Variation in treatment strategies of Swiss general practitioners for subclinical hypothyroidism in older adults.

QUESTIONS UNDER STUDY As the best management of subclinical hypothyroidism is controversial, we aimed to assess variations in treatment strategies depending on different Swiss regions, physician and patient characteristics. METHODS We performed a case-based survey among general practitioners (GPs) in different Swiss regions, which consisted of eight hypothetical cases presenting a female patient with subclinical hypothyroidism and nonspecific complaints differing by age, vitality status and thyroid-stimulating hormone (TSH) concentration. RESULTS A total of 262 GPs participated in the survey. There was considerable variation in the levothyroxine starting dose chosen by GPs, ranging from 25 µg to 100 µg. Across the Swiss regions, GPs in the Bern region were significantly more inclined to treat, with a higher probability of initiating treatment (60%, p = 0.01) and higher mean starting doses (45 µg, p <0.01) compared with the French-speaking region (44%, 36 µg); the Zurich region had intermediate values (52%, 39 µg). We found no association between treatment rate and other physician characteristics. GPs were more reluctant to initiate treatment in 85-year-old than in 70-year-old women (odds ratio [OR] 0.77, 95% confidence interval [CI] 0.63-0.94), and more likely to treat women with a TSH of 15 mU/l than those with a TSH of 6mU/l (OR 8.71, 95% CI 6.21-12.20). CONCLUSIONS There are strong variations in treatment strategies for elderly patients with subclinical hypothyroidism across different Swiss regions, including use of higher starting doses than the recommended 25 µg in the Swiss guidelines, which recommend a starting dose of 25 µg. These variations likely reflect the current uncertainty about the benefits of treatment, which arise from the current lack of evidence from adequately powered clinical trials.

The role of inducible nitric oxide synthase for interstitial remodeling of alveolar septa in surfactant protein D-deficient mice

Surfactant protein D (SP-D) modulates the lung's immune system. Its absence leads to NOS2-independent alveolar lipoproteinosis and NOS2-dependent chronic inflammation, which is critical for early emphysematous remodeling. With aging, SP-D knockout mice develop an additional interstitial fibrotic component. We hypothesize that this age-related interstitial septal wall remodeling is mediated by NOS2. Using invasive pulmonary function testing such as the forced oscillation technique and quasistatic pressure-volume perturbation and design-based stereology, we compared 29-wk-old SP-D knockout (Sftpd(-/-)) mice, SP-D/NOS2 double-knockout (DiNOS) mice, and wild-type mice (WT). Structural changes, including alveolar epithelial surface area, distribution of septal wall thickness, and volumes of septal wall components (alveolar epithelium, interstitial tissue, and endothelium) were quantified. Twenty-nine-week-old Sftpd(-/-) mice had preserved lung mechanics at the organ level, whereas elastance was increased in DiNOS. Airspace enlargement and loss of surface area of alveolar epithelium coexist with increased septal wall thickness in Sftpd(-/-) mice. These changes were reduced in DiNOS, and compared with Sftpd(-/-) mice a decrease in volumes of interstitial tissue and alveolar epithelium was found. To understand the effects of lung pathology on measured lung mechanics, structural data were used to inform a computational model, simulating lung mechanics as a function of airspace derecruitment, septal wall destruction (loss of surface area), and septal wall thickening. In conclusion, NOS2 mediates remodeling of septal walls, resulting in deposition of interstitial tissue in Sftpd(-/-). Forward modeling linking structure and lung mechanics describes the complex mechanical properties by parenchymatous destruction (emphysema), interstitial remodeling (septal wall thickening), and altered recruitability of acinar airspaces.

Virtual Patients in continuing medical education and residency training: a pilot project for acceptance analysis in the framework of a residency revision course in pediatrics.

AIM Virtual patients (VPs) are a one-of-a-kind e-learning resource, fostering clinical reasoning skills through clinical case examples. The combination with face-to-face teaching is important for their successful integration, which is referred to as "blended learning". So far little is known about the use of VPs in the field of continuing medical education and residency training. The pilot study presented here inquired the application of VPs in the framework of a pediatric residency revision course. METHODS Around 200 participants of a pediatric nephology lecture ('nephrotic and nephritic syndrome in children') were offered two VPs as a wrap-up session at the revision course of the German Society for Pediatrics and Adolescent Medicine (DGKJ) 2009 in Heidelberg, Germany. Using a web-based survey form, different aspects were evaluated concerning the learning experiences with VPs, the combination with the lecture, and the use of VPs for residency training in general. RESULTS N=40 evaluable survey forms were returned (approximately 21%). The return rate was impaired by a technical problem with the local Wi-Fi firewall. The participants perceived the work-up of the VPs as a worthwhile learning experience, with proper preparation for diagnosing and treating real patients with similar complaints. Case presentations, interactivity, and locally and timely independent repetitive practices were, in particular, pointed out. On being asked about the use of VPs in general for residency training, there was a distinct demand for more such offers. CONCLUSION VPs may reasonably complement existing learning activities in residency training.

Development and voluntarism in football clubs

Volunteers are still the most important resource for amateur football clubs. However, stable voluntary engagement can no longer be granted. This difficulty is confirmed by existing research across various European countries. From a club management point of view, a detailed understanding of how to attract volunteers and retain them is becoming a high priority. The purpose of this study is (1) to analyse the influence of individual characteristics and corresponding organisational conditions on volunteering and (2) to examine the decision-making processes in relation to implement effective strategies for recruiting volunteers. To answer these questions, the current state of research is summarised and then a multi-level-framework is developed which is based on the structural-individualistic social theory. The individual and context factors for volunteering are estimated in different multi-level models based on a sample of n=1,434 sport club members from 36 sport clubs in Switzerland. Results indicate that volunteering is not just an outcome of individual characteristics such as lower workloads, higher income, children belonging to the sport club, longer club membership, or a strong commitment to the club. It is also influenced by club-specific structural conditions. Concerning decision-making processes an in-depth analysis of recruitment practices for volunteers was conducted in selected clubs (case study design). based on the garbage can model. The results show that systematically designed decision-making processes with a clear regulation of responsibilities seem to solve personnel problems more purposefully and more quickly. Based on the findings some recommendations for volunteer management in football clubs are worked out.

The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.

Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples

I introduce the new mgof command to compute distributional tests for discrete (categorical, multinomial) variables. The command supports largesample tests for complex survey designs and exact tests for small samples as well as classic large-sample x2-approximation tests based on Pearson’s X2, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read, 1984, Journal of the Royal Statistical Society, Series B (Methodological) 46: 440–464). The complex survey correction is based on the approach by Rao and Scott (1981, Journal of the American Statistical Association 76: 221–230) and parallels the survey design correction used for independence tests in svy: tabulate. mgof computes the exact tests by using Monte Carlo methods or exhaustive enumeration. mgof also provides an exact one-sample Kolmogorov–Smirnov test for discrete data.

Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples

A new Stata command called -mgof- is introduced. The command is used to compute distributional tests for discrete (categorical, multinomial) variables. Apart from classic large sample $\chi^2$-approximation tests based on Pearson's $X^2$, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read 1984), large sample tests for complex survey designs and exact tests for small samples are supported. The complex survey correction is based on the approach by Rao and Scott (1981) and parallels the survey design correction used for independence tests in -svy:tabulate-. The exact tests are computed using Monte Carlo methods or exhaustive enumeration. An exact Kolmogorov-Smirnov test for discrete data is also provided.