Stratifying patients at the risk of heart failure hospitalization using existing device diagnostic thresholds

AbstractBackgroundHeart failure hospitalizations (HFHs) cost the US health care system ∼$20 billion annually. Identifying patients at risk of HFH to enable timely intervention and prevent expensive hospitalization remains a challenge. Implantable cardioverter defibrillators (ICDs) and cardiac resynchronization devices with defibrillation capability (CRT-Ds) collect a host of diagnostic parameters that change with HF status and collectively have the potential to signal an increasing risk of HFH. These device-collected diagnostic parameters include activity, day and night heart rate, atrial tachycardia/atrial fibrillation (AT/AF) burden, mean rate during AT/AF, percent CRT pacing, number of shocks, and intrathoracic impedance. There are thresholds for these parameters that when crossed trigger a notification, referred to as device observation, which gets noted on the device report. We investigated if these existing device observations can stratify patients at varying risk of HFH.MethodsWe analyzed data from 775 patients (age: 69 ± 11 year, 68% male) with CRT-D devices followed for 13 ± 5 months with adjudicated HFHs. HFH rate was computed for increasing number of device observations. Data were analyzed by both excluding and including intrathoracic impedance. HFH risk was assessed at the time of a device interrogation session, and all the data between previous and current follow-up sessions were used to determine the HFH risk for the next 30 days.Results2276 follow-up sessions in 775 patients were evaluated with 42 HFHs in 37 patients. Percentage of evaluations that were followed by an HFH within the next 30 days increased with increasing number of device observations. Patients with 3 or more device observations were at 42× HFH risk compared to patients with no device observation. Even after excluding intrathoracic impedance, the remaining device parameters effectively stratified patients at HFH risk.ConclusionAvailable device observations could provide an effective method to stratify patients at varying risk of heart failure hospitalization

A Comparison of Atrial Fibrillation Monitoring Strategies After Cryptogenic Stroke (from the Cryptogenic Stroke and Underlying AF Trial)

Ischemic stroke cause remains undetermined in 30% of cases, leading to a diagnosis of cryptogenic stroke. Paroxysmal atrial fibrillation (AF) is a major cause of ischemic stroke but may go undetected with short periods of ECG monitoring. The Cryptogenic Stroke and Underlying Atrial Fibrillation trial (CRYSTAL AF) demonstrated that long-term electrocardiographic monitoring with insertable cardiac monitors (ICM) is superior to conventional follow-up in detecting AF in the population with cryptogenic stroke. We evaluated the sensitivity and negative predictive value (NPV) of various external monitoring techniques within a cryptogenic stroke cohort. Simulated intermittent monitoring strategies were compared to continuous rhythm monitoring in 168 ICM patients of the CRYSTAL AF trial. Short-term monitoring included a single 24-hour, 48-hour, and 7-day Holter and 21-day and 30-day event recorders. Periodic monitoring consisted of quarterly monitoring through 24-hour, 48-hour, and 7-day Holters and monthly 24-hour Holters. For a single monitoring period, the sensitivity for AF diagnosis was lowest with a 24-hour Holter (1.3%) and highest with a 30-day event recorder (22.8%). The NPV ranged from 82.3% to 85.6% for all single external monitoring strategies. Quarterly monitoring with 24-hour Holters had a sensitivity of 3.1%, whereas quarterly 7-day monitors increased the sensitivity to 20.8%. The NPVs for repetitive periodic monitoring strategies were similar at 82.6% to 85.3%. Long-term continuous monitoring was superior in detecting AF compared to all intermittent monitoring strategies evaluated (p <0.001). Long-term continuous electrocardiographic monitoring with ICMs is significantly more effective than any of the simulated intermittent monitoring strategies for identifying AF in patients with previous cryptogenic stroke

Development and validation of a targeted gene sequencing panel for application to disparate cancers

Next generation sequencing has revolutionised genomic studies of cancer, having facilitated the development of precision oncology treatments based on a tumour’s molecular profile. We aimed to develop a targeted gene sequencing panel for application to disparate cancer types with particular focus on tumours of the head and neck, plus test for utility in liquid biopsy. The final panel designed through Roche/Nimblegen combined 451 cancer-associated genes (2.01 Mb target region). 136 patient DNA samples were collected for performance and application testing. Panel sensitivity and precision were measured using well-characterised DNA controls (n = 47), and specificity by Sanger sequencing of the Aryl Hydrocarbon Receptor Interacting Protein (AIP) gene in 89 patients. Assessment of liquid biopsy application employed a pool of synthetic circulating tumour DNA (ctDNA). Library preparation and sequencing were conducted on Illumina-based platforms prior to analysis with our accredited (ISO15189) bioinformatics pipeline. We achieved a mean coverage of 395x, with sensitivity and specificity of >99% and precision of >97%. Liquid biopsy revealed detection to 1.25% variant allele frequency. Application to head and neck tumours/cancers resulted in detection of mutations aligned to published databases. In conclusion, we have developed an analytically-validated panel for application to cancers of disparate types with utility in liquid biopsy

