Set Of Assessment Tools Research Articles

Utility of the Pediatric Sleep Questionnaire and Pulse Oximetry as Screening Tools in Pediatric Patients with Suspected Obstructive Sleep Apnea Syndrome

Objective. To assess the screening tools in snoring patients. Material and Methods. A retrospective review of data was conducted from children between 2 and 15 years old who were referred on suspicion of obstructive sleep apnea-hypopnea (OSAH) between June 2008 and June 2011. We excluded patients with significant comorbidities. Pediatric Sleep Questionnaire (PSQ), physical exam (PE), and pulse-oximetry data were collected and correlated with the results of the nightly polygraph at home. Results. We selected 98 patients. The 22-item version of the PSQ had sensitivity of 96% and specificity of 36.8%. The overall value of the clinic predictor of OSAH (PSQ and PE together) exhibited an increased specificity 57.6% with 94.6% of sensitivity. The nocturnal home oximetry method used alone was very specific, 92.1%, but had a lower sensitivity, 77.1%. The set of clinical assessment tools used together with pulse-oximetry screening provided excellent specificity 98.1% and a positive predictive value 94.1% globally. The performance of this screening tool is related with the severity of OSAH and accuracy is better in moderate and severe cases. Conclusion. The combination of clinical assessment and pulse-oximetry screening can provide a sufficient diagnostic approach for pediatric patients with suspected OSAH at least in moderate and severe cases.

History and practice of competency‐based assessment

In response to historical trends in expectations of doctors, the goals of medical education are increasingly framed in terms of global competencies. The language of these competencies has tended to adopt a prescriptive, rather than descriptive, approach. However, despite widespread agreement on the importance of competency-based education and more than two decades of study, this effort has not generated a dependable set of assessment tools. Because models of competency are legislated, rather than shaped by scholarly consideration of empirical data, it is unlikely that such models directly reflect actual human behaviour. Efforts to measure clinical behaviours could benefit from increased clarity in three related conceptual areas. Firstly, the language of educational constructs should be framed in terms of data-based hypotheses, rather than in terms of intuitively plausible abilities. Secondly, these constructs should be specified in terms of the situations to which they are relevant, rather than as global personal characteristics. Finally, the resources required to measure these constructs should be rigorously established because a common resource-based metric would allow for rational selection of assessment methods. Specific methods to establish each of these objectives are discussed. The political process of negotiating educational objectives should not be confused with the scientific work of establishing coherent and interpretable patterns of behaviour. Although the two activities can complement one another, each has its own distinct methods and style of discourse. It is thus critical to maintain boundaries between these two approaches to defining professional performance.

Evidence-based Venous Thromboembolism Prophylaxis is Associated With a Six-fold Decrease in Numbers of Symptomatic Venous Thromboembolisms in Rehabilitation Inpatients

To measure the impact of a standardized risk assessment tool and specialty-specific, risk-adjusted venous thromboembolism (VTE) order sets on compliance with American College of Chest Physicians (ACCP) guidelines and the number of symptomatic VTE as assessed by administrative data. Prospective cohort study. Academic hospital inpatient rehabilitation unit. All patients on the rehabilitation unit. Assessment of VTE risk factors and evaluated admission VTE prophylaxis orders before and after implementation of an ACCP guideline-based, specialty-specific VTE risk assessment, and prophylaxis order set by using a standardized data collection form. Discharge diagnostic codes for VTE and pulmonary embolism were tracked by ICD-9 (International Classification of Diseases, 9th edition) discharge diagnosis codes for the 12 months before and 36 months after the intervention. Before implementation of the VTE order set, 27% of patients received VTE prophylaxis in compliance with the 2004 ACCP VTE guidelines. By following implementation of specialty-specific, risk-adjusted VTE order sets, compliance increased to 98%. In the year before VTE order-set implementation, the number of VTEs per admission was 49 per 1000. By following implementation, the number of VTEs steadily decreased each year to 8 per 1000 in 2007 (χ(2) = 14.985; P = .0001). Implementation of a standardized VTE risk assessment tool and prophylaxis order set resulted in a substantial improvement in compliance with ACCP guidelines for VTE prophylaxis and was associated with a 6-fold reduction in the number of symptomatic VTEs in a hospital-based rehabilitation unit.

