Risultati per: Screening della retinopatia diabetica

Circulation, Volume 146, Issue Suppl_1, Page A15026-A15026, November 8, 2022. Introduction:A novel technology utilizing artificial intelligence (AI) to provide real-time image-acquisition guidance, enabling novices to obtain diagnostic echocardiographic (echo) images holds promise to expand the reach of echo screening for rheumatic heart disease (RHD). We evaluated the ability of non-experts to obtain diagnostic quality images in patients with RHD using AI guidance (Caption Health) with color Doppler.Methods:This study was performed in Kampala, Uganda at the Uganda Heart Institute. Nurses and nursing students with no prior echo experience underwent one-day training in the use of AI guidance, which included a 7-view screening protocol with 2D and color Doppler images. Following training, all participants scanned 8-10 patients using AI guidance, half RHD and half normal. The same patients were scanned by two expert sonographers without the use of AI guidance. Each echo was evaluated by a panel of 4 expert echocardiographers blinded to the identity of the scanner (novice/exert) and diagnosis of the patient to provide quality assessment including (1) diagnostic quality to determine presence/absence of RHD, (2) more detailed valvular assessment, and (3) ACEP score 1-5 for each view.Results:Thirty-six novice scanners scanned a total of 50 patients, 25 with RHD and 25 controls. A total of 462 echocardiogram studies were obtained, 351 obtained by non-experts using AI guidance and 111 obtained by expert sonographers without AI guidance. Preliminary analysis of 394 interpretations showed that 95% of non-expert studies were of diagnostic quality to assess for RHD and mitral valve disease (vs 100% by experts, p=0.03), but only 56% of non-expert studies were of diagnostic quality to assess aortic valve disease (vs 97% by experts, p

Circulation, Volume 146, Issue Suppl_1, Page A14675-A14675, November 8, 2022. Introduction:Genome-wide association studies (GWAS) have discovered >300 associations for CAD. Few loci are functionally characterized and may represent new mechanisms of disease.Hypothesis:Can a high-throughput, unbiased transcriptional screen for all candidate GWAS genes identify the causal genes and biological pathways at CAD GWAS loci in endothelial cells (ECs)?Methods:We applied CRISPRi-Perturb-seq to knock down the expression of all genes within 500 Kb of coronary artery disease GWAS loci (2,300 genes in total) and measure their effects on the transcriptome using single-cell RNA-seq.Results:We identified 60 programs of co-expressed genes, which represent core cellular pathways (i.e. ribosome biogenesis) and EC-specific pathways such as flow response and angiogenesis. The EC-specific programs show the greatest contribution to CAD heritability. 6 EC-specific programs have the greatest number of CAD GWAS candidate genes. One of the EC-specific programs had genes regulated byKLF-transcription factors and was enriched for shear-stress response genes. The novel CAD candidate genes in this program included multiple known mediators of the cerebral cavernous malformation (CCM)-signaling complex. 9 known members of the CCM-signaling cascade and several potentially novel mediators of CAD clustered together in theKLFPerturb-seq topic. These included genetic variants in theCCM2,KLF4,RAC1, andHEG1loci as well as genes will a similar transcriptional profile but no prior connection to the CCM-signaling complex.Conclusions:High-throughput functional analysis of 2,300 genes proximal to CAD GWAS loci prioritized pathways—such as angiogenesis and EC migration—that are regulated by multiple risk SNPs. Our study identifies new genes that likely influence risk for CAD, identifies convergence of CAD genes into certain pathways in endothelial cells, and demonstrates a generalizable strategy to connect disease variants to functions.

