ICD diagnostic codes for ≥2 consecutive outpatient visits within the year before the index date. Outcomes were censored at the first occurrence of mortality or relevant ICD codes for MI or stroke.Results:The retrospective cohort included 279,415 patients (56.37% male, mean age 60.31±16.54). All-cause mortality occurred in 12.82% of patients within a 3-year follow-up. The 3-year incidence rates of non-fatal MI and non-fatal stroke were 0.86% and 2.07%, respectively. Multivariate-adjusted Cox hazard ratios (95% confidence intervals) for any composite outcome were 1.51 (1.46-1.57), 2.09 (2.01-2.17), 2.63 (2.53-2.74), and 3.37 (3.24-3.50) for cardiac calcium scores of 1-100, 101-400, 401-1000, and >1000, compared to a score of 0. Adjusted Cox hazard ratios for all-cause mortality were 1.62 (1.56-1.69), 2.29 (2.19-2.39), 2.91 (2.78-3.04), and 3.80 (3.64-3.96) for scores of 1-100, 101-400, 401-1000, and >1000, compared to a score of 0.Conclusion:AI-enabled opportunistic screening of non-contrast chest CT for cardiac calcium scoring is associated with all-cause mortality and cardiovascular events. This is the first large-scale cohort study to use an AI model for comprehensive cardiac calcium screening.

Circulation, Volume 150, Issue Suppl_1, Page A4147650-A4147650, November 12, 2024. Background:Invasive hemodynamics are the gold standard for diagnosis of heart failure with preserved ejection fraction (HFpEF). A novel, FDA-approved artificial intelligence (AI) technology that uses a single, 4-chamber transthoracic echocardiogram (TTE) image to screen patients for HFpEF shows promise as a non-invasive tool to assist in diagnosis. Development of right ventricular (RV) dysfunction is a sign of a more advanced HFpEF. Advanced RV hemodynamic parameters, beyond pulmonary arterial pressures (PAP), have not been well studied in HFpEF. We sought to correlate advanced RV hemodynamic parameters in patients screened for HFpEF with this AI screening tool.Method:We retrospectively evaluated two cohorts of patients with suspected HFpEF that underwent TTE and RHC at our institution. The most recent TTE for each patient was screened using the AI-based analysis tool and was reported as either “suggestive” or “non-suggestive” of HFpEF – labeled as “positive” or “negative,” respectively. Mean PAP, pulmonary vascular resistance (PVR), pulmonary artery pulsatility index (PAPI), RV cardiac power output (RV-CPO), RV myocardial performance score (RV-MPS), and right atrial pressure to pulmonary capillary wedge pressure ratio (RA:PCWP) were calculated using invasive hemodynamic parameters at rest, and exercise when available. RV-CPO was calculated as [(mean PAP-RAP) x cardiac output] /451, and RV-MPS was calculated as (RV-CPO x PAP)x1.5. Median values were calculated. AI positive and negative groups were compared using Student’s t-test.Results:A total of 47 patients (82% women, 79% Black, average EF 62%) were included, with 23 undergoing subsequent exercise RHC. There were 18 (38%) that screened positive for HFpEF, and 29 (62%) screened negative by TTE AI software. Positive patients had a significantly higher mean PAP (median 31 vs 23 mmHg, p=0.01), PVR (2.1 vs 1.3 WU, p=0.02), and RV-CPO (0.26 vs. 0.17, p=0.04) than patients who were screened negative. There were no significant differences in PAPI, RV-MPS, and RA:PCWP at rest. There were no significant differences in mean PAP, PVR, PAPI RV-CPO, RV-MPS, or RA:PCWP with exercise.Conclusion:Patients screened positive for HFpEF by a novel AI TTE software had significantly higher PAP and RV-CPO at rest, but no differences in PAPI, RV-MPS, or RA:PCWP ratio. This tool may help identify more advanced HFpEF.

