Intra-Individual Variability in Alzheimer's Disease and Cognitive Aging: Definitions, Context, and Effect Sizes

To explore different definitions of intra-individual variability (IIV) to summarize performance on commonly utilized cognitive tests (Mini Mental State Exam; Clock Drawing Test); compare them and their potential to differentiate clinically-defined populations; and to examine their utility in predicting clinical change in individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI).) were computed for each of these definitions in 500 simulated replicates using scores on the Mini Mental State Exam and Clock Drawing Test. IIV was computed based on test items separately (‘within test’ IIV) and the two tests together (‘across test’ IIV). The best performing definition was then used to compute IIV for a third test, the Alzheimer's Disease Assessment Scale-Cognitive, and the simulations and effect sizes were again computed. All effect size estimates based on simulated data were compared to those computed based on the total scores in the observed data. Association between total score and IIV summaries of the tests and the Clinician's Dementia Rating were estimated to test the utility of IIV in predicting clinically meaningful changes in the cohorts over 12- and 24-month intervals.ES estimates differed substantially depending on the definition of IIV and the test(s) on which IIV was based. IIV (coefficient of variation) summaries of MMSE and Clock-Drawing performed similarly to their total scores, the ADAS total performed better than its IIV summary.IIV can be computed within (items) or across (totals) items on commonly-utilized cognitive tests, and may provide a useful additional summary measure of neuropsychological test performance

The contrasting role of technology as both supportive and hindering in the everyday lives of people with mild cognitive deficits: a focus group study

Background: It is well known that people with mild cognitive deficits face challenges when performing complex everyday activities, and that the use of technology has become increasingly interwoven with everyday activities. However, less is known of how technology might be involved, either as a support or hindrance, in different areas of everyday life and of the environments where challenges appear. The aim of this study was to investigate the areas of concern where persons with cognitive deficits meet challenges in everyday life, in what environments these challenges appear and how technology might be involved as part of the challenge and/or the solution to the challenge. Methods: Data were gathered through four focus group interviews with participants that live with cognitive deficits or cohabit with a person with cognitive deficits, plus health professionals and researchers in the field. Data were transcribed, coded and categorized, and finally synthesized to trace out the involvement of technology. Results: Five areas of concern in everyday life were identified as offering challenges to persons with cognitive deficits: A) Managing personal finances, B) Getting around, C) Meeting family and friends, D) Engaging with culture and media and, E) Doing everyday chores. Findings showed that the involvement of technology in everyday activities was often contrastive. It could be hindering and evoke stress, or it could bring about feelings of control; that is, being a part of the solution. The involvement of technology was especially obvious in challenges linked to Managing personal finances, which is a crucial necessity in many everyday activities. In contrast, technology was least obviously involved in the area Socializing with family and friends. Conclusions: The findings imply that technology used for orientation and managing finances, often used outside home, would benefit from being further developed in order to be more supportive; i.e. accessible and usable. To make a positive change for many people, the ideas of inclusive design fit well for this purpose and would contribute to an age-friendly society

Training family physicians and residents in family medicine in shared decision making to improve clinical decisions regarding the use of antibiotics for acute respiratory infections: protocol for a clustered randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>To explore ways to reduce the overuse of antibiotics for acute respiratory infections (ARIs), we conducted a pilot clustered randomized controlled trial (RCT) to evaluate DECISION+, a training program in shared decision making (SDM) for family physicians (FPs). This pilot project demonstrated the feasibility of conducting a large clustered RCT and showed that DECISION+ reduced the proportion of patients who decided to use antibiotics immediately after consulting their physician. Consequently, the objective of this study is to evaluate, in patients consulting for ARIs, if exposure of physicians to a modified version of DECISION+, DECISION+2, would reduce the proportion of patients who decide to use antibiotics immediately after consulting their physician.</p> <p>Methods/design</p> <p>The study is a multi-center, two-arm, parallel clustered RCT. The 12 family practice teaching units (FPTUs) in the network of the Department of Family Medicine and Emergency Medicine of Université Laval will be randomized to a DECISION+2 intervention group (experimental group) or to a no-intervention control group. These FPTUs will recruit patients consulting family physicians and residents in family medicine enrolled in the study. There will be two data collection periods: pre-intervention (baseline) including 175 patients with ARIs in each study arm, and post-intervention including 175 patients with ARIs in each study arm (total n = 700). The primary outcome will be the proportion of patients reporting a decision to use antibiotics immediately after consulting their physician. Secondary outcome measures include: 1) physicians and patients' decisional conflict; 2) the agreement between the parties' decisional conflict scores; and 3) perception of patients and physicians that SDM occurred. Also in patients, at 2 weeks follow-up, adherence to the decision, consultation for the same reason, decisional regret, and quality of life will be assessed. Finally, in both patients and physicians, intention to engage in SDM in future clinical encounters will be assessed. Intention-to-treat analyses will be applied and account for the nested design of the trial will be taken into consideration.</p> <p>Discussion</p> <p>DECISION+2 has the potential to reduce antibiotics use for ARIs by priming physicians and patients to share decisional process and empowering patients to make informed, value-based decisions.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="NCT01116076">NCT01116076</a></p

Uncertainty analysis using Bayesian Model Averaging: a case study of input variables to energy models and inference to associated uncertainties of energy scenarios

