Reproducibility of prediction models in health services research

The field of health services research studies the health care system by examining outcomes relevant to patients and clinicians but also health economists and policy makers. Such outcomes often include health care spending, and utilization of care services. Building accurate prediction models using reproducible research practices for health services research is important for evidence-based decision making. Several systematic reviews have summarized prediction models for outcomes relevant to health services research, but these systematic reviews do not present a thorough assessment of reproducibility and research quality of the prediction modelling studies. In the present commentary, we discuss how recent advances in prediction modelling in other medical fields can be applied to health services research. We also describe the current status of prediction modelling in health services research, and we summarize available methodological guidance for the development, update, external validation and systematic appraisal of prediction models

Fifty-Year Fate and Impact of General Medical Journals

Background: Influential medical journals shape medical science and practice and their prestige is usually appraised by citation impact metrics, such as the journal impact factor. However, how permanent are medical journals and how stable is their impact over time? Methods and Results: We evaluated what happened to general medical journals that were publishing papers half a century ago, in 1959. Data were retrieved from ISI Web of Science for citations and PubMed (Journals function) for journal history. Of 27 eligible journals publishing in 1959, 4 have stopped circulation (including two of the most prestigious journals in 1959) and another 7 changed name between 1959 and 2009. Only 6 of these 27 journals have been published continuously with their initial name since they started circulation. The citation impact of papers published in 1959 gives a very different picture from the current journal impact factor; the correlation between the two is non-significant and very close to zero. Only 13 of the 5,223 papers published in 1959 received at least 5 citations in 2009. Conclusions: Journals are more permanent entities than single papers, but they are also subject to major change and their relative prominence can change markedly over time

Pediatric multiple sclerosis: update on diagnostic criteria, imaging, histopathology and treatment choices

Pediatric multiple sclerosis (MS) represents less than 5% of the MS population, but patients with pediatric-onset disease reach permanent disability at a younger age than adult onset patients. Accurate diagnosis at presentation and optimal long-term treatment is vital to mitigate ongoing neuroinflammation and irreversible neurodegeneration. However, it may be difficult to early differentiate pediatric MS from acute disseminated encephalomyelitis (ADEM) and neuromyelitis optica spectrum disorders (NMOSD) as they often have atypical presentation that differs from that of adult-onset MS. The purpose of this review is to summarize the updated views on diagnostic criteria, imaging, histopathology and treatment choices

The association of depression and all-cause and cause-specific mortality: an umbrella review of systematic reviews and meta-analyses

Background: Depression is a prevalent and disabling mental disorder that frequently co-occurs with a wide range of chronic conditions. Evidence has suggested that depression could be associated with excess all-cause mortality across different settings and populations, although the causality of these associations remains unclear. Methods: We conducted an umbrella review of systematic reviews and meta-analyses of observational studies. PubMed, PsycINFO, and Embase electronic databases were searched through January 20, 2018. Systematic reviews and meta-analyses that investigated associations of depression and all-cause and cause-specific mortality were selected for the review. The evidence was graded as convincing, highly suggestive, suggestive, or weak based on quantitative criteria that included an assessment of heterogeneity, 95% prediction intervals, small-study effects, and excess significance bias. Results: A total of 26 references providing 2 systematic reviews and data for 17 meta-analytic estimates met inclusion criteria (19 of them on all-cause mortality); data from 246 unique studies (N = 3,825,380) were synthesized. All 17 associations had P < 0.05 per random effects summary effects, but none of them met criteria for convincing evidence. Associations of depression and all-cause mortality in patients after acute myocardial infarction, in individuals with heart failure, in cancer patients as well as in samples from mixed settings met criteria for highly suggestive evidence. However, none of the associations remained supported by highly suggestive evidence in sensitivity analyses that considered studies employing structured diagnostic interviews. In addition, associations of depression and all-cause mortality in cancer and post-acute myocardial infarction samples were supported only by suggestive evidence when studies that tried to adjust for potential confounders were considered. Conclusions: Even though associations between depression and mortality have nominally significant results in all assessed settings and populations, the evidence becomes weaker when focusing on studies that used structured interviews and those that tried to adjust for potential confounders. A causal effect of depression on all-cause and cause-specific mortality remains unproven, and thus interventions targeting depression are not expected to result in lower mortality rates at least based on current evidence from observational studies

