Predictive ability of an early diagnostic guess in patients presenting with chest pain; a longitudinal descriptive study.

ABSTRACT: BACKGROUND: The intuitive early diagnostic guess could play an important role in reaching a final diagnosis. However, no study to date has attempted to quantify the importance of general practitioners' (GPs) ability to correctly appraise the origin of chest pain within the first minutes of an encounter. METHODS: The validation study was nested in a multicentre cohort study with a one year follow-up and included 626 successive patients who presented with chest pain and were attended by 58 GPs in Western Switzerland. The early diagnostic guess was assessed prior to a patient's history being taken by a GP and was then compared to a diagnosis of chest pain observed over the next year. RESULTS: Using summary measures clustered at the GP's level, the early diagnostic guess was confirmed by further investigation in 51.0% (CI 95%; 49.4% to 52.5%) of patients presenting with chest pain. The early diagnostic guess was more accurate in patients with a life threatening illness (65.4%; CI 95% 64.5% to 66.3%) and in patients who did not feel anxious (62.9%; CI 95% 62.5% to 63.3%). The predictive abilities of an early diagnostic guess were consistent among GPs. CONCLUSIONS: The GPs early diagnostic guess was correct in one out of two patients presenting with chest pain. The probability of a correct guess was higher in patients with a life-threatening illness and in patients not feeling anxious about their pain.

Nanoinventory : a representative survey of nanoparticle usage in Suisse industry

Background Addressing the risks of nanoparticles requires knowledge about their hazards, which is generated progressively, but also about occupational exposure and liberation into the environment. However, currently such information is not systematically collected, therefore the risk assessment of this exposure or liberation lacks quantitative data. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate on the totality of the Swiss workforce. The goal of this study was to evaluate in a representative way the current prevalence and level of nanoparticle usage in Swiss industry, the health, safety and environment measures, and the number of potentially exposed workers. Results A representative, stratified mail survey was conducted among 1,626 clients of the Swiss National Accident Insurance Fund (SUVA). SUVA insures about 80,000 manufacturing firms, which represent 84% of all Swiss manufacturing companies. 947 companies answered the survey (58.3% response rate). Extrapolation to all Swiss manufacturing companies results in 1,309 workers (95%-confidence interval, 1,073 to 1,545) across the Swiss manufacturing sector being potentially exposed to nanoparticles in 586 companies (95%-CI: 145 to 1'027). This corresponds to 0.08% (95%-CI: 0.06% to 0.09%) of all Swiss manufacturing sector workers and to 0.6% (95%-CI: 0.2% to 1.1%) of companies. The industrial chemistry sector showed the highest percentage of companies using nanoparticles (21.2% of those surveyed) and a high percentage of potentially exposed workers (0.5% of workers in these companies), but many other important sectors also reported nanoparticles. Personal protection equipment was the predominant protection strategy. Only a minority applied specific environmental protection measures. Conclusions This is the first representative nationwide study on the prevalence of nanoparticle usage across a manufacturing sector. The information about the number of companies can be used for quantitative risk assessment. Furthermore it can help policy makers designing strategies to support companies in the responsible development of safer nanomaterial use. Noting the low prevalence of nanoparticle usage, there would still seem to be time to introduce necessary protection methods in a proactive and cost effective way in Swiss industry. But if the predicted "nano-revolution" becomes true, now is the time to take action.

Industrial nanoparticle application : representative survey among Swiss companies shows low usage and basic protection means

Manufactured nanoparticles are introduced into industrial processes, but they are suspected to cause similar negative health effects as ambient particles. The poor knowledge about the scale of this introduction did not allow global risk analysis so far. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate on the totality of the Swiss workforce. To gain this kind of information a layered representative questionnaire survey among 1'626 Swiss companies was conducted in 2007. Data was collected about the number of potentially exposed persons in the companies and their protection strategy. The response rate was 58.3%. An expected number of 586 companies (95%−confidence interval 145 to 1'027) was shown by this study to use nanoparticles in Switzerland. Estimated 1'309 (1'073 to 1'545) workers do their job in the same room as a nanoparticle application. Personal protection was shown to be the predominant type of protection means. Companies starting productions with nanomaterials need to consider incorporating protection measures into the plans. This will not only benefit the workers' health, but will also likely increase the competitiveness of the companies. Technical and organisational protection means are not only more cost−effective on the long term, but are also easier to control. Guidelines may have to be designed specifically for different industrial applications, including fields outside nanotechnology, and adapted to all sizes of companies.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Quality of Qualitative Research in the Health Sciences : Analysis of the Common Criteria Present in 58 Assessment Guidelines by Expert Users

The number of qualitative research methods has grown substantially over the last twenty years, both in social sciences and, more recently, in the health sciences. This growth came with questions on the quality criteria needed to evaluate this work, and numerous guidelines were published. The latters include many discrepancies though, both in their vocabulary and construction. Many expert evaluators decry the absence of consensual and reliable evaluation tools. The authors present the results of an evaluation of 58 existing guidelines in 4 major health science fields (medicine and epidemiology; nursing and health education; social sciences and public health; psychology / psychiatry, research methods and organization) by expert users (article reviewers, experts allocating funds, editors, etc.). The results propose a toolbox containing 12 consensual criteria with the definitions given by expert users. They also indicate in which disciplinary field each type of criteria is known to be more or less essential. Nevertheless, the authors highlight the limitations of the criteria comparability, as soon as one focuses on their specific definitions. They conclude that each criterion in the toolbox must be explained to come to broader consensus and identify definitions that are consensual to all the fields examined and easily operational.