BACKGROUND:Disparities in guideline-based quality measures likely contribute to differences in heart failure (HF) outcomes. We evaluated between- and within-hospital differences in the quality of care across sex, race, ethnicity, and insurance for patients hospitalized for HF.METHODS:This retrospective analysis included patients hospitalized for HF across 596 hospitals in the Get With the Guidelines-HF registry between 2016 and 2021. We evaluated performance across 7 measures stratified by patient sex, race, ethnicity, and insurance. We evaluated differences in performance with and without adjustment for the treating hospital. We also measured variation in hospital-specific disparities.RESULTS:Among 685 227 patients, the median patient age was 72 (interquartile range, 61-82) and 47.2% were women. Measure performance was significantly lower (worse) for women compared with men for all 7 measures before adjustment. For 4 of 7 measures, there were no significant sex-related differences after patient-level adjustment. For 20 of 25 other comparisons, racial and ethnic minorities and Medicaid/uninsured patients had similar or higher (better) adjusted measure performance compared with White and Medicare/privately insured patients, respectively. Angiotensin receptor neprilysin inhibitor measure performance was significantly lower for Asian, Hispanic, and Medicaid/uninsured patients, and cardiac resynchronization therapy implant/prescription was lower among women and Black patients after hospital adjustment, indicating within-hospital differences. There was hospital-level variation in these differences. For cardiac resynchronization therapy implantation/prescription, 278 hospitals (46.6%) had >= 2% lower implant/prescription for Black versus White patients compared with 109 hospitals (18.3%) with the same or higher cardiac resynchronization therapy implantation/prescription for Black patients.CONCLUSIONS:HF quality measure performance was equitable for most measures. There were within-hospital differences in angiotensin receptor neprilysin inhibitor and cardiac resynchronization therapy implant/prescription for historically marginalized groups. The magnitude of hospital-specific disparities varied across hospitals.

BACKGROUND There are established sex-specific differences in heart failure with reduced ejection fraction (HFrEF) outcomes. Randomized clinical trials (RCTs) based on cardiovascular outcome benefits, typically either reduced cardiovascular mortality or hospitalization for heart failure (HHF), influence current guidelines for therapy. OBJECTIVES The authors evaluate the representation of women in HFrEF RCTs that observed reduced all-cause or cardiovascular mortality or HHF. METHODS We queried Cumulative Index to Nursing and Allied Health Literature, Excerpta Medica dataBASE, Medical Literature Analysis and Retrieval System Online, and PubMed for HFrEF RCTs that reported a statistically significant benefit of intervention resulting in improved mortality or HHF published from 1980 to 2021. We estimated representation using the participation-to-prevalence ratio (PPR). A PPR of 0.8 to 1.2 was considered representative. RESULTS The final analysis included 33 RCTs. Women represented only 23.2% of all enrolled participants (n = 24,366/ 104,972), ranging from 11.4% to 40.1% per trial. Overall PPR was 0.58, with per-trial PPR estimates ranging from 0.29 to 1.00. Only 5 trials (15.2%) had a PPR of women representative of the disease population. Representation did not change significantly over time. The proportion of women in North American trials was significantly greater than trials conducted in Europe (P = 0.03). The proportion of women was greater in industry trials compared to government-funded trials (P = 0.05). CONCLUSIONS Women are underrepresented in HFrEF RCTs that have demonstrated mortality or HHF benefits and influence current guidelines. Representation is key to further delineation of sex-specific differences in major trial results. Sustained efforts are warranted to ensure equitable and appropriate inclusion of women in HFrEF trials. (JACC Adv 2024;3:100743) (c) 2024 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).

