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PubMed1996

Risk perception: an empirical study of the relationship between worldview and the risk construct.

This study empirically assesses the performance of Holtgrave and Weber's Simplified Conjoint Expected Risk (SCER) model for financial and health stimuli in 3 groups of "worldview holders"-12 hierarchists, 10 individualists, and 16 egalitarians-as described by cultural theory. The SCER model performed well, however, distinctive patterns of model variable selection appeared within each group. Interestingly, the pattern of variable selection paralleled cultural theory's descriptions of each worldview. Differences in the mean perceived risk of activities also tended to correspond to predictions made by cultural theory. Results suggest two mechanisms to explain differences in perceived risk among worldviews: (i) same model variables are evaluated, but given different weight; (ii) different variables are evaluated. Identifying the relevant mechanism for a given situation may enhance the effectiveness of risk communication.

Adult↗

PubMed2002

Dissociating 'what' and 'how' in visual form agnosia: a computational investigation.

Patients with visual form agnosia exhibit a profound impairment in shape perception (what an object is) coupled with intact visuomotor functions (how to act on an object), demonstrating a dissociation between visual perception and action. How can these patients act on objects that they cannot perceive? Although two explanations of this 'what-how' dissociation have been offered, each explanation has shortcomings. A 'pathway information' account of the 'what-how' dissociation is presented in this paper. This account hypothesizes that 'where' and 'how' tasks require less information than 'what' tasks, thereby allowing 'where/how' to remain relatively spared in the face of neurological damage. Simulations with a neural network model test the predictions of the pathway information account. Following damage to an input layer common to the 'what' and 'where/how' pathways, the model performs object identification more poorly than spatial localization. Thus, the model offers a parsimonious explanation of differential 'what-how' performance in visual form agnosia. The simulation results are discussed in terms of their implications for visual form agnosia and other neuropsychological syndromes.

Agnosia↗

PubMed1975

Modeling static and dynamic human cardiovascular responses to exercise.

A human performance model has been developed and described [9] which portrays the human circulatory, thermo regulatory and energy-exchange systems as an intercoupled set. In this model, steady state or static relationships are used to describe oxygen consumption and blood flow. For example, heart rate (HTRT) is calculated as a function of the oxygen and the thermo-regulatory requirements of each body compartment, using the steady state work values of cardiac output (CO, sum of all compartment blood flows) and stroke volume (SV, assumed maximal after 40% maximal oxygen consumption): HTRT=CO/SV. The steady state model has proven to be an acceptable first approximation, but the inclusion of transient characteristics are essential in describing the overall systems' adjustment to exercise stress. In the present study, the dynamic transient characteristics of heart rate, stroke volume and cardiac output were obtained from experiments utilizing step and sinusoidal forcing of work. The gain and phase relationships reveal a probable first order system with a six minute time constant, and are utilized to model the transient characteristics of these parameters. This approach leads to a more complex model but a more accurate representation of the physiology involved. The instrumentation and programming essential to these experiments are described.

Analog-Digital Conversion↗

PubMed2000

Application of neural networks and sensitivity analysis to improved prediction of trauma survival.

The performance of trauma departments is widely audited by applying predictive models that assess probability of survival, and examining the rate of unexpected survivals and deaths. Although the TRISS methodology, a logistic regression modelling technique, is still the de facto standard, it is known that neural network models perform better. A key issue when applying neural network models is the selection of input variables. This paper proposes a novel form of sensitivity analysis, which is simpler to apply than existing techniques, and can be used for both numeric and nominal input variables. The technique is applied to the audit survival problem, and used to analyse the TRISS variables. The conclusions discuss the implications for the design of further improved scoring schemes and predictive models.

Analysis of Variance↗

PubMed1996

Validation of trauma and injury severity score in blunt trauma patients by using a Canadian trauma registry.

