Related Covariates Research Articles

Associations between anxiety and depression symptoms and cognitive testing and neuroimaging in type 2 diabetes

AimsAnxiety, depression, accelerated cognitive decline, and increased risk of dementia are observed in individuals with type 2 diabetes. Anxiety and depression may contribute to lower performance on cognitive tests and differences in neuroimaging observed in individuals with type 2 diabetes. MethodsThese relationships were assessed in 655 European Americans with type 2 diabetes from 504 Diabetes Heart Study families. Participants completed cognitive testing, brain magnetic resonance imaging, the Brief Symptom Inventory Anxiety subscale, and the Center for Epidemiologic Studies Depression-10. ResultsIn analyses adjusted for age, sex, educational attainment, and use of psychotropic medications, individuals with comorbid anxiety and depression symptoms had lower performance on all cognitive testing measures assessed (p≤0.005). Those with both anxiety and depression also had increased white matter lesion volume (p=0.015), decreased gray matter cerebral blood flow (p=4.43×10−6), decreased gray matter volume (p=0.002), increased white and gray matter mean diffusivity (p≤0.001), and decreased white matter fractional anisotropy (p=7.79×10−4). These associations were somewhat attenuated upon further adjustment for health status related covariates. ConclusionsComorbid anxiety and depression symptoms were associated with cognitive performance and brain structure in a European American cohort with type 2 diabetes.

Influence of protected areas on malaria prevalence in Sub-Saharan Africa

IntroductionDespite exponential growth in the number and extent of protected areas globally, their role within disease dynamics remains unclear. Protected areas shape many biophysical and social factors related to malaria prevalence such as land use-land cover, biodiversity, socioeconomic conditions, and human behavior. This work examines the extent to which protected areas influence Plasmodium falciparum malaria prevalence within surrounding human populations throughout Sub-Saharan Africa.. MethodsUsing malaria prevalence data from 2008 to 2012, we tested for differences in mean malaria prevalence at survey locations according to the IUCN classification of the nearest protected area. We also used dual logistic regression and Random Forest approaches to model malaria burdens at survey locations using a variety of known biophysical determinants of malaria in addition to protected area related covariates. ResultsWe found that malaria prevalence differed by IUCN class, with survey locations near IUCN classes Ia and III exhibiting significantly higher prevalence values than all other classes. Additionally, distance to the nearest protected area emerged as an important predictor of malaria prevalence in the logistic regression model, with lower malaria prevalence at locations closer to protected areas (OR: 1.14; 95% CI: 1.10–1.17). Distance was of moderate importance in the Random Forest models; however, the relationship between distance and prevalence was nonlinear.. ConclusionsWe show that, at a continental scale, malaria prevalence was lower for populations closer to protected areas in Africa, compared to farther away. However, we also found evidence of spatially complex relationships, both around individual protected areas, and across protected areas at this geographic extent, reinforcing the need for additional, small-scale case studies. Ultimately, by showing a link between protected areas and disease presence, this work helps improve understanding of the complex, multiscalar drivers of malaria..

Introducing TRICOVA:� Trichotomous Covariance� A Post Hoc Advanced Statistical Test of Qualitative and Quantitative Group Variances to Determine the Strength of the Relationships Between Variables of the Tri�Squared Test

This monograph provides an epistemological rational for novel “Trichotomous Covariance” statistic represented by theacronym [“TRICOVA”]. This new statistic is an innovative in depth way of investigating a Post Hoc Tri–Squared Test as anadvanced data analytical methodology. TRICOVA is a detailed statistical procedure for the internal testing of theoutcomes of a significant transformation of qualitative data into quantitative outcomes through the Tri–Squared Test (firstintroduced in the Journal on Mathematics, and detailed further in the Journal on Educational Technology, Journal onSchool Educational Technology, and in the Journal on Educational Psychology). TRICOVA as an advanced statisticalprocedure; is designed to measure the overall size of the movement (or change) between inputted and outputtedTri–Squared variables. It also is designed to identify the magnitude and type of covariant relationship in existencebetween Tri–Squared Test qualitative and quantitative variables. This new innovative approach to the advancedstatistical post hoc metrics of the Tri–Squared Test adds an additional layer of richness and insight into the inner workingsof the Tri–Squared Test. It also adds considerable value to the mixed methods approach of research design that involvesthe holistic combination and comparison of qualitative and quantitative data outcomes. Two TRICOVA equations arepresented as well as the entire process of advanced statistical Tri–Covariance analytics that display how to conductTrichotomous Covariance inquiry.

