for the Critical Care EEG Monitoring Research Consortium IMPORTANCE Periodic and rhythmic electroencephalographic patterns have been associated with risk of seizures in critically ill patients. However, specific features that confer higher seizure risk remain unclear.OBJECTIVE To analyze the association of distinct characteristics of periodic and rhythmic patterns with seizures. DESIGN, SETTING, AND PARTICIPANTSWe reviewed electroencephalographic recordings from 4772 critically ill adults in 3 academic medical centers from February 2013 to September 2015 and performed a multivariate analysis to determine features associated with seizures. INTERVENTIONS Continuous electroencephalography.MAIN OUTCOMES AND MEASURES Association of periodic and rhythmic patterns and specific characteristics, such as pattern frequency (hertz), Plus modifier, prevalence, and stimulation-induced patterns, and the risk for seizures. RESULTSOf the 4772 patients included in our study, 2868 were men and 1904 were women. Lateralized periodic discharges (LPDs) had the highest association with seizures regardless of frequency and the association was greater when the Plus modifier was present (58%; odds ratio [OR], 2.00, P < .001). Generalized periodic discharges (GPDs) and lateralized rhythmic delta activity (LRDA) were associated with seizures in a frequency-dependent manner (1.
Background The prevalence of hepatitis C virus (HCV) in United States prisoners is high; however, HCV testing and treatment is rare. Infected inmates released back into society contribute to the spread of HCV in the general population. Routine hepatitis screening of inmates followed by treatment with new therapies offers hope to reduce ongoing HCV transmission. Objective To evaluate the health and economic impact of HCV screening and treatment in prisons on the HCV epidemic in the society. Design An agent-based microsimulation model of transmission and progression of HCV. Data Sources Published literature. Target population Population in US prisons and general community. Time horizon 30 years. Perspective Societal. Interventions Risk-based and universal opt-out hepatitis C screening in prisons followed by treatment in a portion of patients. Outcome measures Prevention of HCV transmission and associated-disease in prisons and society, costs, quality-adjusted life years (QALYs), incremental cost-effectiveness ratio (ICER), and total prison budget. Results of Base-Case Analysis Implementing risk-based and opt-out screening could diagnose 41 900–122 700 new HCV cases in the next 30 years in prisons. Compared with no screening, these scenarios could prevent 5500–12 700 new HCV infections caused by releasees, where about 90% of averted infections would have occurred outside of prisons. HCV screening could also prevent 4200–11 700 liver-related deaths. The ICERs of screening scenarios were between $19 600–$29 200/QALY, and the respective 1st year prison budget were between $900 and $1150 million. Prisons would require an additional 12.4% of their current healthcare budget to implement such interventions. Results of Sensitivity Analysis Results were sensitive to the time horizon; and ICERs otherwise remained below $50 000 per QALY. Limitations Data on transmission network, re-infection rate and opt-out HCV screening rate are lacking. Conclusions Universal opt-out HCV screening in prisons is highly cost-effective and would reduce HCV transmission and HCV-associated diseases primarily in the outside community. Investing in US prisons to manage hepatitis C is a strategic approach to address the current epidemic.
Significance This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.
Breast cancer is the most common nonskin cancer and the second leading cause of cancer death in U.S. women. Although mammography is the most effective modality for breast cancer screening, it has several potential risks, including high falsepositive rates. Therefore, the balance of benefits and risks, which depend on personal characteristics, is critical in designing a mammography screening schedule. In contrast to prior research and existing guidelines that consider population-based screening recommendations, we propose a personalized mammography screening policy based on the prior screening history and personal risk characteristics of women. We formulate a finite-horizon, partially observable Markov decision process (POMDP) model for this problem. Our POMDP model incorporates two methods of detection (self or screen), age-specific unobservable disease progression, and age-specific mammography test characteristics. We solve this POMDP optimally after setting transition probabilities to values estimated from a validated microsimulation model. Additional published data is used to specify other model inputs such as sensitivity and specificity of test results. Our results show that our proposed personalized screening schedules outperform the existing guidelines with respect to the total expected quality-adjusted life years, while significantly decreasing the number of mammograms and false-positives. We also report the lifetime risk of developing undetected invasive cancer associated with each screening scenario.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.