Categories Of Likelihood Research Articles

Best Practices for Elevation-Based Assessments of Sea-Level Rise and Coastal Flooding Exposure

Elevation data are critical for assessments of sea-level rise and coastal flooding exposure. Previous research has demonstrated that the quality of data used in elevation-based assessments must be well understood and applied to properly model potential impacts. The cumulative vertical uncertainty of the input elevation data substantially controls the minimum increments of sea-level rise and the minimum planning horizons that can be effectively used in assessments. For regional, continental, or global assessments, several digital elevation models (DEMs) are available for the required topographic information to project potential impacts of increased coastal water levels, whether a simple inundation model is used or a more complex process-based or probabilistic model is employed. When properly characterized, the vertical accuracy of the DEM can be used to report assessment results with the uncertainty stated in terms of a specific confidence level or likelihood category. An accuracy evaluation has been conducted of global DEMs to quantify their inherent vertical uncertainty to demonstrate how accuracy information should be considered when planning and implementing a sea-level rise or coastal flooding assessment. The evaluation approach includes comparison of the DEMs with high-accuracy geodetic control points as the independent reference data over a variety of coastal relief settings. The global DEMs evaluated include SRTM, ASTER GDEM, ALOS World 3D, TanDEM-X, NASADEM, and MERIT. High-resolution, high-accuracy DEM sources, such as airborne lidar and stereo imagery, are also included to give context to the results from the global DEMs. The accuracy characterization results show that current global DEMs are not adequate for high confidence mapping of exposure to fine increments (< 1 m) of sea-level rise or with shorter planning horizons (< 100 years), but they are suitable for general delineation of low elevation coastal zones. In addition to the best practice of rigorous accounting for vertical uncertainty, other recommended procedures are presented for delineation of different types of impact areas (marine and groundwater inundation) and use of regional relative sea-level rise scenarios. The requirement remains for a freely available, high-accuracy, high-resolution global elevation model that supports quantitative sea-level rise and coastal inundation assessments at high confidence levels.

Intention to Participate in Group Prenatal Care: Moving Beyond Yes or No.

Group prenatal care (GPNC) is an alternative model to traditional individual care and may improve public health outcomes. Prior studies suggest that interest in GPNC varies widely and few studies have examined characteristics predictive of interest in this model. The purpose of this study was to inform GPNC recruitment efforts by examining likelihood of participation delineated by characteristics and GPNC perceptions. Pregnant participants received information about GPNC then completed a survey measuring demographic, psychosocial, and reproductive characteristics, likelihood to participate in GPNC, and factors influencing selections. Respondents expressed varied levels of likelihood to participate in GPNC; 16.2% low likelihood, 44.9% moderate likelihood, and 38.9% high likelihood. Characteristics were similar between groups, and thus their use is not recommended when targeting recruitment efforts. Benefits outweighed barriers and threats for the high likelihood category, barriers and threats outweighed benefits for the low likelihood category, and benefits, barriers, and threats were balanced for the moderate likelihood category. Accurately assessing likelihood of participating in GPNC efficiently identifies individuals who are clearly either going to decline or participate, as well as promotes targeted recruitment efforts directed at those who are ambivalent. Understanding and addressing perceived benefits, barriers, and threats supports effective GPNC recruitment.

