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Institution

VU University Medical Center

HealthcareAmsterdam, Noord-Holland, Netherlands
About: VU University Medical Center is a healthcare organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 10882 authors who have published 22907 publications receiving 1156378 citations. The organization is also known as: VUmc.


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Journal ArticleDOI
TL;DR: The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available.
Abstract: The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of revising the 1984 criteria for Alzheimer's disease (AD) dementia. The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. We present criteria for all-cause dementia and for AD dementia. We retained the general framework of probable AD dementia from the 1984 criteria. On the basis of the past 27 years of experience, we made several changes in the clinical criteria for the diagnosis. We also retained the term possible AD dementia, but redefined it in a manner more focused than before. Biomarker evidence was also integrated into the diagnostic formulations for probable and possible AD dementia for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis of AD dementia. Much work lies ahead for validating the biomarker diagnosis of AD dementia.

13,710 citations

Journal ArticleDOI
TL;DR: A systematic review and meta-analysis of placebo-controlled studies examined the efficacy and tolerability of different types of antidepressants, the combination of an antidepressant and an antipsychotic, antipsychotics alone, or natural products in adults with somatoform disorders in adults to improve optimal treatment decisions.
Abstract: BACKGROUND: Somatoform disorders are characterised by chronic, medically unexplained physical symptoms (MUPS). Although different medications are part of treatment routines for people with somatoform disorders in clinics and private practices, there exists no systematic review or meta-analysis on the efficacy and tolerability of these medications. We aimed to synthesise to improve optimal treatment decisions.OBJECTIVES: To assess the effects of pharmacological interventions for somatoform disorders (specifically somatisation disorder, undifferentiated somatoform disorder, somatoform autonomic dysfunction, and pain disorder) in adults.SEARCH METHODS: We searched the Cochrane Depression, Anxiety and Neurosis Review Group's Specialised Register (CCDANCTR) (to 17 January 2014). This register includes relevant randomised controlled trials (RCTs) from The Cochrane Library (all years), MEDLINE (1950 to date), EMBASE (1974 to date), and PsycINFO (1967 to date). To identify ongoing trials, we searched ClinicalTrials.gov, Current Controlled Trials metaRegister, the World Health Organization International Clinical Trials Registry Platform, and the Chinese Clinical Trials Registry. For grey literature, we searched ProQuest Dissertation {\&} Theses Database, OpenGrey, and BIOSIS Previews. We handsearched conference proceedings and reference lists of potentially relevant papers and systematic reviews and contacted experts in the field.SELECTION CRITERIA: We selected RCTs or cluster RCTs of pharmacological interventions versus placebo, treatment as usual, another medication, or a combination of different medications for somatoform disorders in adults. We included people fulfilling standardised diagnostic criteria for somatisation disorder, undifferentiated somatoform disorder, somatoform autonomic dysfunction, or somatoform pain disorder.DATA COLLECTION AND ANALYSIS: One review author and one research assistant independently extracted data and assessed risk of bias. Primary outcomes included the severity of MUPS on a continuous measure, and acceptability of treatment.MAIN RESULTS: We included 26 RCTs (33 reports), with 2159 participants, in the review. They examined the efficacy of different types of antidepressants, the combination of an antidepressant and an antipsychotic, antipsychotics alone, or natural products (NPs). The duration of the studies ranged between two and 12 weeks.One meta-analysis of placebo-controlled studies showed no clear evidence of a significant difference between tricyclic antidepressants (TCAs) and placebo for the outcome severity of MUPS (SMD -0.13; 95{\%} CI -0.39 to 0.13; 2 studies, 239 participants; I(2) = 2{\%}; low-quality evidence). For new-generation antidepressants (NGAs), there was very low-quality evidence showing they were effective in reducing the severity of MUPS (SMD -0.91; 95{\%} CI -1.36 to -0.46; 3 studies, 243 participants; I(2) = 63{\%}). For NPs there was low-quality evidence that they were effective in reducing the severity of MUPS (SMD -0.74; 95{\%} CI -0.97 to -0.51; 2 studies, 322 participants; I(2) = 0{\%}).One meta-analysis showed no clear evidence of a difference between TCAs and NGAs for severity of MUPS (SMD -0.16; 95{\%} CI -0.55 to 0.23; 3 studies, 177 participants; I(2) = 42{\%}; low-quality evidence). There was also no difference between NGAs and other NGAs for severity of MUPS (SMD -0.16; 95{\%} CI -0.45 to 0.14; 4 studies, 182 participants; I(2) = 0{\%}).Finally, one meta-analysis comparing selective serotonin reuptake inhibitors (SSRIs) with a combination of SSRIs and antipsychotics showed low-quality evidence in favour of combined treatment for severity of MUPS (SMD 0.77; 95{\%} CI 0.32 to 1.22; 2 studies, 107 participants; I(2) = 23{\%}).Differences regarding the acceptability of the treatment (rate of all-cause drop-outs) were neither found between NGAs and placebo (RR 1.01, 95{\%} CI 0.64 to 1.61; 2 studies, 163 participants; I(2) = 0{\%}; low-quality evidence) or NPs and placebo (RR 0.85, 95{\%} CI 0.40 to 1.78; 3 studies, 506 participants; I(2) = 0{\%}; low-quality evidence); nor between TCAs and other medication (RR 1.48, 95{\%} CI 0.59 to 3.72; 8 studies, 556 participants; I(2) =14{\%}; low-quality evidence); nor between antidepressants and the combination of an antidepressant and an antipsychotic (RR 0.80, 95{\%} CI 0.25 to 2.52; 2 studies, 118 participants; I(2) = 0{\%}; low-quality evidence). Percental attrition rates due to adverse effects were high in all antidepressant treatments (0{\%} to 32{\%}), but low for NPs (0{\%} to 1.7{\%}).The risk of bias was high in many domains across studies. Seventeen trials (65.4{\%}) gave no information about random sequence generation and only two (7.7{\%}) provided information about allocation concealment. Eighteen studies (69.2{\%}) revealed a high or unclear risk in blinding participants and study personnel; 23 studies had high risk of bias relating to blinding assessors. For the comparison NGA versus placebo, there was relatively high imprecision and heterogeneity due to one outlier study. Although we identified 26 studies, each comparison only contained a few studies and small numbers of participants so the results were imprecise.AUTHORS' CONCLUSIONS: The current review found very low-quality evidence for NGAs and low-quality evidence for NPs being effective in treating somatoform symptoms in adults when compared with placebo. There was some evidence that different classes of antidepressants did not differ in efficacy; however, this was limited and of low to very low quality. These results had serious shortcomings such as the high risk of bias, strong heterogeneity in the data, and small sample sizes. Furthermore, the significant effects of antidepressant treatment have to be balanced against the relatively high rates of adverse effects. Adverse effects produced by medication can have amplifying effects on symptom perceptions, particularly in people focusing on somatic symptoms without medical causes. We can only draw conclusions about short-term efficacy of the pharmacological interventions because no trial included follow-up assessments. For each of the comparisons where there were available data on acceptability rates (NGAs versus placebo, NPs versus placebo, TCAs versus other medication, and antidepressants versus a combination of an antidepressant and an antipsychotic), no clear differences between the intervention and comparator were found.Future high-quality research should be carried out to determine the effectiveness of medications other than antidepressants, to compare antidepressants more thoroughly, and to follow-up participants over longer periods (the longest follow up was just 12 weeks). Another idea for future research would be to include other outcomes such as functional impairment or dysfunctional behaviours and cognitions as well as the classical outcomes such as symptom severity, depression, or anxiety.

