A bootstrap approach for assessing the uncertainty of outcome probabilities when using a scoring system

Background: Scoring systems are a very attractive family of clinical predictive models, because the patient score can be calculated without using any data processing system. Their weakness lies in the difficulty of associating a reliable prognostic probability with each score. In this study a bootstrap approach for estimating confidence intervals of outcome probabilities is described and applied to design and optimize the performance of a scoring system for morbidity in intensive care units after heart surgery. Methods: The bias-corrected and accelerated bootstrap method was used to estimate the 95% confidence intervals of outcome probabilities associated with a scoring system. These confidence intervals were calculated for each score and each step of the scoring-system design by means of one thousand bootstrapped samples. 1090 consecutive adult patients who underwent coronary artery bypass graft were assigned at random to two groups of equal size, so as to define random training and testing sets with equal percentage morbidities. A collection of 78 preoperative, intraoperative and postoperative variables were considered as likely morbidity predictors. Results: Several competing scoring systems were compared on the basis of discrimination, generalization and uncertainty associated with the prognostic probabilities. The results showed that confidence intervals corresponding to different scores often overlapped, making it convenient to unite and thus reduce the score classes. After uniting two adjacent classes, a model with six score groups not only gave a satisfactory trade-off between discrimination and generalization, but also enabled patients to be allocated to classes, most of which were characterized by well separated confidence intervals of prognostic probabilities. Conclusions: Scoring systems are often designed solely on the basis of discrimination and generalization characteristics, to the detriment of prediction of a trustworthy outcome probability. The present example demonstrates that using a bootstrap method for the estimation of outcome-probability confidence intervals provides useful additional information about score-class statistics, guiding physicians towards the most convenient model for predicting morbidity outcomes in their clinical context

Qualified and Unqualified (N-R C) mental health nursing staff - minor differences in sources of stress and burnout. A European multi-centre study

<p>Abstract</p> <p>Background</p> <p>Unqualified/non-registered caregivers (N-R Cs) will continue to play important roles in the mental health services. This study compares levels of burnout and sources of stress among qualified and N-R Cs working in acute mental health care.</p> <p>Methods</p> <p>A total of 196 nursing staff - 124 qualified staff (mainly nurses) and 72 N-R Cs with a variety of different educational backgrounds - working in acute wards or community mental teams from 5 European countries filled out the Maslach Burnout Inventory (MBI), the Mental Health Professional Scale (MHPSS) and the Psychosocial Work Environment and Stress Questionnaire (PWSQ).</p> <p>Results</p> <p>(a) The univariate differences were generally small and restricted to a few variables. Only Social relations (N-R Cs being less satisfied) at Work demands (nurses reporting higher demands) were different at the .05 level. (b) The absolute scores both groups was highest on variables that measured feelings of not being able to influence a work situation characterised by great demands and insufficient resources. Routines and educational programs for dealing with stress should be available on a routine basis. (c) Multivariate analyses identified three extreme groups: (i) a small group dominated by unqualified staff with high depersonalization, (ii) a large group that was low on depersonalisation and high on work demands with a majority of qualified staff, and (iii) a small N-R C-dominated group (low depersonalization, low work demands) with high scores on professional self-doubt. In contrast to (ii) the small and N-R C-dominated groups in (i) and (iii) reflected mainly centre-dependent problems.</p> <p>Conclusion</p> <p>The differences in burnout and sources of stress between the two groups were generally small. With the exception of high work demands the main differences between the two groups appeared to be centre-dependent. High work demands characterized primarily qualified staff. The main implication of the study is that no special measures addressed towards N-R Cs in general with regard to stress and burnout seem necessary. The results also suggest that centre-specific problems may cause more stress among N-R Cs compared to the qualified staff (e.g. professional self-doubt).</p

Identification of a tumor-specific allo-HLA-restricted γδTCR

γδT cells are key players in cancer immune surveillance because of their ability to recognize malignant transformed cells, which makes them promising therapeutic tools in the treatment of cancer. However, the biological mechanisms of how γδT-cell receptors (TCRs) interact with their ligands are poorly understood. Within this context, we describe the novel allo-HLA-restricted and CD8α-dependent Vγ5Vδ1TCR. In contrast to the previous assumption of the general allo-HLA reactivity of a minor fraction of γδTCRs, we show that classic anti-HLA-directed, γδTCR-mediated reactivity can selectively act on hematological and solid tumor cells, while not harming healthy tissues in vitro and in vivo. We identified the molecular interface with proximity to the peptide-binding groove of HLA-A*24:02 as the essential determinant for recognition and describe the critical role of CD8 as a coreceptor. We conclude that alloreactive γδT-cell repertoires provide therapeutic opportunities, either within the context of haplotransplantation or as individual γδTCRs for genetic engineering of tumor-reactive T cells