DEVELOPMENT OF A NOVEL MULTI-BIOMARKER ASSESSMENT SCORE FOR ALZHEIMER’S DISEASE

There is an unmet need for laboratory tools that detect Alzheimer's disease (AD) in its early stages. Biomarkers in cerebrospinal fluid (CSF) have shown great potential in fulfilling this need. The ratio of the peptides β-amyloid (Aβ) 40 and 42 in CSF predicts disease progression. The levels of apolipoprotein E (ApoE) in CSF, and the presence of 1 or more ε4 alleles (APOE4), indicate disease likelihood. Here, we describe a novel algorithm that combines these biomarkers. We have used the algorithm to develop an assessment score that categorizes an individual's likelihood of having AD as higher, lower, or intermediate. Aβ42/ Aβ40 ratio, APOE4allele count, and total ApoE (μg/mL) were determined using mass spectrometry in a training set of 151 specimens from clinically-diagnosed AD and non-AD patients (supplied by UC San Diego ADRC Neuropathology Core and Brain Bank). A diagnosis of AD was based on imaging and cognition tests. The results from the training set were used to develop a logistic regression model. The linear predictor from the regression model was used to create an AD likelihood score. The score was partitioned into 3 groups: higher, intermediate, and lower likelihood. The higher likelihood threshold was selected to allow for a 10% false positive rate, while the lower likelihood threshold was selected to allow for a 10% false negative rate. We validated the model in an initially-blinded separate test cohort of 159 patients independently diagnosed as AD or non-AD using combined genomic and immunochemical methodology. Of the 159 test subjects, 79 were previously diagnosed as AD and 80 were diagnosed as non-AD. Categorization based on logistic regression analysis results is presented in Table 1. Of those in the higher likelihood category, 85.7% (36/42) had at least one APOE4 allele: 47.6% ε2/ε4 or ε3/ε4 (20/42), and 38.1% ε4/ε4 (16/42). The remaining higher likelihood samples, 14.3% (6/42), were APOE4-negative. We have devised a logistic regression model using biomarkers in CSF that has potential to stratify the likelihood of Alzheimer's disease.

Making sense of risk tolerance criteria

Risk analysts spend a great deal of effort quantifying risk, both in terms of consequence and likelihood. But until risk is compared against risk tolerance criteria (RTC), it impossible to know whether that risk is too high or not, and if it is too high, by how much it must be reduced to become tolerable. RTC drive the allocation of finite resources for risk reduction. Rational RTC lead to rational allocation of resources while irrational RTC lead to misallocation of resources and ultimately, poorer safety. Most practitioners acknowledge the need for RTC but do not discuss how they are developed. While a few countries dictate RTC, most governments, including that of the United States, leave it to organizations to establish and justify their own RTC.Traditional PHA risk matrices are flawed in that they frequently employ consequence severity categories for a variety of impact vectors (safety, community, environment, etc.) that are neither internally consistent nor consistent in relationship to each other. They are also flawed in that they use likelihood categories that are not logarithmic, and have risk categories that consider risk in terms of the urgency to do something—anything—rather than have risk categories that consider risk in terms of risk reduction.This work reviews a methodology based on impact equivalency to evaluate whether RTC are structurally sound, and goes to on to explore a variety of risk benchmarks and shows how to infer RTC from them. Finally, the work proposes a methodology for addressing the historically poor equivalency between safety and environmental RTC.

New York City Panel on Climate Change 2015 Report. Chapter 1: Climate observations and projections.

Radley Horton,1,a Daniel Bader,1,a Yochanan Kushnir,2 Christopher Little,3 Reginald Blake,4 and Cynthia Rosenzweig5 1Columbia University Center for Climate Systems Research, New York, NY. 2Ocean and Climate Physics Department, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY. 3Atmospheric and Environmental Research, Lexington, MA. 4Physics Department, New York City College of Technology, CUNY, Brooklyn, NY. 5Climate Impacts Group, NASA Goddard Institute for Space Studies; Center for Climate Systems Research, Columbia University Earth Institute, New York, NY

Workplace air measurements and likelihood of exposure to manufactured nano-objects, agglomerates, and aggregates

Manufactured nano-objects, agglomerates, and aggregates (NOAA) may have adverse effect on human health, but little is known about occupational risks since actual estimates of exposure are lacking. In a large-scale workplace air-monitoring campaign, 19 enterprises were visited and 120 potential exposure scenarios were measured. A multi-metric exposure assessment approach was followed and a decision logic was developed to afford analysis of all results in concert. The overall evaluation was classified by categories of likelihood of exposure. At task level about 53 % showed increased particle number or surface area concentration compared to ‘‘background’’ level, whereas 72 % of the TEM samples revealed an indication that NOAA were present in the workplace. For 54 out of the 120 task-based exposure scenarios, an overall evaluation could be made based on all parameters of the decision logic. For only 1 exposure scenario (approximately 2 %), the highest level of potential likelihood was assigned, whereas in total in 56 % of the exposure scenarios the overall evaluation revealed the lowest level of likelihood. However, for the remaining 42 % exposure to NOAA could not be excluded.