Background Energy models are used to illustrate, calculate and evaluate energy futures under given assumptions. The results of energy models are energy scenarios representing uncertain energy futures. Methods The discussed approach for uncertainty quantification and evaluation is based on Bayesian Model Averaging for input variables to quantitative energy models. If the premise is accepted that the energy model results cannot be less uncertain than the input to energy models, the proposed approach provides a lower bound of associated uncertainty. The evaluation of model-based energy scenario uncertainty in terms of input variable uncertainty departing from a probabilistic assessment is discussed. Results The result is an explicit uncertainty quantification for input variables of energy models based on well-established measure and probability theory. The quantification of uncertainty helps assessing the predictive potential of energy scenarios used and allows an evaluation of possible consequences as promoted by energy scenarios in a highly uncertain economic, environmental, political and social target system. Conclusions If societal decisions are vested in computed model results, it is meaningful to accompany these with an uncertainty assessment. Bayesian Model Averaging (BMA) for input variables of energy models could add to the currently limited tools for uncertainty assessment of model-based energy scenarios

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Return to work of breast cancer survivors: a systematic review of intervention studies

<p>Abstract</p> <p>Background</p> <p>Breast cancer management has improved dramatically in the past three decades and as a result, a population of working age women is breast cancer survivor. Interventions for breast cancer survivors have shown improvements in quality of life and in physical and psychological states. In contrast, efforts aimed at stimulating re-employment and return-to-work interventions for breast cancer survivors have not kept pace. The objective of this review was to study the effects and characteristics of intervention studies on breast cancer survivors in which the outcome was return to work.</p> <p>Methods</p> <p>The Cochrane Controlled Trials Register (The Cochrane Library, Issue 4, 2006), Medline, Ovid, EMBASE and PsychInfo were systematically searched for studies conducted between 1970 to February 2007. Intervention studies for female breast cancer survivors that were focused on return to work were included.</p> <p>Results</p> <p>Our search strategy identified 5219 studies. Four studies out of 100 potentially relevant abstracts were selected and included 46–317 employed women who had had mastectomy, adjuvant therapy and rehabilitation, with the outcome return to work. The intervention programs focused on improvement of physical, psychological and social recovery. Although a substantial percentage (between 75% to 85%) of patients included in these studies returned to work after rehabilitation, it is not clear whether this proportion would have been lower for patients without counseling or exercise, or any other interventions, as three out of four studies did not include a comparison group.</p> <p>Conclusion</p> <p>The most important finding of this review is the lack of methodologically sound intervention studies on breast cancer survivors with the outcome return to work. Using evidence from qualitative and observational studies on cancer and the good results of intervention studies on return to work programs and vocational rehabilitation, return to work interventions for breast cancer survivors should be further developed and evaluated.</p

Pro-inflammatory profile of preeclamptic placental mesenchymal stromal cells: new insights into the etiopathogenesis of preeclampsia.

The objective of the present study was to evaluate whether placental mesenchymal stromal cells (PDMSCs) derived from normal and preeclamptic (PE) chorionic villous tissue presented differences in their cytokines expression profiles. Moreover, we investigated the effects of conditioned media from normal and PE-PDMSCs on the expression of pro-inflammatory Macrophage migration Inhibitory Factor (MIF), Vascular Endothelial Growth Factor (VEGF), soluble FMS-like tyrosine kinase-1 (sFlt-1) and free β-human Chorionic Gonadotropin (βhCG) by normal term villous explants. This information will help to understand whether anomalies in PE-PDMSCs could cause or contribute to the anomalies typical of preeclampsia. METHODS: Chorionic villous PDMSCs were isolated from severe preeclamptic (n = 12) and physiological control term (n = 12) placentae. Control and PE-PDMSCs’s cytokines expression profiles were determined by Cytokine Array. Control and PE-PDMSCs were plated for 72 h and conditioned media (CM) was collected. Physiological villous explants (n = 48) were treated with control or PE-PDMSCs CM for 72 h and processed for mRNA and protein isolation. MIF, VEGF and sFlt-1 mRNA and protein expression were analyzed by Real Time PCR and Western Blot respectively. Free βhCG was assessed by immunofluorescent. RESULTS: Cytokine array showed increased release of pro-inflammatory cytokines by PE relative to control PDMSCs. Physiological explants treated with PE-PDMSCs CM showed significantly increased MIF and sFlt-1 expression relative to untreated and control PDMSCs CM explants. Interestingly, both control and PE-PDMSCs media induced VEGF mRNA increase while only normal PDMSCs media promoted VEGF protein accumulation. PE-PDMSCs CM explants released significantly increased amounts of free βhCG relative to normal PDMSCs CM ones. CONCLUSIONS: Herein, we reported elevated production of pro-inflammatory cytokines by PE-PDMSCs. Importantly, PE PDMSCs induced a PE-like phenotype in physiological villous explants. Our data clearly depict chorionic mesenchymal stromal cells as central players in placental physiopathology, thus opening to new intriguing perspectives for the treatment of human placental-related disorders as preeclampsia

Effect of Age on Variability in the Production of Text-Based Global Inferences

As we age, our differences in cognitive skills become more visible, an effect especially true for memory and problem solving skills (i.e., fluid intelligence). However, by contrast with fluid intelligence, few studies have examined variability in measures that rely on one’s world knowledge (i.e., crystallized intelligence). The current study investigated whether age increased the variability in text based global inference generation–a measure of crystallized intelligence. Global inference generation requires the integration of textual information and world knowledge and can be expressed as a gist or lesson. Variability in generating two global inferences for a single text was examined in young-old (62 to 69 years), middle-old (70 to 76 years) and old-old (77 to 94 years) adults. The older two groups showed greater variability, with the middle elderly group being most variable. These findings suggest that variability may be a characteristic of both fluid and crystallized intelligence in aging