Citations

Abstract According to the 2020 report of the American Heart Association’s Heart & Stroke Statistics report, nearly 1,000 people are dying daily because of sudden out-of-hospital cardiac arrests and unfortunately, their survival rate is as low as 10%. Hypertrophic Cardiomyopathy (HCM), a relatively rare genetic heart disease is one of these diseases but finding the right patient for the implantation of ICD is still a research question. Implantation of cardioverter-defibrillator (ICD) can save the life of some of these patients. Due to the complexity of the identification of HCM patients, financial burdens, and the clinical risks involved in the ICD implantation procedure, HCM patients will go into a monitoring state before reaching the implantation trigger. Our study cohort shows about 82% of HCM deaths, did not have an ICD, which highlights the need to improve the pre-screening algorithms. In the current paper, we have proposed a new deep learning-based unsupervised clustering technique to facilitate the prioritization of patients to undergo ICD device implantation. This model uses over 900 echocardiographic measurements to find patients who benefit more from the ICD implantation procedure. Our model was trained and tested over 6 years of echo reports collected at Mayo Clinic. This model can be used as a decision support assistant for cardiologists in finding the right HCM patient when decision-making is hard.

Introduction: OAC are recommended for AF patients with CHA 2 DS 2 -VASc ≥2 in men or ≥3 in women (high-risk group), may be considered in patients with CHA 2 DS 2 -VASc 1 in men or 2 in women (medium-risk group), and are reasonable to omit in patients with CHA 2 DS 2 -VASc 0 in men or 1 in women (low-risk group). Furthermore, NOACs are recommended over warfarin in most AF patients. This study aimed to investigate AF stroke prevention treatment patterns in patients managed in routine practice, in particular, the under-use of OAC in the high-risk group and over-use in the low-risk group. Methods: Adult patients with AF were identified using de-identified claims for commercial and Medicare Advantage enrollees in the OptumLabs Data Warehouse. Prescription fills were assessed within 90 days of a patient’s AF encounter between 1/1/2016-12/31/2020. Patients with other indications for OAC, such as VTE, recent joint replacement, prior mechanical or bioprosthetic valve replacement, rheumatic mitral stenosis, and patients who underwent LAAO were excluded. Results: Among the 339,197 AF patients, 4.4%, 8.0%, and 87.6% were in the low-, medium-, and high-risk groups, respectively. The mean age was 51.2 ±10.5 yr, 59.9 ±9.4 yr, and 75.1 ±8.8 yr. In the low-risk group, 29.6% were treated with OAC, whereas in the high-risk group, 40.3% were not treated with any antithrombotic therapy and 7.5% used thienopyridine only. Although 71% of patients on OAC were on a NOAC, the proportion of patients on NOAC decreased from 91% in the low-risk group to 69% in the high-risk group. Conclusions: There are potentially both under-use of guideline-recommended stroke prevention therapies in the high-risk patients and over-use in the low-risk group. Because patients at a high risk of stroke are also at a high risk of major and intracranial bleeding who might benefit from NOACs, the decreased use of NOAC in high-risk patients might highlight the need for future quality improvement efforts.

Abstract Although costimulatory molecules have been shown to boost antitumor immune responses, their significance in stomach adenocarcinoma (STAD) is unknown. The purpose of this study was to examine the gene expression patterns of costimulatory molecule genes in STAD and to develop a predictive signature to aid in therapy selection and outcome prediction. We used 60 costimulatory family genes from prior research to conduct the first complete costimulatory molecule analysis in STAD patients. For the two groups discovered, consensus clustering analysis based on these 60 genes indicated unique distribution patterns and prognostic differences. Then, using Lasso and Cox regression analysis, 9 costimulatory molecular gene pairs (CMGPs) of prognostic value were discovered. With these 9 CMGPs, we were able to develop a costimulatory molecule-related prognostic signature, which performed well in an external dataset. For STAD patients, the signature was proved to be a risk factor independent of clinical characteristics, indicating that this may be employed in conjunction with clinical considerations. An further connection between the signature and immunotherapy response was discovered. People who had high mutation rates, an abundance of infiltrating immune cells, and an immunosuppressive milieu were classed as high-risk. It is possible that patients classed as high-risk have a better prognosis for immunotherapy since these patients have greater cytolytic activity scores and immunophenoscores of CTLA4 and PD-L1/PD-L2 blocker As a consequence, clinicians might use our signature to better assess patient prognosis and develop treatment plans.