Circulation, Volume 150, Issue Suppl_1, Page A4146283-A4146283, November 12, 2024. Objective:The incidence of cognitive decline following coronary artery bypass grafting (CABG) is well-documented, significantly impacting patient morbidity, mortality, and quality of life. We conducted a systematic review that examines cognitive outcomes in CABG randomized controlled trials (RCTs) to identify which cognitive assessments were used, their administration frequency, attrition rates, and their effectiveness in detecting perioperative cognitive changes in control groups.Methods:We conducted a search of MEDLINE, EMBASE, Cochrane Library, and PsycINFO for CABG RCTs that included cognitive assessments, from January 2005 to December 2023. Descriptive statistics were used to summarize the frequency, domains, and attrition rates of each cognitive task. For tasks assessed both pre- and post-operatively in at least three RCTs, control group scores and standard deviations were reported.Results:Out of 3337 screened studies, 2163 were CABG RCTs, and only 69 (3.2%) included cognitive evaluations (Figure 1). These trials involved 15,839 subjects (79% male, mean age 64.4, median follow-up time 90 days) and used 145 unique cognitive tasks. The Trailmaking Test Part B (40/69; 58.0%) and Part A (38/69; 55.0%) were the most frequently used. Only 7 tasks had means and standard deviations reported before and after surgery in more than three RCTs, and none detected significant pre- to post-operative changes. Attrition rates averaged 19.3%, with a wide range from 0% to 62%. Figure 2 demonstrates the decline in cognitive assessments in CABG trials over the years, with a sharp decline after 2014. Trials that assessed cogntion after 2014 tended to favor screening tasks (MMSE/MoCA) alone.Conclusion:Cognitive assessments are infrequent in CABG trials, and existing tests fail to consistently detect cognitive changes. To effectively evaluate and address cognitive impact after CABG, new assessment strategies that are resilient to attrition and practical for use in diverse trial settings are needed.

Circulation, Volume 150, Issue Suppl_1, Page A4112869-A4112869, November 12, 2024. Introduction:Sitosterolemia, a hereditary disorder marked by elevated plant sterol levels, presents diagnostic challenges due to its similarity to other lipid disorders. The development of the Sitosterolemia Risk Prediction Scale (SRPS) aims to address this by synthesising genetic, clinical, and dietary data into a coherent risk assessment model.Research Question:We propose that a structured risk scale, integrating diverse factors known to affect sitosterolemia, can significantly improve the accuracy of predicting the disorder. The SRPS is hypothesised to facilitate early detection and inform targeted interventions.Aim:The primary aim is to conceptualise and outline the SRPS, which categorises individuals into risk categories based on a point system reflecting genetic predispositions, clinical symptoms, dietary habits, and response to treatments. This scale seeks to enhance the clinical identification of sitosterolemia, promoting timely and personalised management strategies.Methods:A detailed table was generated to present the SRPS, categorising risk factors into genetic, clinical, dietary, and response to treatment. This innovative method allowed for the efficient synthesis and visualisation of complex data.Results:The SRPS table methodically organizes risk factors into low (0-2 points), moderate (3-5 points), and high (6+ points) categories. This stratification guides further diagnostic actions, ranging from exploring alternative causes of hyperlipidemia to necessitating comprehensive genetic and lipid analyses.Conclusion:The SRPS represents an innovative framework for assessing sitosterolemia risk, highlighting the potential benefits of integrating genetic, clinical, and dietary information. It further underscores the importance of a multifactorial approach in the early detection and management of sitosterolemia.

