Risultati per: Nuovo test per lo screening del cancro alla prostata

Circulation, Volume 150, Issue Suppl_1, Page A4145321-A4145321, November 12, 2024. Introduction:Pulmonary dysfunction is a risk factor for increased mortality in patients with acute coronary syndromes (ACS). The purpose of this study was to investigate the association between thrombogenicity and pulmonary function test abnormalities in patients with ACS.Methods:We included ACS patients who underwent successful percutaneous coronary intervention (PCI). Pulmonary function was assessed by spirometry based on the forced expiratory volume in one second (FEV1%pred) after PCI. Thrombogenicity was evaluated with the thromboelastography and conventional hemostatic measures.Results:Among 323 patients, 90 patients (28.8%) had pulmonary dysfunction (moderate or severe spirometric abnormality, FEV1%pred

Circulation, Volume 150, Issue Suppl_1, Page A4143506-A4143506, November 12, 2024. Background:Anatomic burden of coronary artery disease (CAD) has been considered a consistent prognostic marker. Inflammation also increases the cardiovascular risk and plays a significant role in the evolution of atherosclerosis. The progression of CAD impacts the responses to exercise, reducing functional capacity. Despite this knowledge, the specific interplay between inflammation and atherosclerotic burden in influencing submaximal exercise capacity, particularly oxygen uptake (VO2) kinetics, remains underexplored in CAD. This study aims to investigate how these factors correlate with VO2on-kinetics in the Six-minute Walk Test (6MWT) in patients with CAD.METHODS:Patients with obstructive CAD, confirmed by coronary angiography, underwent a 6MWT using a mobile telemetric cardiopulmonary monitoring to assess functional capacity and the VO2on-kinetics through the mean response time corrected by work (wMRT). Inflammatory markers were analyzed by dosage of high-sensitivity C-reactive protein, interferon-gama, tumor necrosis factor alpha and interleukins (IL), IL-6, IL-8 and IL-10. Coronary atherosclerotic burden was evaluated by the Grading Scale for Anatomic Burden of Disease from COURAGE Trial. Correlation analyses were performed according to the symmetric distribution of data, using Pearson’s (r) or Spearman’s rank correlation coefficients(rs).RESULTS:A total of thirty-four patients aged between 60.3±8.0 years were enrolled, presenting body mass index of 26.0±3.7kg/cm2, left ventricular ejection fraction of 0.50±0.14, walking distance of 443±66m, VO2at steady-state (VO2SS) of 896±240ml/min and wMRT of 1.64×10-3± 1.00×10-3min2/ml. Although correlated with distance and VO2SS(r=-0.472;p=0.002 and r=-0.434;p=0.015, respectively), atherosclerotic burden was not associated with wMRT (p=0.17). High-sensitivity C-reactive protein and IL-8 were negatively associated with both distance and VO2SS(rs=-0.428;p=0.001/ rs=-0.543;p=0.001 and rs=-0.438;p=0.014/ rs=-0.407;p=0.019) and positively correlated with wMRT (rs=0.412;p=0.022/ rs=0.505;p=0.003).CONCLUSION:In contrast to anatomic burden, inflammatory markers were associated with both walking intensity and VO2kinetics. Therefore, inflammation may be more crucial to exercise response mechanisms than coronary stenosis, suggesting a paradigm shift in our understanding of clinical repercussions of obstructive CAD. Actions able to attenuate the inflammatory profile may improve exercise capacity and prognosis.

Circulation, Volume 150, Issue Suppl_1, Page A4140796-A4140796, November 12, 2024. BACKGROUND:Coronary artery spasm (CAS) is a cause of variant angina and is typically diagnosed by intracoronary acetylcholine (ACH) provocation test. Investigations regarding association between the severity of coronary artery stenosis and the minimum responsive dose of ACH required for provocation is limited.METHODS:In this study, 3,915 patients who underwent the acetylcholine (ACH) provocation test and showed CAS between October 2004 and December 2022 were enrolled. Significant CAS was defined as temporary narrowing of ≥70% during the ACH test. Patients were divided into three groups, based on the minimum responsive dose of ACH: A1 group (20ug, n=227), A2 group (50ug, n=1,366) and A3 group (100ug, n=2,322).RESULTS:In patients who were documented with positive intracoronary ACH provocation test, 5.8% responded at the lowest dose (20ug), 34.9% responded at the medium doses (50ug) and 59.3% responded only at the highest dose of ACH (100ug). The baseline characteristics of the patients among the 3 groups were similar, demonstrating no significant difference in the prevalence of hypertension, diabetes mellitus, and dyslipidemia. However, patients who responded at lower dose showed higher proportion of smokers (A1 37.9% vs. A2 35.7% vs. A3 31.0%, p=0.004). A1 group demonstrated the highest proportion of severe stenosis (63.0%), followed by A2 group (60.1%) and A3 group (47.4%) (Figure 1).CONCLUSION:In patients with chest pain with positive intracoronary ACH provocation test, severe stenotic lesions were found to be more frequent and more susceptible in patients who responded at lower doses of ACH.