Background: Statins are the cornerstone of treatment of patients with atherosclerotic cardiovascular disease (ASCVD). Despite this, multiple studies have shown that women with ASCVD are less likely to be prescribed statins than men. The objective of this study was to use Natural Language Processing (NLP) to elucidate factors contributing to this disparity. Methods: Our cohort included adult patients with two or more encounters between 2014 and 2021 with an ASCVD diagnosis within a multisite electronic health record (EHR) in Northern California. After reviewing structured EHR prescription data, we used a benchmark deep learning NLP approach, Clinical Bidirectional Encoder Representations from Transformers (BERT), to identify and interpret discussions of statin prescriptions documented in clinical notes. Clinical BERT was evaluated against expert clinician review in 20% test sets. Results: There were 88,913 patients with ASCVD (mean age 67.8 +/- 13.1 years) and 35,901 (40.4%) were women. Women with ASCVD were less likely to be prescribed statins compared with men (56.6% vs 67.6%, p <0.001), and, when prescribed, less likely to be prescribed guideline-directed high-intensity dosing (41.4% vs 49.8%, p <0.001). These disparities were more pronounced among younger patients, patients with private insurance, and those for whom English is their preferred language. Among those not prescribed statins, women were less likely

Background: There are established sex-specific differences in heart failure with reduced ejection fraction (HFrEF) outcomes. Randomized clinical trials (RCTs) based on cardiovascular outcome benefits, typically either reduced cardiovascular mortality or hospitalization for heart failure (HHF), and influence current guidelines for therapy. Objectives: To evaluate the representation of women in HFrEF RCTs that observed reduced all-cause or cardiovascular mortality or HHF. Methods: We queried Excerpta Medica dataBASE, Medical Literature Analysis and Retrieval System Online, Cumulative Index to Nursing and Allied Health Literature, and PubMed for HFrEF RCTs that reported a statistically significant benefit of intervention resulting in improved mortality or HHF published from 1980 to 2021. We estimated representation using the participation-to-prevalence ratio (PPR). PPR was calculated based on the proportion of women with HFrEF in the Framingham cohort (40%). A PPR of 0.8 to 1.2 was considered representative. Results: The final analysis included 33 RCTs. All trials except two were mentioned in the 2022 American College of Cardiology/American Heart Association/Heart Failure Society of America Guidelines for the Management of Heart Failure. Women represented 23.2% of enrolled participants (n = 24,363/ 104,972), ranging from 11.4% to 40.1% per-trial. Overall PPR was 0.58, with per-trial estimates ranging from 0.29 - 1.00. Five trials (15.2%) had a PPR of women representative of the disease population. Representation didn’t change significantly by the decade examined. The proportion of women in North American and Multiregional trials was significantly greater than in trials conducted in Europe (p = 0.04). The proportion of women was greater in industry trials compared to government-funded trials (p = 0.05). Conclusions: Women are underrepresented in HFrEF RCTs that have demonstrated mortality or HHF benefits, which may affect the sex-specific generalizability of major trial results. Sustained efforts are warranted to ensure equitable and appropriate inclusion of women in HFrEF trials.