Modeling Urban Atmospheric Anthrax Spores Dispersion: Assessment of Health Impacts and Policy Implications

AbstractPurposeTo model atmospheric dispersion of weapon grade anthrax spores over an urban region using a mass transit system (subway) as a delivery system. IntroductionThe accessibility and carrying capacity of mass transit system (s) makes it an attractive target for terrorists. There are multiple, historical accounts of terrorists attacks involving transit systems. Metropolitan underground transportation rail systems (subways) are of special interest because of a potential harm to a large number of commuters and damage to the transportation infrastructure. MethodsWe assumed that multiple release points of anthrax spores within the National Capital Region (NCR‐Washington, District of Columbia) METRO rail system will result in the escape of the spores into the atmosphere. Potential factors affecting atmospheric dispersion of spores and the regional infrastructure were the subject of literature searches, modeling exercises and expert reviews. A Geographic Information System (GIS) and the Operational Multiscale Environment Model with Grid Adaptivity (OMEGA) were used to model the affected area. ResultsThe GIS together with the OMEGA software programs characterized the extent of the ground footprint and provided the number of the NCR residential, businesses and health care infrastructure under the plume at 120 minutes after the release. It was concluded that the maximum environmental and health impacts would occur if the spores were released in the early morning during the summer months (low humidity and ultra‐violet radiation). This assumption was based on the analysis of the weather patterns and prevailing winds in the NCR. ConclusionsThe atmospheric dispersion model superimposed over the regional GIS suggests that the extent of the affected infrastructure will be negligible. However it has the potential to disrupt the functioning of the mass transit system, affect serviced residential areas, commercial and/or federal facilities. While the number of affected medical and other facilities will be minimal, a significant number of commuters and resident will be exposed to the spores and overload the existing health care infrastructure. Policy implicationsAdopting a set of realistic threats assessment tools using GIS and atmospheric modeling, and addressing risk reduction strategies such as deploying real time biological agents monitoring sensors, can significantly improve the security of metropolitan communities served by interconnected mass transport systems. Field testing to validate our modeling assumptions and results will help with the training of disaster response teams, health care providers, transportation system operators and improve passengers' safety. Limitations This study has not been validated by actual field test data and as such is hypothetical and subject to a significant bias. Assumption of a release of a large amount (several kilograms) of anthrax spores undetected might be unrealistic based on existing physical surveillance and security practices. Patterns of spores' dispersion into fixed structures serviced by the subway system were not modeled in this research. The dispersion model does not take into account the progressive reduction of the number of anthrax spores as a function of the distance from the release source.

Spiritual Assessment and Native Americans: Establishing the Social Validity of a Complementary Set of Assessment Tools

Although social work practitioners are increasingly likely to administer spiritual assessments with Native American clients, few qualitative assessment instruments have been validated with this population. This mixed-method study validates a complementary set of spiritual assessment instruments. Drawing on the social validity literature, a sample of experts in Native culture (N = 50) evaluated the instruments' cultural consistency, strengths, limitations, and areas needing improvement. Regarding the degree of congruence with Native American culture, verbally based spiritual histories ranked highest and diagrammatically oriented spiritual genograms ranked lowest, although all instruments demonstrated at least moderate levels of consistency with Native culture.The results also suggest that practitioners' level of spiritual competence plays a crucial role in ensuring the instruments are operationalized in a culturally appropriate manner.