Circulation, Volume 150, Issue Suppl_1, Page A4141112-A4141112, November 12, 2024. Background:It is estimated that Peripheral Artery Disease (PAD) affects between 8.5 and 12 million Americans and its prevalence among adults over 40 years of age is increasing. PAD disproportionately affects Black Americans who, at any age, are twice as likely to experience PAD as their white counterparts but are less likely to be screened and benefit from early diagnosis and treatment.Research Questions/Hypothesis:Despite the high prevalence of PAD and the importance of early intervention, screening for PAD remains limited and/or underutilized particularly in primary care settings where most cases of PAD can be identified. This study sought to understand provider knowledge of PAD, associated risk factors, treatment, understanding of disparities in PAD and barriers and facilitators of PAD screening. It was hypothesized that limited resources, lack of awareness on the part of providers and patients, limitations of training in vascular medicine, and other issues are contributing to PAD morbidity and mortality, particularly among Black and Hispanic populations.Methods:Because no current PAD survey was found in the literature, a survey for providers to determine their knowledge, attitude, and beliefs about PAD and the importance and process of PAD screening for patients at risk was developed. The survey was administered to CommonSpirit Health providers in Sacramento, CA between December 2023- January 2024. Specialties engaged in the survey (N=145) included primary care, endocrine, nephrology, cardiology and podiatry providers.Results:Response rate was 21%. Of those responding, primary care was the specialty most represented(69%). A total of 65% of respondents identified medical treatment of risk factors as the primary way to treat PAD, 32% rated their knowledge of risk reduction therapies in PAD as below average, and 88% of respondents were either somewhat or not familiar with racial disparities in PAD. 24% of respondents identified the ‘lack of knowledge of PAD management guidelines’ as the most important barrier to their patients with PAD not receiving risk reduction therapies.Conclusions:Initial survey of providers identifies lack of knowledge as a key indicator of PAD screening practices, including knowledge on racial disparities in PAD. These identified gaps can inform targeted interventions to improve screening, early detection and treatment of PAD.

Circulation, Volume 150, Issue Suppl_1, Page A4147292-A4147292, November 12, 2024. Background:Tissue hypoxia and chronic anemia associated with sickle cell disease (SCD) leads to structural and physiological alterations in the heart. Early detection of heart failure (HF) in patients with SCD can assist with timely interventions, but current methods (e.g., echocardiogram and heart MRI) are not easily accessible in resource-deprived settings. The integration of artificial intelligence (AI)-powered tools utilizing low-cost ECG data to increase the power to detect more patients eligible for early treatment, thus improving patient outcomes, and needs to be validated.Hypothesis:We hypothesize that ECG-AI models developed to detect incident HF in the general population can detect HF in SCD patients.Methods/Approach:We previously developed an ECG-AI model employing convolutional neural networks to classify patients with HF using a large ECG-repository at Wake Forest Baptist Health (WFBH). This model was developed using 1,078,198 digital ECGs from 165,243 patients, 73% White, 19% Black, and 52% female individuals, with a mean age (SD) of 58 (15) years. The hold-out AUC of this previous model in distinguishing ECGs of HF patients from controls was 0.87. In this study, we externally validated this ECG-AI model using SCD patients’ data from the University of Tennessee Health Science Center (UTHSC). Additionally, a logistic regression (LR) model was constructed in the UTHSC cohort by incorporating other simple demographic variables with the outcome of ECG-AI model.Results/Data:The UTHSC external validation cohort included data from 2,107 SCD patients (188 HF and 1,919 SCD patients with no HF), 98% were Black, 72% were female, with a mean age of 39 (14) years. Despite demographic differences between the validation (more Blacks) and derivation cohorts (lower age), our ECG-AI model accurately identified HF with an AUC of 0.80 (0.77-0.82) in the UTHSC SCD cohort. When incorporating ECG-AI outcome (an ECG-based risk value between 0 and 1), age, sex, and race in a LR model, the AUC significantly improved (DeLong Test, p