Circulation, Volume 146, Issue Suppl_1, Page A10105-A10105, November 8, 2022. Introduction:Hypercholesterolemia is often asymptomatic and requires cholesterol screening to be identified. Current guidelines recommend adults at low risk for cardiovascular disease (CVD) to receive cholesterol screening at least every 5 years with more frequent screenings in older adults and/or at higher CVD risk. Yet, currently, about 25% of Americans do not meet the every-5-year screening recommendations. While disparities in the prevention and treatment of hypercholesterolemia continue to rise, little is known regarding factors influencing cholesterol screening among older Americans in the past 10 years.Methods:This longitudinal analysis used data from the Health and Retirement Study (HRS). HRS is a nationally representative survey of older adults in the U.S. The current study focused on data collected from 2008 (Wave 9) to 2018 (Wave 14). Participants who passed away by 2019, ever had CVD or stroke, were under age 55 at baseline, had more than 3 waves of missing data in self-reported cholesterol screening, or any missing data in covariates were excluded from the current analysis. In total, 7643 participants were included. Meeting cholesterol screening recommendations was defined as those reporting more than two cholesterol screenings between waves 9-14. Poisson regression and logistic regression were used for data analysis.Results:Compared to Black, Indigenous, and People of Color (BIPOC), White older Americans were more likely to meet cholesterol screening recommendations (odds ratio= 1.60; p

Circulation, Volume 146, Issue Suppl_1, Page A13225-A13225, November 8, 2022. Introduction:Frailty is a major risk factor for adverse health events in older adults with cardiovascular disease.Hypothesis:We sought to develop and validate a predictive model leveraging data available in the electronic health record to screen for frailty as defined by a prospective reference standard.Methods:We conducted a population-based cohort study using data from the Canadian Longitudinal Study of Aging (CLSA). From 2010-2015, the CLSA enlisted a diverse and multi-ethnic sample of community-dwelling adults 45-85 years of age. Comprehensive phenotyping was performed through interviews at participants’ homes and assessments at data collection sites. Frailty was quantified by the 47-item Frailty Index (FI) Examination, consisting of tests for age-related deficits in physical performance, body composition, cardiovascular and pulmonary physiology, cognitive and sensory function. After dividing our sample into training (80%) and test (20%) sets, we compared machine learning and linear regression models to predict the FI based on age, sex, comorbidities, and blood test results. We used the H2O AutoML platform (DAI 1.10.2) to iteratively determine the optimal model.Results:The cohort consisted of 30,097 adults with a mean age of 63±10 years and 51% females. The mean FI score was 0.28±0.08 (best-worst 0.07-0.70). The gradient-boosted machine learning model achieved an R2of 0.512 and a root mean squared error (RMSE) of 0.058 to regress FI scores, and an area under the curve of 0.766 to classify FI quintiles, selecting the following 10 variables in descending order of importance: age, chronic heart failure, hypertension, glycated hemoglobin, high-sensitivity C-reactive protein, high-density lipoprotein, red cell distribution width, vitamin D, female sex, and diabetes. The linear regression model achieved a similar R2and RMSE with all 62 input variables and a modest decline after selecting the top 10 input variables using a leaps-and-bounds algorithm.Conclusions:Frailty screening can be performed at scale for clinical or research purposes using common clinical and biochemical inputs. Our machine learning model predicted frailty with a manageable number of inputs and yielded pathophysiological insights about their relative importance.

Circulation, Volume 146, Issue Suppl_1, Page A11770-A11770, November 8, 2022. Background:Association of cardiovascular disease with cancer is caused by an increased risk of coronary artery disease (CAD), in part attributable to the association of standard risk factors with both coronary disease and cancer. In addition to these drivers of accelerated plaque formation, treatment used in breast cancer therapy is associated with CAD.Purpose:Cancer patients require an individualised approach for managing CAD and there is an unmet need to define the benefit of CAD screening on outcomes in cancer survivors and the cost-effectiveness of this approach is unknown.Methods:A Markov model was assembled using three states; well, myocardial infarction and death. Base case scenario was a 55 year old female treated for breast cancer, followed up 10 years post treatment. Costs, utilities, and transition probabilities were derived from published literature. Costs are in 2021 AUD$ and calculated from a societal perspective. Costs and utilities were discounted at 3% per annum. Sensitivity analyses were performed on key inputs including transition probabilities of well state and MI, costs of CAD and screening test. Willing-to-pay threshold of AUD$50,000 was selected.Results:Screening cancer survivors for CAD dominated no screening, providing cost savings of $1916 and QALY savings of 5.9 QALYs per-patient. Major determinants were probabilities of MI, death and costs of screening and MI. There was no change in life expectancy.Conclusion:Screening for CAD provided an increase in long-term QALY and reduction in healthcare costs in breast cancer survivors at least 10 years post treatment. ​