HomeJournal of the American Heart AssociationAhead of PrintImpact of Virtual Interviewing on Cardiovascular Fellowship Applicant Diversity: Insights From 2 Academic Programs Open AccessRapid CommunicationPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toOpen AccessRapid CommunicationPDF/EPUBImpact of Virtual Interviewing on Cardiovascular Fellowship Applicant Diversity: Insights From 2 Academic Programs Celeste Witting, Joshua W. Knowles, Doreen DeFaria Yeh, Tariku J. Beyene, Santosh E. Gummipundi, Paul A. Heidenreich and Celina M. Yong Celeste WittingCeleste Witting https://orcid.org/0000-0003-2077-0291 , Department of Medicine, , Stanford University, , Stanford, , CA, , USA, , Joshua W. KnowlesJoshua W. Knowles https://orcid.org/0000-0003-1922-7240 , Division of Cardiovascular Medicine and Cardiovascular Institute, , Stanford University, , Stanford, , CA, , USA, , Stanford Diabetes Research Center, , Stanford University, , Stanford, , CA, , USA, , Stanford Prevention Research Center, , Stanford University, , Stanford, , CA, , USA, , Doreen DeFaria YehDoreen DeFaria Yeh , Cardiovascular Research Center, , Mass General Research Institute, Massachusetts General Hospital, , Boston, , MA, , USA, , Tariku J. BeyeneTariku J. Beyene https://orcid.org/0000-0002-7474-1966 , Veterans Affairs Palo Alto Healthcare System, , Palo Alto, , CA, , USA, , Santosh E. GummipundiSantosh E. Gummipundi https://orcid.org/0000-0002-8960-8869 , Division of Cardiovascular Medicine and Cardiovascular Institute, , Stanford University, , Stanford, , CA, , USA, , Paul A. HeidenreichPaul A. Heidenreich https://orcid.org/0000-0001-7730-8490 , Division of Cardiovascular Medicine and Cardiovascular Institute, , Stanford University, , Stanford, , CA, , USA, , Veterans Affairs Palo Alto Healthcare System, , Palo Alto, , CA, , USA, and Celina M. YongCelina M. Yong * Correspondence to: Celina M. Yong, MD, MBA, MSc, Palo Alto Veterans Affairs Healthcare System, Stanford University, 3801 Miranda Ave, 111C. Palo Alto, CA 94304. Email: E-mail Address: [email protected] https://orcid.org/0000-0003-3054-6576 , Division of Cardiovascular Medicine and Cardiovascular Institute, , Stanford University, , Stanford, , CA, , USA, , Veterans Affairs Palo Alto Healthcare System, , Palo Alto, , CA, , USA, Originally published29 Dec 2023https://doi.org/10.1161/JAHA.123.030255Journal of the American Heart Association. 2023;0:e030255Cardiovascular training programs matriculate a disproportionately low number of women and underrepresented in medicine (UIM) trainees, with only 21% female, 4.5% Black, and 7% Hispanic fellows reported in recent years.1 With the onset of the COVID‐19 pandemic, virtual interviewing replaced in‐person interviewing for cardiology fellowship positions across the United States beginning with the 2021 matriculation cycle, with a concomitant 12.5% increase in cardiology fellowship applications per program nationwide.2 However, little is known about the influence of these changes on the diversity of the interviewee pool.In a 2‐center retrospective study, we sought to identify demographic changes among trainees who interviewed for the Stanford General Cardiology Fellowship Program (matching 7 fellows per year) and Massachusetts General Hospital Cardiovascular Disease Fellowship Program (matching 8 fellows per year). This study was institutional review board exempt and did not require informed consent. Trainees' self‐reported sex, race, and ethnicity data were studied. UIM applicants were defined as those who self‐identified as Black or Hispanic. We compared the cohort who interviewed in person (2018–2020 matriculation years) with those who interviewed virtually (2021–2023 matriculation years). Tests of proportions and t tests were used for categorical and numerical variables, respectively. Percentage of UIM and distance from residency site were estimated using generalized linear model accounting for potential clustering by fellowship site as a random effect. The data for this study are available from the corresponding author upon reasonable request.A total of 633 interviewees across all years were studied from both programs (mean of 54 interviews per year per program from 36 residency programs during in‐person versus 62 interviews per year per program from 42 programs during virtual interviews). Virtual interviewing was associated with a higher percentage of UIM interviewees (10.2% [95% CI, 7.4%–14.0%] during in‐person versus 27.7% [95% CI, 23.1%–33.0%] during virtual years, P<0.01), such that the odds of a UIM candidate being interviewed were 3.4 (95% CI, 2.2–5.3) times higher during the virtual compared with the in‐person period (Figure [A]). Individual year‐to‐year comparisons (2019 versus 2020, 2020 versus 2021, 2021 versus 2022) revealed that the only year with a significant change was from 2020 (in person) to 2021 (virtual), such that the odds of a UIM candidate interviewing was 2.9 (95% CI, 1.0–8.3; P=0.04) times higher with the switch to virtual interviews. The changes in distribution of UIM applicants were magnified among those ranked to match in the top 20 spots, from 10.0% (95% CI, 5.4%–17.7%) UIM during in‐person interviewing to 36.0% (95% CI, 27.2%–45.9%) during virtual interviewing years (P<0.01). The percentage of women in the top 20 spots increased marginally from 42.0% (95% CI, 32.7%–51.9%) during in‐person interviews to 56.0% (95% CI, 46.1%–65.4%; P=0.05). Mapping the change in the proportion of interviewees from each region suggests a pattern of candidates interviewing from farther regions for both institutions (Figure [B]). However, there was no significant change in the mean distance from the applicant's residency program to the fellowship program location (1150.1 [95% CI, 525.6–2516.7] miles during in‐person versus 1278.8 [95% CI, 643.3–2542.1] miles during virtual interviewing, P=0.42).Download figureDownload PowerPointFigure . Shifts in sociodemographic profiles of cardiology fellowship interviewees with transition to virtual interviewing.A, Trends in proportion of underrepresented in medicine interviewees during in‐person vs virtual interviewing (P<0.01 for both). Total interviews at Stanford: 150 in person, 166 virtual. Total interviews at MGH: 173 in person, 144 virtual. B, Geographic distribution of interviewees relative to fellowship program location. Left is Stanford data, right is MGH; star shows program location. Values are mean number of interviewees from each region annually, and relative % of total interviewees from that region, in person and virtual. IP indicates in person; MGH, Massachusetts General Hospital; UIM, underrepresented in medicine; and V, virtual.We find that the virtual interviewing process was significantly associated with greater proportions of UIM trainees being interviewed and ranked highly by 2 competitive academic cardiology fellowship programs in the United States. This may partially be driven by increased geographic diversity of the interviewee pool enabled by virtual interviews. The majority of the increase in UIM representation was seen between 2020 and 2021, concomitant with the change in interview modality, which argues against progressive programmatic prioritization of diversity and equity over time as the sole contributor.These findings should be considered hypothesis generating, as there are key limitations to this study. First, although we statistically adjusted for fellowship site, the potential for confounding persists. The decision to interview at a fellowship program is complex and personal, and programs' decisions of whom to interview can be similarly nuanced; these additional factors were not captured in this study. The 2 programs studied are highly competitive academic cardiology training programs, which may not represent all cardiology programs. Finally, we could not access data on noninterviewed applicants; future research is needed to explore trends in the overall applicant pool.In sum, these findings suggest that virtual interviewing may promote diversity of interviewees to selective cardiology programs. Given the likely continued reliance on virtual interviewing, further research is needed to understand the degree to which this may present its own set of potential biases and whether the trends among interviewees noted here translate to the cohort who ultimately match. It will also be important to determine whether the observed changes among interviewees in this study were driven by applicant choice versus institutional programmatic changes or other confounders.Sources of FundingCelina M. Yong is funded by a Veterans Affairs Health Services Career Development Award (1IK2HX002236‐01A2). Joshua W. Knowles receives funding from the National Institute of Diabetes, and Digestive and Kidney Diseases of the National Institutes of Health (R01DK120565, R01DK116750, P30DK116074) and the American Heart Association.DisclosuresNone.Footnotes* Correspondence to: Celina M. Yong, MD, MBA, MSc, Palo Alto Veterans Affairs Healthcare System, Stanford University, 3801 Miranda Ave, 111C. Palo Alto, CA 94304. Email: cyong@stanford.eduThis article was sent to Mahasin S. Mujahid, PhD, MS, FAHA, Associate Editor, for review by expert referees, editorial decision, and final disposition.For Sources of Funding and Disclosures, see page 3.References1 Mylavarapu P, Gupta NE, Gudi V, Mylavarapu A, Daniels LB, Patel M. Diversity within the most competitive internal medicine fellowships: examining trends from 2008 to 2018. J Gen Intern Med. 2020; 35:2537–2544. doi: 10.1007/s11606-020-06008-5CrossrefMedlineGoogle Scholar2 Huppert LA, Santhosh L, Babik JM. Trends in US internal medicine residency and fellowship applications during the COVID19 pandemic vs previous years. JAMA Netw Open. 2021; 4:e218199. doi: 10.1001/jamanetworkopen.2021.8199CrossrefMedlineGoogle Scholar eLetters(0) eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate. Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page. Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetails Article Information Metrics Copyright © 2023 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley BlackwellThis is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.https://doi.org/10.1161/JAHA.123.030255PMID: 38156448 Manuscript receivedMarch 18, 2023Manuscript acceptedOctober 4, 2023Originally publishedDecember 29, 2023 Keywordscardiologydiversitytrainingvirtual interviewingPDF download Subjects Health Equity