The coronary calcium treadmill test: A new approach to the initial workup of patients with suspected coronary artery disease

Due to the growth of cardiac testing and increasing cost of cardiovascular healthcare, the development of more cost-effective strategies has now become a dominant issue regarding future utilization of cardiac imaging procedures. To that end, we review the potential of combining two relatively inexpensive tests, the coronary artery calcium (CAC) scan and exercise electrocardiography (ECG), as a first-line test for the workup of patients with suspected coronary artery disease (CAD). The CAC scan was initially introduced as a screening test for CAD, based on data indicating that it is a specific marker for atherosclerosis, predicts clinical risk in accordance with the magnitude of CAC, and provides incremental information for prognostic risk compared to more readily available clinical data. However, CAC scores also predict the likelihood of observing myocardial ischemia among patients undergoing exercise myocardial perfusion SPECT imaging. Exercise ECG predicts clinical events according to the ST-segment response and according to functional exercise capacity, with the latter parameter as a stronger predictor of clinical outcomes. Like CAC scores, exercise functional capacity can also be used to predict the likelihood of ischemia since ischemia diminishes proportionally with increasing exercise capacity. Recent work indicates that when patients are designated by Bayesian analyses into low, intermediate, and high likelihood categories for CAD based on clinical data and the response to exercise ECG, the frequency of inducible myocardial ischemia is very low among both low and intermediate CAD likelihood patients who have a CAC score <400. Future studies are needed to investigate what clinical factors might further modify the CAC-ischemia relationship. On the basis of current data, an initial testing strategy that employs the combined calcium treadmill test has the inherent ability to designate a substantial number of intermediate likelihood patients who would not require further testing due to relatively low CAC scores and reasonable functional capacity.

Initial state of single spines affects probability of induction of cerebellar long term depression in a stochastic model

Cerebellar long-term depression (LTD) is a type of synaptic plasticity which shows a robust and persistent decrease in the synaptic transmission between parallel fibers (PF) and Purkinje cells (PC), expressed as a reduction in the number of synaptic AMPA receptors. Our lab recently developed a stochastic model of the LTD signaling network, including a PKC-ERK-cPLA2 positive feedback loop and mechanisms of AMPAR trafficking, and tuned the model to replicate calcium uncaging experiments [1]. Probabilistically, signaling activity switches between two discrete stable states (LTD or non-LTD). In single spines, the probability of LTD occurrence is only modulated by the concentration and duration of the signal used to trigger it, and inputs with the same magnitude give rise to one of two responses. The detailed kinetic model of the signaling and trafficking network involved in the induction of cerebellar LTD was developed based on extensive experimental data. The model was solved stochastically and deterministically using STEPS (http://steps.sourceforge.net/), a well validated simulator that implements the Stochastic Simulation Algorithm (SSA)[2]. The reasons for the bistable behavior in single spines is not fully understood. Molecular memory of the compartment, i.e. initial state of molecules before calcium injection, may play a role in altering the probability of a spine to undergo LTD induction or not. We address the possible effects of this initial state on the observed bistable behavior quantitatively. Preliminary analysis of these initial conditions for several simulations lead to their categorization on the basis of LTD probability observed for a particular calcium concentration and pulse duration (for simplicity we named them as High LTD likelihood, Normal LTD likelihood and Low LTD likelihood). We then confirmed these categories for different calcium conditions. The probability of LTD induction has a dependence on calcium pulse duration well-described by the Hill equation. The High and Normal LTD likelihood cases showed similar characteristics, though the Low LTD likelihood category showed different Hill parameters and also didn't saturate at 100 percent. Observations when varying the time before calcium input showed that the High and Normal LTD likelihood states exist only on the order of minutes and dissipate afterwards. In depth understanding of these different initial states may give better insights into the underlying molecular mechanisms causing bistable behavior. This is an important phenomena, as it is also observed in other forms of long-term synaptic plasticity and in many other biological processes.

