Publication trends of shared decision making in 15 high impact medical journals: a full-text review with bibliometric analysis.

BACKGROUND: Shared Decision Making (SDM) is increasingly advocated as a model for medical decision making. However, there is still low use of SDM in clinical practice. High impact factor journals might represent an efficient way for its dissemination. We aimed to identify and characterize publication trends of SDM in 15 high impact medical journals. METHODS: We selected the 15 general and internal medicine journals with the highest impact factor publishing original articles, letters and editorials. We retrieved publications from 1996 to 2011 through the full-text search function on each journal website and abstracted bibliometric data. We included publications of any type containing the phrase "shared decision making" or five other variants in their abstract or full text. These were referred to as SDM publications. A polynomial Poisson regression model with logarithmic link function was used to assess the evolution across the period of the number of SDM publications according to publication characteristics. RESULTS: We identified 1285 SDM publications out of 229,179 publications in 15 journals from 1996 to 2011. The absolute number of SDM publications by journal ranged from 2 to 273 over 16 years. SDM publications increased both in absolute and relative numbers per year, from 46 (0.32% relative to all publications from the 15 journals) in 1996 to 165 (1.17%) in 2011. This growth was exponential (P < 0.01). We found fewer research publications (465, 36.2% of all SDM publications) than non-research publications, which included non-systematic reviews, letters, and editorials. The increase of research publications across time was linear. Full-text search retrieved ten times more SDM publications than a similar PubMed search (1285 vs. 119 respectively). CONCLUSION: This review in full-text showed that SDM publications increased exponentially in major medical journals from 1996 to 2011. This growth might reflect an increased dissemination of the SDM concept to the medical community.

Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging.

Methods are presented to map complex fiber architectures in tissues by imaging the 3D spectra of tissue water diffusion with MR. First, theoretical considerations show why and under what conditions diffusion contrast is positive. Using this result, spin displacement spectra that are conventionally phase-encoded can be accurately reconstructed by a Fourier transform of the measured signal's modulus. Second, studies of in vitro and in vivo samples demonstrate correspondence between the orientational maxima of the diffusion spectrum and those of the fiber orientation density at each location. In specimens with complex muscular tissue, such as the tongue, diffusion spectrum images show characteristic local heterogeneities of fiber architectures, including angular dispersion and intersection. Cerebral diffusion spectra acquired in normal human subjects resolve known white matter tracts and tract intersections. Finally, the relation between the presented model-free imaging technique and other available diffusion MRI schemes is discussed.

A clinical prognostic model for the identification of low-risk patients with acute symptomatic pulmonary embolism and active cancer.

BACKGROUND: Physicians need a specific risk-stratification tool to facilitate safe and cost-effective approaches to the management of patients with cancer and acute pulmonary embolism (PE). The objective of this study was to develop a simple risk score for predicting 30-day mortality in patients with PE and cancer by using measures readily obtained at the time of PE diagnosis. METHODS: Investigators randomly allocated 1,556 consecutive patients with cancer and acute PE from the international multicenter Registro Informatizado de la Enfermedad TromboEmbólica to derivation (67%) and internal validation (33%) samples. The external validation cohort for this study consisted of 261 patients with cancer and acute PE. Investigators compared 30-day all-cause mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. RESULTS: In the derivation sample, multivariable analyses produced the risk score, which contained six variables: age > 80 years, heart rate ≥ 110/min, systolic BP < 100 mm Hg, body weight < 60 kg, recent immobility, and presence of metastases. In the internal validation cohort (n = 508), the 22.2% of patients (113 of 508) classified as low risk by the prognostic model had a 30-day mortality of 4.4% (95% CI, 0.6%-8.2%) compared with 29.9% (95% CI, 25.4%-34.4%) in the high-risk group. In the external validation cohort, the 18% of patients (47 of 261) classified as low risk by the prognostic model had a 30-day mortality of 0%, compared with 19.6% (95% CI, 14.3%-25.0%) in the high-risk group. CONCLUSIONS: The developed clinical prediction rule accurately identifies low-risk patients with cancer and acute PE.