OBJECTIVE: To compare outcomes in blunt trauma by using Trauma and Injury Severity Score (TRISS) models derived from the Major Trauma Outcome Study (MTOS) and the Ontario Trauma Registry (OTR) as well as to evaluate the role of the Revised Trauma Score within the TRISS model. METHODS: Consecutive blunt trauma cases from 11 Level I trauma centers over a 4-year period were identified from the OTR. Coefficients of the Revised Trauma Score were modified using the Ontario data and this score was tested by using the Hosmer-Lemeshow Goodness of Fit Test. Two Ontario-specific TRISS models were developed with revised coefficients. The first used the standard Revised Trauma Score and the second used the Revised Trauma Score with regenerated coefficients. The accuracy of mortality predictions for all models were compared by using a Hosmer-Lemeshow Goodness of Fit procedure. Additionally, each TRISS models performance characteristics and receiver operating characteristic (ROC) curves were used to evaluate their discriminative capabilities. RESULTS: A total of 5,436 cases were incorporated in the analysis. Patients with all component TRISS variables had a significantly lower mortality compared to all blunt trauma patients (7.0% vs. 15.5%,p < 0.01). Use of the Revised Trauma Score led to the exclusion of 40% of cases because of absent data necessary to compute the score. The Hosmer-Lemeshow Goodness of Fit statistic for the Revised Trauma Score was 79.45 (p = 0.0001). The Hosmer-Lemeshow Goodness of Fit Statistic ranged from 11.42, p = 0.175 and 13.1, p = 0.125 for the Ontario TRISS models compared to 25.62, p < 0.005 for the MTOS TRISS model. Sensitivity of all three TRISS models ranged from 98% to 99% with specificity ranging from 24% to 35%. ROC curves were identical for all three TRISS models. CONCLUSIONS: TRISS demonstrated satisfactory performance in a Canadian blunt trauma population. Although revision of coefficients led to a better fit on the Hosmer-Lemeshow statistic, ROC curves demonstrated virtually identical performance of the MTOS and Ontario-based TRISS models. The poor performance of the Revised Trauma Score and the observation that its use led to the exclusion of 40% of cases with a higher mortality raises concerns regarding its use in the TRISS model.

Adult↗

PubMed2001

Muscle recruitment by the min/max criterion -- a comparative numerical study.

This paper introduces the min/max criterion for simulation of muscle recruitment in multiple muscle systems. The criterion is introduced and justified by comparison to two known criterion types: the polynomial criterion and the soft saturation criterion. The comparison is performed on a planar three-muscle elbow model performing a dumbbell curl. A generalized form of the soft saturation criterion is introduced, and it is shown that the min/max criterion can be interpreted as the limit of the classical criteria when the exponents in their mathematical expressions approach infinity. We finally show how the min/max criterion can be cast into a form that allows for efficient and robust numerical solution by linear programming. It is concluded that the min/max criterion possesses a number of attractive physiological as well as algorithmic advantages.

Algorithms↗

PubMed1991

Prospective payment for Medicare hospital capital: implications of the research.

The special characteristics of capital have an important effect on the cross-section variation in hospitals' capital costs. Variables reflecting capital age and financing differences perform as expected and add substantial explanatory power to capital cost models. However, even with the inclusion of these variables, the capital-cost models perform poorly compared with total-cost models. The empirical findings of this article support using the total-cost models to develop a common set of adjustment factors for capital and operating payment amounts in the Medicare prospective payment system.

Capital Expenditures↗

PubMed2004

Coding response to a case-mix measurement system based on multiple diagnoses.

OBJECTIVE: To examine the hospital coding response to a payment model using a case-mix measurement system based on multiple diagnoses and the resulting impact on a hospital cost model. DATA SOURCES: Financial, clinical, and supplementary data for all Ontario short stay hospitals from years 1997 to 2002. STUDY DESIGN: Disaggregated trends in hospital case-mix growth are examined for five years following the adoption of an inpatient classification system making extensive use of combinations of secondary diagnoses. Hospital case mix is decomposed into base and complexity components. The longitudinal effects of coding variation on a standard hospital payment model are examined in terms of payment accuracy and impact on adjustment factors. PRINCIPAL FINDINGS: Introduction of the refined case-mix system provided incentives for hospitals to increase reporting of secondary diagnoses and resulted in growth in highest complexity cases that were not matched by increased resource use over time. Despite a pronounced coding response on the part of hospitals, the increase in measured complexity and case mix did not reduce the unexplained variation in hospital unit cost nor did it reduce the reliance on the teaching adjustment factor, a potential proxy for case mix. The main implication was changes in the size and distribution of predicted hospital operating costs. CONCLUSIONS: Jurisdictions introducing extensive refinements to standard diagnostic related group (DRG)-type payment systems should consider the effects of induced changes to hospital coding practices. Assessing model performance should include analysis of the robustness of classification systems to hospital-level variation in coding practices. Unanticipated coding effects imply that case-mix models hypothesized to perform well ex ante may not meet expectations ex post.

