Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review.

BACKGROUND: A medication-related Clinical Decision Support System (CDSS) is an application that analyzes patient data to provide assistance in medication-related care processes. Despite its potential to improve the clinical decision-making process, evidence shows that clinicians do not always use CDSSs in such a way that their potential can be fully realized. This systematic literature review provides an overview of frequently-reported barriers and facilitators for acceptance of medication-related CDSS. MATERIALS AND METHODS: Search terms and MeSH headings were developed in collaboration with a librarian, and database searches were conducted in Medline, Scopus, Embase and Web of Science Conference Proceedings. After screening 5404 records and 140 full papers, 63 articles were included in this review. Quality assessment was performed for all 63 included articles. The identified barriers and facilitators are categorized within the Human, Organization, Technology fit (HOT-fit) model. RESULTS: A total of 327 barriers and 291 facilitators were identified. Results show that factors most often reported were related to (a lack of) usefulness and relevance of information, and ease of use and efficiency of the system. DISCUSSION: This review provides a valuable insight into a broad range of barriers and facilitators for using a medication-related CDSS as perceived by clinicians. The results can be used as a stepping stone in future studies developing medication-related CDSSs.

Fall-Risk-Increasing Drugs: A Systematic Review and Meta-analysis: III. Others.

BACKGROUND AND OBJECTIVE: The use of psychotropic medication and cardiovascular medication has been associated with an increased risk of falling. However, other frequently prescribed medication classes are still under debate as potential risk factors for falls in the older population. The aim of this systematic review and meta-analysis is to evaluate the associations between fall risk and nonpsychotropic and noncardiovascular medications. METHODS AND DESIGN: A systematic review and meta-analysis. A search was conducted in Medline, PsycINFO, and Embase. Key search concepts were "falls," "aged," "medication," and "causality." Studies were included that investigated nonpsychotropic and noncardiovascular medications as risk factors for falls in participants ≥60 years or participants with a mean age ≥70 years. A meta-analysis was performed using the generic inverse variance method, pooling unadjusted and adjusted odds ratio (OR) estimates separately. RESULTS: In a qualitative synthesis, 281 studies were included. The results of meta-analysis using adjusted data were as follows (a pooled OR [95% confidence interval]): analgesics, 1.42 (0.91-2.23); nonsteroidal anti-inflammatory drugs (NSAIDs), 1.09 (0.96-1.23); opioids, 1.60 (1.35-1.91); anti-Parkinson drugs, 1.54 (0.99-2.39); antiepileptics, 1.55 (1.25-1.92); and polypharmacy, 1.75 (1.27-2.41). Most of the meta-analyses resulted in substantial heterogeneity that did not disappear after stratification for population and setting in most cases. In a descriptive synthesis, consistent associations with falls were observed for long-term proton pump inhibitor use and opioid initiation. Laxatives showed inconsistent associations with falls (7/20 studies showing a positive association). CONCLUSION: Opioid and antiepileptic use and polypharmacy were significantly associated with increased risk of falling in the meta-analyses. Long-term use of proton pump inhibitors and opioid initiation might increase the fall risk. Future research is necessary because the causal role of some medication classes as fall-risk-increasing drugs remains unclear, and the existing literature contains significant limitations.

Fall-Risk-Increasing Drugs: A Systematic Review and Meta-Analysis: II. Psychotropics.

BACKGROUND AND OBJECTIVE: Falls are a major public health problem in older adults. Earlier studies showed that psychotropic medication use increases the risk of falls. The aim of this study is to update the current knowledge by providing a comprehensive systematic review and meta-analysis on psychotropic medication use and falls in older adults. METHODS AND DESIGN: This study is a systematic review and meta-analysis. A search was conducted in Medline, PsycINFO, and Embase. Key search concepts were "falls," "aged," "medication," and "causality." Studies were included that investigated psychotropics (antipsychotics, antidepressants, anxiolytics, sedatives, and hypnotics) as risk factors for falls in participants ≥60 years of age or participants with a mean age of ≥70 years. Meta-analyses were performed using generic inverse variance method pooling unadjusted and adjusted odds ratio (OR) estimates separately. RESULTS: In total, 248 studies met the inclusion criteria for qualitative synthesis. Meta-analyses using adjusted data showed the following pooled ORs: antipsychotics 1.54 [95% confidence interval (CI) 1.28-1.85], antidepressants 1.57 (95% Cl 1.43-1.74), tricyclic antidepressants 1.41 (95% CI 1.07-1.86), selective serotonin reuptake inhibitors 2.02 (95% CI 1.85-2.20), benzodiazepines 1.42 (95%, CI 1.22-1.65), long-acting benzodiazepines 1.81 (95%, CI 1.05-3.16), and short-acting benzodiazepines 1.27 (95%, CI 1.04-1.56) Most of the meta-analyses resulted in substantial heterogeneity that did not disappear after stratification for population and healthcare setting. CONCLUSIONS: Antipsychotics, antidepressants, and benzodiazepines are consistently associated with a higher risk of falls. It is unclear whether specific subgroups such as short-acting benzodiazepines and selective serotonin reuptake inhibitors are safer in terms of fall risk. Prescription bias could not be accounted for. Future studies need to address pharmacologic subgroups as fall risk may differ depending on specific medication properties. Precise and uniform classification of target medication (Anatomical Therapeutic Chemical Classification) is essential for valid comparisons between studies.

CD133+ and Nestin+ Glioma Stem-Like Cells Reside Around CD31+ Arterioles in Niches that Express SDF-1α, CXCR4, Osteopontin and Cathepsin K.

Poor survival of high-grade glioma is at least partly caused by glioma stem-like cells (GSLCs) that are resistant to therapy. GSLCs reside in niches in close vicinity of endothelium. The aim of the present study was to characterize proteins that may be functional in the GSLC niche by performing immunohistochemistry on serial cryostat sections of human high-grade glioma samples. We have found nine niches in five out of five high-grade glioma samples that were all surrounding arterioles with CD31+ endothelial cells and containing cellular structures that were CD133+ and nestin+. All nine niches expressed stromal-derived factor-1α (SDF-1α), its receptor C-X-C chemokine receptor type 4 (CXCR4), osteopontin and cathepsin K. SDF-1α plays a role in homing of CXCR4+ stem cells and leukocytes, whereas osteopontin and cathepsin K promote migration of cancer cells and leukocytes. Leukocyte-related markers, such as CD68, macrophage matrix metalloprotease-9, CD177 and neutrophil elastase were often but not always detected in the niches. We suggest that SDF-1α is involved in homing of CXCR4+ GSLCs and leukocytes and that cathepsin K and osteopontin are involved in the migration of GSLCs out of the niches.