Circulation, Volume 146, Issue Suppl_1, Page A10137-A10137, November 8, 2022. Introduction:Clinical practice guidelines recommend regular chronic kidney disease (CKD) screening after a diagnosis of hypertension (HTN) or type 2 diabetes (T2DM). Annual monitoring of kidney function increases early detection of CKD and improves quality of life. However, disparities in neighborhood characteristics can impact access to routine care, including CKD screening.Hypothesis:We hypothesize area deprivation index (ADI), a national ranking of neighborhood sociodemographic disadvantage would predict annual CKD screening and CKD development among newly diagnosed HTN or T2DM patients.Methods:Electronic health records of patients (n=235,208) with an new HTN or T2DM diagnosis between 2015-2018 were abstracted using International Classification Codes. Patients were followed for three years to assess annual CKD screening (one estimated glomerular filtration rate and urinary albumin-to-creatine ratio) and CKD development (CKD or end stage renal disease). ADI ranks (1-100) were divided into quintiles (Q1=least deprived, Q5=most deprived). Multivariable logistic regression models evaluated associations between ADI quintiles with CKD screening and CKD development.Results:Most patients were White (57%) females (55%) with solely HTN (65%). Few with only T2DM (9%) and 26% had both. Screening was highest for patients who developed HTN and T2DM during the study (44%) compared to only T2DM (38%) or HTN (4%). CKD developed for 9% of patients with HTN and T2DM, but 0% for only HTN or T2DM. Compared to the least deprived patients, the most deprived were less likely to not be screened in the first year of HTN or T2DM diagnosis (Odds Ratio (OR)= 0.77; 95% confidence interval (CI): 0.73, 0.80). The most deprived patients were more likely to develop CKD compared to the least deprived patents (OR=1.98, 95%CI: 1.75, 2.23).Conclusions:The most deprived patients were more likely to be screened annually and almost twice as likely to develop CKD compared to the least deprived. Although an increase in deprivation is associated with poor lifestyle choices which can lead to an increase in CKD, it’s possible early diagnosis is due to an increase in screening, thus leading to an increase in quality of life through monitoring kidney function.

Circulation, Volume 146, Issue Suppl_1, Page A9447-A9447, November 8, 2022. Introduction:Transthyretin amyloid cardiomyopathy (ATTR-CM) is an underdiagnosed cause of heart failure (HF) among patients aged > 60 years. While the V122I variant that is associated with hereditary ATTR-CM is present in 3.4% of self-identified Black individuals in the US (or 1.5 million people), the phenotypic penetrance of this allele remains incompletely defined owing to age-dependent expression and limited methods for disease ascertainment.Methods:The Screening for Cardiac Amyloidosis with Nuclear Imaging in Minority Populations (SCAN-MP) study is a currently accruing multisite cohort designed to determine the prevalence of ATTR-CM using Tc-99m-Pyrophosphate imaging in older (age > 60 years) Black and Hispanic individuals with HF.TTRgenotype is determined by 4-exon targeted PCR, while functional, biochemical, and echocardiographic testing is performed. Data are presented here as an interim analysis performed using Kruskal-Wallis testing for the first 240 self-identified Black participants.Results:The prevalence of V122I was 6.7% (n=16 carriers of whom 7 had ATTR-CM), yielding a phenotypic penetrance of 44% (95% CI 20%, 70%) at a median age of 82 (IQR 74, 85) years. Allele carriers with ATTR-CM (Group 3) were older and more likely male, with lower 6-minute walk distance and LVEF, when compared to carriers without ATTR-CM (Group 2, Table) or wild-type, non-amyloid HF controls (Group 1). Other functional, biochemical, and echocardiographic parameters were predictably different between Group 3 and the other groups but similar between Groups 1 and 2 except for prealbumin levels (Group 1: 25 mg/dl vs. Group 2: 20.5 mg/dl, p < 0.05).Conclusion:The clinical penetrance of V122I among elderly Black individuals with HF and a median age of 82 years was 44%, suggesting that genotype alone is insufficient to infer ATTR-CM as the cause of HF in this clinical context. Prealbumin concentration may be useful to identify ATTR-CM in V122I carriers.

