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Annals of Internal Medicine Feb 2015Increases in prescriptions of opioid medications for chronic pain have been accompanied by increases in opioid overdoses, abuse, and other harms and uncertainty about... (Review)
Review
BACKGROUND
Increases in prescriptions of opioid medications for chronic pain have been accompanied by increases in opioid overdoses, abuse, and other harms and uncertainty about long-term effectiveness.
PURPOSE
To evaluate evidence on the effectiveness and harms of long-term (>3 months) opioid therapy for chronic pain in adults.
DATA SOURCES
MEDLINE, the Cochrane Central Register of Controlled Trials, the Cochrane Database of Systematic Reviews, PsycINFO, and CINAHL (January 2008 through August 2014); relevant studies from a prior review; reference lists; and ClinicalTrials.gov.
STUDY SELECTION
Randomized trials and observational studies that involved adults with chronic pain who were prescribed long-term opioid therapy and that evaluated opioid therapy versus placebo, no opioid, or nonopioid therapy; different opioid dosing strategies; or risk mitigation strategies.
DATA EXTRACTION
Dual extraction and quality assessment.
DATA SYNTHESIS
No study of opioid therapy versus no opioid therapy evaluated long-term (>1 year) outcomes related to pain, function, quality of life, opioid abuse, or addiction. Good- and fair-quality observational studies suggest that opioid therapy for chronic pain is associated with increased risk for overdose, opioid abuse, fractures, myocardial infarction, and markers of sexual dysfunction, although there are few studies for each of these outcomes; for some harms, higher doses are associated with increased risk. Evidence on the effectiveness and harms of different opioid dosing and risk mitigation strategies is limited.
LIMITATIONS
Non-English-language articles were excluded, meta-analysis could not be done, and publication bias could not be assessed. No placebo-controlled trials met inclusion criteria, evidence was lacking for many comparisons and outcomes, and observational studies were limited in their ability to address potential confounding.
CONCLUSION
Evidence is insufficient to determine the effectiveness of long-term opioid therapy for improving chronic pain and function. Evidence supports a dose-dependent risk for serious harms.
PRIMARY FUNDING SOURCE
Agency for Healthcare Research and Quality.
Topics: Analgesics, Opioid; Chronic Pain; Drug Administration Schedule; Drug Overdose; Fractures, Bone; Humans; Myocardial Infarction; Opioid-Related Disorders; Quality of Life; Risk Assessment; Risk Factors; Sexual Dysfunction, Physiological
PubMed: 25581257
DOI: 10.7326/M14-2559 -
Journal of Biomedical Informatics Nov 2023Adequate methods to promptly translate digital health innovations for improved patient care are essential. Advances in Artificial Intelligence (AI) and Machine Learning... (Review)
Review
INTRODUCTION
Adequate methods to promptly translate digital health innovations for improved patient care are essential. Advances in Artificial Intelligence (AI) and Machine Learning (ML) have been sources of digital innovation and hold the promise to revolutionize the way we treat, manage and diagnose patients. Understanding the benefits but also the potential adverse effects of digital health innovations, particularly when these are made available or applied on healthier segments of the population is essential. One of such adverse effects is overdiagnosis.
OBJECTIVE
to comprehensively analyze quantification strategies and data-driven definitions for overdiagnosis reported in the literature.
METHODS
we conducted a scoping systematic review of manuscripts describing quantitative methods to estimate the proportion of overdiagnosed patients.
RESULTS
we identified 46 studies that met our inclusion criteria. They covered a variety of clinical conditions, primarily breast and prostate cancer. Methods to quantify overdiagnosis included both prospective and retrospective methods including randomized clinical trials, and simulations.
CONCLUSION
a variety of methods to quantify overdiagnosis have been published, producing widely diverging results. A standard method to quantify overdiagnosis is needed to allow its mitigation during the rapidly increasing development of new digital diagnostic tools.
Topics: Male; Humans; Retrospective Studies; Artificial Intelligence; Overdiagnosis; Prospective Studies; Prostatic Neoplasms
PubMed: 37769829
DOI: 10.1016/j.jbi.2023.104506 -
Animals : An Open Access Journal From... Aug 2022Dog ownership and dog walking brings various health benefits for urban dwellers, especially since the COVID-19 pandemic, but trigger a number of controversies. Dog parks... (Review)
Review
Dog ownership and dog walking brings various health benefits for urban dwellers, especially since the COVID-19 pandemic, but trigger a number of controversies. Dog parks have become increasingly significant public resources in the pandemic to support these benefits while facing intense conflicts. To develop effective dog parks in urban settings, growing numbers of scholars have provided insights into the design and management strategies for addressing the benefits and conflicts. The objective of this study is to synthesize and analyze various aspects of dog park design and management and to assess identified strategies for enhancing their benefits while mitigating their drawbacks. Following the PRISMA guidelines, a systematic study was conducted to synthesize the benefits, conflicts, and management strategies of dog parks, supported by Citespace. Benefits and conflicts in dog park design and management have been synthesized and organized according to their frequency of presence and the statistical results. We analyzed and assessed existing design and management strategies. Through this systematic study, we discovered the need obtain o po experimental evidence on effective dog park design and management to enhance their benefits while mitigating their sources of conflict and limitations in the intensity of park visitors' physical activity in off-leash areas. Guidelines for the design and management strategies for effective dog parks were made to enhance their benefits while alleviating conflicts in the future development of sustainable dog parks that promote healthy relationships between canines and residents in urban built environments.