Comorbidity↗

PubMed2005

On the retrieval of significant wave heights from spaceborne Synthetic Aperture Radar using the Max-Planck Institut algorithm.

Synthetic Aperture Radar (SAR) onboard satellites is the only source of directional wave spectra with continuous and global coverage. Millions of SAR Wave Mode (SWM) imagettes have been acquired since the launch in the early 1990's of the first European Remote Sensing Satellite ERS-1 and its successors ERS-2 and ENVISAT, which has opened up many possibilities specially for wave data assimilation purposes. The main aim of data assimilation is to improve the forecasting introducing available observations into the modeling procedures in order to minimize the differences between model estimates and measurements. However there are limitations in the retrieval of the directional spectrum from SAR images due to nonlinearities in the mapping mechanism. The Max-Planck Institut (MPI) scheme, the first proposed and most widely used algorithm to retrieve directional wave spectra from SAR images, is employed to compare significant wave heights retrieved from ERS-1 SAR against buoy measurements and against the WAM wave model. It is shown that for periods shorter than 12 seconds the WAM model performs better than the MPI, despite the fact that the model is used as first guess to the MPI method, that is the retrieval is deteriorating the first guess. For periods longer than 12 seconds, the part of the spectrum that is directly measured by SAR, the performance of the MPI scheme is at least as good as the WAM model.

Journal Article↗

PubMed2005

Observation, imagination and execution of an effortful movement: more evidence for a central explanation of motor imagery.

In this study subjects had to imagine, observe and perform a series of 25 squat movements while lifting two dumbbells of 12.5 kg each (one with each hand). This movement is effortful and requires substantial activation of peripheral systems. It was asked whether subjects when they imagined that they were performing the movements or when they observed a model performing the squat movements would show increased activity in EMG, heart rate and respiration compared with a control condition where they sat relaxed in a comfortable chair or a condition where they actually performed the squat movements. Two groups of subjects participated in the experiment: experienced squatters and novices. By employing these two groups we were able to study the differential effect of earlier experience with the target movement on peripheral activation. The results showed that with the exception of respiration no significant peripheral activation could be measured related to motor imagery. Although a clear distinction in experience existed between the experienced squatters versus the novices, no relevant imagery-related differences could be obtained between the two groups. The results are discussed in the light of a central explanation of motor imagery.

Adolescent↗

PubMed1997

A logistic regression model when some events precede treatment: the effect of thrombolytic therapy for acute myocardial infarction on the risk of cardiac arrest.

When outcomes occur in clinical trials before treatment can be given, neither intent-to-treat nor according-to-protocol analyses give optimal estimates of the treatment effect. A better approach employs a time-dependent variable for treatment. Intent-to-treat analyses are conservative, biasing against treatment; according-to-protocol analyses bias in favor of treatment. We show how to measure the effect of a time-dependent variable in a logistic regression using person-time intervals as units of measurement and describe appropriate methods for reporting model performance. The method is applied to develop a model to predict the probability that a patient with a myocardial infarction will have a sudden cardiac arrest within 48 hours of presentation to emergency medical services both when treated with thrombolysis and when not treated. We use a time-dependent treatment variable because many patients went into cardiac arrest while awaiting treatment. This technique has been programmed into an electrocardiograph for real-time use in an emergency department.

Aged↗

PubMed2000

The use of clinical prediction formulas in the evaluation of obstructive sleep apnea.