The impact of information on decision-making in palliative care

Résumé Ce travail vise à clarifier les résultats contradictoires de la littérature concernant les besoins des patients d'être informés et de participer à la prise de décision. La littérature insiste sur le contenu de l'information comme base de la prise de décision, bien qu'il existe des preuves que d'autres contenus sont importants pour les patients. La thèse essaie en outre d'identifier des possibilités de mieux répondre aux préférences d'information et de participation des patients. Les travaux ont porté en particulier sur les soins palliatifs. Une analyse de la littérature donne un aperçu sur les soins palliatifs, sur l'information des patients et sur leur participation à la prise de décisions thérapeutiques. Cette analyse résume les résultats d'études précédentes et propose un: modèle théorique d'information, de prise de décision et de relation entre ces deux domaines. Dans le cadre de ce travail, deux études empiriques ont utilisé des questionnaires écrits adressés à des personnes privées et à des professionnels de la santé, couvrant la Suisse et le Royaume Uni, pour identifier d'éventuelles différences entre ces deux pays. Les enquêtes ont été focalisées sur des patients souffrant de cancer du poumon. Les instruments utilisés pour ces études proviennent de la littérature afin de les rendre comparables. Le taux de réponse aux questionnaires était de 30-40%. La majorité des participants aux enquêtes estime que les patients devraient: - collaborer à la prise de décision quant à leur traitement - recevoir autant d'information que possible, positive aussi bien que négative - recevoir toutes les informations mentionnées dans le questionnaire (concernant la maladie, le diagnostic et les traitements), tenant compte de la diversité des priorités des patients - être soutenus par des professionnels de la santé, leur famille, leurs amis et/ou les personnes souffrant de la même maladie En plus, les participants aux enquêtes ont identifié divers contenus de l'information aux patients souffrant d'une maladie grave. Ces contenus comprennent entre autres: - L'aide à la prise de décision concernant le traitement - la possibilité de maintenir le contrôle de la situation - la construction d'une relation entre le patient et le soignant - l'encouragement à faire des projets d'avenir - l'influence de l'état émotionnel - l'aide à la compréhension de la maladie et de son impact - les sources potentielles d'états confusionnels et d'états anxieux La plupart des contenus proposés sont positifs. Les résultats suggèrent la coexistence possible de différents contenus à un moment donné ainsi que leur changement au cours du temps. Un modèle est ensuite développé et commenté pour présenter le diagnostic d'une maladie grave. Ce modèle est basé sur la littérature et intègre les résultats des études empiriques réalisées dans le cadre de ce travail. Ce travail analyse également les sources préférées d'information et de soutien, facteurs qui peuvent influencer ou faire obstacle aux préférences d'information et de participation. Les deux groupes de participants considèrent les médecins spécialistes comme la meilleure source d'information. En ce qui concerne le soutien, les points de vue divergent entre les personnes privées et les professionnels de la santé: généralement, les rôles de soutien semblent peu définis parmi les professionnels. Les barrières à l'information adéquate du patient apparaissent fréquemment liées aux caractéristiques des professionnels et aux problèmes d'organisation. Des progrès dans ce domaine contribueraient à améliorer les soins fournis aux patients. Finalement, les limites des études empiriques sont discutées. Celles-ci comprennent, entre autres, la représentativité restreinte des participants et les objections de certains groupes de participants à quelques détails des questionnaires. Summary The present thesis follows a call from the current body of literature to better understand patient needs for information and for participation in decision-making, as previous research findings had been contradictory. Information so far seems to have been considered essentially as a means to making treatment decisions, despite certain evidence that it may have a number of other values to patients. Furthermore, the thesis aims to identify ways to optimise meeting patient preferences for information and participation in treatment decisions. The current field of interest is palliative care. An extensive literature review depicts the background of current concepts of palliative care, patient information and patient involvement into treatment decisions. It also draws together results from previous studies and develops a theoretical model of information, decision-making, and the relationship between them. This is followed by two empirical studies collecting data from members of the general public and health care professionals by means of postal questionnaires. The professional study covers both Switzerland and the United Kingdom in order to identify possible differences between countries. Both studies focus on newly diagnosed lung cancer patients. The instruments used were taken from the literature to make them comparable. The response rate in both surveys was 30-40%, as expected -sufficient to allow stastical tests to be performed. A third study, addressed to lung cancer patients themselves, turned out to require too much time within the frame available. A majority of both study populations thought that patients should: - have a collaborative role in treatment-related decision-making -receive as much information as possible, good or bad - receive all types of information mentioned in the questionnaire (about illness, tests, and treatment), although priorities varied across the study populations - be supported by health professionals, family members, friends and/or others with the same illness Furthermore they identified various 'meanings' information may have to patients with a serious illness. These included: - being an aid in treatment-related decision-making - allowing control to be maintained over the situation - helping the patient-professional relationship to be constructed - allowing plans to be made - being positive for the patient's emotional state - helping the illness and its impact to be understood - being a source of anxiety - being a potential source of confusion to the patient Meanings were mostly positive. It was suggested that different meanings could co-exist at a given time and that they might change over time. A model of coping with the disclosure of a serious diagnosis is then developped. This model is based on existing models of coping with threatening events, as takeñ from the literature [ref. 77, 78], and integrates findings from the empirical studies. The thesis then analyses the remaining aspects apparent from the two surveys. These range from the identification of preferred information and support providers to factors influencing or impeding information and participation preferences. Specialist doctors were identified by both study populations as the best information providers whilst with regard to support provision views differed between the general public and health professionals. A need for better definition of supportive roles among health care workers seemed apparent. Barriers to information provision often seem related to health professional characteristics or organisational difficulties, and improvements in the latter field could well help optimising patient care. Finally, limitations of the studies are discussed, including questions of representativness of certain results and difficulties with or objections against questionnaire details by some groups of respondents.