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 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 A4142502-A4142502, November 12, 2024. Background:AI-ECG is a cost-effective tool for left ventricular dysfunction (LVD) screening. However, its cost-effectiveness for other forms of structural heart disease (SHD) is unknown. While AI-ECG is inexpensive, a drawback is low positive predictive value (PPV), which leads to high costs from unnecessary follow-up tests. Therefore, strategies to improve the yield of AI-ECG-based screening are needed.Aim:To evaluate the cost savings of a stepwise approach to SHD screening with AI-ECG followed by POCUS compared to AI-ECG alone.Methods:286 adult outpatients undergoing AI-ECG were selected at random. Participants received same-day POCUS and had a recent TTE (our gold standard for SHD). We evaluated four SHDs: aortic stenosis (AS), cardiac amyloidosis (CA), HCM, and LVD. The costs of AI-ECG ($75) and TTE ($1,305) were obtained from Healthcare Bluebook. The cost of POCUS ($100) was estimated independently. Cost savings were analyzed for simultaneous screening for all forms of SHD and screening for individual SHDs.Results:AI-ECG identified potential SHD in 125 patients, but only 39 were true positives by TTE (31% PPV). In AI-ECG positive patients, POCUS demonstrated findings of SHD in 52/125. Compared to TTE, this stepwise approach yielded 32 true positives and 20 false positives (62% PPV). The cost per patient diagnosed with SHD was $4,733 with AI-ECG alone but decreased to $3,182 with stepwise screening (33% cost savings). Screening for individual SHDs resulted in cost reduction from $18,724 to $6,315 (66% savings) for AS, $21,023 to $12,230 (42% savings) for CA, $9,883 to $6,175 (38% savings) for HCM, and $4,019 to $3,582 (11% savings) for LVD.Conclusions:Stepwise screening for SHD with AI-ECG followed by POCUS significantly reduces costs compared to AI-ECG alone. We also suggest a model for parallel screening for multiple SHDs, which is likely more cost-effective than screening for individual SHDs.

Circulation, Volume 150, Issue Suppl_1, Page A4117646-A4117646, November 12, 2024. Introduction:The HeartMate 3 (HM3) LVAD, was shown to have a higher survival free of hemocompatibility related adverse events (HRAE) compared to its predecessors (HM2, HVAD). Superior HM3 outcomes are attributed to wide blood flow pathways coupled with frictionless movement and intrinsic pulsatility, reducing shear stress and blood stasis. It is unknown if improved hemocompatibility can withstand pump restart after prolonged shutdown. We herein report a case of HM3 pump stoppage without subsequent HRAE.Case Presentation:A 41-year-old male underwent HVAD implant in 2019 for advanced non-ischemic cardiomyopathy. This was exchanged to HM3 for recurrent neurological events despite therapeutic anticoagulation. Ten months after exchange, he awakened one morning to find his LVAD had been off for an unknown period but had not heard any device alarms (85dB if on battery power, 165dB if on wall power). Since he felt well he changed to battery power resulting in immediate pump restart. Log file analysis showed pump stoppage 2 am – 10 am, without preceding low flow alarms or power elevations.Management and Outcomes:In the ER INR was 1.5 (2.8 one week prior) and systemic heparin was started. Evaluation included: 1) CT brain without acute infarcts 2) echocardiogram without intracardiac thrombus 3) CT Angiography with patency of the inflow cannula and outflow graft 4) stable serial LDH measurements. The controller was exchanged, and analysis noted normal function. 1-year later the patient is maintained on warfarin and aspirin 325mg without further HRAE. Given the patient’s neurologic history and pump stoppage event, we did not invoke ARIES trial guidance and thus continued aspirin.Conclusion:Pump stoppage occurs when there is complete battery depletion, disconnection of both power leads, or the percutaneous lead from system controller. Our case is unique in that the duration of pump shutdown was 8 hours and INR subtherapeutic, without HRAE in the background of neurologic events on HVAD support. It has been previously reported that complete outflow graft thrombosis can occur shortly after LVAD decommissioning. The HM3 User Manual recommends restarting the pump immediately if off for a few minutes and using clinical judgment for longer durations due to increased risk for thromboembolic events. Our case adds to the paucity of existing data on improved hemocompatibility of the HM3 during rare circumstances of the ultimate test in hemocompatibility: complete pump shut down.