Mapping local regression for spatial object-pairs

ABSTRACTLocal regression methods such as geographically weighted regression (GWR) can provide specific information about individual locations (or places) in spatial analysis that is useful for mapping nonstationary covariate relationships. However, the distance-based weighting schemes used in GWR are only adaptable for spatial objects that are point or area features. In particular, spatial object-pairs pose a challenge for local analysis because they have a linear dimensionality rather than a point dimensionality. This paper proposes using an alternative local regression model – quantile regression (QR) – for investigating the stationarity of regression parameters with respect to these linear features as well as facilitating the visualization of the results. An empirical example of a gravity model analysis of trade patterns within Europe is used to illustrate the utility of the proposed method.

Predictive Factors for Voluntary and/or Paid Work among Adults in their Sixties

Population aging is a current challenge globally as the Baby Boomers are heading towards retirement. In Finland, a regional-council postulated that the rate of retirement in the region will leave more than half of the population retired in the near future. Hence, this study conducted logistic regressions for predictive factors for voluntary and paid work among adults in their 60s from the region by using the Aging and Well-being of North-Savo Survey. Chi Square tests were also implemented in order to examine the link between their current engagement and their well-being. The logistic regressions implemented showed relative covariates of education, income, health and socioeconomic delineation as predictive factors for current and future engagements in voluntary and paid work. Chi Square tests also revealed a link between the current engagement of the respondents and their well-being. However, further studies will be needed so as to determine the differences in the relativity of the predictive factors by gender. In addition, the study suggests the importance of continuing the discussion of older adult’s productive engagement and its value base in relation to income and outcomes, as well as spiritual empathy and sustainable future for the elderly.

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd.

Determinants of Children's Exhaled Nitric Oxide: New Insights from Quantile Regression.

While the fractional concentration of exhaled nitric oxide (FeNO) has proven useful in asthma research, its exact role in clinical care remains unclear, in part due to unexplained inter-subject heterogeneity. In this study, we assessed the hypothesis that the effects of determinants of the fractional concentration of exhaled nitric oxide (FeNO) vary with differing levels of FeNO. In a population-based cohort of 1542 school children aged 12–15 from the Southern California Children's Health Study, we used quantile regression to investigate if the relationships of asthma, socio-demographic and clinical covariates with FeNO vary across its distribution. Differences in FeNO between children with and without asthma increased steeply as FeNO increased (Estimated asthma effects (in ppb) at selected 20th, 50th and 80th percentiles of FeNO are 2.4, 6.3 and 22.2, respectively) but the difference was steeper with increasing FeNO in boys and in children with active rhinitis (p-values<0.01). Active rhinitis also showed significantly larger effects on FeNO at higher concentrations of FeNO (Estimated active rhinitis effects (in ppb) at selected 20th, 50th and 80th percentiles of FeNO are 2.1, 5.7 and 14.3, respectively). Boys and children of Asian descent had higher FeNO than girls and non-Hispanic whites; these differences were significantly larger in those with higher FeNO (p-values<0.01). In summary, application of quantile regression techniques provides new insights into the determinants of FeNO showing substantially varying effects in those with high versus low concentrations.

Going with the flow: Tidal influence on the occurrence of the harbour porpoise (Phocoena phocoena) in the Marsdiep area, The Netherlands

