Prediction of functional capacity in chronic heart failure patients using myocardial tissue Doppler

Background. Exercise therapy improves functional capacity in CHF, but selection and individualization of training would be helped by a simple non-invasive marker of peak VO2. Peak VO2 in these pts is difficult to predict without direct measurement, and LV ejection fraction is a poor predictor. Myocardial tissue velocities are less load-dependent, and may be predictive of the exercise response in CHF pts. We sought to use tissue velocity as a predictor of peak VO2 in CHF pts. Methods. Resting 2D-echocardiography and tissue Doppler imaging were performed in 182 CHF pts (159 male, age 62±10 years) before and after metabolic exercise testing. The majority of these patients (129, 71%) had an ischemic cardiomyopathy, with resting EF of 35±13% and a peak VO2 of 13.5±4.7 ml/kg/min. Results. Neither resting EF (r=0.15) nor peak EF (r=0.18, both p=NS) were correlated with peak VO2. However, peak VO2 correlated with peak systolic velocity in septal (Vss, r=0.31) and lateral walls (Vsl, r=0.26, both p=0.01). In a general linear model (r2 = 0.25), peak VO2 was calculated from the following equation: 9.6 + 0.68*Vss - 0.09*age + 0.06*maximum HR. This model proved to be a superior predictor of peak VO2 (r=0.51, p=0.01) than the standard prediction equations of Wasserman (r= -0.12, p=0.01). Conclusions. Resting tissue Doppler, age and maximum heart rate may be used to predict functional capacity in CHF patients. This may be of use in selecting and following the response to therapy, including for exercise training.

The prediction and representation of phase equilibria and physicochemical properties in complex slag systems

The development of new experimental techniques for the determination of phase equilibria in complex slag systems, chemical thermodynamic, and viscosity models is reported. The new experimental data, and new thermodynamic and viscosity models, have been combined in a custom-designed computer software package to produce limiting operability diagrams for slag systems. These diagrams are used to describe phase equilibria and physicochemical properties in complex slag systems. The approach is illustrated with calculations on the system FeO-Fe2O3-CaO-SiO-Al2O3 at metallic iron saturation, slags produced in coal slagging gasifiers, and in the reprocessing of nonferrous smelting slags. This article was presented at the Mills Symposium Molten Metals, Slags and Glasses-Characterisation of Properties and Phenomena held in London in August 2000.

Statistical tests of load-unload response ratio signals by lattice solid model: Implication to tidal triggering and earthquake prediction

Statistical tests of Load-Unload Response Ratio (LURR) signals are carried in order to verify statistical robustness of the previous studies using the Lattice Solid Model (MORA et al., 2002b). In each case 24 groups of samples with the same macroscopic parameters (tidal perturbation amplitude A, period T and tectonic loading rate k) but different particle arrangements are employed. Results of uni-axial compression experiments show that before the normalized time of catastrophic failure, the ensemble average LURR value rises significantly, in agreement with the observations of high LURR prior to the large earthquakes. In shearing tests, two parameters are found to control the correlation between earthquake occurrence and tidal stress. One is, A/(kT) controlling the phase shift between the peak seismicity rate and the peak amplitude of the perturbation stress. With an increase of this parameter, the phase shift is found to decrease. Another parameter, AT/k, controls the height of the probability density function (Pdf) of modeled seismicity. As this parameter increases, the Pdf becomes sharper and narrower, indicating a strong triggering. Statistical studies of LURR signals in shearing tests also suggest that except in strong triggering cases, where LURR cannot be calculated due to poor data in unloading cycles, the larger events are more likely to occur in higher LURR periods than the smaller ones, supporting the LURR hypothesis.

Determinants of functional capacity in patients with chronic heart failure: Role of filling pressure and systolic and diastolic function

