763 resultados para Adverse event relatedness


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This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.

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A significantly increased water regime can lead to inundation of rivers, creeks and surrounding floodplains- and thus impact on the temporal dynamics of both the extant vegetation and the dormant, but viable soil-seed bank of riparian corridors. The study documented changes in the soil seed-bank along riparian corridors before and after a major flood event in January 2011 in southeast Queensland, Australia. The study site was a major river (the Mooleyember creek) near Roma, Central Queensland impacted by the extreme flood event and where baseline ecological data on riparian seed-bank populations have previously been collected in 2007, 2008 and 2009. After the major flood event, we collected further soil samples from the same locations in spring/summer (November–December 2011) and in early autumn (March 2012). Thereafter, the soils were exposed to adequate warmth and moisture under glasshouse conditions, and emerged seedlings identified taxonomically. Flooding increased seed-bank abundance but decreased its species richness and diversity. However, flood impact was less than that of yearly effect but greater than that of seasonal variation. Seeds of trees and shrubs were few in the soil, and were negatively affected by the flood; those of herbaceous and graminoids were numerous and proliferate after the flood. Seed-banks of weedy and/or exotic species were no more affected by the flood than those of native and/or non-invasive species. Overall, the studied riparian zone showed evidence of a quick recovery of its seed-bank over time, and can be considered to be resilient to an extreme flood event.

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Objective The human Ureaplasma species are the microbes most frequently isolated from placentae of women who deliver preterm. The role of Ureaplasma species has been investigated in pregnancies at <32 weeks of gestation, but currently no studies have determined the prevalence of ureaplasmas in moderately preterm and late-preterm (hereafter, “moderate/late preterm”) infants, the largest cohort of preterm infants. Methods Women delivering moderate/late preterm infants (n = 477) and their infants/placentae (n = 535) were recruited, and swab specimens of chorioamnion tissue, chorioamnion tissue specimens, and cord blood specimens were obtained at delivery. Swab and tissue specimens were cultured and analyzed by 16S ribosomal RNA polymerase chain reaction (PCR) for the presence of microorganisms, while cord blood specimens were analyzed for the presence of cytokines, chemokines, and growth factors. Results We detected microorganisms in 10.6% of 535 placentae (443 were delivered late preterm and 92 were delivered at term). Significantly, Ureaplasma species were the most prevalent microorganisms, and their presence alone was associated with histologically confirmed chorioamnionitis in moderate/late preterm and term placentae (P < .001). The presence of ureaplasmas in the chorioamnion was also associated with elevated levels of granulocyte colony-stimulating factor (P = .02). Conclusions These findings have important implications for infection and adverse pregnancy outcomes throughout gestation and should be of major consideration for obstetricians and neonatologists.

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BACKGROUND Negative donation experiences, including vasovagal reactions, deter donor retention. However, whether this deterrence effect varies as a function of whole blood (WB) donation history and requests to donate the same or a different product remains unclear. STUDY DESIGN AND METHODS The responses of 894 eligible WB donors who had been approached to convert to plasmapheresis and 954 eligible first-time plasmapheresis donors who had been surveyed on their last donation experience and their intention to donate plasma were considered. This information was matched with individual vasovagal reaction records, deferral category, WB donation history, and subsequent donation behavioral data obtained from the blood collection agency. RESULTS Path analysis indicated that the application of a deferral and an officially recorded vasovagal reaction decreased donors' intentions to continue plasmapheresis donation, but had no effect on WB donors' intentions to convert to plasmapheresis. Consistent with past findings, vasovagal reactions occurred more frequently with female and inexperienced donors. CONCLUSION Experiencing vasovagal reactions and deferrals may not universally deter donors from continuing to donate. Rather, the offer to convert to another form of donation—in this instance, plasmapheresis—after experiencing a negative donation event while donating WB may be sufficient to eliminate the deterrence effect on retention.

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The idea of extracting knowledge in process mining is a descendant of data mining. Both mining disciplines emphasise data flow and relations among elements in the data. Unfortunately, challenges have been encountered when working with the data flow and relations. One of the challenges is that the representation of the data flow between a pair of elements or tasks is insufficiently simplified and formulated, as it considers only a one-to-one data flow relation. In this paper, we discuss how the effectiveness of knowledge representation can be extended in both disciplines. To this end, we introduce a new representation of the data flow and dependency formulation using a flow graph. The flow graph solves the issue of the insufficiency of presenting other relation types, such as many-to-one and one-to-many relations. As an experiment, a new evaluation framework is applied to the Teleclaim process in order to show how this method can provide us with more precise results when compared with other representations.

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Objective: We aimed to assess the impact of task demands and individual characteristics on threat detection in baggage screeners. Background: Airport security staff work under time constraints to ensure optimal threat detection. Understanding the impact of individual characteristics and task demands on performance is vital to ensure accurate threat detection. Method: We examined threat detection in baggage screeners as a function of event rate (i.e., number of bags per minute) and time on task across 4 months. We measured performance in terms of the accuracy of detection of Fictitious Threat Items (FTIs) randomly superimposed on X-ray images of real passenger bags. Results: Analyses of the percentage of correct FTI identifications (hits) show that longer shifts with high baggage throughput result in worse threat detection. Importantly, these significant performance decrements emerge within the first 10 min of these busy screening shifts only. Conclusion: Longer shift lengths, especially when combined with high baggage throughput, increase the likelihood that threats go undetected. Application: Shorter shift rotations, although perhaps difficult to implement during busy screening periods, would ensure more consistently high vigilance in baggage screeners and, therefore, optimal threat detection and passenger safety.