One of the most important factors explaining the distribution and behaviour of coastal marine mammals are tides. Tidal forces drive a large number of primary and secondary processes, such as changes in water depth, salinity, temperature, current velocity and direction. Unravelling which tidal process is the most influential for a certain species is often challenging, due to a lack of observations of all tide related covariates, strong correlation between them, and the elusive nature of most marine organisms which often hampers their detection.In the Marsdiep area, a tidal inlet between the North Sea and the Dutch Wadden Sea, the presence of harbour porpoises (Phocoena phocoena) was studied as a function of tide related covariates. Observations were carried out in early spring from a ferry crossing the inlet on a half hourly basis. Environmental and sightings data were collected by one observer, while an on-board Acoustic Doppler Current Profiler (ADCP) and temperature sensor continuously recorded current velocity profiles and temperature, respectively. Sea surface temperature and salinity were measured at a nearby jetty. Sightings (n=134) were linked to tidal elevation, geographical position, local depth-averaged current velocity, water temperature (with and without trend correction) and salinity.Variation in sighting rate was best described by salinity, with highest sighting rate at high levels of salinity (>30gkg−1), indicating that porpoises enter the area in bodies of (more saline) North Sea water. Second best variable was time of day, with the highest sighting rate early morning, and decreasing during the day. However, surveys in the morning happened to coincide more often with high water and hence, the apparent time of day effect could be due to collinearity. Most porpoises were present in the northern part of the Marsdiep, particularly during high tide.Tide dependent sighting rates confirmed that porpoises reside in the North Sea, and enter the western Wadden Sea during the flood and leave during ebb. This tidal influx is most likely related to prey availability, which corresponds to other recent studies in this area showing higher fish abundance during high tide. Documenting information on tide related patterns could be used in practice, when e.g. planning anthropogenic activities or assessing critical habitats for this species.

Rational Decision-Making Process Choosing Fairness Over Monetary Gain as Decision Criteria

Objective: This study tests the hypothesis that the decision-making process in humans is often based on the fairness rather than the monetary gain/loss, when they are confronted with a choice between fairness and monetary gain/loss. Methods: The classical Ultimatum Game (UG) is used as the experimental paradigm to quantify the threshold crossover-point to switch the decision from rejection to acceptance. The fairness stimulus-response function is used for quantifying the decision threshold and the co-variation relationship between fairness and monetary gain/loss. Results: The results show that the level of fairness perception is always 27.5% lower for the rejection decision than the acceptance decision, irrespective of the offer-ratio (i.e., monetary gain/loss) or the baseline level of fairness for that decision. The data also show a co-variation relationship between fairness and offer-ratio (monetary gain/loss), but such proportionality relationship is decoupled at the even-split singularity point. The analysis shows that the decision crossover threshold is located at a slightly unfair perception, indicating tolerance to some unfairness in the decision. This suggests that a rejection decision is made when the unfairness perception threshold is reached. Conclusion: These analyses validated the hypothesis that the decision to accept/reject the monetary offer is logically consistent using the fairness criterion as the threshold for decision along the fairness-axis — even for accepting inequitable offers or rejecting hyper-equitable offers, irrespective of the amount of monetary gain/loss. The apparent decision based on the monetary gain/loss criterion is only a side effect of the co-variation between fairness and monetary gain.

Maximum A Posteriori Bayesian Estimation of Chromatographic Parameters by Limited Number of Experiments.

The aim of this work was to develop a nonlinear mixed-effect chromatographic model able to describe the retention times of weak acids and bases in all possible combinations of organic modifier content and mobile-phase pH. Further, we aimed to identify the influence of basic covariates, like lipophilicity (log P), dissociation constant (pK(a)), and polar surface area (PSA), on the intercompound variability of chromatographic parameters. Lastly, we aimed to propose the optimal limited experimental design to the estimation process of parameters through a maximum a posteriori (MAP) Bayesian method to facilitate the method development process. The data set comprised retention times for two series of organic modifier content collected at different pH for a large series of acids and bases. The obtained typical parameters and their distribution were subsequently used as priors to improve the estimation process from reduced design with a variable number of preliminary experiments. The MAP Bayesian estimator was validated using two external-validation data sets. The common literature model was used to relate analyte retention time with mobile-phase pH and organic modifier content. A set of QSRR-based covariate relationships was established. It turned out that four preliminary experiments and prior information that includes analyte pK(a), log P, acid/base type, and PSA are sufficient to accurately predict analyte retention in virtually all combined changes of pH and organic modifier content. The MAP Bayesian estimator of all important chromatographic parameters controlling retention in pH/organic modifier gradient was developed. It can be used to improve parameter estimation using limited experimental design.