Circulation, Volume 146, Issue Suppl_1, Page A10257-A10257, November 8, 2022. Introduction:Transthyretin cardiac amyloidosis (ATTR-CA) has been associated with severe aortic stenosis (AS), with some studies finding up to 20% of patients who undergo transcatheter aortic replacement (TAVR) have ATTR-CA. New therapies for ATTR-CA have brought significant interest in identifying patients at high risk for this disease. The purpose of this study was to prospectively evaluate the yield of universal testing for ATTR-CA in older patients with severe AS.Methods:All patients ≥ 70 years with severe, native, and degenerative AS seen in valve clinic for evaluation of TAVR were referred for technetium-99m pyrophosphate cardiac scintigraphy (PYP scan). Diagnosis was made via a combination of planar grade, heart to contralateral lung ratio, and single positron emission computed tomography/computed tomography. Patients with a positive PYP scan were referred for appropriate laboratory testing to rule out AL amyloidosis. Clinical and echocardiographic factors were correlated with the PYP result.Results:Over a 12-month period, 787 patients with severe AS were screened of which 543 met the inclusion criteria. Of these patients, 298 underwent a PYP scan with 232 not undergoing the scan for logistical and scheduling issues during the pandemic. The positivity rate was 4.3% (13/298). Patients with a positive PYP scan had higher rates of carpal tunnel syndrome (54% vs 14%, p -18%) (100% vs 69%, p=0.044), low stroke volume index (≤35 ml/m2) (92% vs 42%, p

Circulation, Volume 146, Issue Suppl_1, Page A12318-A12318, November 8, 2022. Introduction:Pre-eclampsia (Pec) and gestational hypertension (GHT) are potential explanations for the female preponderance of heart failure with preserved ejection fraction. How and when to use this information clinically is unclear.Hypothesis:We hypothesized that subclinical disturbances of left ventricular (LV) structure and function (stage B heart failure, SBHF) are more common at 5-10 years post-partum in women with a history of Pec compared with women with GHT or uneventful pregnancies.Methods:The proportion of SBHF were compared between 25 women with Pec, 16 with GHT or normal pregnancy. Sub-group analysis comparing patients with and without hypertension at follow-up were also conducted.Results:Among 41 participants (age 40±6 years), followed at 9 years, SBHF was reported in 35% participants with Pec and 53% with GHT (p=0.32). Diastolic blood pressure was significantly higher in patients with SBHF than without (94±21 vs. 81±13 mmHg, p=0.035), and a similar trend was observed with systolic blood pressure (147±42 vs. 128±22mmHg, p=0.099). SBHF was observed in 6 (55%) of 11 pts with hypertension at follow-up, but only in 7 (32%) of 22 without (p=0.27). Mean LV end-diastolic volume (117.2±19.1 vs. 93.3±13.1mL,p=0.03), LV end-systolic volume (51.9±7.5 vs. 42±7 mL,p=0.04), LV mass index (73±8.6 vs. 67.3±14.6mmHg, p=0.41), E/e’ (Sept: 9.7±2.7 vs. 7.5±1.7,p=0.009; Lat: 7.4±2.6 vs. 5.5±1.7,p=0.02) were higher in participants with hypertension than without.Conclusions:9 years after pregnancy, SBHF was prevalent in pts with both previous Pec and GHT, but was not significantly different between the entities. Echocardiographic screening may add little to blood pressure follow-up in the identification of HF risk.