Prognostic value of automated vs visual analysis for adenosine stress myocardial perfusion SPECT in patients without prior coronary artery disease: A case-control study

PurposeWe aimed to evaluate the prognostic value of automated quantitative hypoperfusion parameters derived from adenosine stress myocardial perfusion SPECT (MPS) for predicting sudden or cardiac death (CD) in case-controlled patients with suspected coronary artery disease (CAD). MethodsWe considered patients with available adenosine stress Tc-99m sestamibi MPS scans and follow-up information. 81 CD patients from a registry of 428 patients documented by the National Death Index were directly matched in a retrospective case-control design to patients without CD by key clinical parameters (age by deciles, gender, no early revascularization, pre-test likelihood categories, diabetes, and chest pain symptoms). Multivariable analysis of stress MPS total perfusion deficit (STPD) and major clinical confounders were used as predictors of CD. Visual 17-segment summed stress segmental scores (VSSS) obtained by an expert reader, were compared to STPD. ResultsCD patients had higher stress hypoperfusion measures compared to controls [STPD: 7.0% vs 3.6% (P < .05), VSSS: 5.3 vs 2.1 (P < .05)]. By univariate analysis, STPD and VSSS have similar predictive power (the areas under receiver operator characteristics curves: STPD = 0.64, VSSS = 0.63; Kaplan-Meier models: χ2 = 7.59, P = .0059 for STPD and χ2 = 11.10, P = .0009 for VSSS). The multiple Cox proportional hazards regression models with continuous perfusion measures showed that STPD had similar power to normalized VSSS as a predictor for CD (χ2 = 4.92; P = .027) vs (χ2 = 8.90; P = .003). ConclusionsQuantitative analysis is comparable to expert visual scoring in predicting CD in a case-controlled study.

Letter to the Editor regarding the article 'The effect of applying NICE guidelines for the investigation of stable chest pain on out-patient cardiac services in the UK'

Sir, We read with interest the observations made by Patterson et al .1 The study determines the likelihood of coronary artery disease (CAD) in ALL subjects using Table 1 of the National Institute of Health and Clinical Excellence (NICE) Clinical Guidance 95 (CG95) and reports the number of subjects in each likelihood category. This is at odds with guidance which states that the likelihood of CAD should be estimated in people without confirmed CAD in whom stable angina cannot be diagnosed or excluded based on clinical assessment alone. The authors do not report the number of patients with confirmed CAD and consequently do not exclude these patients when analysing the likelihood …

ウラン加工施設を対象とした総合安全解析手法の開発

The integrated safety analysis (ISA) procedure has been developed to apply risk-informed regulation to uranium fuel fabrication and enrichment facilities. The major development efforts are as follows: (a) preparing the risk level matrix as an index for items-relied-on-for-safety (IROFS) identification, (b) defining requirements of IROFS, and (c) determining methods of IROFS importance based on the results of risk- and scenario-based analyses. For the risk level matrix, the consequence and likelihood categories have been defined by taking into account the Japanese regulatory laws, rules, and safety standards. The trial analyses using the developed procedure have been performed for several representative processes of the reference uranium fuel fabrication and enrichment facilities. This paper presents the results of the ISA for the sintering process of the reference fabrication facility. The results of the trial analyses have demonstrated the applicability of the procedure to the risk-informed regulation of these facilities.

Network-based scoring system for genome-scale metabolic reconstructions

BackgroundNetwork reconstructions at the cell level are a major development in Systems Biology. However, we are far from fully exploiting its potentialities. Often, the incremental complexity of the pursued systems overrides experimental capabilities, or increasingly sophisticated protocols are underutilized to merely refine confidence levels of already established interactions. For metabolic networks, the currently employed confidence scoring system rates reactions discretely according to nested categories of experimental evidence or model-based likelihood.ResultsHere, we propose a complementary network-based scoring system that exploits the statistical regularities of a metabolic network as a bipartite graph. As an illustration, we apply it to the metabolism of Escherichia coli. The model is adjusted to the observations to derive connection probabilities between individual metabolite-reaction pairs and, after validation, to assess the reliability of each reaction in probabilistic terms. This network-based scoring system uncovers very specific reactions that could be functionally or evolutionary important, identifies prominent experimental targets, and enables further confirmation of modeling results.ConclusionsWe foresee a wide range of potential applications at different sub-cellular or supra-cellular levels of biological interactions given the natural bipartivity of many biological networks.