Relationship between Remembering, Understanding and Applying of Bloom Taxonomy’s Cognitive Domain and Students Academic Achievement in Mathematics

Bloom’s taxonomy of educational objectives has been used by educators as a useful model of learning concepts and ideas. While every Mathematics teacher would dream of his/her students reaching the highest level of Bloom’s taxonomy, the reality in Nigeria and other developing countries is far from this. This study investigated the relationship between three dimensions of the cognitive domain namely: remembering, understanding and applying and mathematics achievement among secondary students in Nigeria. A measure of the three levels of the cognitive domain was used for data collection from 250 respondents. Multivariate statistical techniques via Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM) revealed that the observed variables’ measuring the latent constructs: remembering, understanding and applying measured it. Significant covariance relationships among the latent constructs were established. The three dimensions of the cognitive domain directly and positively influenced academic achievement of mathematics students. Lastly, the overall model fit the data. Suggestions are offered on the effective utilization of the three dimensions of the cognitive domain in mathematics instructional contents delivery.

Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling.

Studies on factors of low birth weight in Malawi have neglected the flexible approach of using smooth functions for some covariates in models. Such flexible approach reveals detailed relationship of covariates with the response. The study aimed at investigating risk factors of low birth weight in Malawi by assuming a flexible approach for continuous covariates and geographical random effect. A Bayesian geo-additive model for birth weight in kilograms and size of the child at birth (less than average or average and higher) with district as a spatial effect using the 2010 Malawi demographic and health survey data was adopted. A Gaussian model for birth weight in kilograms and a binary logistic model for the binary outcome (size of child at birth) were fitted. Continuous covariates were modelled by the penalized (p) splines and spatial effects were smoothed by the two dimensional p-spline. The study found that child birth order, mother weight and height are significant predictors of birth weight. Secondary education for mother, birth order categories 2-3 and 4-5, wealth index of richer family and mother height were significant predictors of child size at birth. The area associated with low birth weight was Chitipa and areas with increased risk to less than average size at birth were Chitipa and Mchinji. The study found support for the flexible modelling of some covariates that clearly have nonlinear influences. Nevertheless there is no strong support for inclusion of geographical spatial analysis. The spatial patterns though point to the influence of omitted variables with some spatial structure or possibly epidemiological processes that account for this spatial structure and the maps generated could be used for targeting development efforts at a glance.

Using spatial gradient analysis to clarify species distributions with application to South African protea

Typical ecological gradient analyses consider variation in the response of plants along a gradient of covariate values, but generally constrain themselves to predetermined response curves and ignore spatial autocorrelation. In this paper, we develop a formal spatial gradient analysis. We adopt the mathematical definition of gradients as directional rates of change with regard to a spatial surface. We view both the response and the covariate as spatial surfaces over a region of interest with respective gradient behavior. The gradient analysis we propose enables local comparison of these gradients. At any spatial location, we compare the behavior of the response surface with the behavior of the covariate surface to provide a novel form of sensitivity analysis. More precisely, we first fit a joint hierarchical Bayesian spatial model for a response variable and an environmental covariate. Then, after model fitting, at a given location, for each variable, we can obtain the posterior distribution of the derivative in any direction. We use these distributions to compute spatial sensitivities and angular discrepancies enabling a more detailed picture of the spatial nature of the response–covariate relationship. This methodology is illustrated using species presence probability as a response to elevation for two species of South African protea. We also offer a comparison with sensitivity analysis using geographically weighted regression. We show that the spatial gradient analysis allows for more extensive inference and provides a much richer description of the spatially varying relationships.

A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables

This paper formulates a generalized heterogeneous data model (GHDM) that jointly handles mixed types of dependent variables—including multiple nominal outcomes, multiple ordinal variables, and multiple count variables, as well as multiple continuous variables—by representing the covariance relationships among them through a reduced number of latent factors. Sufficiency conditions for identification of the GHDM parameters are presented. The maximum approximate composite marginal likelihood (MACML) method is proposed to estimate this jointly mixed model system. This estimation method provides computational time advantages since the dimensionality of integration in the likelihood function is independent of the number of latent factors. The study undertakes a simulation experiment within the virtual context of integrating residential location choice and travel behavior to evaluate the ability of the MACML approach to recover parameters. The simulation results show that the MACML approach effectively recovers underlying parameters, and also that ignoring the multi-dimensional nature of the relationship among mixed types of dependent variables can lead not only to inconsistent parameter estimation, but also have important implications for policy analysis.

Parkinson's disease-related spatial covariance pattern identified with resting-state functional MRI.