Circulation, Volume 146, Issue Suppl_1, Page A12279-A12279, November 8, 2022. Introduction:Homozygous familial hypercholesterolemia (HoFH) is a rare genetic disorder characterized by extremely elevated low-density lipoprotein cholesterol (LDL-c) and very high risk of premature atherosclerotic cardiovascular (ASCVD) and aortic/supraortic valve heart diseases (VHD). The study aim was to examine clinical and biochemical trajectories of a cohort of HoFH patients since childhood.Methods:In this longitudinal study we assessed the incidence of manifest or subclinical ASCVD (coronary or carotid) and VHD as well as plasma lipids in a cohort of HoFH subjects during a 12.9 ± 9.6 years follow-up.Results:From the 868 individuals ≤19 y-old (at baseline) that were genotyped on a genetic cascade screening program, 420 (48.4%) had an FH mutation. From children bearing mutations, 12 were true homozygotes and 1 was compound heterozygote (53.8% females, mean age 7.5 ± 4.1 years at the first visit). During follow-up all were on statin and ezetimibe therapies, and the mean final dose of atorvastatin was 56 ± 27 mg/d (n=10); and rosuvastatin, 26 ± 17 mg/d (n=3). Initial and on treatment LDL-c were 655 ± 177 mg/dL and 399 ± 150 mg/dL, respectively, with a mean 39.1% reduction (-256 mg/dL). None were under LDL apheresis; 2 patients used mipomersen, 2 lomitapide, and 2 are currently using PCSK9 inhibitors. Subclinical cardiovascular disease, either coronary, carotid or in aortic valve, was identified in 38.5% (n=5; mean age 16.4 ± 9.8 years), whereas 30.8% had a clinical cardiovascular event (n=4; mean age 22.8 ± 6.8 years), with 2 deaths. Therefore, 69.3% had either subclinical or manifest cardiovascular disease.Conclusion:Despite early diagnosis and LDL-c reduction HoFH is still marked by an adverse and premature cardiovascular disease progression. Conventional lipid lowering therapies are not adequate to prevent ASCVD and VHD disease course.

Circulation, Volume 146, Issue Suppl_1, Page A10856-A10856, November 8, 2022. Introduction:Prior AF screening trials demonstrated low yield, highlighting the need for more targeted approaches. An AI algorithm was developed to identify ECG signatures of AF risk during normal sinus rhythm, which has been validated in diverse external populations.Hypothesis:An AI-guided, targeted screening approach could improve the diagnosis of AF.MethodsWe conducted a pragmatic decentralized trial to prospectively recruit patients with stroke risk factors but no prior AF. The AI algorithm was applied to the ECGs performed in routine practice and divided patients into high- or low-risk groups. The primary endpoint was AF lasting ≥ 30 seconds on a subsequent 30-day continuous cardiac rhythm monitor. In a secondary analysis, trial participants were 1:1 propensity score-matched to real-world controls derived from the eligible but unenrolled population.ResultsA total of 1,003 patients from 40 U.S. states completed the study, with a mean age of 74 [SD 8.8] years. Over a mean of 22.3 days of continuous monitoring, AF was detected in 6 (1.6%) of low-risk patients and 48 (7.6%) of high-risk patients (OR 4.98 [2.11-11.75], p

Circulation, Volume 146, Issue Suppl_1, Page A10560-A10560, November 8, 2022. Introduction.The mHealth Screening to Prevent Strokes (mSToPS) study reported that, compared with standard care, screening older Americans for AF using 2-week Zio patch monitors increased AF diagnosis and oral anticoagulant prescription within one year. The monitored group was also observed to have fewer strokes and deaths at 3 years. The cost-effectiveness of AF screening in this manner has not been explored.Methods.We conducted a health economic analysis of AF screening with Zio patch monitors using patient-level data from the mSToPS study. Clinical outcomes and costs from the payer perspective were obtained from enrollment through 3 years using Aetna claims data. Individual costs, survival and quality-adjusted survival (QALYs) were projected over a lifetime horizon using regression modeling, US life tables and external literature where needed. Potential imbalances between groups were adjusted for with propensity score bin bootstrapping.Results.Study group participants (mean age 74 years, 41% female, median CHA2DS2-VASC score 3) wore an average of 1.7 two-week monitors at an average cost of $601/person. Over 3 years, monitored individuals were more likely than unmonitored to have outpatient visits, including to cardiology, but less likely to require emergency department visits or hospitalization (see Table). Pharmacy costs over 3 years were similar between groups. Total adjusted 3-year costs, including monitors, were slightly higher (difference $1,170, 95% CI -1315 to 3657) in the monitoring group. In patient-level projections, the monitoring group had slightly better total and quality-adjusted survival (11.91 vs. 11.82 life years, 9.38 vs. 9.30 QALYs) and slightly higher lifetime costs, resulting in an incremental cost-effectiveness ratio of $16,978/QALY gained.Conclusions.Based on lifetime projections derived from the mSToPS study, we found AF screening using 2-week Zio patch monitors to provide high value from a health economic perspective.

