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Sensitivity analysis of common statistical models used to study the short-term effects of air pollution on health.

The relationship between photochemical air pollutants (nitrogen dioxide and ozone) and emergency room admissions for asthma in Madrid (Spain) for the period 1995-1998 was analysed using the statistical models commonly used to studying the short-term effects of air pollution on health: linear and Cochrane-Orcutt regression, standard Poisson and Poisson corrected by overdispersion, Poisson autoregressive models, and generalised additive models. Linear regression models presented residual autocorrelation, Poisson regression models also showed overdispersion, and generalised additive models did not show residual autocorrelation and overdispersion was substantially reduced. Linear models provided biased estimates because our health outcome is non-normally distributed. Estimates from Poisson regression allowing for overdispersion and autocorrelation did not differ substantially from those reported by generalised additive models, which present the best model fit in terms of the absence of autocorrelation and reduction of overdispersion.

Air Pollutants↗

Building intelligent alarm systems by combining mathematical models and inductive machine learning techniques Part 2--sensitivity analysis.

In an earlier study an approach was described to generate intelligent alarm systems for monitoring ventilation of patients via mathematical simulation and machine learning. However, ventilator settings were not varied. In this study we investigated whether an alarm system could be created with which a satisfactory classification performance could be obtained under a wide variety of ventilator settings, by varying inspiratory to expiratory time (I:E) ratio, tidal volume and respiratory rate. In a first experiment three patient data sets were modeled, each with a different I:E ratio. A part of each data set was used to construct an alarm system for each I:E ratio. The remaining part was used to test the performance of the alarm systems. The three training sets were also combined to construct one alarm system, which was tested with the three test sets. Finally, all alarm systems were tested with data generated by a patient simulator. Similar experiments were performed for the tidal volume and the respiratory rate. It was concluded that an optimally functioning alarm system should contain a library of rule sets, one for each set of ventilator settings. A second best alternative is to take all possible settings into consideration when constructing the training set. Classification performance of the trees that were trained with multiple ventilator settings ranged from 98 to 100% for all test sets. When tested with the independent patient simulator data the classification performance of these trees ranged from 80 to 100%.

Airway Resistance↗

Air pollution and morbidity: a sensitivity analysis of alternative monitors, pollutants, and averaging times.

Large cross-sectional data bases containing observations at the individual level are well suited for exploring the functional relationship between ambient air quality and health outcome. Since these analyses require the use of fixed-site air pollution monitors to measure pollution exposure, the results are subject to continued uncertainty. This study addresses three major concerns related to the use of these monitors. The results indicate that: (1) particulate matter alone is an important air pollution source of morbidity. It does not appear to mask or incorporate the effect of other air pollutants; (2) the estimated impact of air pollution on health is insensitive to actual monitor location. However, combining central city and suburban residents can lead to an underestimate of the pollution impact; and (3) the results are generally consistent when either a short or long term measure of pollution exposure is used.

Adolescent↗

Relative effectiveness of interposed abdominal compression CPR: sensitivity analysis and recommended compression rates.

UNLABELLED: Interposed abdominal compression, IAC-CPR incorporates alternating chest and abdominal compressions to generate enhanced artificial circulation during cardiac arrest. The technique has been generally successful in improving blood flow and survival compared to standard CPR; however, some questions remain. OBJECTIVE: To determine "why does IAC-CPR produce more apparent benefit in some subjects than in others?" and "what is the proper compression rate, given that there are actually two compressions (chest and abdomen) in each cycle?" METHOD: Computer models provide a means to search for subtle effects in complex systems. The present study employs a validated 12-compartment mathematical model of the human circulation to explore the effects upon systemic perfusion pressure of changes in 35 different variables, including vascular resistances, vascular compliances, and rescuer technique. CPR with and without IAC was modeled. RESULTS AND CONCLUSIONS: Computed results show that the effect of 100 mmHg abdominal compressions on systemic perfusion pressure is relatively constant (about 16 mmHg augmentation). However, the effect of chest compression depends strongly upon chest compression frequency and technique. When chest compression is less effective, as is often true in adults, the addition of IAC produces relatively dramatic augmentation (e.g. from 24 to 40 mmHg). When chest compression is more effective, the apparent augmentation with IAC is relatively less (e.g. from 60 to 76 mmHg). The optimal frequency for uninterrupted IAC-CPR is near 50 complete cycles/min with very little change in efficacy over 20-100 cycles/min. In theory, the modest increase in systemic perfusion pressure produced by IAC can make up in part for poor or ineffective chest compressions in CPR. IAC appears relatively less effective in circumstances when chest pump output is high.

Abdomen↗

Sensitivity analysis of calculated exposure concentrations and dissipation of DEHP in a topsoil compartment: the influence of the third phase effect and dissolved organic matter (DOM).

The fate and risk assessment of hydrophobic substances in the terrestrial environment can be associated with large errors. These can be attributed to the partitioning and process coefficients derived in experimental studies and to the model set-up that is designed to calculate the exposure concentrations. In many cases, the concentration of xenobiotics are low in the environment, which gives the aqueous phase the characteristics of a true solution, which are in accordance with the thermodynamic description of dilute solutions. Under these circumstances, the conventional equilibrium coefficients, such as Kd, Henry's Law constant H and the bioconcentration factor, BCF, are independent of the activity coefficient of the partitioning compound in the respective phases. However, for hydrophobic substances, these coefficients are often measured in laboratory experiments, where the nominal concentration levels are above the substance saturation point within the bulk water phase. In the case of the phthalates, the hydrophobic effect induces the formation of microdroplets (third phase) in the bulk water phase, by which the system is characterised as a heterogeneous mixture. Consequently, the linearity between dissolved and sorbed concentration is no longer true. Furthermore, in the terrestrial and aquatic environment, the presence of natural Dissolved Organic Matter (DOM) will have an influence on the fate and effects of hydrophobic substances. Hydrophobic compounds show large affinity for sorption to DOM, and contrary to Fixed Organic Matter (FOM), DOM is mobile and can be transported through the soil pores with the advective flow. It is therefore crucial that dispersed or emulsified phases within the continuous aqueous phase, e.g. DOM and microemulsions of phthalates, are distinguished from true solutions in the experimental measurements of partitioning coefficients, e.g. in order not to underestimate the mobility of sorbed substance. These aspects are treated in this study, where the exposure concentration, vertical transport and microbial degradation of Di-(2-ethylhexyl)-phthalate (DEHP) is modelled in an organic rich topsoil compartment, using experimental partitioning coefficients and degradation rates from the literature. Two model set-ups are derived for the topsoil compartment, i.e. (1) a system with dilute solution of substance and (2) a system with the presence of a third phase of microdroplets. In both models, the presence of DOM is incorporated. The first model shows that the error in the calculated exposure concentration, by using partitioning coefficients derived under unfavourable experimental conditions, compared to realistic conditions, amounts to 1400%. A comparison between the two models shows that when emulsion formation is not incorporated in the model, the calculated flux will be overestimated by a factor of 60.

Adsorption↗

Sensitive analysis of plasma physostigmine levels using dual-cell electrochemistry in the redox mode.

A column liquid chromatographic method using dual-electrode, redox electrochemical detection has been developed for measuring plasma and cerebrospinal fluid physostigmine levels. The method is suitable for detecting drug levels in a geriatric population following oral ingestion of sustained-release physostigmine preparations and for determining the pharmacokinetics of these preparations in biological fluids.

Administration, Oral↗