Viral-mediated overexpression of mutant huntingtin to model HD in various species.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by an expansion of CAG repeats in the huntingtin (Htt) gene. Despite intensive efforts devoted to investigating the mechanisms of its pathogenesis, effective treatments for this devastating disease remain unavailable. The lack of suitable models recapitulating the entire spectrum of the degenerative process has severely hindered the identification and validation of therapeutic strategies. The discovery that the degeneration in HD is caused by a mutation in a single gene has offered new opportunities to develop experimental models of HD, ranging from in vitro models to transgenic primates. However, recent advances in viral-vector technology provide promising alternatives based on the direct transfer of genes to selected sub-regions of the brain. Rodent studies have shown that overexpression of mutant human Htt in the striatum using adeno-associated virus or lentivirus vectors induces progressive neurodegeneration, which resembles that seen in HD. This article highlights progress made in modeling HD using viral vector gene transfer. We describe data obtained with of this highly flexible approach for the targeted overexpression of a disease-causing gene. The ability to deliver mutant Htt to specific tissues has opened pathological processes to experimental analysis and allowed targeted therapeutic development in rodent and primate pre-clinical models.

Effective continuing professional development for translating shared decision making in primary care: A study protocol.

Background: Shared decision making (SDM) is a process by which a healthcare choice is made jointly by the healthcare professional and the patient. SDM is the essential element of patient-centered care, a core concept of primary care. However, SDM is seldom translated into primary practice. Continuing professional development (CPD) is the principal means by which healthcare professionals continue to gain, improve, and broaden the knowledge and skills required for patient-centered care. Our international collaboration seeks to improve the knowledge base of CPD that targets translating SDM into the clinical practice of primary care in diverse healthcare systems. Methods: Funded by the Canadian Institutes of Health Research (CIHR), our project is to form an international, interdisciplinary research team composed of health services researchers, physicians, nurses, psychologists, dietitians, CPD decision makers and others who will study how CPD causes SDM to be practiced in primary care. We will perform an environmental scan to create an inventory of CPD programs and related activities for translating SDM into clinical practice. These programs will be critically assessed and compared according to their strengths and limitations. We will use the empirical data that results from the environmental scan and the critical appraisal to identify knowledge gaps and generate a research agenda during a two-day workshop to be held in Quebec City. We will ask CPD stakeholders to validate these knowledge gaps and the research agenda. Discussion: This project will analyse existing CPD programs and related activities for translating SDM into the practice of primary care. Because this international collaboration will develop and identify various factors influencing SDM, the project could shed new light on how SDM is implemented in primary care.