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 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 A4144283-A4144283, November 12, 2024. Introduction:Pulmonary arterial hypertension (PAH) remains an underrecognized, fatal disease. Limited awareness, non-specific symptoms, and late referral to accredited PH centers all contribute to an overall poor prognosis. The previously validated Virtual Echocardiography Screening Tool (VEST) uses 3 routine transthoracic echocardiogram (TTE) parameters (left atrial size, transmitral E:e’ and systolic interventricular septal flattening) to recognize a high PAH likelihood. A positive VEST score has been shown to have 80% sensitivity and 76% specificity for PAH hemodynamics, while a VEST score of +3 has 92.7% specificity for PAH hemodynamics with a positive predictive value of 88.0%.Aim:We aimed to implement a novel algorithm via our electronic medical record (EMR) as an automated VEST calculator to identify patients with a high likelihood of PAH.Methods:An automated EMR VEST calculator was applied retrospectively to 4,952 patients who underwent TTE with TR velocity >/= 2.9 m/s at an accredited PH center from 12/2021-8/2023. Automated EMR VEST scores were validated by comparison to 60 manually scored echocardiograms. Those with VEST score of +3 (highest risk for PAH) underwent chart review to identify whether they were seen by a PH specialist.Results:There was 100% correlation between the automated EMR VEST scores and the manual results.Of the 4,952 patients, 1,655 had a positive automated EMR VEST score, and 355 had a score of +3, predicting the highest likelihood of PAH and warranting urgent referral to an accredited PH center. Of those patients with a +3 score, 103 (29.0%) were never seen by a PH specialist (Fig 1).Conclusion:VEST is a validated, noninvasive and accessible screening tool for identification of patients with a high likelihood of PAH likely to benefit from early referral to a PH center. We present a novel, accurate, and automated EMR algorithm for determination of the VEST score to prompt urgent referral for PH expert evaluation and timely initiation of complex medical therapies. These findings highlight the potential of future artificial intelligence and machine-learning applications for improved recognition of life-threatening PAH.

Circulation, Volume 150, Issue Suppl_1, Page A4137986-A4137986, November 12, 2024. Background:Clinical trial screening is labor-intensive, time-consuming, and error prone. We have developed RECTIFIER, an AI-based clinical trial screening tool, to enhance the efficiency and accuracy of patient recruitment. This study aims to evaluate RECTIFIER’s effectiveness compared to manual screening in a randomized implementation study.Methods:This study was designed as an implementation study as part of an active heart failure trial named COPILOT-HF (NCT05734690). Potential eligible patients were identified via a structured electronic medical record query and randomized to be screened for clinical trial eligibility either by RECTIFIER or manually by clinical staff. The outcome measures included the number of patients contacted, and the number of patients reached for clinical trial enrollment. Data was collected over a period of 3 months.Results:A total of 3834 patients were included in the study, with 1919 patients randomized to the RECTIFIER group and 1915 patients to the manual screening group (Figure). Study staff could manually screen only 1367 patients at the end of the 3-month period. RECTIFIER identified more eligible patients compared to manual screening (833[43.4%] vs. 284[14.8%], p

Circulation, Volume 150, Issue Suppl_1, Page A4140642-A4140642, November 12, 2024. Background:The diagnosis of VVS largely relies on clinical history and simple diagnostic tools (e.g., electrocardiogram) to rule out dangerous differential diagnoses. However, using the head-up tilt test (HUTT) has become controversial among clinicians. This retrospective study aims to evaluate whether the prodromal symptoms experienced during HUTT are consistent with those experienced during spontaneous syncope.Methods:This study utilized data from the HUTT registry at the Syncope Unit of the tertiary Heart Center, focusing on adults aged 18 and older diagnosed with VVS. Diagnoses were based on clinical histories, physical examinations, and the latest syncope guidelines. Out of 1914 patients with HUTT results, 764 patients with positive tests were analyzed for mutual prodromal symptoms during HUTT and spontaneous syncope.Results:The McNemar test revealed significant differences for several symptoms, including palpitation (X2 = 30.59, P < 0.001), nausea (X2 = 16.13, P < 0.001), chest pain (X2 = 24.32, P < 0.001), abdominal discomfort (X2 = 22.33, P < 0.001), flushing (X2 = 10.87, P < 0.001), and aura (X2 = 19.86, P < 0.001), indicating discrepancies in the occurrence of these symptoms. Cohen's Kappa values ranged from 0.06 to 0.32, signifying slight to fair agreement. Specifically, diaphoresis (k = 0.32), palpitation (k = 0.27), and vertigo (k = 0.25) demonstrated fair agreement, whereas nausea, aura, chest pain, abdominal discomfort, and flushing exhibited slight agreement. Among the 640 patients who experienced prodrome during spontaneous syncope, 110 (17.19%) had no symptoms. Conversely, among the 123 patients who did not experience prodrome, 96 (78.05%) experienced at least one symptom during the tilt test (Figure).Conclusion:The assessment of prodromal symptoms during HUTT compared to spontaneous syncope showed significant differences for several symptoms and overall low levels of agreement. Also, tilt cannot differentiate patients with or without prodrome during their spontaneous spells.