Self-reported neurological symptoms in relation to CO emissions due to problem gas appliance installations in London: a cross-sectional survey

BackgroundPrevious research by the authors found evidence that up to 10% of particular household categories may be exposed to elevated carbon monoxide (CO) concentrations from poor quality gas appliance installations. The literature suggests certain neurological symptoms are linked to exposure to low levels of CO. This paper addresses the hypothesis that certain self-reported neurological symptoms experienced by a householder are linked to an estimate of their CO exposure.MethodsBetween 27 April and 27 June 2006, 597 homes with a mains supply of natural gas were surveyed, mainly in old, urban areas of London. Qualified gas engineers tested all gas appliances (cooker, boiler, gas fire, and water heater) and reported, according to the Gas Industry Unsafe Situations Procedure, appliances considered At Risk (AR), Immediately Dangerous (ID) or Not to Current Standards (NCS). Five exposure risk categories were defined based on measurement of CO emitted by the appliance, its features and its use, with "high or very high" exposure category where occupants were considered likely to be exposed to levels greater than 26 ppm for one hour. The prevalence of symptoms at each level of exposure was compared with that at lowest level of exposure.ResultsOf the households, 6% were assessed as having a "high or very high" risk of exposure to CO. Of the individuals, 9% reported at least one neurological symptom. There was a statistically significant association between "high or very high" exposure risk to CO and self-reported symptoms compared to "no exposure" likelihood, for households not in receipt of benefit, controlling for "number of residents" and presence of pensioners, OR = 3.23 (95%CI: 1.28, 8.15). Risk ratios across all categories of exposure likelihood indicate a dose-response pattern. Those households in receipt of benefit showed no dose-response pattern.ConclusionThis study found an association between risk of CO exposure at low concentration, and prevalence of self-reported neurological symptoms in the community for those households not in receipt of benefit. As health status was self-reported, this association requires further investigation.

Data Augmentation Algorithms for Detecting Conserved Domains in Protein Sequences: A Comparative Study

Protein conserved domains are distinct units of molecular structure, usually associated with particular aspects of molecular function such as catalysis or binding. These conserved subsequences are often unobserved and thus in need of detection. Motif discovery methods can be used to find these unobserved domains given a set of sequences. This paper presents the data augmentation (DA) framework that unifies a suite of motif-finding algorithms through maximizing the same likelihood function by imputing the unobserved data. The data augmentation refers to those methods that formulate iterative optimization by exploiting the unobserved data. Two categories of maximum likelihood based motif-finding algorithms are illustrated under the DA framework. The first is the deterministic algorithms that are to maximize the likelihood function by performing an iteratively optimal local search in the alignment space. The second is the stochastic algorithms that are to iteratively draw motif location samples via Monte Carlo simulation and simultaneously keep track of the superior solution with the best likelihood. As a result, four DA motif discovery algorithms are described, evaluated, and compared by aligning real and simulated protein sequences.

Clozapine-Related Myocarditis and Cardiomyopathy in an Australian Metropolitan Psychiatric Service

Myocarditis and cardiomyopathy are rarely reported complications of clozapine treatment. The incidence of clozapine-related myocarditis has been variably reported at between 0.03% and 0.19% of initiations and cardiomyopathy has been reported even less commonly. In our Brisbane-based service, nine of 94 patients initiated on clozapine over the previous 3 years appeared to have experienced myocarditis or cardiomyopathy. The unique co-location of our service with a major cardiothoracic hospital facilitated a review of identified cases to inform decisions regarding clozapine treatment and rechallenge in this service. Cases were identified by survey of psychiatric and cardiac medical staff at The Prince Charles Hospital and subjected to re-evaluation by a multidiscipline consensus panel. The panel compared cases to international reports and identified the clinical features that supported a diagnosis of clozapine-related myocarditis or cardiomyopathy. This process resulted in the stratification of the nine cases into the following categories of diagnostic likelihood: three highly probable, three probable, and two possible cases of clozapine-related myocarditis, and one possible case of clozapine-related cardiomyopathy. Successful clozapine rechallenge/continuation was undertaken in two patients and the panel agreed that this was a viable future option for several other patients. Findings of the panel review supported the initial clinical diagnoses. This confirmed that there was an apparent high incidence of clozapine-related myocarditis within this service, for which there was no clear reason. Mechanisms underlying clozapine-related myocarditis and cardiomyopathy, as well as successful clozapine continuation and rechallenge were considered, but definitive explanations remain unknown. This review highlighted the clinician's role in post-marketing drug surveillance to guide rational management of suspected adverse drug effects.