11,458 citations

Journal ArticleDOI
TL;DR: The criteria can be used in systematic reviews of health status questionnaires, to detect shortcomings and gaps in knowledge of measurement properties, and to design validation studies.

7,439 citations

Journal ArticleDOI
TL;DR: Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories, and a new framework aimed at overcoming their limitations is developed.
Abstract: Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations. A systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity. Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a 'behaviour system' involving three essential conditions: capability, opportunity, and motivation (what we term the 'COM-B system'). This forms the hub of a 'behaviour change wheel' (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health's 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence's guidance on reducing obesity. Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions.

6,692 citations

Journal ArticleDOI
TL;DR: This research framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms and envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD.
Abstract: In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a "research framework" because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

5,126 citations


Authors

Showing all 10902 results

NameH-indexPapersCitations
John Q. Trojanowski2261467213948
Dorret I. Boomsma1761507136353
Brenda W.J.H. Penninx1701139119082
Michael John Owen1601110135795
Lex M. Bouter158767103034
Frederik Barkhof1541449104982
Ichiro Kawachi149121690282
Walter Paulus14980986252
Philip Scheltens1401175107312
Herbert Y. Meltzer137114881371
Pim Cuijpers13698269370
Jeffrey S. Flier13131478430
Peter Tugwell129948125480
Gonneke Willemsen12957576976
Chris J.L.M. Meijer12873378705
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20237
202239
2021472
2020585
2019978
20181,950