Circulation, Volume 146, Issue Suppl_1, Page A11937-A11937, November 8, 2022. Introduction:Isolated cardiac sarcoidosis (ICS) poses a diagnostic challenge due to its patchy myocardial involvement and low yield of endomyocardial biopsy (EMB). The diagnosis is often suggested by (18)F-fluorodeoxyglucose (FDG) avidity on positron emission tomograpy (PET) scan. Genetic cardiomyopathies (some of which may be FDG-avid) often present with similar clinical manifestations as ICS, so we evaluated a systematic screening strategy in which all patients with suspected ICS were offered genetic testing.Methods:We reviewed all patients in our Multi-Disciplinary Sarcoid Consortium for those given a diagnosis of ICS by the referring provider based on FDG-PET scans with myocardial but no systemic FDG avidity. These patients were offered genetic testing with commercially available genetic cardiomyopathy and arrhythmia panels (168 genes).Results:Of 110 patients referred, 16 met inclusion criteria, 1 had EMB-proven ICS, 1 did not consent, and 14 were referred for genetic testing. Ten patients (71%) also underwent cardiac MRI, of which 9 had late gadolinium enhancement. Mean age was 61.7±11.6 years, 12 (86%) were male. Mean ejection fraction at time of presentation was 43±10%. Four patients (29%) had presented with atrio-ventricular block, 12 (86%) with ventricular arrhythmias and 12 (86%) with left ventricular systolic dysfunction. Eight (57%) had EMB without granulomas (6 had not undergone EMB). Of these 14 patients, 5 (36%) had pathogenic mutations: 2 inLMNA,2 inTPM1,and 1 inMYBPC3. All 5 patients’ clinical phenotype was consistent with their genotype and 3 had previously been immunosuppressed without clinical improvement or resolution of FDG avidity.Conclusions:Genetic cardiomyopathy is often misdiagnosed as “isolated cardiac sarcoid.” A screening strategy of genetic testing all patients with isolated myocardial FDG avidity on FDG-PET scans had a 36% yield for pathogenic mutations and should be considered as part of routine clinical care.

Circulation, Volume 146, Issue Suppl_1, Page A14935-A14935, November 8, 2022. Introduction:The electrocardiogram (ECG) contains information about age-related changes in cardiovascular physiology, which have been linked with the frailty syndrome.Hypothesis:We sought to develop and validate a predictive model leveraging the 12-lead ECG to screen for frailty as defined by a prospective reference standard.Methods:We conducted a population-based cohort study using data from the Canadian Longitudinal Study of Aging (CLSA). From 2010-2015, the CLSA enlisted a diverse and multi-ethnic sample of community-dwelling adults 45-85 years of age. Comprehensive phenotyping was performed through interviews at participants’ homes and assessments at data collection sites. Frailty was quantified by the 110-item Frailty Index (FI) Composite, consisting of self-reported comorbidities, blood tests, physical performance tests, body composition tests, cardiovascular and pulmonary tests, cognitive and sensory tests. After dividing our sample into training (80%) and test (20%) sets, we developed an end-to-end deep neural network to predict the FI score based on the 12-lead ECG time series.Results:A total of 26,700 ECGs with paired FI scores were evaluated. For classification of FI quintiles, a bidirectional long short-term memory (BiLSTM) neural network with a cross-entropy loss function achieved a 5-fold mean area under the receiver operating characteristics curve (AUROC) of 0.70 and area under the precision-recall curve (AUPRC) of 0.36. Predictive performance was superior for classification of the first (most robust) quintile that had AUROC 0.79 and AUPRC 0.46, and the fifth (most frail) quintile that had AUROC 0.79 and AUPRC 0.56, as compared to the middle quintiles that had AUROC 0.60-0.69 and AUPRC 0.27-0.29.Conclusions:Our deep learning model can be used to screen for high or low levels of frailty based on the readily available 12-lead ECG. Additional research is underway to gain insights into other representations of the ECG signal and relative importance of the ECG features.