Clozapine-related myocarditis and cardiomyopathy in an Australian metropolitan psychiatric service

Myocarditis and cardiomyopathy are rarely reported complications of clozapine treatment. The incidence of clozapine-related myocarditis has been variably reported at between 0.03% and 0.19% of initiations and cardiomyopathy has been reported even less commonly. In our Brisbane-based service, nine of 94 patients initiated on clozapine over the previous 3 years appeared to have experienced myocarditis or cardiomyopathy. The unique co-location of our service with a major cardiothoracic hospital facilitated a review of identified cases to inform decisions regarding clozapine treatment and rechallenge in this service.Cases were identified by survey of psychiatric and cardiac medical staff at The Prince Charles Hospital and subjected to re-evaluation by a multidiscipline consensus panel. The panel compared cases to international reports and identified the clinical features that supported a diagnosis of clozapine-related myocarditis or cardiomyopathy.This process resulted in the stratification of the nine cases into the following categories of diagnostic likelihood: three highly probable, three probable, and two possible cases of clozapine-related myocarditis, and one possible case of clozapine-related cardiomyopathy. Successful clozapine rechallenge/continuation was undertaken in two patients and the panel agreed that this was a viable future option for several other patients.Findings of the panel review supported the initial clinical diagnoses. This confirmed that there was an apparent high incidence of clozapine-related myocarditis within this service, for which there was no clear reason. Mechanisms underlying clozapine-related myocarditis and cardiomyopathy, as well as successful clozapine continuation and rechallenge were considered, but definitive explanations remain unknown. This review highlighted the clinician's role in post-marketing drug surveillance to guide rational management of suspected adverse drug effects.

Exploring the demand for a voluntary Medicare prescription drug benefit.

The purposes of this study were (1) to assess the utility of the economic theory of demand for insurance for modeling voluntary Medicare drug benefit enrollment decisions and (2) to explore the degree of adverse selection and crowd-out that might occur under a voluntary enrollment Medicare prescription benefit. Data were collected using a cross-sectional, mail survey of 2,100 community-dwelling adults aged 65 and older in Wisconsin. Respondents were asked to evaluate their likelihood of enrollment in any of 4 hypothetical drug benefit plans under the assumption that they could enroll in one of the hypothetical plans or maintain their current coverage. Data analyses included bivariate comparisons across enrollment likelihood categories and logit analysis of enrollment likelihood as a function of respondent characteristics. 1041 usable survey forms were returned for an adjusted response rate of 51.5%. Older adults with 4 or more chronic conditions were most likely to report that they were "very likely" to enroll in one of the hypothetical drug plans, as were those with the highest out-of-pocket drug spending in the previous 30 days. Respondents with no or self-purchased drug benefits were more likely than those with employer-based plans to express a higher likelihood of enrollment in one of the hypothetical plans. Adverse selection may be problematic for a voluntary enrollment Medicare drug benefit. Given that high out-of-pocket drug spending (secondary to drug coverage source) was a consistent predictor of enrollment likelihood, demand-side factors affecting the crowding out of employer-based drug coverage sources by a voluntary enrollment drug benefit appear minimal. However, the availability of a Medicare prescription benefit may still lead to crowd-out through employer incentives.

On Subjective Probability Forecasting

Abstract The subjective process of probability forecasting is analyzed. It is found to contain a sorling aspect, in which the forecaster distributes all instances into an ordered set of categories of likelihood of occurrence, and a laboling aspect, in which the forecaster assigns an anticipated relative frequency, or probability, of occurrence for each category. These two aspects are identified with the concepts of sharpness and validity, which have been introduced by other writers. The verification score proposed by Brier is shown to consist of the sum of measures of these two qualities. A satisfactory measure of synoptic skill is obtained by applying the Brier score to the synoptic probability forecast and to a control forecast of the climatological probability, and by expressing the difference as a percentage of the control score. In an analysis of a large number of short-range probability forecasts made by instructors and students in the synoptic laboratory of the Massachusetts Institute of Technology...