Circulation, Volume 150, Issue Suppl_1, Page A4137770-A4137770, November 12, 2024. Background:Metabolic syndrome is a cluster of conditions that increase the risk of heart disease and diabetes. Early identification and management are crucial, particularly in economically challenged regions where access to healthcare may be limited.Research Questions/Hypothesis:User-friendly self-report data accurately predict metabolic outcomes.Aims:To develop and validate nomograms for individualized estimation of metabolic syndrome risk.Methods:Data from 521 college students (60.1% aged 17-20 years; 68.7% female; 28.0% white) were collected in 2022/2023 from two Brazilian cities. These cities are located in the country’s poorest states, with Gini indices of 0.56 and 0.43. The potential predictors include demographic and economic variables, school-related factors, behaviors, and body weight. Based on predictors for abdominal obesity identified through multilevel logistic regression, we created a nomogram model. We performed the Hosmer-Lemeshow test to assess model calibration and used a bootstrapping approach (B = 150) for internal validation. To evaluate external validity, we assessed metabolic syndrome in a subset of 375 students. The area under the receiver operating characteristic curve (AUROC), with a threshold of 0.70, was used to evaluate the model’s discrimination accuracy.Results:We identified 114 (23.0%) college students who were abdominally obese. We found ten variables associated with the primary outcome: age, biological sex, physical education facilities, enrollment in sports competition (during elementary school); grade retention, preferred subject, physical education classes per week; enrollment in sports training (during secondary school); adherence of 24-hour movement behaviors and body weight. The proposed nomogram showed acceptable performance in the AUROC (0.94 [95% CI: 0.92-0.96). The calibration assessment indicated reasonable consistency of our model (p > 0.05). In the internal validation, we observed a decreased predictive capability (AUROC = 0.86).Conclusion:The 24h-MESYN risk score offers an effective self-screening tool for college students from diverse racial and ethnic backgrounds in economically challenged regions to assess their risk of developing metabolic syndrome.

Circulation, Volume 150, Issue Suppl_1, Page A4145524-A4145524, November 12, 2024. Introduction:White-coat hypertension (WCH) and masked hypertension (MH) complicate accurate blood pressure (BP) monitoring. While ambulatory BP monitoring (ABPM) is effective, its high cost and limited availability are significant barriers.Hypothesis:We hypothesized that a machine learning (ML) model using clinical data from a single outpatient visit could accurately predict WCH and MH.Aims:This study aimed to develop and validate ML-based prediction models for WCH and MH using accessible clinical data to improve diagnostic efficiency and accessibility.Methods:We enrolled patients from two hypertension cohorts, after excluding those with incomplete data. Patients were classified by office BP and ABPM readings per American Heart Association guidelines. ML models, including Multi-layer Perceptron （MLP）, Support Vector Machine (SVM), and Tabular Prior-Data Fitted Network (Tab-PFN), were developed. Input parameters included demographic data (age, gender, height, weight, smoker), and office BP (OBP) and heart rate measurements. Principal Component Analysis (PCA), kernel PCA (kPCA), or t-distributed stochastic neighbor embedding (t-SNE) were used to improve class separability.Results:The study population comprised 1481 participants with a mean age of 47.6 years (SD 13.6), 65% of whom were male and 20.1% were smokers. OBP measurements showed a mean systolic BP (SBP) of 128.7 mmHg (SD 15.4) and a mean diastolic BP (DBP) of 84.2 mmHg (SD 11.6). ABPM showed a mean 24-hour systolic BP of 122.5 mmHg (SD 11.8) and diastolic BP of 79.3 mmHg (SD 10.1). The inclusion of demographic and OBP data, along with advanced resampling and dimensionality reduction techniques, significantly improved the model’s predictive ability. The final TabPFN model achieved the best performance with recall, precision, F1 score, and accuracy of 0.747, 0.931, 0.829, and 0.807 for WCH, and 0.713, 0.954, 0.816, and 0.907 for MH.Conclusion:Our ML-based model effectively predicts WCH and MH using accessible clinical data, offering a cost-effective alternative before applying ABPM.