Background: Primary sclerosing cholangitis (PSC) is a major risk factor for cholangiocarcinoma (CCA). We investigated biliary and fecal microbiota to determine whether specific microbes in the bile or stool are associated with PSC or CCA. Methods: Bile was obtained from 32 patients with PSC, 23 with CCA with PSC, 26 with CCA without PSC, and 17 controls. Over 90% of bile samples were from patients with perihilar CCA. Stool was obtained from 31 patients with PSC (11 were matched to bile), 16 with CCA with PSC (10 matched to bile), and 11 with CCA without PSC (6 matched to bile). Microbiota composition was assessed using 16SrRNA-marker-based sequencing and was compared between groups. Results: Bile has a unique microbiota distinguished from negative DNA controls and stool. Increased species richness and abundance of Fusobacteria correlated with duration of PSC and characterized the biliary microbiota in CCA. Stool microbiota composition showed no significant differences between groups. Conclusions: We identified a unique microbial signature in the bile of patients with increased duration of PSC or with CCA, suggesting a role for microbiota-driven inflammation in the pathogenesis and or progression to perihilar CCA. Further studies are needed to test this hypothesis.

Introduction: Mobile thrombi are commonly observed on endovascular leads at the time of catheter ablation. Transseptal puncture poses a risk of paradoxical embolism. We sought to examine the risk of stroke or systemic embolism after transseptal ablation in patients with and without cardiac implantable electronic devices (CIEDs). Methods: Using a large, national administrative claims database we identified 31,720 patients who underwent a catheter ablation requiring transseptal puncture between 1/1/2004 and 9/30/2014. We created two propensity-matched cohorts, matching on age, gender, race, household income, region, Charlson index, CHADS-Vasc score, and year and indication for ablation (5,533 patients with CIEDs and 11,300 patients without devices). Incidence rates (events/100 patient-years) and propensity score-matched cox proportional hazards models (with 95% confidence intervals) were used to estimate risk of stroke, transient ischemic attack, or systemic embolism for patients with or without CIEDs. We also examined the impact of presence of a CIED and oral anticoagulation (OAC) use on risk of stroke or systemic embolism within the matched cohort. Average follow up was 2.1 years. Results: The event rate was 1.5 per 100 person years in patients without device, and 1.9 per 100 person years in patients with device. Among patients not on OAC, presence of a cardiac device was associated with an increased risk of stroke or systemic embolism (HR 1.71 [1.24-2.35], P<0.01) whereas there was no association among patients treated with OAC (0.98 [0.75_1.28], p=ns) (Figure). Conclusions: Cardiac devices are associated with an increased risk of stroke or systemic embolism after transseptal ablation, but this risk is attenuated with post ablation OAC use. Anticoagulation should be considered for all patients with CIEDs post transseptal ablation, regardless of the presence of another compelling indication for anticoagulation.