Background Previous work suggesting a better correlation of diastolic than systolic function with exercise capacity in heart failure may reflect the -relative insensitivity and load-dependence of ejection fraction (EF). We sought the correlation of new and more sensitive methods of quantifying systolic and diastolic function and filling pressure with functional capacity. Methods We studied 155 consecutive exercise tests on 95 patients with congestive heart failure (81 male, aged 62 +/- 10 years), who underwent resting 2-climensional echocardiography and tissue Doppler imaging before and after measurement of maximum oxygen uptake (peak VO2)Results The resting EF was 3 1 % 10% and a peak VO(2)was 13 +/- 5 mL/kg/min; the majority of these patients (80%) had an ischemic cardiornyopathy. Resting EF (r 0.14, P =.09) correlated poorly with peak VO2 and mean systolic (r = 0.23, P =.004) and diastolic tissue velocities (r 0.18, P =.02). Peak EF was weakly correlated with the mean systolic (r = 0.18, P =.02) and diastolic velocities (r = 0.16, P <.04). The mean sum of systolic and diastolic velocities in both annuli (r = 0.30, P <.001) and E/Ea ratio (r 0.31, P <.001) were better correlated with peak VO2 Prediction of peak VO2 was similar with models based on models of filling pressure (R = 0.61), systolic factors (R = 0.63), and diastolic factors (R 0.59), although a composite model of filling pressure, systolic and diastolic function was a superior predictor of peak VO2 (R 0.69; all P<.001). Conclusions The reported association of diastolic rather than systolic function with functional capacity may have reflected the limitations of EF. Functional capacity appears related not only to diastolic function, but also to systolic function and filling pressure, and is most closely associated with a combination of these factors.

Prediction of subcellular localization using sequence-biased recurrent networks

Motivation: Targeting peptides direct nascent proteins to their specific subcellular compartment. Knowledge of targeting signals enables informed drug design and reliable annotation of gene products. However, due to the low similarity of such sequences and the dynamical nature of the sorting process, the computational prediction of subcellular localization of proteins is challenging. Results: We contrast the use of feed forward models as employed by the popular TargetP/SignalP predictors with a sequence-biased recurrent network model. The models are evaluated in terms of performance at the residue level and at the sequence level, and demonstrate that recurrent networks improve the overall prediction performance. Compared to the original results reported for TargetP, an ensemble of the tested models increases the accuracy by 6 and 5% on non-plant and plant data, respectively.

Disease risk and mortality prediction in intensive care patients with pneumonia. Australian and New Zealand practice in intensive care (ANZPIC II)

This study of ventilated patients investigated pneumonia risk factors and outcome predictors in 476 episodes of pneumonia (48% community-acquired pneumonia, 24% hospital-acquired pneumonia, 28% ventilator-associated pneumonia) using a prospective survey in 14 intensive care units within Australia and New Zealand. For community acquired pneumonia, mortality increased with immunosuppression (OR 5.32, CI 95% 1.58-17.99, P < 0. 01), clinical signs of consolidation (OR 2.43, CI 95% 1.09-5.44, P = 0. 03) and Sepsis-Related Organ Failure Assessment (SOFA) scores (OR 1.19, CI 95% 1.08-1.30, P < 0. 001) but improved if appropriate antibiotic changes were made within three days of intensive care unit admission (OR 0.42, CI 95% 0.20-0.86, P = 0.02). For hospital-acquired pneumonia, immunosuppression (OR 6.98, CI 95% 1.16-42.2, P = 0.03) and non-metastatic cancer (OR 3.78, CI 95% 1.20-11.93, P = 0.02) were the principal mortality predictors. Alcoholism (OR 7.80, CI 95% 1.20-1750, P < 0.001), high SOFA scores (OR 1.44, CI 95% 1.20-1.75, P = 0.001) and the isolation of high risk organisms including Pseudomonas aeruginosa, Acinetobacter spp, Stenotrophomonas spp and methicillin resistant Staphylococcus aureus (OR 4.79, CI 95% 1.43-16.03, P = 0.01), were associated with increased mortality in ventilator-associated pneumonia. The use of non-invasive ventilation was independently protective against mortality for patients with community-acquired and hospital-acquired pneumonia (OR 0.35, CI 95% 0.18-0.68, P = 0.002). Mortality was similar for patients requiting both invasive and non-invasive ventilation and non-invasive ventilation alone (21% compared with 20% respectively, P = 0.56). Pneumonia risks and mortality predictors in Australian and New Zealand ICUs vary with pneumonia type. A history of alcoholism is a major risk factor for mortality in ventilator-associated pneumonia, greater in magnitude than the mortality effect of immunosuppression in hospital-acquired pneumonia or community-acquired pneumonia. Non-invasive ventilation is associated with reduced ICU mortality. Clinical signs of consolidation worsen, while rationalising antibiotic therapy within three days of ICU admission improves mortality for community-acquired pneumonia patients.