Relative apical longitudinal sparing (RALS) on echocardiography has become an increas-ingly used tool to evaluate for cardiac amyloidosis (CA), but the predictive value of this finding remains unclear. This is a retrospective analysis at a single tertiary care center across 3 years. Patients were included if they had RALS, defined by strain ratio & GE;2.0 on echocardiography, and sufficient laboratory, imaging, or histopathologic workup to indi-cate their likelihood of CA. Patients were stratified by their likelihood of CA, and contri-butions of other co-morbidities previously shown to be associated with RALS. Of the 220 patients who had adequate workup to determine their likelihood of having CA, 50 (22.7%) had confirmed CA, 35 (15.9%) had suspicious CA, 83 (37.7%) had unlikely CA, and 52 (23.7%) had ruled-out CA. The positive predictive value of RALS for CA was 38.6% for confirmed or suspicious CA. The remaining 61.4% of patients who were unlikely or ruled out for CA had other co-morbidities such as hypertension, chronic kidney disease, malig-nancy, or aortic stenosis, 17.0% of this group had none of these co-morbidities. In our ter-tiary care cohort of patients with RALS pattern on echocardiography, we found that fewer than half of patients with RALS were likely to have CA. Given the increasing use of strain technology, further studies are warranted to determine the optimal strategy for assessing CA in a patient with RALS. & COPY; 2023 Elsevier Inc. All rights reserved. (Am J Cardiol 2023;200:66-71)