In this study, we sought to identify a disease-related spatial covariance pattern of spontaneous neural activity in Parkinson's disease using resting-state functional magnetic resonance imaging (MRI). Time-series data were acquired in 58 patients with early to moderate stage Parkinson's disease and 54 healthy controls, and analyzed by Scaled Subprofile Model Principal Component Analysis toolbox. A split-sample analysis was also performed in a derivation sample of 28 patients and 28 control subjects and validated in a prospective testing sample of 30 patients and 26 control subjects. The topographic pattern of neural activity in Parkinson's disease was characterized by decreased activity in the striatum, supplementary motor area, middle frontal gyrus, and occipital cortex, and increased activity in the thalamus, cerebellum, precuneus, superior parietal lobule, and temporal cortex. Pattern expression was elevated in the patients compared with the controls, with a high accuracy (90%) to discriminate the patients from the controls. The split-sample analysis produced a similar pattern but with a lower accuracy for group discrimination in both the derivation (80%) and the validation (73%) samples. Our results showed that resting-state functional MRI can be potentially useful for identification of Parkinson's disease-related spatial covariance patterns, and for differentiation of Parkinson's disease patients from healthy controls at an individual level.

Exploring the Paradox of Intimate Partner Violence and Increased Contraceptive Use in sub-Saharan Africa.

We question the positive effect of intimate partner violence on women's modern contraceptive use in sub-Saharan Africa found in previous studies. The explanations offered for this counter-intuitive result are either that women make greater efforts to avoid childbearing in conflictual relationships, or that endogeneity bias exists. Endogeneity bias stems from the inability of researchers to attribute a specific cause to one variable when they are unable to control for related missing covariates. Demographic and Health Survey data from 13 countries in sub-Saharan Africa provide evidence for the latter but not the former. Indeed, using simple probit regression models, we observe a positive relationship between intimate partner violence and modern contraceptive use in Burkina Faso, Mali, Nigeria, Tanzania, and Zimbabwe. This effect remains unchanged when controlling for various measures of women's autonomy in the household, showing that these two variables interact with contraceptive use independently. However, the use of recursive bivariate probit and Rosenbaum bounds sensitivity analysis to control for endogeneity biases erodes the initial positive effect in the five countries, although only partially in Burkina Faso. Our research shows that the previously reported findings arise from poor model specification and highlights the need for more appropriate data to assess the effect of intimate partner violence on modern contraceptive use in sub-Saharan Africa.

Characterization of random stress fields obtained from polycrystalline aggregate calculations using multi-scale stochastic finite elements

The spatial variability of stress fields resulting from polycrystalline aggregate calculations involving random grain geometry and crystal orientations is investigated. A periodogram-based method is proposed to identify the properties of homogeneous Gaussian random fields (power spectral density and related covariance structure). Based on a set of finite element polycrystalline aggregate calculations the properties of the maximal principal stress field are identified. Two cases are considered, using either a fixed or random grain geometry. The stability of the method w.r.t the number of samples and the load level (up to 3.5% macroscopic deformation) is investigated.

Should we trust the Z-score? Evidence from the European Banking Industry

We investigate the accuracy of the Z-score, a widely used proxy of bank soundness, on a sample of European banks from 12 countries over the period 2001–2011. Specifically, we run a horse race analysis between the Z-score and the CAMELS related covariates. Using probit and complementary log–log models, we find that the Z-score's ability to identify distress events, both in the whole period and during the crisis years (2008–2011), is at least as good as the CAMELS variables, but with the advantage of being less data demanding. Finally, the Z-score proves to be more effective when bank business models may be more sophisticated as it is the case for large and commercial banks.