The appetitive motivation scale and other BAS measures in the prediction of Approach and Active Avoidance

The Appetitive Motivation Scale (Jackson & Smillie, 2004) is a new trait conceptualisation of Gray's (I 970 199 1) Behavioural Activation System. In this experiment we explore relationships that the Appetitive Motivation Scale and other measures of Gray's model have with Approach and Active Avoidance responses. Using a sample of 144 undergraduate students, both Appetitive Motivation and Sensitivity to Reward (from the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, SPSRQ; Torrubia, Avila, Molto, & Ceseras, 2001), were found to be significant predictors of Approach and Active Avoidance response latency. This confirms previous experimental validations of the SPSRQ (e.g., Avila, 2001) and provides the first experimental evidence for the validity of the Appetitive Motivation scale. Consistent with interactive views of Gray's model (e.g., Corr, 2001), high SPSRQ Sensitivity to Punishment diminished the relationship between Sensitivity to Reward and our BAS criteria. Measures of BIS did not however interact in this way with the appetitive motivation scale. A surprising result was the failure for any of Carver and White's (1994) BAS scales to correlate with RST criteria. Implications of these findings and potential future directions are discussed. (C) 2004 Elsevier Ltd. All rights reserved.

Efffluent flux prediction in variably saturated soil zones within a septic tank-soil absorption trench

The treatment and hydraulic mechanisms in a septic tank-soil absorption system ( SAS) are highly influenced by the clogging layer or biomat zone which develops on bottom and lower sidewall surfaces within the trench. Flow rates through the biomat and sub-biomat zones are governed largely by the biomat hydraulic properties (resistance and hydraulic conductivity) and the unsaturated hydraulic conductivity of the underlying soil. One- and 2-dimensional models were used to investigate the relative importance of sidewall and vertical flow rates and pathways in SAS. Results of 1-dimensional modelling show that several orders of magnitude variation in saturated hydraulic conductivity (Ks) reduce to a 1 order of magnitude variation in long-term flow rates. To increase the reliability of prediction of septic trench hydrology, HYDRUS-2D was used to model 2-dimensional flow. In the permeable soils, under high trench loading, effluent preferentially flowed in the upper region of the trench where no resistant biomat was present (the exfiltration zone). By comparison, flow was more evenly partitioned between the biomat zones and the exfiltration zones of the low permeability soil. An increase in effluent infiltration corresponded with a greater availability of exfiltration zone, rather than a lower resistance of biomat. Results of modelling simulations demonstrated the important role that a permeable A horizon may play in limiting surface surcharge of effluent under high trench hydraulic loading.

Interference between propagating changes and its effect on system failure

Computer-based, socio-technical systems projects are frequently failures. In particular, computer-based information systems often fail to live up to their promise. Part of the problem lies in the uncertainty of the effect of combining the subsystems that comprise the complete system; i.e. the system's emergent behaviour cannot be predicted from a knowledge of the subsystems. This paper suggests uncertainty management is a fundamental unifying concept in analysis and design of complex systems and goes on to indicate that this is due to the co-evolutionary nature of the requirements and implementation of socio-technical systems. The paper shows a model of the propagation of a system change that indicates that the introduction of two or more changes over time can cause chaotic emergent behaviour.

Model-Driven safety evaluation with state-event-based component failure annotations

Over the past years, the paradigm of component-based software engineering has been established in the construction of complex mission-critical systems. Due to this trend, there is a practical need for techniques that evaluate critical properties (such as safety, reliability, availability or performance) of these systems. In this paper, we review several high-level techniques for the evaluation of safety properties for component-based systems and we propose a new evaluation model (State Event Fault Trees) that extends safety analysis towards a lower abstraction level. This model possesses a state-event semantics and strong encapsulation, which is especially useful for the evaluation of component-based software systems. Finally, we compare the techniques and give suggestions for their combined usage

An automated failure mode and effect analysis based on high-level design specificication with behavior trees

Formal methods have significant benefits for developing safety critical systems, in that they allow for correctness proofs, model checking safety and liveness properties, deadlock checking, etc. However, formal methods do not scale very well and demand specialist skills, when developing real-world systems. For these reasons, development and analysis of large-scale safety critical systems will require effective integration of formal and informal methods. In this paper, we use such an integrative approach to automate Failure Modes and Effects Analysis (FMEA), a widely used system safety analysis technique, using a high-level graphical modelling notation (Behavior Trees) and model checking. We inject component failure modes into the Behavior Trees and translate the resulting Behavior Trees to SAL code. This enables us to model check if the system in the presence of these faults satisfies its safety properties, specified by temporal logic formulas. The benefit of this process is tool support that automates the tedious and error-prone aspects of FMEA.