Circulation, Volume 150, Issue Suppl_1, Page A4143847-A4143847, November 12, 2024. Introduction:Our previous studies have shown that sustained activation of the DNA damage response (DDR) in cardiomyocytes leads to p53/p21 activation and cardiac dysfunction. Although the DDR generally involves molecules in DNA replication and repair pathways, the non-proliferative nature of cardiomyocytes suggests a cardio-specific DDR mechanism. However, our understanding of DDR in cardiomyocytes remains limited. Here, we aim to use CRISPR interference (CRISPRi) knockdown screens to identify genes critically involved in DDR regulation in human cardiomyocytes. We hypothesize that identifying these gene clusters may allow us to develop methods to prevent cardiac dysfunction by suppressing DDR in cardiomyocytes.Methods and Results:We established a human iPS cell line stably expressing dCas9-KRAB, which allows CRISPRi-mediated gene knockdown, and differentiated the cells into cardiomyocytes. The resulting human iPS cell-derived cardiomyocytes (hiPSCMs) showed the achievement of approximately 80% knockdown efficiency after gRNA transfection. We stimulated the hiPSCMs with H2O2and quantitatively evaluated the expression levels of the DDR markers γH2AX and p21 by immunostaining using the Operetta®high content imaging system. The DDR markers showed a significant concentration-dependent increase in response to H2O2administration. For arrayed CRISPRi screening, we constructed a gRNA library targeting 437 DDR-related genes. Using this library, we knocked down each DDR-related gene in hiPSCMs followed by H2O2stimulation. We quantified the expression levels of DDR markers by calculating the fluorescence intensity ratios relative to control after gene knockdown, and standardized them to calculate Z scores for all 437 genes. The screening successfully revealed the differential impact of each gene knockdown on γH2AX and p21 expression. We identified 71 genes that significantly affected their expression (Z-score < -1 or > 1). Mapping these genes to DDR pathways highlighted the differential impact of gene knockdown within the same pathway, and stratified their importance in cardiomyocytes.Conclusions:Arrayed CRISPR screening using hiPSCMs revealed differential functional significance of DDR-related genes in cardiomyocytes, identifying 71 genes of particularly significant importance. These findings provide a critical understanding of the cardio-specific DDR pathway and important clues for establishing an appropriate method to suppress DDR in the failing heart.

Circulation, Volume 150, Issue Suppl_1, Page A4141975-A4141975, November 12, 2024. Background:Refugee populations often experience high rates of cardiovascular disease (CVD). Factors such as significant physiological stress, trauma, limited access to healthcare, substance abuse, and poor lifestyle choices contribute to disease progression and an increased incidence of cardiovascular events. We sought to evaluate the feasibility of using wearables to obtain high-fidelity ECG signals for CVD screening in refugees in Jordan.Methods:This observational cross-sectional study involved outpatients at one of four regional United Nations’ primary care clinics for Palestinian refugee in Jordan. Research assistants collected health histories from consented patients and recorded a 30-second, 6-lead ECG using a handheld, Bluetooth-enabled, wearable device (KardiaMobile 6L, AliveCor Inc., Mountain View, CA, USA). The digital ECG signals were stored on the Bluetooth-synced mobile device and then exported to a cloud server for offline analysis. The raw ECG recordings were preprocessed, and a single median beat was calculated per lead. Waveforms were segmented, and duration and amplitude measures were determined using a previously validated custom algorithm (University of Pittsburgh, PA, USA). All ECG recordings were reviewed by an independent physician.Result:The sample included 31 patients (age 52±13, 64% Females). Risk factors were prevalent in this group, including hypertension (74%), high cholesterol (65%), diabetes (64%), in-camp living (33%), and smoking (30%). Figure 1 shows the population-averaged median beat with 99% CI distribution of this sample. Mean QRS duration was 95±23 ms (range 53−150) and QTc interval was 403±53 (range 267−513). Most patients were in normal sinus rhythm (84%), and remaining patients were in atrial fibrillation or flutter (16%). Other clinically significant abnormalities included non-specific ST-T changes (9.7%), left bundle branch block (1.6%), and LVH with left ventricular strain (1.6%).Conclusion:This pilot study demonstrated that it is feasible to obtain high fidelity ECG signals using wearables to screen for CVD in refugees. Such affordable, noninvasive, point-of-care screening tools could enable early diagnosis and treatment in these patients.