Muscle performance investigated with a novel smart compression garment based on pressure sensor force myography and its validation against EMG

Muscle activity and fatigue performance parameters were obtained and compared between both a smart compression garment and the gold-standard, a surface electromyography (EMG) system during high-speed cycling in seven participants. The smart compression garment, based on force myography (FMG), comprised of integrated pressure sensors that were sandwiched between skin and garment, located on five thigh muscles. The muscle activity was assessed by means of crank cycle diagrams (polar plots) that displayed the muscle activity relative to the crank cycle. The fatigue was assessed by means of the median frequency of the power spectrum of the EMG signal; the fractal dimension (FD) of the EMG signal; and the FD of the pressure signal. The smart compression garment returned performance parameters (muscle activity and fatigue) comparable to the surface EMG. The major differences were that the EMG measured the electrical activity, whereas the pressure sensor measured the mechanical activity. As such, there was a phase shift between electrical and mechanical signals, with the electrical signals preceding the mechanical counterparts in most cases. This is specifically pronounced in high-speed cycling. The fatigue trend over the duration of the cycling exercise was clearly reflected in the fatigue parameters (FDs and median frequency) obtained from pressure and EMG signals. The fatigue parameter of the pressure signal (FD) showed a higher time dependency (R2 = 0.84) compared to the EMG signal. This reflects that the pressure signal puts more emphasis on the fatigue as a function of time rather than on the origin of fatigue (e.g., peripheral or central fatigue). In light of the high-speed activity results, caution should be exerted when using data obtained from EMG for biomechanical models. In contrast to EMG data, activity data obtained from FMG are considered more appropriate and accurate as an input for biomechanical modeling as they truly reflect the mechanical muscle activit

Design and evaluation of smart wearable undergarment for monitoring physiological extremes in firefighting

For workers in extreme environments, such as firefighters, thermal protective clothing is essential to protect them from exposures to high heat and life threatening risks. This study will investigate the design of a new smart protective clothing system, which incorporates sensors in the undergarment to measure physiological data, such as skin temperature, heat flux and heat rate to assess the thermal status of the worker. The aim of this paper is to outline the design of the smart wearable undergarment and the evaluation process for testing the smart undergarment in a controlled environment

The impact of general and internal medicine journals publishing in 1959.

<p>*Thomson ISI Journal Impact Factor, as derived from the 2008 Journal Citation Reports edition. It is calculated by dividing the total number of citations received in 2008 by items published in 2006 or 2007 by the number of original articles and reviews published in 2006 and 2007. Note that the nominator includes citations to all items published by a journal regardless of whether this is an original article, review or other type of item (e.g. editorial, essay, etc), while the denominator includes only original articles (articles and proceedings papers, a category that did not exist in 1959) and reviews. Moreover, the journal impact factor considers papers published during two years and the citations that they received in a single year (one or two years after their publication year, respectively). Therefore, the definition is slightly different from the 2-year citation impact metric that we used for papers published in 1959. The last column that shows the 2-year citation impact per paper for papers published in 2007 (citations to papers or reviews published in 2007 during 2008 and 2009 divided by the number of papers or reviews published in 2007) is conceptually identical to the respective metric for papers published in 1959. The Thomson ISI Journal Impact Factor was almost perfectly correlated with the 2-year impact of papers published in 2007 (r = 0.993, p<0.001) therefore correlations with the 1959-impact metrics were unaltered, when the 2-year impact of papers published in 2007 was used in the correlation analyses instead of the Thomson ISI Journal Impact Factor.</p><p>JIF: journal impact factor; NP: not publishing currently; NI: not indexed in ISI Web of Science currently.</p