Autistic spectrum disorder: evaluating a possible contributing or causal role of epilepsy.

The onset of epilepsy in brain systems involved in social communication and/or recognition of emotions can occasionally be the cause of autistic symptoms or may aggravate preexisting autistic symptoms. Knowing that cognitive and/or behavioral abnormalities can be the presenting and sometimes the only symptom of an epileptic disorder or can even be caused by paroxysmal EEG abnormalities without recognized seizures, the possibility that this may apply to autism has given rise to much debate. Epilepsy and/or epileptic EEG abnormalities are frequently associated with autistic disorders in children but this does not necessarily imply that they are the cause; great caution needs to be exercised before drawing any such conclusions. So far, there is no evidence that typical autism can be attributed to an epileptic disorder, even in those children with a history of regression after normal early development. Nevertheless, there are several early epilepsies (late infantile spasms, partial complex epilepsies, epilepsies with CSWS, early forms of Landau-Kleffner syndrome) and with different etiologies (tuberous sclerosis is an important model of these situations) in which a direct relationship between epilepsy and some features of autism may be suspected. In young children who primarily have language regression (and who may have autistic features) without evident cause, and in whom paroxysmal focal EEG abnormalities are also found, the possible direct role of epilepsy can only be evaluated in longitudinal studies.

Signalling, mating success and paternal investment in sticklebacks (Gasterosteus aculeatus): A theoretical model

I present an optimisation model that links paternal investment, male display and female choice. Although deviced for sticklebacks, it readily applies to other fish with male guarding behaviour. It relies on a few basic assumptions on the ways hatching success depends on paternal investment and clutch size, and male survival on paternal investment and signaling. Paternal investment is here a state-dependent decision, and signal a condition-dependent handicap by which males inform females of how much they are willing to invest. Series of predictions are derived on female and male breeding strategies, including optimal levels of signaling and paternal investment as functions of clutch size, own condition, and residual reproductive value, as well as alternative strategies such as egg kleptoparasitism. Some predictions already have empirical support, for which the present model provides new interpretations. Other might readily be tested, e.g. by simple clutch-size manipulations.

Development and validation of a clinical decision rule for the diagnosis of influenza.

INTRODUCTION: A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza. METHODS: We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported. RESULTS: The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing. CONCLUSION: A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.

Comparison of the polynomial model against explicit measurements of noise components for different mammography systems.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

Changes in the use of broad-spectrum antibiotics after withdrawal of cefepime from the market: an interrupted time series analysis

Background and objective: Cefepime was one of the most used broad-spectrum antibiotics in Swiss public acute care hospitals. The drug was withdrawn from market in January 2007, and then replaced by a generic since October 2007. The goal of the study was to evaluate changes in the use of broad-spectrum antibiotics after the withdrawal of the cefepime original product. Design: A generalized regression-based interrupted time series model incorporating autocorrelated errors assessed how much the withdrawal changed the monthly use of other broad-spectrum antibiotics (ceftazidime, imipenem/cilastin, meropenem, piperacillin/ tazobactam) in defined daily doses (DDD)/100 bed-days from January 2004 to December 2008 [1, 2]. Setting: 10 Swiss public acute care hospitals (7 with\200 beds, 3 with 200-500 beds). Nine hospitals (group A) had a shortage of cefepime and 1 hospital had no shortage thanks to importation of cefepime from abroad. Main outcome measures: Underlying trend of use before the withdrawal, and changes in the level and in the trend of use after the withdrawal. Results: Before the withdrawal, the average estimated underlying trend (coefficient b1) for cefepime was decreasing by -0.047 (95% CI -0.086, -0.009) DDD/100 bed-days per month and was significant in three hospitals (group A, P\0.01). Cefepime withdrawal was associated with a significant increase in level of use (b2) of piperacillin/tazobactam and imipenem/cilastin in, respectively, one and five hospitals from group A. After the withdrawal, the average estimated trend (b3) was greatest for piperacillin/tazobactam (+0.043 DDD/100 bed-days per month; 95% CI -0.001, 0.089) and was significant in four hospitals from group A (P\0.05). The hospital without drug shortage showed no significant change in the trend and the level of use. The hypothesis of seasonality was rejected in all hospitals. Conclusions: The decreased use of cefepime already observed before its withdrawal from the market could be explained by pre-existing difficulty in drug supply. The withdrawal of cefepime resulted in change in level for piperacillin/tazobactam and imipenem/cilastin. Moreover, an increase in trend was found for piperacillin/tazobactam thereafter. As these changes generally occur at the price of lower bacterial susceptibility, a manufacturers' commitment to avoid shortages in the supply of their products would be important. As perspectives, we will measure the impact of the changes in cost and sensitivity rates of these antibiotics.