Background Statins are guideline‐recommended medications that reduce cardiovascular events in patients with diabetes. Yet, statin use is concerningly low in this high‐risk population. Identifying reasons for statin nonuse, which are typically described in unstructured electronic health record data, can inform targeted system interventions to improve statin use. We aimed to leverage a deep learning approach to identify reasons for statin nonuse in patients with diabetes. Methods and Results Adults with diabetes and no statin prescriptions were identified from a multiethnic, multisite Northern California electronic health record cohort from 2014 to 2020. We used a benchmark deep learning natural language processing approach (Clinical Bidirectional Encoder Representations from Transformers) to identify statin nonuse and reasons for statin nonuse from unstructured electronic health record data. Performance was evaluated against expert clinician review from manual annotation of clinical notes and compared with other natural language processing approaches. Of 33 461 patients with diabetes (mean age 59±15 years, 49% women, 36% White patients, 24% Asian patients, and 15% Hispanic patients), 47% (15 580) had no statin prescriptions. From unstructured data, Clinical Bidirectional Encoder Representations from Transformers accurately identified statin nonuse (area under receiver operating characteristic curve [AUC] 0.99 [0.98–1.0]) and key patient (eg, side effects/contraindications), clinician (eg, guideline‐discordant practice), and system reasons (eg, clinical inertia) for statin nonuse (AUC 0.90 [0.86–0.93]) and outperformed other natural language processing approaches. Reasons for nonuse varied by clinical and demographic characteristics, including race and ethnicity. Conclusions A deep learning algorithm identified statin nonuse and actionable reasons for statin nonuse in patients with diabetes. Findings may enable targeted interventions to improve guideline‐directed statin use and be scaled to other evidence‐based therapies.