Circulation, Volume 146, Issue Suppl_1, Page A9822-A9822, November 8, 2022. Background:Data mining of electronic health records (EHR) has been used as a strategy to identify patients with undiagnosed familial hypercholesterolemia (FH). Most studies have been limited by the absence of both phenotypic and genotypic data in the same cohort.Methods:Using a subset of the Geisinger MyCode Community Health Initiative (MyCode) cohort with both exome sequencing and EHR data (n=130,257), we ran two FH screening algorithms to determine genetic and phenotypic diagnostic yields: the Mayo Clinic algorithm (Mayo), which identifies those with LDL-C levels >190 mg/dL, and FIND FH®, the Family Heart Foundation’s machine learning model, to identify individuals with phenotypes suggestive of FH. With 29,243 excluded by Mayo (for secondary causes of hypercholesterolemia, no lipid value in EHR), 52,034 excluded by FIND-FH (insufficient data to run the model), and 187 excluded for prior FH diagnosis, a final cohort of 59,729 participants screened by both algorithms was created. Genetic diagnosis was based on the presence of a pathogenic or likely pathogenic (P/LP) variant in 3 genes implicated in FH via genomic screening. Charts from 180 variant negative participants (60 controls; 120 identified by FIND FH and/or Mayo) were reviewed to calculate Dutch Lipid Clinic Network scores; a score >5 defined probable or definite FH.Results:Mayo flagged 10,415 subjects; 164 (1.6%) had an FH P/LP variant. FIND-FH flagged 573; 28 (4.9%) had an FH P/LP variant giving a net yield from both algorithms of 167/240 (70%). Confirmation of a phenotypic diagnosis was constrained by lack of EHR data on physical findings or family history (high cholesterol, premature atherosclerotic disease) required for score calculation. Phenotypic FH by chart review was present by Mayo and/or FIND-FH in 13/120 vs 2/60 not flagged by either (p< 0.09).Conclusion:After excluding those with a prior FH diagnosis, applying two recognized phenotypic FH screening algorithms to the eligible MyCode cohort identified 70% of those with a P/LP FH variant. Limitations to this approach include participant exclusions for each algorithm, a low yield of positive genomic screening for Mayo, and a low yield of participants for FIND FH. Phenotypic diagnosis was rarely achievable due to missing data.

Circulation, Volume 146, Issue Suppl_1, Page A13601-A13601, November 8, 2022. Introduction:Truncating variants inTTN(TTNtvs) are the largest genetic cause of dilated cardiomyopathies (DCM). In populations, genetic variation inTTNis pervasive and penetrance estimates for DCM are low, even when carriers are limited to those withTTNtvs in exons with “percentage spliced in” index > 90 (hiPSI), a representation of constitutive cardiac expression. Patients with cardiomyopathies (CM) often carry a large number of other cardiac conditions, such as atrial fibrillation (Afib). We sought to confirm this association and determine whether the presence of Afib and a hiPSITTNtv predicted CM.Results:Leveraging clinicogenomic data from ~450,000 individuals in two health systems, we show support for associations with both CM and Afib at the population level. We perform a sliding window analysis ofTTNtvs and confirm the association is specific to hiPSI exons, with no meaningful associations in exons with less cardio expression. The combination of hiPSITTNtv carrier status and early Afib diagnosis (dx before age 60) finds a subset ofTTNcarriers at high risk for CM (34% prevalence) – this risk is 3.5 fold higher than that of all hiPSITTNtv carriers (9% prevalence) and 5-fold higher than non-carriers with early Afib (5% prevalence, p=4.8e-56 after controlling for age and sex). Further, Afib either predates or is concurrently diagnosed with CM in 72% of those with both diagnoses.Conclusion:CM and Afib are linked in hiPSITTNtv carriers and may represent progressive manifestations of structurally-based heart failure. Our retrospective analysis suggests hiPSITTNtv screening (~0.5% of cohorts) in conjunction with routine monitoring for arrhythmias may be an effective strategy to improve outcomes and reduce the incidence of severe cardio outcomes in the population.