Circulation, Volume 150, Issue Suppl_1, Page A4137945-A4137945, November 12, 2024. Background:Juvenile sudden cardiac death (SCD) has high impact on the family and society of the victim. While SCD screening programmes are effective in athletes, most (70-80%) young non-athletes individuals are not routinely screened.Research question:We hypothesized that a low-cost screening program may early identify subjects at risk of juvenile SCD, even in non-athletes.Goals:To evaluate the prevalence of SCD-related abnormal findings and, ultimately, to test the effectiveness of a screening programme in high schools.Methods:Between April 2023 and June 2024, high school individuals were enrolled in a screening programme in Tuscany (Pisa, Lucca and Livorno), based on a questionnaire investigating family history of juvenile SCD or diseases predisposing to SCD and symptoms (syncope, palpitations, chest pain), and digitally recorded electrocardiograms (ECGs). In case of abnormal findings, second-line investigations locally (echocardiography, Holter ECG monitoring and/or exercise testing) or third-line investigations at Fondazione Monasterio, Pisa, Italy (cardiac MRI, genetics or electrophysiological testing) were planned. Only preliminary results of the first-line screening are hereby reported.Results:We have currently enrolled 872 individuals (age 17.1±1.8 years, 481 [55%] males, 288 [33%] smokers, 102 [11.7%] recreational drugs users, and 645 [74%] non-competitive athletes). At questionnaires, 56 individuals (6.4%) had a family history of SCD, 32 (3.7%) a first-degree relative with cardiomyopathy, and 13 (1.5%) with channelopathy. As for symptoms, 21 participants (2.4%) reported chest pain or 26 (3%) syncope during exertion, while 90 (10.3%) paroxysmal palpitations. At ECG, we found 2 cases (0.2%) with a type-2 Brugada pattern, 1 female case (0.1%) with prolonged QTc interval (QTc 480 ms), 20 cases (2.3%) with V1-V3 T wave inversion (age > 16 years), 18 cases (2%) of left ventricular hypertrophy (non-athletes), and 4 cases (0.5%) with atypical ventricular ectopy. After the first-line screening, 61 (7%) and 10 (1.2%) individuals were referred to second and third-line investigations, which are currently ongoing.Conclusions:We hereby propose a screening model in high schools that includes specific health questionnaires and digitally recorded ECGs. From preliminary analyses, this approach seems sensitive enough to be tested as a model to favour the early diagnosis of diseased conditions associated with juvenile SCD in the general population.

Circulation, Volume 150, Issue Suppl_1, Page A4140494-A4140494, November 12, 2024. Background:Primary care after pregnancy is recommended, especially for individuals with recent adverse pregnancy outcomes (APOs, such as preeclampsia or gestational diabetes), who are at increased risk for future heart disease. Health-related social needs (HRSNs) are recognized barriers to care, yet their pregnancy-related prevalence and associations with care are unknown. We sought to (1) describe the pregnancy-related prevalence of HRSNs, and (2) assess associations between pregnancy-related HRSNs and subsequent linkage to primary care.Methods:We analyzed electronic health record data for individuals with prenatal care and delivery (2018-2021) at our urban safety-net hospital. HRSNs were assessed via a routine screener, and we summarized individual responses during pregnancy through 6 weeks post partum as: any positive, all negative, or never screened. Postpartum linkage to primary care was defined as a completed primary care visit after 6 weeks through 1 year post partum. We analyzed the prevalence of HRSNs and their associations with linkage to primary care, using adjusted log-linked binomial regression models. In stratified models we assessed for effect modification by APO history and other variables.Results:Of 4941 individuals in our sample, 53% identified as Black non-Hispanic and 21% as Hispanic, 68% were publicly insured, and 93% completed ≥1 HRSN screening. Nearly 1 in 4 screened positive for any HRSN, most often food insecurity (14%) or housing instability (12%), and 53% linked to primary care. Compared with those who screened negative for all HRSNs (n=3491), linkage to primary care was similar among those who screened positive for any HRSNs (n=1079; adjusted risk ratio, aRR 1.04, 95% confidence interval, CI: 0.98-1.10) and lower among those never screened (n=371; aRR 0.77, 95% CI: 0.68-0.86). We found no evidence of effect modification by APO history, race/ethnicity, insurance, language, or Covid-19 pandemic exposure.Conclusions:In this diverse postpartum sample, we identified a 24% prevalence of pregnancy-related HRSNs and 53% subsequent linkage to primary care. Linkage to primary care was not associated with HRSN screening result (positive versus negative) but was significantly negatively associated with being missed by HRSN screening. Further research is needed to better understand HRSN screening practices and who is missed by screening, and to identify modifiable barriers to postpartum primary care especially after APOs.