STUDY OBJECTIVES: To prospectively study the utility of four clinical prediction models for either predicting the presence of obstructive sleep apnea (OSA, apnea-hypopnea index [AHI] > or = 10/hour), or prioritizing patients for a split-night protocol (AHI(3)20/hour). DESIGN: All patients presenting for OSA evaluation completed a research questionnaire that included questions from previously developed clinical prediction models. The probability of sleep apnea for each patient for each model was calculated based upon the equation used in the model. Based upon two cutoffs of apnea-hypopnea index, 10 and 20, the sensitivity, specificity, and positive predictive value were calculated. For the cutoffs AHI > or =10 and > or =20, receiver operating characteristic curves were generated and the areas under the curves calculated. Comparisons of demographic information and symptom response were compared between patients with and without OSA, and men vs. women. SETTING: Urban, accredited sleep disorders center. PATIENTS OR PARTICIPANTS: All patients referred for evaluation of OSA who underwent polysomnography. INTERVENTIONS: N/A. RESULTS: 370 patients (191 men, 179 women) completed the study. 248 of the 370 (67%) patients had an AHI(3)10; 180 of the 370 (49%) had an AHI> or =20. For AHI > or =10, the sensitivities ranged from 76 to 96%, specificities from 13%-54%, positive predictive values from 69%-77% using the probability cutoff of the original investigators; the areas under the curve from 0.669 to 0.736. For AHI(3)20, the areas under the ROC curves ranged from 0.700 to 0.757; using cutoffs to maximized specificity, the sensitivities ranged from 33%-39%, specificities from 87%-93%, and positive predictive values from 72%-85%. All the models performed better for men. CONCLUSIONS: The clinical prediction models tested are not be sufficiently accurate to discriminate between patients with or without OSA but could be useful in prioritizing patients for split-night polysomnography.

Adult↗

PubMed2000

Does diagnostic information contribute to predicting functional decline in long-term care?

BACKGROUND: Compared with the acute-care setting, use of risk-adjusted outcomes in long-term care is relatively new. With the recent development of administrative databases in long-term care, such uses are likely to increase. OBJECTIVES: The objective of this study was to determine the contribution of ICD-9-CM diagnosis codes from administrative data in predicting functional decline in long-term care. RESEARCH DESIGN: We used a retrospective sample of 15,693 long-term care residents in VA facilities in 1996. METHODS: We defined functional decline as an increase of > or =2 in the activities of daily living (ADL) summary score from baseline to semiannual assessment. A base regression model was compared to a full model enhanced with ICD-9-CM codes. We calculated validated measures of model performance in an independent cohort. RESULTS: The full model fit the data significantly better than the base model as indicated by the likelihood ratio test (chi2 = 179, df = 11, P <0.001). The full model predicted decline more accurately than the base model (R2 = 0.06 and 0.05, respectively) and discriminated better (c statistics were 0.70 and 0.68). Observed and predicted risks of decline were similar within deciles between the 2 models, suggesting good calibration. Validated R2 statistics were 0.05 and 0.04 for the full and base models; validated c statistics were 0.68 and 0.66. CONCLUSIONS: Adding specific diagnostic variables to administrative data modestly improves the prediction of functional decline in long-term care residents. Diagnostic information from administrative databases may present a cost-effective alternative to chart abstraction in providing the data necessary for accurate risk adjustment.

Activities of Daily Living↗

PubMed1993

Development and validation of a limited sampling strategy for 5-fluorouracil given by bolus intravenous administration.

A wide range of interindividual variability of 5-fluorouracil (5-FU) pharmacokinetics exists after bolus administration. The degree to which this variability in 5-FU exposure impacts upon the response and toxicity of the drug has not been determined. The area under the concentration time curve (AUC) is a commonly used indicator of exposure, but normally requires the collection of 8-10 timed blood samples after i.v. bolus administration. This presents difficulties if large-scale population samplings are required. This study involved the development and testing of a strategy to estimate AUC from a limited number of blood samples in patients with gastrointestinal and breast cancer. The optimal single time point for AUC estimation was 0.17 h (r2 = 0.954). Addition of the 0.75 h time point significantly improved predictability (r2 = 0.983). Addition of a third or fourth time point did not provide further benefit. These models were then tested separately in a group of women who received a higher dose of 5-FU. The two data points model performed significantly better than the single time point model (r2 = 0.70 and 0.85, respectively). The AUC of standard dose 5-FU after bolus administration can be reliably estimated from two timed samples taken 10 and 45 min after injection.

Adult↗

PubMed1999

Linear and nonlinear analysis of human dynamic cerebral autoregulation.