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Aerosol particles in the atmosphere are known to significantly influence ecosystems, to change air quality and to exert negative health effects. Atmospheric aerosols influence climate through cooling of the atmosphere and the underlying surface by scattering of sunlight, through warming of the atmosphere by absorbing sun light and thermal radiation emitted by the Earth surface and through their acting as cloud condensation nuclei. Aerosols are emitted from both natural and anthropogenic sources. Depending on their size, they can be transported over significant distances, while undergoing considerable changes in their composition and physical properties. Their lifetime in the atmosphere varies from a few hours to a week. New particle formation is a result of gas-to-particle conversion. Once formed, atmospheric aerosol particles may grow due to condensation or coagulation, or be removed by deposition processes. In this thesis we describe analyses of air masses, meteorological parameters and synoptic situations to reveal conditions favourable for new particle formation in the atmosphere. We studied the concentration of ultrafine particles in different types of air masses, and the role of atmospheric fronts and cloudiness in the formation of atmospheric aerosol particles. The dominant role of Arctic and Polar air masses causing new particle formation was clearly observed at Hyytiälä, Southern Finland, during all seasons, as well as at other measurement stations in Scandinavia. In all seasons and on multi-year average, Arctic and North Atlantic areas were the sources of nucleation mode particles. In contrast, concentrations of accumulation mode particles and condensation sink values in Hyytiälä were highest in continental air masses, arriving at Hyytiälä from Eastern Europe and Central Russia. The most favourable situation for new particle formation during all seasons was cold air advection after cold-front passages. Such a period could last a few days until the next front reached Hyytiälä. The frequency of aerosol particle formation relates to the frequency of low-cloud-amount days in Hyytiälä. Cloudiness of less than 5 octas is one of the factors favouring new particle formation. Cloudiness above 4 octas appears to be an important factor that prevents particle growth, due to the decrease of solar radiation, which is one of the important meteorological parameters in atmospheric particle formation and growth. Keywords: Atmospheric aerosols, particle formation, air mass, atmospheric front, cloudiness

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Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art.

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The overlapping sound pressure waves that enter our brain via the ears and auditory nerves must be organized into a coherent percept. Modelling the regularities of the auditory environment and detecting unexpected changes in these regularities, even in the absence of attention, is a necessary prerequisite for orientating towards significant information as well as speech perception and communication, for instance. The processing of auditory information, in particular the detection of changes in the regularities of the auditory input, gives rise to neural activity in the brain that is seen as a mismatch negativity (MMN) response of the event-related potential (ERP) recorded by electroencephalography (EEG). --- As the recording of MMN requires neither a subject s behavioural response nor attention towards the sounds, it can be done even with subjects with problems in communicating or difficulties in performing a discrimination task, for example, from aphasic and comatose patients, newborns, and even fetuses. Thus with MMN one can follow the evolution of central auditory processing from the very early, often critical stages of development, and also in subjects who cannot be examined with the more traditional behavioural measures of auditory discrimination. Indeed, recent studies show that central auditory processing, as indicated by MMN, is affected in different clinical populations, such as schizophrenics, as well as during normal aging and abnormal childhood development. Moreover, the processing of auditory information can be selectively impaired for certain auditory attributes (e.g., sound duration, frequency) and can also depend on the context of the sound changes (e.g., speech or non-speech). Although its advantages over behavioral measures are undeniable, a major obstacle to the larger-scale routine use of the MMN method, especially in clinical settings, is the relatively long duration of its measurement. Typically, approximately 15 minutes of recording time is needed for measuring the MMN for a single auditory attribute. Recording a complete central auditory processing profile consisting of several auditory attributes would thus require from one hour to several hours. In this research, I have contributed to the development of new fast multi-attribute MMN recording paradigms in which several types and magnitudes of sound changes are presented in both speech and non-speech contexts in order to obtain a comprehensive profile of auditory sensory memory and discrimination accuracy in a short measurement time (altogether approximately 15 min for 5 auditory attributes). The speed of the paradigms makes them highly attractive for clinical research, their reliability brings fidelity to longitudinal studies, and the language context is especially suitable for studies on language impairments such as dyslexia and aphasia. In addition I have presented an even more ecological paradigm, and more importantly, an interesting result in view of the theory of MMN where the MMN responses are recorded entirely without a repetitive standard tone. All in all, these paradigms contribute to the development of the theory of auditory perception, and increase the feasibility of MMN recordings in both basic and clinical research. Moreover, they have already proven useful in studying for instance dyslexia, Asperger syndrome and schizophrenia.