Circulation, Volume 150, Issue Suppl_1, Page A4118724-A4118724, November 12, 2024. Background:The New York Heart Association (NYHA) classification is a subjective tool that is commonly used in clinical practice to assess symptoms and functional capacity of patients with heart failure (HF). Correct assignment of NYHA is essential to facilitate evidence-based management.Research Question:What is the validity of the CLASS-HF Guide compared to the 6-minute walk test (6MWT)?Purpose:To examine the validity of the new investigator-developed CLASS-HF guide to assist in appropriate assignment of NYHA Class relative to the 6MWT.Methods:A multi-site, cross-sectional study in three cardiology clinical sites (two specializing in HF) recruited 103 patients in various classes and stages of HF. Providers assigned patients their NYHA Classification using the CLASS-HF guide. Patients then performed the 6MWT with test staff blinded to the assigned NYHA class. Exertion, dyspnea, and walk distance were captured post-test. The validity of the guide-assisted classification was then examined for convergent validity with 6MWT outcomes. Data analysis was performed with correlations, ANOVA, and multivariable regression.Results:Of the 103 total participants, 65.1% were male, 18.4% were non-White, with an average age of 66.0 ± 15.5 years old. A little less than one-third (30.1%) had HFpEF (LVEF ≥ 50%). Provider-assigned NYHA Class was 22.3% I, 38.8% II, 35.0% III and 3.9% IV. The average distance walked during the 6MWT by class was: 367.1 ± 85.6 m for I, 343.7 ± 104.7 m for II, 261.6 ± 73.9 m for III, and 184.6 ± 114.0 m for IV. Convergent validity of NYHA class with Borg exertion (Spearman’sr= .546,p< .001) and dyspnea (r= .504,p< .001) was strong. A statistically significant inverse correlation was found between NYHA assigned class and meters walked during the 6MWT (r= -.469,p< .001), with significant mean differences (ANOVAF(3,99) = 10.72,p< .001) in distance walked for: NYHA Class I vs. III (md= 105.5 m), I vs. IV (md= 182.6 m), II vs. III (md= 82.1 m), II vs. IV (md= 159.2 m). Increasing NYHA class remained significantly associated with lower 6MWT distance (F(3,90)=5.22,p= .002) in multivariable regression (Adj.R-squared= .575) controlling for age, sex, race/ethnicity, diagnosis, site, Borg exertion and dyspnea, and 6MWT stopping/pausing.Conclusion:Validity evidence was found for NYHA class assignment after use of the CLASS-HF guide with respect to 6MWT distance and post-test perceived exertion and dyspnea.

Circulation, Volume 150, Issue Suppl_1, Page A4146883-A4146883, November 12, 2024. Introduction:Peripheral arterial disease (PAD) is caused by a lack of blood flow to the musculature relative to its metabolism which results in pain. PAD impacts up to 20% of patients around the world. PAD involves macrovascular and microvascular dysfunction. Near-infrared spectroscopy (NIRS) measures muscle oxygenation levels and assesses microvascular function. The standard of care for diagnosing PAD is the ankle-brachial index (ABI), which assesses macrovascular disease, and the 6-minute walk test (6MWT), which measures gait speed and claudication. NIRS has the potential to monitor progression of PAD.Hypothesis:NIRS measurement of muscle oxygenation, during a standard test of vascular occlusion and post-occlusive hyperemia, the vascular occlusion test (VOT), is predictive of PAD severity as determined by ABI and 6MWT.Methods:We studied 24 patients diagnosed with PAD. The mean age of the patients was 71.3 years, including 54% (n=13) males and 46% (n=11) females. The VOT consisted of rest, occlusion, and reperfusion phases each lasting 5 min (15 min total). Muscle oxygen saturation levels were recorded at 2 hertz. For every patient, 6 features were extracted from the VOT data using computational methods. The VOT features from 15 patients were used to train function-fitting neural network models to predict ABI and 6MWT Continuous Distance. The models were then used to predict ABI and 6MWT Continuous Distance from the VOT features of 9 test patients not used in the training,Results:For patients in the test set, the ABI and 6MWT Continuous Distance predicted by the models differed from the actual measurements by 14%±13% and 15%±17%, respectively (Figure 1). For patients in the training set, the ABI and 6MWT Continuous Distance predicted by the models differed from the actual measurements by 0±0% and 12%±11%, respectively (Figure 1).Conclusion:The VOT has the potential to predict the ABI and 6MWT Continuous Distance of patients diagnosed with PAD, suggesting that the VOT can be automated and used to monitor the severity of PAD. With more data from both healthy patients and PAD patients, and improvement of the model, we anticipate that the VOT will complement ABI and 6MWT in the diagnosis and monitoring of PAD.

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.