36 resultados para Methods Time Measurement (MTM)
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OBJECTIVE The number of suicides assisted by right-to-die associations has increased in recent years in Switzerland. The aim of our study was to compare time trends in rates of assisted and unassisted suicide from 1991-2008. METHODS The Swiss National Cohort is a longitudinal study of mortality in the Swiss population; based on linkage of census data with mortality records up to 2008. The Federal Statistical Office coded suspected assisted suicides from 1998 onwards; and from 2003 onwards right-to-die associations reported the suicides they assisted. We used Poisson regression to analyse trends in rates of suicide per 100'000 person-years, by gender and age groups (15-34, 35-64, 65-94 years). RESULTS A total of 7'940'297 individuals and 24'842 suicides were included. In women, rates changed little in the younger age groups but increased in 65-94-year-olds, due to an increase in suicide by poisoning (from 5.1 to 17.2 per 100'000; p <0.001). An increase in suicides by poisoning was also observed in older men (from 8.6 to 18.2; p<0.001). Most suicides by poisoning were assisted. In men, suicide rates declined in all age groups, driven by declines in suicide with firearms. CONCLUSIONS Research is needed to gain a better understanding of the reasons for the tripling of assisted suicide rates in older women, and the doubling of rates in older men, of attitudes and vulnerabilities of those choosing assisted suicide, and of access to palliative care. Rates of assisted suicide should be monitored; including data on patient characteristics and underlying comorbidities.
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A fast and automatic method for radiocarbon analysis of aerosol samples is presented. This type of analysis requires high number of sample measurements of low carbon masses, but accepts precisions lower than for carbon dating analysis. The method is based on online Trapping CO2 and coupling an elemental analyzer with a MICADAS AMS by means of a gas interface. It gives similar results to a previously validated reference method for the same set of samples. This method is fast and automatic and typically provides uncertainties of 1.5–5% for representative aerosol samples. It proves to be robust and reliable and allows for overnight and unattended measurements. A constant and cross contamination correction is included, which indicates a constant contamination of 1.4 ± 0.2 μg C with 70 ± 7 pMC and a cross contamination of (0.2 ± 0.1)% from the previous sample. A Real-time online coupling version of the method was also investigated. It shows promising results for standard materials with slightly higher uncertainties than the Trapping online approach.
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Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.
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This article centers on the computational performance of the continuous and discontinuous Galerkin time stepping schemes for general first-order initial value problems in R n , with continuous nonlinearities. We briefly review a recent existence result for discrete solutions from [6], and provide a numerical comparison of the two time discretization methods.
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BACKGROUND The aim of newborn screening (NBS) for CF is to detect children with 'classic' CF where early treatment is possible and improves prognosis. Children with inconclusive CF diagnosis (CFSPID) should not be detected, as there is no evidence for improvement through early treatment. No algorithm in current NBS guidelines explains what to do when sweat test (ST) fails. This study compares the performance of three different algorithms for further diagnostic evaluations when first ST is unsuccessful, regarding the numbers of children detected with CF and CFSPID, and the time until a definite diagnosis. METHODS In Switzerland, CF-NBS was introduced in January 2011 using an IRT-DNA-IRT algorithm followed by a ST. In children, in whom ST was not possible (no or insufficient sweat), 3 different protocols were applied between 2011 and 2014: in 2011, ST was repeated until it was successful (protocol A), in 2012 we proceeded directly to diagnostic DNA testing (protocol B), and 2013-2014, fecal elastase (FE) was measured in the stool, in order to determine a pancreas insufficiency needing immediate treatment (protocol C). RESULTS The ratio CF:CFSPID was 7:1 (27/4) with protocol A, 2:1 (22/10) with protocol B, and 14:1 (54/4) with protocol C. The mean time to definite diagnosis was significantly shorter with protocol C (33days) compared to protocol A or B (42 and 40days; p=0.014 compared to A, and p=0.036 compared to B). CONCLUSIONS The algorithm for the diagnostic part of the newborn screening used in the CF centers is important and affects the performance of a CF-NBS program with regard to the ratio CF:CFSPID and the time until definite diagnosis. Our results suggest to include FE after initial sweat test failure in the CF-NBS guidelines to keep the proportion of CFSPID low and the time until definite diagnosis short.
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INTRODUCTION Monitoring breathing pattern is especially relevant in infants with lung disease. Recently, a vest-based inductive plethysmograph system (FloRight®) has been developed for tidal breathing measurement in infants. We investigated the accuracy of tidal breathing flow volume loop (TBFVL) measurements in healthy term-born infants and infants with lung disease by the vest-based system in comparison to an ultrasonic flowmeter (USFM) with a face mask. We also investigated whether the system discriminates between healthy infants and those with lung disease. METHODS Floright® measures changes in thoracoabdominal volume during tidal breathing through magnetic field changes generated by current-carrying conductor coils in an elastic vest. Simultaneous TBFVL measurements by the vest-based system and the USFM were performed at 44 weeks corrected postmenstrual age during quiet unsedated sleep. TBFVL parameters derived by both techniques and within both groups were compared. RESULTS We included 19 healthy infants and 18 infants with lung disease. Tidal volume per body weight derived by the vest-based system was significantly lower with a mean difference (95% CI) of -1.33 ml/kg (-1.73; -0.92), P < 0.001. Respiratory rate and ratio of time to peak tidal expiratory flow over total expiratory time (tPTEF/tE) did not differ between the two techniques. Both systems were able to discriminate between healthy infants and those with lung disease using tPTEF/tE. CONCLUSION FloRight® accurately measures time indices and may discriminate between healthy infants and those with lung disease, but demonstrates differences in tidal volume measurements. It may be better suited to monitor breathing pattern than for TBFVL measurements.