994 resultados para volume algorithm
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INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) is a new ventilatory mode in which ventilator settings are adjusted based on the electrical activity detected in the diaphragm (Eadi). This mode offers significant advantages in mechanical ventilation over standard pressure support (PS) modes, since ventilator input is determined directly from patient ventilatory demand. Therefore, it is expected that tidal volume (Vt) under NAVA would show better correlation with Eadi compared with PS, and exhibit greater variability due to the variability in the Eadi input to the ventilator. OBJECTIVES. To compare tidal volume variability in PS and NAVA ventilation modes, and its correlation with patient ventilatory demand (as characterized by maximum Eadi). METHODS. Acomparative study of patient-ventilator interaction was performed for 22 patients during standard PS with clinician determined ventilator settings; and NAVA, with NAVA gain set to ensure the same peak airway pressure as the total pressure obtained in PS. A 20 min continuous recording was performed in each ventilator mode. Respiratory rate, Vt, and Eadi were recorded. Tidal volume variance and Pearson correlation coefficient between Vt and Eadi were calculated for each patient. A periodogram was plotted for each ventilator mode and each patient, showing spectral power as a function of frequency to assess variability. RESULTS. Median, lower quartile and upper quartile values for Vt variance and Vt/Eadi correlation are shown in Table 1. The NAVA cohort exhibits substantially greater correlation and variance than the PS cohort. Power spectrums for Vt and Eadi are shown in Fig. 1 (PS and NAVA) for a typical patient. The enlarged section highlights how changes in Eadi are highly synchronized with NAVA ventilation, but less so for PS. CONCLUSIONS. There is greater variability in tidal volume and correlation between tidal volume and diaphragmatic electrical activity with NAVA compared to PS. These results are consistent with the improved patient-ventilator synchrony reported in the literature.
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OBJECTIVE: In general population survey instruments that measure volume of drinking, additional questions and shorter reference periods yield higher volumes. Comparison studies have focused on volume but not on associations between volume and consequences. METHOD: From a cohort study on substance use risk factors (Cohort Study on Substance Use Risk Factors [C-SURF]), baseline data were analyzed for 5,074 young (approximately 20-year-old) men who were drinkers in the past 12 months. Volume of drinking was measured by a generic quantity-frequency (QF) instrument, an extended QF (separately for weekends and weekdays) instrument with 12-months recall, and a retrospective past-week diary. Associations of consequences with and without attribution of alcohol as a cause, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), criteria for dependence, and DSM-5 alcohol use disorder in the past 12 months were analyzed. RESULTS: The generic QF measure resulted in lower volume compared with either the extended QF measure (more questions) or the retrospective diary (the most questions and the shortest recall period). For outcomes, however, the extended QF assessment performed the best and the diary the worst. CONCLUSIONS: Higher volume yields are not always better regarding associations with outcomes. The extended QF instrument better captures the variability of drinking. The retrospective diary performs poorly for associations because of the mismatch with the recall period for past-12-months consequences and the potential for misclassification of past-week abstainers and heavy drinkers because of an uncommon past week. Diaries are not recommended for research investigating individual associations between exposure and outcomes in young populations if consequences are measured with a sufficiently long interval to capture rare consequences. (J. Stud. Alcohol Drugs, 75, 880-888, 2014).
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In the following report, chapter two examines the extent and causes of health inequalities. The causes of inequalities are broad and some of them reach beyond the capabilities and responsibilities of both the Department of Health and the NHS. This report therefore focuses on the effectiveness of the policies of the Department of Health and the NHS.