The linear dynamic relationship between systemic arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) was studied by time- and frequency-domain analysis methods. A nonlinear moving-average approach was also implemented using Volterra-Wiener kernels. In 47 normal subjects, ABP was measured with Finapres and CBFV was recorded with Doppler ultrasound in both middle cerebral arteries at rest in the supine position and also during ABP drops induced by the sudden deflation of thigh cuffs. Impulse response functions estimated by Fourier transfer function analysis, a second-order mathematical model proposed by Tiecks, and the linear kernel of the Volterra-Wiener moving-average representation provided reconstructed velocity model responses, for the same segment of data, with significant correlations to CBFV recordings corresponding to r = 0.52 +/- 0.19, 0.53 +/- 0.16, and 0.67 +/- 0.12 (mean +/- SD), respectively. The correlation coefficient for the linear plus quadratic kernels was 0.82 +/- 0.08, significantly superior to that for the linear models (P < 10(-6)). The supine linear impulse responses were also used to predict the velocity transient of a different baseline segment of data and of the thigh cuff velocity response with significant correlations. In both cases, the three linear methods provided equivalent model performances, but the correlation coefficient for the nonlinear model dropped to 0.26 +/- 0.25 for the baseline test set of data and to 0.21 +/- 0.42 for the thigh cuff data. Whereas it is possible to model dynamic cerebral autoregulation in humans with different linear methods, in the supine position a second-order nonlinear component contributes significantly to improve model accuracy for the same segment of data used to estimate model parameters, but it cannot be automatically extended to represent the nonlinear component of velocity responses of different segments of data or transient changes induced by the thigh cuff test.

Adult↗

PubMed2006

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility.

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.

Air Pollutants↗

PubMed1999

Observational learning in children with Down syndrome and developmental delays: the effect of presentation speed in videotaped modelling.

Children with severe developmental delays (three with Down syndrome and three with autism as the primary diagnosis) observed a videotaped model performing two basic dressing skills without prompting, verbal or otherwise, or explanation by an instructor. In a within-subjects design, dressing skills that were presented at a relatively slow presentation speed through videotaped modelling were eventually performed better than those presented at a relatively fast speed. These data in combination with evidence from this laboratory that passive modelling of basic skills is more effective than interactive modelling (e.g., Biederman, Fairhall, Raven, & Davey, 1998; Biederman, Davey, Ryder, & Franchi, 1994; Biederman, Ryder, Davey, & Gibson, 1991) suggest that standard instructional techniques warrant reexamination both from the basis of instructional effectiveness and the efficient use of the allotment of teacher time.

Child↗

PubMed2026

MRI-based radiomics model for predicting VEGFA expression and prognosis in lower-grade glioma.

BACKGROUND: Gliomas are the most common primary tumors of the central nervous system. Their treatment remains highly challenging, with high rates of associated disability and mortality. Conventional prognostic indicators no longer adequately satisfy the clinical demands of precision medicine. Therefore, it is essential to further explore novel prognostic biomarkers to enable accurate risk stratification and to provide new reference indicators for personalized precision therapy. PURPOSES: This study aimed to investigate the prognostic significance of vascular endothelial growth factor A (VEGFA) in patients diag nosed with lower-grade gliomas (LGGs) using an MRI based radiomics model. METHODS: Data regarding VEGFA expression and clinical records of LGG patients were retrieved from The Cancer Genome Atlas (TCGA). Corresponding preoperative MRI data were obtained from The Cancer Imaging Archive (TCIA) for radiomic feature extraction. Patients were stratified into high- and low- VEGFA expression groups based on survival information from the current cohort using the survminer package. The overall survival (OS) was assessed using Kaplan-Meier analysis and Cox proportional hazards regression. Predictive models were developed using logistic regression (LR), and model performance was evaluated via receiver operating characteristic (ROC) curve analysis, with area under the curve (AUC) values reported. An optimized model incorporating the Akaike information criterion (AIC) was also constructed (AIC-LR). RESULTS: VEGFA expression was significantly associated with OS (P = 0.002). Multivariate Cox regression confirmed VEGFA as an independent prognostic factor (hazard ratio [HR] = 2.545, 95% confidence interval: 1.422-4.555). Furthermore, VEGFA expression correlated with immune infiltration levels, particularly of M1 and M2 macrophages and T follicular helper cells, and was associated with enrichment in Wnt signaling and B cell receptor signaling pathways. The LR and AIC-LR models demonstrated acceptable predictive performance, with AUCs of 0.728 (95% CI: 0.612-0.843) and 0.725(95% CI: 0.612-0.839) in the training cohort, and 0.704 (95% CI: 0.562-0.847) and 0.718(95% CI: 0.576-0.861) in the validation cohort, respectively. CONCLUSIONS: The MRI based radiomics model showed potential for noninvasive assessment of VEGFA expression and may provide auxiliary information for prognostic evaluation in LGG. Further validation in larger samples and independent external cohorts is required before clinical application.

Radiomics↗