Circulation, Volume 150, Issue Suppl_1, Page A4135476-A4135476, November 12, 2024. Purpose:When the heart is exposed to stresses such as myocardial infarction or hypertension, it undergoes compensatory hypertrophy in response. However, continuation of the stress causes this compensatory mechanism to fail, and eventually systolic dysfunction or decompensated heart failure occur. As the hypertrophy of individual cardiomyocytes has been observed in this process, controlling cardiomyocyte hypertrophy is a potential target the prevention and treatment of heart failure. In this study, we constructed a high throughput screening (HTS) assay using cardiomyocyte hypertrophy as an index parameter. Compounds that inhibit cardiomyocyte hypertrophy were selected from our low molecular compound library.Methods and Results:In the primary screening, cultured rat primary cardiomyocytes were treated with each compound at a final concentration of 1 µM and then stimulated with 30 µM phenylephrine (PE) for 48 hours. These cells were subjected to fluorescent immunostaining with α-actinin, and cardiomyocyte area was measured using an ArrayScan™ system. The hypertrophy inhibition rate (%) of each compound was calculated as [(PE(+) – compound) / (PE(+) – PE(-))] × 100. The compounds with a hypertrophy inhibition rate greater than 50% and less than 150% were selected as hit compounds. In the secondary screening, these hit compounds were evaluated based on the dose-dependency of cardiomyocyte hypertrophy inhibition and the inhibition of the mRNA levels of the cardiac hypertrophy response genes ANF and BNP using real-time PCR. From the 269 low molecular-weight compounds in the original compound library, eight were selected through the primary and secondary screenings. Among them, we focused on Reference Number 409 (RFN-409). Western blotting indicated that RFN-409 inhibited PE-induced p38 activation. Next, we investigated the effect of RFN-409 on heart failure. Eight-week-old male C57 BL/6J mice were subjected to transverse aortic constriction (TAC) surgery and then randomly assigned to intraperitoneal treatment with RFN-409 (3, 10 mg/kg) or vehicle for eight weeks. RFN-409 at 10 mg/kg significantly prevented TAC-induced increase in left ventricular posterior wall thickness and decrease in left ventricular fractional shortening.Discussion:RFN-409 suppressed TAC-induced development of heart failure, at least partially by inhibiting p38 activity. These findings suggest that RFN-409 may be an effective agent for heart failure therapy.