Adaptive MLS-HDMR metamodeling techniques for high dimensional problems

Metamodeling technique is to represent the approximation of input variables and output variables. With the exponential increase of dimension of assigned problems, accurate and robust model is difficult to achieve by popular regression methodologies. High-dimensional model representation (HDMR) is a general set of metamodel assessment and analysis tools to improve the efficiency of deducing high dimensional underlying system behavior. In this paper, a new HDMR, based on moving least square (MLS), termed as MLS-HDMR, is introduced. The MLS-HDMR naturally explores and exploits the linearity/nonlinearity and correlation relationships among variables of the underlying function, which is unknown or computationally expensive. Furthermore, to improve the efficiency of the MLS-HDMR, an intelligent sampling strategy, DIviding RECTangles (DIRECT) method is used to sample points. Multiple mathematical test functions are given to illustrate the modeling principles, procedures, and the efficiency and accuracy of the MLS-HDMR models with problems of a wide scope of dimensionalities.

Long term cardiovascular risk models’ combination

The correct diagnosis of cardiovascular disease is a key factor to reduce social and economic costs. In this context, cardiovascular disease risk assessment tools are of fundamental importance. This work addresses two major drawbacks of the current cardiovascular risk score systems: reduced number of risk factors considered by each individual tool and the inability of these tools to deal with incomplete information. To achieve these goals a two phase strategy was followed. In the first phase, a common representation procedure, based on a Naïve-Bayes classifier methodology, was applied to a set of current risk assessment tools. Classifiers’ individual parameters and conditional probabilities were initially evaluated through a frequency estimation method. In a second phase, a combination scheme was proposed exploiting the particular features of Bayes probabilistic reasoning, followed by conditional probabilities optimization based on a genetic algorithm approach. This strategy was applied to describe and combine ASSIGN and Framingham models. Validation results were obtained based on individual models, assuming their statistical correctness. The achieved results are very promising, showing the potential of the strategy to accomplish the desired goals.

Quantitative Analysis of Dynamic Contrast-Enhanced and Diffusion-Weighted Magnetic Resonance Imaging for Oncology inR

The package dcemriS4 provides a complete set of data analysis tools for quantitative assessment of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Image processing is provided for the ANALYZE and NIfTI data formats as input with all parameter estimates being output in NIfTI format. Estimation of T1 relaxation from multiple flip-angle acquisitions, using either constant or spatially-varying flip angles, is performed via nonlinear regression. Both literature-based and data-driven arterial input functions are available and may be combined with a variety of compartmental models. Kinetic parameters are obtained from nonlinear regression, Bayesian estimation via Markov chain Monte Carlo or Bayesian maximum a posteriori estimation. A non-parametric model, using penalized splines, is also available to characterize the contrast agent concentration time curves. Estimation of the apparent diffusion coefficient (ADC) is provided for diffusion-weighted imaging. Given the size of multi-dimensional data sets commonly acquired in imaging studies, care has been taken to maximize computational efficiency and minimize memory usage. All methods are illustrated using both simulated and real-world medical imaging data available in the public domain.

Incorporation of the Multiple Barrier Approach in drinking water risk assessment tools

A number of existing risk assessment tools make reference to, or incorporate, a Multiple Barrier Approach to drinking water safety. Three waterborne disease outbreaks that occurred in developed nations were used as case studies to test a selected set of risk assessment tools. The outbreaks were used to determine how well the risk assessment tools identify hazards and vulnerabilities associated with different barriers to drinking water contamination.

A French network of bipolar expert centres: A model to close the gap between evidence-based medicine and routine practice

BackgroundBipolar disorders are a major public health concern. Efforts to provide optimal care by general practitioners and psychiatrists are undermined by the complexity of the disorder and difficulties in applying clinical practice guidelines and new research findings to the spectrum of cases seen in day to day practice. MethodA national network of bipolar expert centres was established. Each centre has established strong links to local health services and provides support to clinicians in delivering personalized care plans derived from systematic case assessments undertaken at the centre. ResultsA common set of diagnostic and clinical assessment tools has been adopted at eight centres. Evaluations are undertaken by trained assessors and cross-centre reliability is monitored. A web application, e-bipolar© is used to record data in a common computerized medical file. Anonymized data is entered into a shared national database for use in multi-centre audit and research. ConclusionsInstead of offering treatment advice based on clinical practice guidelines recommendations for selected sub-populations of patients (a ‘top-down’ approach), the French bipolar network offers systematic, comprehensive, longitudinal, and multi-dimensional assessments of cases representative of general bipolar populations. This ‘bottom-up’ strategy may offer a more efficient and effective way to transfer knowledge and share expertise as the referrer can appreciate the rationale underpinning suggested treatment protocols and more readily apply such principles and approaches to other cases. The network also builds an infrastructure for clinical cohort and comparative-effectiveness research on more representative patient populations.