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Tutkimuksen taustalla on väestön ikääntyminen ja iäkkäiden lisääntynyt lääkkeiden käyttö. Ikääntyminen aiheuttaa elimistössä useita muutoksia, jotka voivat muuttaa lääkevastetta ja altistaa potilaan haittavaikutuksille. Iäkkäillä riski joutua sairaalaan lääkkeen haittavaikutuksen vuoksi on arvioitu olevan neljä kertaa suurempi kuin nuoremmilla. Monet lääkkeiden yhteis- ja haittavaikutukset olisivat ehkäistävissä välttämällä iäkkäillä tiettyjä lääkeaineita. Iäkkäiden lääkehoitojen seurantaa ja arviointia varten on kehitetty erilaisia suosituksia sekä Suomessa että kansainvälisesti. Tutkimuksen tavoitteena oli luoda Suomen oloihin soveltuva, hoitajien koulutettuina käytettävissä oleva, avohoidon yli 65-vuotiaiden iäkkäiden lääkitykseen liittyviä riskejä arvioiva työkalu. Työkalun avulla voitaisiin löytää ne potilaat, joiden lääkitykseen liittyy paljon riskejä. Tutkimuksen aineistona olivat laaja kansainvälinen kirjallisuuskatsaus iäkkäiden lääkehoitoihin liittyvistä tekijöistä sekä asiantuntijakommentoinnit, joiden perusteella luotiin alustava arviointityökalu. Alustava arviointityökalu validoitiin kolmikierroksisella Delfoi-menetelmällä. Delfoi-menetelmä on laadullinen konsensusmenetelmä, joka perustuu asiantuntijoiden arvioihin tutkittavasta asiasta. Kaksi ensimmäistä Delfoi-kierrosta mittasivat alustavan arviointityökalun kohtien soveltuvuutta ja kolmas kierros kohtien tärkeyttä arvioitaessa iäkkään lääkityksiin liittyviä riskejä. Tutkimuksen Delfoi-kierroksien vastaajiksi pyydettiin 33 geriatrian asiantuntijaa, joista vastaajiksi lupautui 11 lääkäriä, 3 proviisoria ja 4 sairaanhoitajaa. Delfoi-kierrosten tuloksia analysoitiin sekä kvantitatiivisesti että kvalitatiivisesti. Tutkimuksen tuloksena saatu arviointityökalu käsittää 19 iäkkäiden lääkehoitoa arvioivaa kohtaa. Asiantuntijapaneelin mukaan kaikki arviointityökalun lääkitykseen liittyviä riskejä mittaavat kohdat ovat tärkeitä tai jokseenkin tärkeitä, joten työkalun voidaan olettaa olevan validi mitattaessa lääkitykseen liittyviä riskejä. Jatkotutkimuksissa työkalun käytettävyyttä sekä riskien mittaamiskykyä tulee testata sekä arviointityökalun käyttäjien että potilaiden keskuudessa. Kehitettyä työkalua voidaan jatkossa hyödyntää esimerkiksi koulutustarkoituksissa sen varsinaisen käyttötarkoituksen lisäksi. Työkalun avulla iäkkäiden lääkehoitoa voidaan tulevaisuudessa toteuttaa entistä turvallisemmin ja tarkoituksenmukaisemmin.

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The performance of the Advanced Regional Prediction System (ARPS) in simulating an extreme rainfall event is evaluated, and subsequently the physical mechanisms leading to its initiation and sustenance are explored. As a case study, the heavy precipitation event that led to 65 cm of rainfall accumulation in a span of around 6 h (1430 LT-2030 LT) over Santacruz (Mumbai, India), on 26 July, 2005, is selected. Three sets of numerical experiments have been conducted. The first set of experiments (EXP1) consisted of a four-member ensemble, and was carried out in an idealized mode with a model grid spacing of 1 km. In spite of the idealized framework, signatures of heavy rainfall were seen in two of the ensemble members. The second set (EXP2) consisted of a five-member ensemble, with a four-level one-way nested integration and grid spacing of 54, 18, 6 and 1 km. The model was able to simulate a realistic spatial structure with the 54, 18, and 6 km grids; however, with the 1 km grid, the simulations were dominated by the prescribed boundary conditions. The third and final set of experiments (EXP3) consisted of a five-member ensemble, with a four-level one-way nesting and grid spacing of 54, 18, 6, and 2 km. The Scaled Lagged Average Forecasting (SLAF) methodology was employed to construct the ensemble members. The model simulations in this case were closer to observations, as compared to EXP2. Specifically, among all experiments, the timing of maximum rainfall, the abrupt increase in rainfall intensities, which was a major feature of this event, and the rainfall intensities simulated in EXP3 (at 6 km resolution) were closest to observations. Analysis of the physical mechanisms causing the initiation and sustenance of the event reveals some interesting aspects. Deep convection was found to be initiated by mid-tropospheric convergence that extended to lower levels during the later stage. In addition, there was a high negative vertical gradient of equivalent potential temperature suggesting strong atmospheric instability prior to and during the occurrence of the event. Finally, the presence of a conducive vertical wind shear in the lower and mid-troposphere is thought to be one of the major factors influencing the longevity of the event.