Circulation, Volume 150, Issue Suppl_1, Page A4131622-A4131622, November 12, 2024. Introduction:Chronic liver disease affects more than 1.5 billion adults worldwide, but the majority of cases are asymptomatic and undiagnosed. Echocardiography is broadly performed and visualizes the liver; however, this information is not diagnostically leveraged.Hypothesis and Aims:We hypothesized that a deep-learning algorithm can detect chronic liver diseases using subcostal echocardiography images that contains hepatic tissue. To develop and evaluate a deep learning algorithm on subcostal echocardiography videos to enable opportunistic screening for chronic liver disease.Methods:We identified adult patients who received echocardiography and abdominal imaging (either abdominal ultrasound or abdominal magnetic resonance imaging) with ≤30 days between tests. A convolutional neural network pipeline was developed to predict the presence of cirrhosis or steatotic liver disease (SLD) using echocardiogram images. The model performance was evaluated in a held-out test dataset, dataset in which diagnosis was made by magnetic resonance imaging, and external dataset.Results:A total of 2,083,932 echocardiography videos (51,608 studies) from Cedars-Sinai Medical Center (CSMC) were used to develop EchoNet-Liver, an automated pipeline that identifies high quality subcostal images from echocardiogram studies and detects presence of cirrhosis or SLD. In a total of 11,419 quality-controlled subcostal videos from 4,849 patients, a chronic liver disease detection model was able to detect the presence of cirrhosis with an AUC of 0.837 (0.789 – 0.880) and SLD with an AUC of 0.799 (0.758 – 0.837). In a separate test cohort with paired abdominal MRIs, cirrhosis was detected with an AUC of 0.726 (0.659-0.790) compared to MR elastography and SLD was detected with an AUC of 0.704 (0.689-0.718). In the external test cohort of 66 patients (n = 130 videos), the model detected cirrhosis with an AUC of 0.830 (0.738 – 0.909) and SLD with an AUC of 0.768 (0.652 – 0.875).Conclusions:Deep learning assessment of clinically indicated echocardiography enables opportunistic screening of SLD and cirrhosis. Application of this algorithm may identify patients who may benefit from further diagnostic testing and treatment for hepatic disease.

Circulation, Volume 150, Issue Suppl_1, Page A4141994-A4141994, November 12, 2024. Background:Screening trials for atrial fibrillation (AF) have produced mixed results; however, it is unclear if there is a subset of individuals for whom screening would be effective. Identifying such a subgroup would support targeted screening.Methods:We conducted a secondary analysis of VITAL-AF (NCT03515057), a randomized trial of one-time, single-lead ECG screening during primary care visits. We tested two approaches to identify a subgroup that would benefit from screening (i.e., heterogenous screening effects). First, we use a potential outcomes framework to develop an effect-based model. Specifically, we predicted the likelihood of AF diagnosis under both screening and usual care conditions using LASSO, a penalized regression method. The difference between these probabilities was the predicted screening effect. Second, we used the CHARGE-AF score, a validated AF risk model. We used interaction testing to determine if the observed diagnosis rates in the screening and control arms were statistically different when stratified by decile of the predicted screening effect and predicted AF risk.Results:Baseline characteristics were similar between the screening (n=15187) and usual care (n=15078) groups (mean age 74 years, 59% female). On average, screening did not significantly increase the AF diagnosis rate (2.55 vs. 2.30 per 100 person-years, rate difference 0.24, 95%CI -0.18 to 0.67). Patients in the highest decile of predicted screening efficacy (n=3026, 10%) experienced a large and statistically significant increase in AF diagnosis rates due to screening (6.5 vs. 3.06 per 100 person-years, rate difference 3.45, 95%CI 1.62 to 5.28; interaction p-value 0.038) (Figure 1). In this group, the mean age was 84 years and 68% were female. Participants in the highest decile of AF risk using the CHARGE-AF score did not have a statistically significant increase in AF diagnosis rates due to screening (Figure 2). Predicted screening effectiveness and predicted AF risk were poorly correlated (Spearman coefficient 0.13).Conclusions:One-time screening may increase AF diagnoses in a subgroup of older adults with the largest predicted screening effect. In contrast, predicted AF risk was a poor proxy for predicted screening efficacy. These data caution against the assumption that high AF risk is necessarily correlated with high screening efficacy. Prospective studies are needed to validate whether AF screening is effective in the subgroup identified in this study.