Predictive modeling pilot project for readmissions in heart failure patients with preserved ejection fraction

Objectives: To pilot a predictive model evaluating hospital readmissions for heart failure with preserved ejection fraction (HFpEF) patients and the association with management by a cardiologist, number of comorbidities, and type of treatment. Methods: This is a retrospective, observational study of claims data to evaluate the effect of various factors: age, gender, provider, baseline inpatient admissions, comorbidities and baseline drug treatment classes (e.g. antiarrhythmic, beta blocker, calcium channel blocker, diuretic, RAAS-inhibiting agents) on number of readmissions, time to readmission, and odds of readmission. Patients ≥18 years of age with an inpatient admission with a primary discharge diagnosis of HFpEF between October 1, 2011 and September 30, 2014 were identified and data were assessed 1-year pre- and post-hospitalization. Patient characteristics were described, and patients treated by a cardiologist were compared to those who were not. Multivariate regression and Cox proportional hazard models were used to assess the association of all-cause and heart failure-related readmissions adjusting for demographic and clinical covariates. Results: A total of 264 patients with HFpEF were identified (60.2% female; mean age of 79 years (SD 10.8) of which 77 [29%] did not see a cardiologist. Patients who saw a cardiologist were more likely to be male and had a greater number of comorbidities including diabetes, dyslipidemia, hypertension, coronary heart disease, cardiomyopathy, and valvular heart disease than those without cardiologist. Overall, 51% of the patients had an all-cause readmission and 15% had an HF-related readmission. Patients who had a cardiologist were associated with more all-cause readmissions (IRR of 2.21, p=0.0003) and a shorter time to all-cause readmissions (HR of 1.91, p=0.004). Being on diuretics was associated with more heart failure-related readmissions (IRR of 2.84, p=0.0301). A higher number of all-cause readmission was associated with patients having more comorbidities (IRR of 1.19, p=0.0038). Conclusion: This study demonstrated that all-cause and heart failure-related readmission is high in patients with HFpEF. The pilot predictive models show that various factors associated with higher risk patients, such as those with cardiologist management, more comorbidities, and use of diuretics, may be associated with increased hospital readmissions.Pharmaceutical Science

MultiRobustBench: Benchmarking Robustness Against Multiple Attacks

The bulk of existing research in defending against adversarial examples focuses on defending against a single (typically bounded Lp-norm) attack, but for a practical setting, machine learning (ML) models should be robust to a wide variety of attacks. In this paper, we present the first unified framework for considering multiple attacks against ML models. Our framework is able to model different levels of learner's knowledge about the test-time adversary, allowing us to model robustness against unforeseen attacks and robustness against unions of attacks. Using our framework, we present the first leaderboard, MultiRobustBench, for benchmarking multiattack evaluation which captures performance across attack types and attack strengths. We evaluate the performance of 16 defended models for robustness against a set of 9 different attack types, including Lp-based threat models, spatial transformations, and color changes, at 20 different attack strengths (180 attacks total). Additionally, we analyze the state of current defenses against multiple attacks. Our analysis shows that while existing defenses have made progress in terms of average robustness across the set of attacks used, robustness against the worst-case attack is still a big open problem as all existing models perform worse than random guessing.Comment: ICML 202

Activation of Nlrp3 Inflammasomes Enhances Macrophage Lipid-Deposition and Migration: Implication of a Novel Role of Inflammasome in Atherogenesis

Although Nlrp3 inflammasome activation in macrophages has been shown to be critical for the development of atherosclerosis upon atherogenic stimuli, it remains unknown whether activated Nlrp3 inflammasomes by other non-atherogenic stimuli induce alterations in macrophages that may contribute in the concert with other factors to atherogenesis. Thus, the present study tested the hypothesis that activation of Nlrp3 inflammasomes by ATP, which is a classical non-lipid danger stimulus, enhances the migration of macrophage and increases lipids deposition in macrophages accelerating foam cell formation. We first demonstrated that extracellular ATP (2.5 mM) markedly increased the formation and activation of Nlrp3 inflammasomes in bone marrow macrophages (BMMs) from wild type (Asc+/+) mice resulting in activation of caspase-1 and IL-1β production. In these Asc+/+ macrophages, such stimulation of inflammasomes by non-lipid ATP was similar to those induced by atherogenic stimuli such as cholesterol crystals or 7-ketocholesterol. Both non-lipid and lipid forms of stimuli induced formation and activation of Nlrp3 inflammasomes, which were prevented by Asc gene deletion. Interestingly, Asc+/+ BMMs had dramatic lipids accumulation after stimulation with ATP. Further, we demonstrated that large amount of cholesterol was accumulated in lysosomes of Asc+/+ BMMs when inflammasomes were activated by ATP. Such intracellular and lysosomal lipids deposition was not observed in Asc−/− BMMs and also prevented by caspase-1 inhibitor WEHD. In addition, in vitro and in vivo experiments revealed that migration of Asc+/+ BMMs increased due to stimulation of Nlrp3 inflammasomes, which was markedly attenuated in Asc−/− BMMs. Together, these results suggest that activation of Nlrp3 inflammasomes remarkably increases the susceptibility of macrophages to lipid deposition and their migration ability. Such novel action of inflammasomes may facilitate entry or retention of macrophages into the arterial wall, where they form foam cells and ultimately induce atherosclerosis