Eight years experience from a skeletal dysplasia referral center in a tertiary hospital in Southern India: A model for the diagnosis and treatment of rare diseases in a developing country.

We report on a series of 514 consecutive diagnoses of skeletal dysplasia made over an 8-year period at a tertiary hospital in Kerala, India. The most common diagnostic groups were dysostosis multiplex group (n = 73) followed by FGFR3 (n = 49) and osteogenesis imperfecta and decreased bone density group (n = 41). Molecular confirmation was obtained in 109 cases. Clinical and radiographic evaluation was obtained in close diagnostic collaboration with expert groups abroad through Internet communication for difficult cases. This has allowed for targeted biochemical and molecular studies leading to the correct identification of rare or novel conditions, which has not only helped affected families by allowing for improved genetic counseling and prenatal diagnosis but also resulted in several scientific contributions. We conclude that (1) the spectrum of genetic bone disease in Kerala, India, is similar to that of other parts of the world, but recessive entities may be more frequent because of widespread consanguinity; (2) prenatal detection of skeletal dysplasias remains relatively rare because of limited access to expert prenatal ultrasound facilities; (3) because of the low accessibility to molecular tests, precise clinical-radiographic phenotyping remains the mainstay of diagnosis and counseling and of gatekeeping to efficient laboratory testing; (4) good phenotyping allows, a significant contribution to the recognition and characterization of novel entities. We suggest that the tight collaboration between a local reference center with dedicated personnel and expert diagnostic networks may be a proficient model to bring current diagnostics to developing countries. © 2014 Wiley Periodicals, Inc.

Diffusion Spectrum Imaging after stroke shows structural changes in the contra-lateral motor network correlating with functional recovery

There is growing interest in understanding the role of the non-injured contra-lateral hemisphere in stroke recovery. In the experimental field, histological evidence has been reported that structural changes occur in the contra-lateral connectivity and circuits during stroke recovery. In humans, some recent imaging studies indicated that contra-lateral sub-cortical pathways and functional and structural cortical networks are remodeling, after stroke. Structural changes in the contra-lateral networks, however, have never been correlated to clinical recovery in patients. To determine the importance of the contra-lateral structural changes in post-stroke recovery, we selected a population of patients with motor deficits after stroke affecting the motor cortex and/or sub-cortical motor white matter. We explored i) the presence of Generalized Fractional Anisotropy (GFA) changes indicating structural alterations in the motor network of patientsâeuro? contra-lateral hemisphere as well as their longitudinal evolution ii) the correlation of GFA changes with patientsâeuro? clinical scores, stroke size and demographics data iii) and a predictive model.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Toxic substances in blood: an analysis of current recommendations under a Bayesian (decision) approach

This article extends existing discussion in literature on probabilistic inference and decision making with respect to continuous hypotheses that are prevalent in forensic toxicology. As a main aim, this research investigates the properties of a widely followed approach for quantifying the level of toxic substances in blood samples, and to compare this procedure with a Bayesian probabilistic approach. As an example, attention is confined to the presence of toxic substances, such as THC, in blood from car drivers. In this context, the interpretation of results from laboratory analyses needs to take into account legal requirements for establishing the 'presence' of target substances in blood. In a first part, the performance of the proposed Bayesian model for the estimation of an unknown parameter (here, the amount of a toxic substance) is illustrated and compared with the currently used method. The model is then used in a second part to approach-in a rational way-the decision component of the problem, that is judicial questions of the kind 'Is the quantity of THC measured in the blood over the legal threshold of 1.5 μg/l?'. This is pointed out through a practical example.