Pitfalls and Technical Aspects during the Research of Intestinal Anastomotic Healing in Rats

Background: Fundamental experimental research into intestinal anastomotic healing in rodent models will gain increasing interest in the future. Methods: The aim of this study was to describe our 5-year experience with a standardized experimental setup of small and large bowel anastomoses in a rodent model and present a basic set of assessment tools investigating anastomotic healing. Anastomotic technique, perioperative complications such as anastomotic insufficiency (AI) and obstructive ileus were in the focus. Results: During different studies with varying study patterns, 167 rat small bowel anastomoses and 120 colonic anastomoses were performed. Overall mortality was 3.6% in small bowel and 2.5% in colonic anastomoses, AI occurred in 2.9 and 4%, respectively. A postoperative obstructive ileus was seen in 3/167 small bowel anastomoses and none in the colonic group. Conclusion: When performing experimental intestinal anastomoses in a standardized operative setting and critically considering special perioperative issues, the incidence of relevant complications can be maintained at an adequately low level.

Stochastic sensitivity analysis using preconditioning approach

PurposeHigh‐dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high‐dimensional relationships between sets of input and output model variables. It is an efficient formulation of the system response, if higher‐order cooperative effects are weak, allowing the physical model to be captured by the lower‐order terms. The paper's aim is to develop a new computational tool for estimating probabilistic sensitivity of structural/mechanical systems subject to random loads, material properties and geometry.Design/methodology/approachWhen first‐order HDMR approximation of the original high‐dimensional limit state is not adequate to provide the desired accuracy to the sensitivity analysis, this paper presents an enhanced HDMR (eHDMR) method to represent the higher‐order terms of HDMR expansion by expressions similar to the lower‐order ones with monomial multipliers. The accuracy of the HDMR expansion can be significantly improved using preconditioning with a minimal number of additional input‐output samples without directly invoking the determination of second‐ and higher‐order terms. As a part of this effort, the efficacy of HDMR, which is recently applied to uncertainty analysis, is also demonstrated. The method is based on computing eHDMR approximation of system responses and score functions associated with probability distribution of a random input. Surrogate model is constructed using moving least squares interpolation formula. Once the surrogate model form is defined, both the probabilistic response and its sensitivities can be estimated from a single probabilistic analysis, without requiring the gradients of performance functions.FindingsThe results of two numerical examples involving mathematical function and structural/solid‐mechanics problems indicate that the sensitivities obtained using eHDMR approximation provide significant accuracy when compared with the conventional Monte Carlo method, while requiring fewer original model simulations.Originality/valueThis is the first time where application of eHDMR concepts is explored in the stochastic sensitivity analysis. The present computational approach is valuable to the practical modelling and design community.

Probabilistic stability assessment of slopes using high dimensional model representation

This paper presents a new computational tool for probabilistic stability assessment of earth slopes/embankments. The method involves high dimensional model representation (HDMR) that facilitates lower dimensional approximation of the original limit state, response surface generation of HDMR component functions, and Monte Carlo simulation. HDMR is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is a very efficient formulation of the system response, if higher-order variable correlations are weak, allowing the physical model to be captured by the first few lower-order terms. Once the approximate form of the original limit state is defined, the failure probability can be obtained by statistical simulation. Results of four numerical examples indicate that the proposed method provides accurate and computationally efficient estimates of the failure probability of earth slopes/embankments.