Abstract Introduction: The risk of specific clinical subtype of breast cancer (defined by ER and HER2 status) among women in the general population who are carriers of germline pathogenic variants (PVs) in cancer predisposition genes is not well-defined. Methods: A total of 13,153 women with breast cancer (ER+/HER2-: 9381; ER+/HER2+: 1462; ER-/HER2+: 690; and ER-/HER2-: 1620) and 25,005 unaffected women (controls) from nine studies within the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium that were not enriched for family history or early onset disease were included in the present analysis. A multiplex amplicon-based panel was used to perform germline sequencing for cancer predisposition genes. Case-control associations for each of the four clinical subtype of breast cancer was performed for PVs in 5 common breast cancer predisposition genes (ATM, BRCA1, BRCA2, CHEK2 and PALB2) utilizing a logistic regression model adjusting for study, age at diagnosis, race/ethnicity and family history of breast cancer. Results: The frequency of PVs in 5 genes was 3.8% for ER+/HER2-, 6.2% for ER+/HER2+, 4.2% for ER-/HER2+ and 9.3% for ER-/HER2- subtypes. PVs in BRCA1 and BRCA2 were associated with high risk (Odds Ratio (OR) &gt;4) for all clinical subtypes of breast cancer, but the risk was highest (OR&gt;8) for ER-/HER2- breast cancer. PVs in PALB2 were associated with high risk (OR&gt;4) of ER-/HER2- and ER+/HER2+ subtypes and moderate risk (OR: 2-4) of ER+/HER2- breast cancer. Irrespective of the HER2 status, PVs in ATM were associated with a moderately increased risk (OR: 2-4) of ER+ breast cancer but the risk of ER- breast cancer was not elevated. In contrast, PVs in CHEK2 were associated with high risk (OR&gt;4) of ER+/HER2+ breast cancer and moderate risk (OR: 2-4) of ER+/HER2- and ER-/HER2+ breast cancer, but the risk of ER-/HER2- breast cancer was not elevated. Conclusions: This study provides population-based estimates of risk of specific clinical subtypes of breast cancer which will be useful for genetic counseling and targeting appropriate screening strategies in PV carriers based on subtype specific risks of breast cancer. Citation Format: Siddhartha Yadav, Chunling Hu, Nicholas J. Boddicker, Eric Polley, Steven Hart, Rohan Gnanaolivu, Jie Na, Hongyan Huang, Song Yao, Celine M. Vachon, Lauren Teras, Jack A. Taylor, Dale P. Sandler, Julie R. Palmer, Janet E. Olson, Susan Neuhausen, Elena Martinez, Sara Lindstroem, Loic Le Marchand, Charles Kooperberg, Christopher Haiman, Mia M. Gaudet, James V. Lacey, Kimberly A. Bertrand, Leslie Bernstein, Paul W. Auer, Christine Ambrosone, Jeffrey N. Weitzel, Peter Kraft, David E. Goldgar, Katherine L. Nathanson, Susan M. Domchek, Fergus J. Couch, CARRIERS Consortium. Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-09-01.

Abstract Nicotinamide adenine dinucleotide (NAD) levels decline during aging, contributing to physical and metabolic dysfunction. The NADase CD38 plays a key role in age‐related NAD decline. Whether the inhibition of CD38 increases lifespan is not known. Here, we show that the CD38 inhibitor 78c increases lifespan and healthspan of naturally aged mice. In addition to a 10% increase in median survival, 78c improved exercise performance, endurance, and metabolic function in mice. The effects of 78c were different between sexes. Our study is the first to investigate the effect of CD38 inhibition in naturally aged animals.

Abstract Background Pancreatic neuroendocrine tumors (pNETs) are rare cancers with outcomes determined by multiple factors including grade, stage, and clinical presentation. In this study, we aimed to determine the prognosis of patients with pNETs using a large population-based database. Materials and Methods In this population-based study, we identified patients with pNETs from the SEER 18 registry (2000-2016) using a combination of ICD-O-3 and histology codes. We calculated age-adjusted incidence rates using SEER*Stat 8.3.5. In addition, we analyzed overall survival (OS) using the Kaplan-Meier method, and investigated prognostic factors using a multivariable Cox proportional hazards model. Results A total of 8944 pNETs patients were identified. Annual incidence rates increased from 0.27 to 1.00 per 100 000. This was largely explained by an increase in number of patients diagnosed with localized disease in more recent years (2012-2016). Median OS was 68 months (95% CI [64, 73]) and 5-year OS rates in localized, regional, and metastatic disease were 83%, 67%, and 28%, respectively. There was a significant improvement in OS for patients diagnosed between 2009 and 2016 (median OS 85 months) compared with those diagnosed between 2000 and 2008 (median OS 46 months) (HR 0.66; 95% CI [0.62, 0.70]). This improvement in OS was consistent across all stages. Conclusions and Relevance This study shows a steady increase pNETs incidence with notable stage migration to earlier stages in recent years. This increase in incidence is accompanied by a significant improvement in survival across different disease stages.

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular disease development and outcomes, the need for more effective approaches to screening for risk factors and phenotypes in women is ever urgent. Public health surveillance and health care delivery systems now continuously generate massive amounts of data that could be leveraged to enable both screening of cardiovascular risk and implementation of tailored preventive interventions across a woman’s life span. However, health care providers, clinical guidelines committees, and health policy experts are not yet sufficiently equipped to optimize the collection of data on women, use or interpret these data, or develop approaches to targeting interventions. Therefore, we provide a broad overview of the key opportunities for cardiovascular screening in women while highlighting the potential applications of artificial intelligence along with digital technologies and tools.