The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer

Abstract: Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors

CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers

Funder: Breast Cancer Now (BCN); doi: https://doi.org/10.13039/100009794Funder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289Funder: RCUK | Medical Research Council (MRC); doi: https://doi.org/10.13039/501100000265Funder: U.S. Department of Health & Human Services | National Institutes of Health (NIH)Funder: Wellcome Trust (Wellcome); doi: https://doi.org/10.13039/100004440Funder: EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013)); doi: https://doi.org/10.13039/100011199; Grant(s): HEALTH-F2-2009-223175, HEALTH-F2-2009-223175Funder: Genome Canada (Génome Canada); doi: https://doi.org/10.13039/100008762Funder: Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada); doi: https://doi.org/10.13039/501100000024Funder: Quebec Breast cancer Foundation Genome QuebecFunder: U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine (NLM); doi: https://doi.org/10.13039/100000092Funder: EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013))Funder: European Union’s Horizon 2020Funder: Deutsche Krebshilfe (German Cancer Aid); doi: https://doi.org/10.13039/501100005972Funder: BCAST - European Union’s Horizon 2020Funder: Breast Cancer Now; doi: https://doi.org/10.13039/501100007913Abstract: Background: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. Methods: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. Results: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (−49.2%, 95% CI −56.1% to −41.1%, P = 3.1 × 10–18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (−26.7%, 95% CI −39.4% to −11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82–0.91, P = 6.9 × 10–8). Conclusions: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women

Attractive Toxic Sugar Bait (ATSB) For Control of Mosquitoes and Its Impact on Non-Target Organisms: A Review

Mosquito abatement programs contend with mosquito-borne diseases, insecticidal resistance, and environmental impacts to non-target organisms. However, chemical resources are limited to a few chemical classes with similar modes of action, which has led to insecticide resistance in mosquito populations. To develop a new tool for mosquito abatement programs that control mosquitoes while combating the issues of insecticidal resistance, and has low impacts of non-target organisms, novel methods of mosquito control, such as attractive toxic sugar baits (ATSBs), are being developed. Whereas insect baiting to dissuade a behavior, or induce mortality, is not a novel concept, as it was first introduced in writings from 77 AD, mosquito baiting through toxic sugar baits (TSBs) had been quickly developing over the last 60 years. This review addresses the current body of research of ATSB by providing an overview of active ingredients (toxins) include in TSBs, attractants combined in ATSB, lethal effects on mosquito adults and larvae, impact on non-target insects, and prospects for the use of ATSB

An ensemble of features based deep learning neural network for reduction of inappropriate atrial fibrillation detection in implantable cardiac monitors

Background: Multiple studies have reported on classification of raw electrocardiograms (ECGs) using convolutional neural networks (CNNs). Objective: We investigated an application-specific CNN using a custom ensemble of features designed based on characteristics of the ECG during atrial fibrillation (AF) to reduce inappropriate AF detections in implantable cardiac monitors (ICMs). Methods: An ensemble of features was developed and combined to form an input signal for the CNN. The features were based on the morphological characteristics of AF, incoherence of RR intervals, and the fact that AF begets more AF. A custom CNN model and the RESNET18 model were trained using ICM-detected AF episodes that were adjudicated to be true AF or false detections. The trained models were evaluated using a test dataset from independent patients. Results: The training and validation datasets consisted of 31,757 AF episodes (2516 patients) and 28,506 false episodes (2126 patients). The validation set (20% randomly chosen episodes of each type) had an area under the curve of 0.996 for custom CNN (0.993 for RESNET18). Thresholds were chosen to obtain a relative sensitivity and specificity of 99.2% and 92.8%, respectively (99.2% and 87.9% for RESNET18, respectively). The performance in the independent test set (4546 AF episodes from 418 patients; 5384 false episodes from 605 patients) showed an area under the curve of 0.993 (0.991 for RESNET18) and relative sensitivity and specificity of 98.7% and 91.4%, respectively, at chosen thresholds (98.9% and 88.2% for RESNET18, respectively). Conclusion: An ensemble of features-based CNNs was developed that reduced inappropriate AF detection in ICMs by over 90% while preserving sensitivity