Perceptions and Barriers of Survivorship Care in Asia: Perceptions From Asian Breast Cancer Survivors.

PurposeWith the long-term goal to optimize post-treatment cancer care in Asia, we conducted a qualitative study to gather in-depth descriptions from multiethnic Asian breast cancer survivors on their perceptions and experiences of cancer survivorship and their perceived barriers to post-treatment follow-up.MethodsTwenty-four breast cancer survivors in Singapore participated in six structured focus group discussions. The focus group discussions were voice recorded, transcribed verbatim, and analyzed by thematic analysis.ResultsBreast cancer survivors were unfamiliar with and disliked the term "survivorship," because it implies that survivors had undergone hardship during their treatment. Cognitive impairment and peripheral neuropathy were physical symptoms that bothered survivors the most, and many indicated that they experienced emotional distress during survivorship, for which they turned to religion and peers as coping strategies. Survivors indicated lack of consultation time and fear of unplanned hospitalization as main barriers to optimal survivorship care. Furthermore, survivors indicated that they preferred receipt of survivorship care at the specialty cancer center.ConclusionBudding survivorship programs in Asia must take survivor perspectives into consideration to ensure that survivorship care is fully optimized within the community

False Data Injection Attack on Atmospheric Electric Field in Thunderstorm Warning

Thunderstorm warning plays an important role in lightning prevention and disaster mitigation. In practical applications, thunderstorm warning system is also vulnerable to attacks, such as False Data Injection Attack (FDIA). However, there is a lack of research on False Data Injection Attack for thunderstorm warning. Therefore, this paper put forwards a FDIA method based on principal component analysis (PCA) for atmospheric electric field (AEF), which is usually used for thunderstorm warning. In the FDIA scenario, the AEF-based thunderstorm warning algorithm is also introduced with electric field differential index (EFDI). Finally, experiments are conducted based on AEF data collected by an atmospheric electric field meter (AEFM) about the real thunderstorm. The experimental results show that FDIA seriously interferes with the results of the AEF-based thunderstorm warning

The mouse and ferret models for studying the novel avian-origin human influenza A (H7N9) virus.

BackgroundThe current study was conducted to establish animal models (including mouse and ferret) for the novel avian-origin H7N9 influenza virus.FindingsA/Anhui/1/2013 (H7N9) virus was administered by intranasal instillation to groups of mice and ferrets, and animals developed typical clinical signs including body weight loss (mice and ferrets), ruffled fur (mice), sneezing (ferrets), and death (mice). Peak virus shedding from respiratory tract was observed on 2 days post inoculation (d.p.i.) for mice and 3-5 d.p.i. for ferrets. Virus could also be detected in brain, liver, spleen, kidney, and intestine from inoculated mice, and in heart, liver, and olfactory bulb from inoculated ferrets. The inoculation of H7N9 could elicit seroconversion titers up to 1280 in ferrets and 160 in mice. Leukopenia, significantly reduced lymphocytes but increased neutrophils were also observed in mouse and ferret models.ConclusionsThe mouse and ferret model enables detailed studies of the pathogenesis of this illness and lay the foundation for drug or vaccine evaluation

A Five-Year Prospective Evaluation of Anticholinergic Cognitive Burden and Falls in the Malaysian Elders Longitudinal Research (MELoR) study

Acknowledgements This third-wave follow-up interviews were funded by the Ministry of Higher Education Fundamental Research Grant Scheme (FRGS/1/2019/SKK02/UM/01/1). The Malaysian Elders Longitudinal Research study is now part of the Transforming Cognitive Frailty into Later-Life Self-Sufficiency (AGELESS) study which merges two existing longitudinal studies of ageing and is funded by the Ministry of Higher Education Long-Term Research Grant Scheme (LRGS/1/2019/UM/01/1/1). We would also like to acknowledge the hard work and dedication of the MELoR investigators and research team.Peer reviewedPostprin