Mo1165 Prediction for Mortality in Patients With Non-Variceal Upper Gastrointestinal Bleeding: Novel DGSG Score

Background: Acute upper gastrointestinal bleeding (UGIB) is a common medical emergency resulting in significant morbidity, mortality and cost of care. Whilst red blood cell (RBC) transfusion may be life-saving in massive UGIB, recent controlled trials suggest that a liberal transfusion practice is associated with increased re-bleeding rates and reduced survival after UGIB. 1 Aim: To determine the association between transfusion and rebleeding, mortality at 30 days and at one year after acute non-variceal UGIB. Methods: A retrospective, cohort study of patients who underwent endoscopy at three Western Australian tertiary hospitals for a suspected acute non-variceal UGIB in the period 2008-2010. A detailed chart review and linkage to hospital morbidity, emergency department, death registration and patient blood management data was performed. Logistic regression models were used to investigate factors associated with odds of an early rebleed. Cox models were used to identify factors associated with mortality outcomes. Results: There were 2,238 individuals with a total of 2,370 UGIB admission records. The median age at presentation for first UGIB was 70 years (range 19 to 99 years) and 63% of the cohort was male. Increasing volumes of early RBC transfusion was associated with increased odds of an early rebleed in a dose response trend but only in patients who presented with an Hb >90g/dl (OR 1.5; 95% CI 1.3-1.8; p=0.001). 30-day mortality was 4.9% (n=109). An increased rate of 30 day mortality was observed with increasing number of units of FFP (HR 2.3; 95% CI 1.1-4.6; p=0.02) and platelets (HR 3.7; 95% CI 1.8-7.7; p=0.001) transfused during the UGIB admission after adjusting for other patient and treatment related covariates. There were a further 200 deaths (9%) that occurred after 30 days but within one year of UGIB admission. Transfusion of greater than five units of FFP during the UGIB admission was associated with increased one year mortality (HR 6.7; 95% CI 3.3-13.4; p=0.001) but only for patients who had an INR 150,000 and after adjusting for other covariates. RBC transfusion was not associated with mortality outcomes. Conclusion: In this large, multicentre study, early RBC transfusion was associated with increased rebleeding in patients who presented with Hb > 90g/dl. FFP transfusion and not RBC transfusion was associated with increased mortality outcomes for patients, particularly those with a normal coagulation profile. Reference: 1. Villanueva et al, NEJM 2013; 368: 11-21.

Mo1164 Red Blood Cell Transfusion Is Associated With Increased Rebleeding but Fresh Frozen Plasma With Increased Mortality in Acute Non-Variceal Upper Gastrointestinal Bleeding

Background: Acute upper gastrointestinal bleeding (UGIB) is a common medical emergency resulting in significant morbidity, mortality and cost of care. Whilst red blood cell (RBC) transfusion may be life-saving in massive UGIB, recent controlled trials suggest that a liberal transfusion practice is associated with increased re-bleeding rates and reduced survival after UGIB. 1 Aim: To determine the association between transfusion and rebleeding, mortality at 30 days and at one year after acute non-variceal UGIB. Methods: A retrospective, cohort study of patients who underwent endoscopy at three Western Australian tertiary hospitals for a suspected acute non-variceal UGIB in the period 2008-2010. A detailed chart review and linkage to hospital morbidity, emergency department, death registration and patient blood management data was performed. Logistic regression models were used to investigate factors associated with odds of an early rebleed. Cox models were used to identify factors associated with mortality outcomes. Results: There were 2,238 individuals with a total of 2,370 UGIB admission records. The median age at presentation for first UGIB was 70 years (range 19 to 99 years) and 63% of the cohort was male. Increasing volumes of early RBC transfusion was associated with increased odds of an early rebleed in a dose response trend but only in patients who presented with an Hb >90g/dl (OR 1.5; 95% CI 1.3-1.8; p=0.001). 30-day mortality was 4.9% (n=109). An increased rate of 30 day mortality was observed with increasing number of units of FFP (HR 2.3; 95% CI 1.1-4.6; p=0.02) and platelets (HR 3.7; 95% CI 1.8-7.7; p=0.001) transfused during the UGIB admission after adjusting for other patient and treatment related covariates. There were a further 200 deaths (9%) that occurred after 30 days but within one year of UGIB admission. Transfusion of greater than five units of FFP during the UGIB admission was associated with increased one year mortality (HR 6.7; 95% CI 3.3-13.4; p=0.001) but only for patients who had an INR 150,000 and after adjusting for other covariates. RBC transfusion was not associated with mortality outcomes. Conclusion: In this large, multicentre study, early RBC transfusion was associated with increased rebleeding in patients who presented with Hb > 90g/dl. FFP transfusion and not RBC transfusion was associated with increased mortality outcomes for patients, particularly those with a normal coagulation profile. Reference: 1. Villanueva et al, NEJM 2013; 368: 11-21.