Introduction: The goal of cardiovascular training programs is to increase recruitment of women and underrepresented in medicine (UIM) trainees. Due to the COVID-19 pandemic, virtual interviewing replaced in-person interviewing for cardiology fellowship applications in the United States. However, there is little data on the influence of these changes on fellowship candidate diversity. Methods: In a single-center retrospective study, we identified demographic changes in the profiles of trainees who interviewed for the Stanford University Cardiovascular Fellowship Program before and after the transition to virtual interviewing (2019 and 2020 vs 2021 and 2022 cycles). UIM applicants were defined as those who self-identified Black or Hispanic. Test of proportions and t-test were used for categorical and numeric variables respectively. Results: Over four years, 2250 trainees applied, 212 candidates interviewed, and 24 were accepted to the fellowship. Of those interviewed, 42.0% were women, 9.9% were Black, and 9.4% were Hispanic. The proportion of UIM trainees interviewed increased from 10.5% during the in-person years to 30.2% during the virtual years (p < 0.001; Figure 1A). The increase among women was not statistically significant (40% in-person vs. 44% virtual, p = 0.58). The geographic distribution shifted over time to include lower representation from closer Western programs (40% in-person to 29% virtual) and higher representation from Northeast programs (35% in-person to 44% virtual; Figure 1B). The weighted mean distance of represented residency programs nominally increased from 1730 miles to 2067 miles away (p = 0.06). Conclusions: Virtual interviews were associated with a three-fold increase in UIM interviewed applicants for cardiology fellowship positions at a single center. Further research is warranted to assess the full impact of virtual interviews, as well as to understand and mitigate potential bias in the evolving selection process.

Although cardiovascular disease (CVD) is the leading cause of death in women, cardiovascular risk factors remain underrecognized and undertreated. Hyperlipidemia is one of the leading modifiable risk factors for CVD. Statins are the mainstay of lipid lowering therapy (LLT), with additional agents such as ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors as additive or alternative therapies. Clinical trials have demonstrated that these LLTs are equally efficacious in lipid lowering and cardiovascular risk reduction in women as they are in men. Although the data on statin teratogenicity is evolving, in times of pregnancy or attempted pregnancy, most lipid-lowering agents are generally avoided due to lack of high-quality safety data. This leads to limited treatment options in pregnant women with hyperlipidemia or cardiovascular disease. During the perimenopausal period, the mainstay of lipid management remains consistent with guidelines across all ages. Hormone replacement therapy for cardiovascular risk reduction is not recommended. Future research is warranted to target sex-based disparities in LLT initiation and persistence across the life course.

Introduction: Statins are life-saving medications for patients with atherosclerotic cardiovascular disease (ASCVD), but women with ASCVD are persistently less likely to be prescribed statins than men. This study aims to use Natural Language Processing (NLP) to further elucidate patient and provider factors contributing to this disparity. Methods: The study cohort included patients with >2 ASCVD encounters between 2014 and 2021 within a multisite electronic health record (EHR) in Northern California. Data from a random sample of our cohort (N = 942) was manually annotated to develop a benchmark deep learning natural language processing (NLP) approach, Clinical Bidirectional Encoder Representations from Transformers (BERT); 80% of these were used for model training and 20% for testing. After reviewing structured EHR data (e.g. prescriptions, allergies), BERT was used to identify and interpret discussions of statins in clinical notes. Results: Of 88,913 patients with ASCVD (mean age 67.8 ± 13.1 years), 35,901 (40.4%) were women. Women were less likely to be prescribed statins (56.6% vs. 67.6%, p < 0.001). Only 18.6% of nonallergic patients without a statin prescription had a mention of statins in unstructured EHR text. Statin use through unstructured text was less likely to be identified among women than men (32.8% vs. 42.6%, p < 0.001). Reasons for statin nonuse did not significantly differ by gender (Figure). Conclusions: Women with ASCVD were less likely to be use statins, and this disparity became more pronounced with the inclusion of unstructured data. An NLP approach revealed actionable reasons for statin nonuse. Future studies should leverage these approaches to monitor and track statin adherence by combining structured and unstructured data in real-world populations.

