Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates

International audienceCaffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the Pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate

The emergence of inequality in social groups: network structure and institutions affect the distribution of earnings in cooperation games

From small communities to entire nations and society at large, inequality in wealth, social status, and power is one of the most pervasive and tenacious features of the social world. What causes inequality to emerge and persist? In this study, we investigate how the structure and rules of our interactions can increase inequality in social groups. Specifically, we look into the effects of four structural conditions—network structure, network fluidity, reputation tracking, and punishment institutions—on the distribution of earnings in network cooperation games. We analyze 33 experiments comprising 96 experimental conditions altogether. We find that there is more inequality in clustered networks compared to random networks, in fixed networks compared to randomly rewired and strategically updated networks, and in groups with punishment institutions compared to groups without. Secondary analyses suggest that the reasons inequality emerges under these conditions may have to do with the fact that fixed networks allow exploitation of the poor by the wealthy and clustered networks foster segregation between the poor and the wealthy, while the burden of costly punishment falls onto the poor, leaving them poorer. Surprisingly, we do not find evidence that inequality is affected by reputation in a systematic way but this could be because reputation needs to play out in a particular network environment in order to have an effect. Overall, our findings suggest possible strategies and interventions to decrease inequality and mitigate its negative impact, particularly in the context of mid- and large-sized organizations and online communities

Motives and comprehension in a public goods game with induced emotions

This study analyses the sensitivity of public goods contributions through the lens of psychological motives. We report the results of a public goods experiment in which subjects were induced with the motives of care and anger through autobiographical recall. Subjects' preferences, beliefs, and perceptions under each motive are compared with those of subjects experiencing a neutral autobiographical recall control condition. We find, but only for those subjects with the highest comprehension of the game, that care elicits significantly higher contributions than anger, with the control treatment in between. This positive influence of the care motive on unconditional giving is accounted for partly by preferences for giving and partly by the beliefs concerning greater contributions by others. Anger also affects attention to own and other's payoffs (using mouse tracking) and perceptions of the game's incentive structure (cooperative or competitive)

Peer expectations about outstanding competencies of men and women medical students

Men and women enrolled in a combined premedical-medical school programme were asked as they began their clinical training to rate their anticipated competence on sixteen criteria relevant to medical practice. Competence dimensions tapped scientific/technical skills, dedication/commitment, and interpersonal skills. Students then were asked to nominate one classmate whom they expected might be‘the best’in each area. Self-ratings revealed few differences among men and women. Peer nominations, however, revealed a preponderance of male nominees in ten competence areas. Women dominated nominations only in the category of sensitivity to patients. Patterns persisted when peer nominations were controlled for students’academic standing and self-ratings on parallel dimensions. The data suggest that medical school peer groups share expectations about competencies of men and women as physicians which are consistent with generalized sex stereotypes and career patterns of men and women physicians.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74843/1/1467-9566.ep11340055.pd

A randomised controlled trial of nurse-managed trial conclusion following early phase cancer trial participation

The effect of a nurse-managed intervention, for early phase cancer trial participants at trial conclusion, on psychosocial outcomes was evaluated at two cancer centres in the Midlands, England using a randomised controlled trial. It involved 117 patients who were participating in an early phase cancer clinical trial. It was a nurse-managed trial exit, which included a trial exit interview, trial feedback information leaflet and telephone follow-up compared with standard care at trial conclusion. Psychological distress at 1 week and 4–6 weeks post-trial conclusion, patient's knowledge and understanding and patient's satisfaction were assessed. The results showed there was no significant difference between the two groups regarding scores for anxiety and depression at time one and time two. There is some suggestion that the intervention reduced anxiety from trial conclusion to follow-up (P=0.27). Patients in both groups felt they had contributed to cancer research through trial participation. However, intervention patients were more likely to feel that they knew how the trial was going (P<0.001), knew how other people in the trial were doing (P=0.001), had all the feedback they needed about the trial they took part in (P<0.01) and knew how they would be followed up (P=0.02). Patient satisfaction with the intervention was high (median score=4.5 where 5 is greatest satisfaction). In conclusion, nurse-managed trial conclusion led to positive outcomes for patients who had recently completed a clinical trial

Risk factors for revision due to infection after primary total hip arthroplasty: A population-based study of 80,756 primary procedures in the Danish Hip Arthroplasty Registry

There has been a limited amount of research on risk factors for revision due to infection following total hip arthroplasty (THA), probably due to low absolute numbers of revisions. We therefore studied patient- and surgery-related risk factors for revision due to infection after primary THA in a population-based setting