Comparing Bayesian network, artificial neural networks, classification trees and classical logistic models in quantitative risk assessment: an application to the European Registry of Foreign Body Injuries in Children

Risk assessment is the systematic study of decisions subject to uncertain consequences.An increasing interest has been focused on modelling techniques like Bayesian networks (BNs) since their capability of (1) combining...

P20 Functional capacity is significantly impaired in primary biliary cirrhosis and related to orthostatic symptoms

IntroductionPrimary biliary cirrhosis (PBC) is associated with a significant and diverse symptom burden independent of conventional markers of disease severity. It is unclear how this symptom load impacts upon function...

3.2.1 System Security Capability Assessment Model Development and Application

AbstractThe INCOSE Systems Engineering Capability Assessment Model (SECAM) has been adapted to apply to the system security domain. Service organizations that do not produce an industrial manufactured product are the initial target of this new variation of capability assessment model. The primary goal of this work is the deployment of an adaptive set of organizational security assessment tools that provide the basis for controlled, structured organizational improvement of the existing security context. A new quick look assessment method is also presented to help an organization minimize the cost and time associated with this type of activity.

A Native American Perspective on Spiritual Assessment: The Strengths and Limitations of a Complementary Set of Assessment Tools

Mental health practitioners are increasingly called on to administer spiritual assessments with Native American clients, in spite of limited training on the topic. To help practitioners better understand the strengths and limitations of various assessment instruments from a Native perspective, this study used a sample of recognized experts in Native American culture (N = 50) to evaluate a complementary set of spiritual assessment instruments or tools. Specifically, each instrument's degree of consistency with Native culture was evaluated along with its strengths and limitations for use with Native clients. A brief overview of each instrument is provided, along with the results, to familiarize readers with a repertoire of spiritual assessment tools so that the most culturally appropriate method can be selected in a given clinical context.

Reliability analysis of 500 MWe PHWR inner containment using high-dimensional model representation

In this paper, uncertainty analysis of Indian 500 MWe Pressurized Heavy Water Reactor (PHWR) subjected to an accidental pressure is carried out using a computational tool based on High Dimensional Model Representation (HDMR) that facilitates lower dimensional approximation of the original high dimensional implicit limit state/performance function. The method involves response surface generation of HDMR component functions, and Monte Carlo simulation. HDMR is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is very efficient formulation of the system response, if higher-order variable correlations are weak, allowing the physical model to be captured by first few lower-order terms. Once the approximate form of the original implicit limit state/performance function is defined, the failure probability can be obtained by statistical simulation. Reliability estimates of PHWR inner containment subjected to an internal pressure exceeding the design pressure, considering three stages of progressive failure prior to collapse are presented.

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.

Statistical assessment of ocean observing networks – A study of water level measurements in the German Bight

A set of tools for the statistical assessment of ocean observing networks is presented and applied for the analysis of different instrumentation scenarios in the German Bight. An optimal linear estimator is used to re-construct ocean state parameters from observations taking into account both the prior distribution of the state and measurement errors. The proposed method enables a re-construction of any scalar parameter or vector field with linear relationship to the state. The performance of the observing network is quantified in terms of the re-construction quality. Apart from the capability of the network to provide estimates of state parameters at the time of the observations, the potential of the measurements for forecasts is investigated as well. Furthermore, a generic method to compare single measurements with continuous observations is presented. Finally, a technique is described to quantify the relative importance of different components of an observational network. The proposed methods are applied to water level measurements in the German Bight. A numerical model is used to estimate the background statistics. Synthetic measurements provided by tide gauges, satellite altimeters, and HF radar are considered in the analysis. The estimation of the complete water level field in the German Bight is compared for altimeter and tide gauge measurements. It is shown that the orientation of the satellite track with respect to the coastline is of high relevance. The importance of water level measurements taken in deeper water, e.g., at the FINO-1 platform, is demonstrated. It is shown that continuous tide gauge measurements provide more information on the area mean water level in the German Bight than altimeter observations taken by ENVISAT and JASON-1/2. It is furthermore shown how the information provided by a tide gauge propagates with the Kelvin wave. Implications for the design of an assimilation scheme are discussed.