BACKGROUND There are sociodemographic disparities in outcomes of heart failure with reduced ejection fraction (HFrEF), but disparities in guideline-directed medical therapy (GDMT) remain poorly characterized.OBJECTIVES This study aimed to analyze GDMT treatment rates in eligible patients with recently diagnosed HFrEF, and to determine how rates vary by sociodemographic characteristics.METHODS This retrospective cohort study included patients diagnosed with HFrEF at Veterans Affairs (VA) hospitals from 2013 to 2019. The authors analyzed GDMT treatment rates and doses, excluding patients with contraindications. Therapies of interest were evidence-based beta-blockers (BBs), renin-angiotensin system inhibitors (RASIs), angiotensin receptor-neprilysin inhibitors (ARNIs), and mineralocorticoid antagonists (MRAs). The authors compared adjusted treatment rates by race and ethnicity, neighborhood social vulnerability, rurality, distance to medical care, and sex.RESULTS The cohort comprised 126,670 VA patients with recently diagnosed HFrEF. The study found that racial and ethnic minorities had similar or higher treatment rates than White patients. Patients residing in socially vulnerable neighborhoods had 3.4% lower ARNI (95% CI: 1.9%-5.0%) treatment rates. Patients residing farther from specialty care had similar rates of GDMT therapy overall, but were less likely to be taking at least 50% of the target doses of either BBs (4.0% less likely; 95% CI: 3.1%-5.0%) or RASIs (5.0% less likely; 95% CI: 4.1%-6.0%) compared with those closer to care.CONCLUSIONS Among VA patients with recently diagnosed HFrEF, the authors did not find that racial and ethnic minority patients were less likely to receive GDMT. However, appropriate dose up-titration may occur less frequently in more remote patients. (J Am Coll Cardiol HF 2023;11:161-172) Published by Elsevier on behalf of the American College of Cardiology Foundation.

Introduction: Statins are guideline-recommended and potentially life-saving for individuals with diabetes. Yet, statin use is concerningly low in this group. Identifying reasons for statin nonuse can inform targeted interventions. We hypothesize that clinical reasoning around reasons for statin nonuse may be buried in unstructured, narrative portions of the electronic health record (EHR). We aimed to identify reasons for statin nonuse in patients with diabetes from unstructured EHRs using deep learning. Methods: Adults diagnosed with diabetes from 2014 to 2020 with no statin prescriptions were identified from a multisite EHR health system in Northern California. We used a benchmark deep learning natural language processing (NLP) approach, Clinical Bidirectional Encoder Representations from Transformers (BERT), to identify statin nonuse and reasons for statin nonuse from unstructured EHRs. Clinical BERT was evaluated against expert clinician review in 20% test sets. Results: Of 33,461 patients with diabetes (mean age 59+15y, 49% women, 36% White, 24% Asian, 15% Hispanic), nearly half (47%) lacked statin prescriptions. By leveraging unstructured data containing any mention of statin-related terms, Clinical BERT accurately identified statin nonuse (area under the receiver operating characteristic curve (AUC 0.99 [0.98-1.0]) and identified key patient, clinician, and system reasons for statin nonuse, including statin-associated side effects, guideline-discordant clinician practice, and patient hesitancy (AUC 0.90 [0.86-0.93]; Figure). Conclusions: In a multiethnic diabetes cohort, we identified actionable reasons for statin nonuse using a deep learning approach to mine unstructured EHRs. Findings may enable targeted interventions to improve guideline-directed statin use and be readily scaled to other evidence-based therapies.

Introduction: Non-Hispanic Black (NHB) adults with atrial fibrillation (AF) are less likely to undergo catheter ablation (AFCA) compared with non-Hispanic White (NHW) adults even among those with heart failure and even though previous studies have shown that NHB patients with AF were more symptomatic. Hypothesis: We hypothesize that differences in outpatient referrals to Cardiology and Electrophysiology (EP) contribute to the racial disparity in AFCA. Methods: Using data from the Northwestern Medicine Enterprise Data Warehouse, we curated a retrospective cohort of NHB and NHW patients with newly diagnosed AF between 1/1/2011 and 12/31/2019 in an outpatient office visit to Internal Medicine/Primary Care (IM/PC), Cardiology, or Heart Failure (HF). Rates of AFCA and referral rates from IM/PC to Cardiology or EP and from Cardiology and HF to EP were compared between NHB and NHW patients using logistic regression models adjusted for demographic characteristics and comorbidities. Results: Of the 5,555 included patients, the mean age was 68 years (SD 13.4), 61% were male, 15% were NHB, and the mean CHA 2 DS 2- VASc score was 3.5 (SD 2.0). 373 patients (6.7%) underwent AFCA. NHB patients had a higher prevalence of comorbidities. NHB patients were significantly less likely to undergo AFCA compared with NHW patients (OR 0.61, 95% CI 0.40-0.92, p = 0.02), and this difference persisted even when limited to the subset of patients who had visited EP (N=1,840, OR 0.65, CI 0.42-0.98, p = 0.04). Among patients diagnosed in IM/PC, NHB patients were 1.47 times more likely to be referred to Cardiology than NHW patients (CI 1.09-1.97, p = 0.01), but the rates of referral to EP were similar (OR 0.94, CI 0.72-1.24, p = 0.68) ( Figure ). Conclusion: NHB patients diagnosed in the outpatient setting are less likely to undergo AFCA compared with NHW patients, but referral patterns do not explain these findings. Exploration of other factors should be considered to mitigate disparities in care related to AFCA.