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Our objective was to establish the age-related 3D size of maxillary, sphenoid, and frontal sinuses. A total of 179 magnetic resonance imaging (MRI) of children under 17 years (76 females, 103 males) were included and sinuses were measured in the three axes. Maxillary sinuses measured at birth (mean+/-standard deviation) 7.3+/-2.7 mm length (or antero-posterior)/4.0+/-0.9 mm height (or cranio-caudal)/2.7+/-0.8 mm width (or transverse). At 16 years old, maxillary sinus measured 38.8+/-3.5 mm/36.3+/-6.2 mm/27.5+/-4.2 mm. Sphenoid sinus pneumatization starts in the third year of life after conversion from red to fatty marrow with mean values of 5.8+/-1.4 mm/8.0+/-2.3 mm/5.8+/-1.0 mm. Pneumatization progresses gradually to reach at 16 years 23.0+/-4.5 mm/22.6+/-5.8 mm/12.8+/-3.1 mm. Frontal sinuses present a wide variation in size and most of the time are not valuable with routine head MRI techniques. They are not aerated before the age of 6 years. Frontal sinuses dimensions at 16 years were 12.8+/-5.0 mm/21.9+/-8.4 mm/24.5+/-13.3 mm. A sinus volume index (SVI) of maxillary and sphenoid sinus was computed using a simplified ellipsoid volume formula, and a table with SVI according to age with percentile variations is proposed for easy clinical application. Percentile curves of maxillary and sphenoid sinuses are presented to provide a basis for objective determination of sinus size and volume during development. These data are applicable to other techniques such as conventional X-ray and CT scan.
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BACKGROUND: Using a bench test model, we investigated the hypothesis that neonatal and/or adult ventilators equipped with neonatal/pediatric modes currently do not reliably administer pressure support (PS) in neonatal or pediatric patient groups in either the absence or presence of air leaks. METHODS: PS was evaluated in 4 neonatal and 6 adult ventilators using a bench model to evaluate triggering, pressurization, and cycling in both the absence and presence of leaks. Delivered tidal volumes were also assessed. Three patients were simulated: a preterm infant (resistance 100 cm H2O/L/s, compliance 2 mL/cm H2O, inspiratory time of the patient [TI] 400 ms, inspiratory effort 1 and 2 cm H2O), a full-term infant (resistance 50 cm H2O/L/s, compliance 5 mL/cm H2O, TI 500 ms, inspiratory effort 2 and 4 cm H2O), and a child (resistance 30 cm H2O/L/s, compliance 10 mL/cm H2O, TI 600 ms, inspiratory effort 5 and 10 cm H2O). Two PS levels were tested (10 and 15 cm H2O) with and without leaks and with and without the leak compensation algorithm activated. RESULTS: Without leaks, only 2 neonatal ventilators and one adult ventilator had trigger delays under a given predefined acceptable limit (1/8 TI). Pressurization showed high variability between ventilators. Most ventilators showed TI in excess high enough to seriously impair patient-ventilator synchronization (> 50% of the TI of the subject). In some ventilators, leaks led to autotriggering and impairment of ventilation performance, but the influence of leaks was generally lower in neonatal ventilators. When a noninvasive ventilation algorithm was available, this was partially corrected. In general, tidal volume was calculated too low by the ventilators in the presence of leaks; the noninvasive ventilation algorithm was able to correct this difference in only 2 adult ventilators. CONCLUSIONS: No ventilator performed equally well under all tested conditions for all explored parameters. However, neonatal ventilators tended to perform better in the presence of leaks. These findings emphasize the need to improve algorithms for assisted ventilation modes to better deal with situations of high airway resistance, low pulmonary compliance, and the presence of leaks.
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Most cases of emphysema are managed conservatively. However, in severe symptomatic emphysema associated with hyperinflation, lung volume reduction (LVR) may be proposed to improve dyspnea, exercice capacity, pulmonary functions, walk distance and to decrease long-term mortality. LVR may be achieved either surgically (LVRS) or endoscopically (EVLR by valves or coils) according to specific clinical criteria. Currently, the optimal approach is discussed in a multidisciplinary setting. The latter permits a personalized evaluation the patient's clinical status and allows the best possible therapeutic intervention to be proposed to the patient.