Introduction: In prior studies of patients with left ventricular thickness, the 2D speckle tracking strain echocardiography (STE) finding of relative apical sparing of longitudinal strain (RALS) was associated with a high sensitivity and specificity for diagnosing cardiac amyloidosis (CA). Use of STE is increasing, but the positive predictive value (PPV) of RALS for identifying CA among other etiologies in a large, contemporary patient population is unknown. Hypothesis: While RALS will still carry high predictive value for diagnosing CA, a significant proportion of patients will have other identifiable etiologies. Methods: We retrospectively reviewed 97 patients with RALS (defined as strain ratio ≥ 2.0) on echocardiography between June 2017 and June 2020 who had workup for CA, with cardiac MRI, 99m Technetium-pyrophosphate scan, serum/urine protein electrophoresis, and/or biopsies. These patients were then categorized into 4 groups relative to suspicion for CA (confirmed, suspicious, unlikely, ruled out). Patients without CA (unlikely/ruled out) were screened for comorbidities, including potential etiologies of RALS. Results: Of the 97 patients included, 40 (41%) were women and 39 (40%) were black. 17 (18%) had confirmed and 8 (8%) had suspicious CA while 72 (74%) had unlikely or ruled out CA. Of the confirmed cases, 10 (10%) were diagnosed with TTR amyloidosis and 7 (7%) were diagnosed with AL amyloidosis. The PPV of RALS for CA was 26% (25/97). Among the 72 patients with RALS without CA, 17 (24%) had no comorbidity, 4 (6%) had chronic kidney disease (CKD), 17 (24%) had hypertension (HTN), 16 (22%) had CKD and HTN, 2 (3%) had a malignancy treated with chemotherapy, 1 (1%) had aortic stenosis (AS), and 15 (24%) had multiple comorbidities (Figure 1). Conclusions: In a patient population with non-selective use of STE, the PPV of RALS for CA was 26%. Given the increasing use of STE, recognition of other etiologies of RALS should be noted.

Non-Hispanic black (NHB) patients with atrial fibrillation (AF) are more likely to experience symptoms and have a lower quality of life than non-Hispanic white (NHW) patients with AF; however, NHB patients are less likely to be managed with a rhythm control strategy, including undergoing AF catheter ablation (AFCA), compared with NHW patients.

Tocilizumab, an interleukin-6 receptor antagonist, has been used to treat critically ill patients with coronavirus disease-2019. We present the case of a previously immunocompetent man with coronavirus disease-2019 who developed invasive pulmonary aspergillosis after treatment with tocilizumab, illustrating the importance of considering opportunistic infections when providing immune modulating therapy.

The death of a child is felt by extended family, friends, and community members. Most bereavement care research focuses on programs for parents. Little is known about the efficacy of support programs for other grieving individuals. We conducted a scoping review of the literature describing the efficacy of bereavement support programs for siblings, extended family (other than parents), and community members after pediatric death. We found only four reports describing the efficacy of bereavement support programs for this population. All articles described benefits of the intervention studied. Overall, more rigorous and larger-scale studies are needed.