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INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) is an assisted ventilatorymode in which the ventilator is driven by the electrical activity of the diaphragm (Eadi).NAVAimproves patient-ventilator synchrony [1] but little is known about how to set the NAVA gaini.e., how to choose the ratio between Eadi and delivered pressure. The aim of the present studywas to assess the relationship between Eadi and tidal volume (Vt) at various NAVA gainsettings and to evaluate whether modifying the gain influenced this relationship in non-invasivelyventilated (NIV) patients.METHODS. Prospective interventional study comparing 3 values of NAVA gain during NIV(20 min each). NAVA100 was set by the clinician according to the manufacturer's recommendations.In NAVA50 and NAVA150 the gain was set as -50% and +50% of NAVA100gain respectively. Vt and maximal Eadi value (Eadi max) were recorded. The ratio Vt/Eadi wasthen assessed for each breath. 5-95% range (range 90) of Vt/Eadi was calculated for eachpatient at each NAVA gain setting. Vt/Eadi ratio has the advantage to give an objectiveassessment Vt/Eadi max relationship independently from the nature of this relationship. Asmaller Range90 indicates a better matching of Vt to Eadi max.RESULTS. 12 patients were included, 5 had obstructive pulmonary disease and 2 mixedobstructive and restrictive disease. For NAVA100, the median [IQR] Range 90 was 32[19-87]. For NAVA150 Range 90 was 37 [20-95] and for NAVA50 Range 90 was 33 [16-92].That means that globally NAVA100 allowed a better match between Eadi max and Vt thanNAVA50 and 150. However, by patient, NAVA100 had the lowest Range 90 value for only 4patients (33%), NAVA150 for 2 (17%) and NAVA50 for 6 (50%) patients, indicating thatNAVA100 was not the best NAVA gain for minimizing Range 90 in every patients.Comparing the lowest Range 90 value to the next lowest for each patient, showed that 3 patientshad differences of less than 10% (one each for NAVA50, NAVA100 and NAVA150). Theremainder had differences from 17 to 24%, indicating that most patients (9/12 or 75%) had aclear better match between Eadi and Vt for one specific NAVA gain.CONCLUSIONS. Different NAVA gains yielded markedly different ability to match Vt toEadi max. This approach could be a new way to determine optimalNAVAgain for each patientbut require further investigations.REFERENCE. Piquilloud L, et al. Intensive Care Med 2011;37:263-71.
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This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed
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In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm
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INTRODUCTION Hemodynamic resuscitation should be aimed at achieving not only adequate cardiac output but also sufficient mean arterial pressure (MAP) to guarantee adequate tissue perfusion pressure. Since the arterial pressure response to volume expansion (VE) depends on arterial tone, knowing whether a patient is preload-dependent provides only a partial solution to the problem. The objective of this study was to assess the ability of a functional evaluation of arterial tone by dynamic arterial elastance (Ea(dyn)), defined as the pulse pressure variation (PPV) to stroke volume variation (SVV) ratio, to predict the hemodynamic response in MAP to fluid administration in hypotensive, preload-dependent patients with acute circulatory failure. METHODS We performed a prospective clinical study in an adult medical/surgical intensive care unit in a tertiary care teaching hospital, including 25 patients with controlled mechanical ventilation who were monitored with the Vigileo(®) monitor, for whom the decision to give fluids was made because of the presence of acute circulatory failure, including arterial hypotension (MAP ≤65 mmHg or systolic arterial pressure <90 mmHg) and preserved preload responsiveness condition, defined as a SVV value ≥10%. RESULTS Before fluid infusion, Ea(dyn) was significantly different between MAP responders (MAP increase ≥15% after VE) and MAP nonresponders. VE-induced increases in MAP were strongly correlated with baseline Ea(dyn) (r(2) = 0.83; P < 0.0001). The only predictor of MAP increase was Ea(dyn) (area under the curve, 0.986 ± 0.02; 95% confidence interval (CI), 0.84-1). A baseline Ea(dyn) value >0.89 predicted a MAP increase after fluid administration with a sensitivity of 93.75% (95% CI, 69.8%-99.8%) and a specificity of 100% (95% CI, 66.4%-100%). CONCLUSIONS Functional assessment of arterial tone by Ea(dyn), measured as the PVV to SVV ratio, predicted arterial pressure response after volume loading in hypotensive, preload-dependent patients under controlled mechanical ventilation.