PubMed: 36077971
DOI: 10.3390/ani12172251 -
International Journal of Environmental... Sep 2022The Himalayan region is a fragile high mountain landscape where the population experiences acute vulnerability within a complex coupled human-natural system due to... (Review)
Review
The Himalayan region is a fragile high mountain landscape where the population experiences acute vulnerability within a complex coupled human-natural system due to environmental, social, and economic linkages. The lack of significant regional and spatial knowledge of multi-faceted vulnerabilities hinders any potential recommendations to address these vulnerabilities. We systematically reviewed the literature to recommend mitigation interventions based on the region's socio-economic and ecological vulnerability research to date. We applied the PRISMA (Preferred Reporting of Items for Systematic Review and Meta-Analysis) criteria to search for results from four comprehensive databases. For our assessment, we compiled a final sample ( = 59) of vulnerability research papers to examine the vulnerability types, spatial variation, assessment methodology, and significant drivers of change. Our study represented all Himalayan countries, namely, India, Nepal, Pakistan, China, and Bhutan. More than half of the vulnerability studies were conducted in the central Himalayan region, a quarter in the western Himalayas, and a few in the eastern Himalayas. Our review revealed that the primary drivers of change were climate change, land use/land cover, and glacial lake formation. The vulnerability assessments in the Himalayan region primarily used social science methods as compared to natural science methods. While the vulnerability studies seldom assessed mitigation interventions, our analysis identified fourteen recommendations. The recommended interventions mainly included policy interventions, livelihood improvement, and adaptation measures. This study emphasized that sustainable development requires cross-sectoral interventions to manage existing resources and mitigate the confronting vulnerabilities of the region.
Topics: Acclimatization; Climate Change; Humans; India; Lakes; Nepal
PubMed: 36231508
DOI: 10.3390/ijerph191912177 -
Heliyon Mar 2022The world has faced many disasters in recent years, but flood impacts have gained immense importance and attention due to their adverse effects. More than half of global... (Review)
Review
The world has faced many disasters in recent years, but flood impacts have gained immense importance and attention due to their adverse effects. More than half of global flood destruction and damages occur in the Asia region, which causes losses of life, damage infrastructure, and creates panic conditions among the communities. To provide a better understanding of flood hazard management, flood vulnerability assessment is the primary objective. In this case, vulnerability is the central construct in flood analysis and assessment. Many researchers have defined different approaches and methods to understand vulnerability assessment and how geographic information systems assess the flood vulnerability and their associated risk. Geographic information systems track and predict the disaster trend and mitigate the risk and damages. This study systematically reviews the methodologies used to measure floods and their vulnerabilities by integrating geographic information system. Articles on flood vulnerability from 2010 to 2020 were selected and reviewed. Through the systematic review methodology of five research engines, the researchers discovered a difference in flood vulnerability assessment tools and techniques that can be bridged by integrating high-resolution data with a multidimensional vulnerability methodology. The study reviewed several vulnerability components and directly examined the shortcomings in flood vulnerability approaches at different levels. The research contributed that the indicator-based approach gives a better understanding of vulnerability assessment. The geographic information system provides an effective environment for mapping and precise analysis to mitigate the flood disaster
PubMed: 35284686
DOI: 10.1016/j.heliyon.2022.e09075 -
Journal of Theoretical Biology Jul 2022The many respiratory viruses that cause influenza-like illness (ILI) are reported and tracked as one entity, defined by the CDC as a group of symptoms that include a...
The many respiratory viruses that cause influenza-like illness (ILI) are reported and tracked as one entity, defined by the CDC as a group of symptoms that include a fever of 100 degrees Fahrenheit, a cough, and/or a sore throat. In the United States alone, ILI impacts 9-49 million people every year. While tracking ILI as a single clinical syndrome is informative in many respects, the underlying viruses differ in parameters and outbreak properties. Most existing models treat either a single respiratory virus or ILI as a whole. However, there is a need for models capable of comparing several individual viruses that cause respiratory illness, including ILI. To address this need, here we present a flexible model and simulations of epidemics for influenza, RSV, rhinovirus, seasonal coronavirus, adenovirus, and SARS/MERS, parameterized by a systematic literature review and accompanied by a global sensitivity analysis. We find that for these biological causes of ILI, their parameter values, timing, prevalence, and proportional contributions differ substantially. These results demonstrate that distinguishing the viruses that cause ILI will be an important aspect of future work on diagnostics, mitigation, modeling, and preparation for future pandemics.
Topics: Epidemics; Humans; Influenza, Human; Rhinovirus; Virus Diseases; Viruses
PubMed: 35490763
DOI: 10.1016/j.jtbi.2022.111145 -
Drug and Alcohol Dependence Jun 2023Prescription drug monitoring programs (PDMPs) are used to mitigate harms from high-risk medicines including misuse, prescription shopping, overdoses, and death. Previous... (Review)
Review
BACKGROUND
Prescription drug monitoring programs (PDMPs) are used to mitigate harms from high-risk medicines including misuse, prescription shopping, overdoses, and death. Previous systematic reviews report inconsistent findings. We undertook a systematic review of reviews to 1) describe and identify the methods and outcome measures used to evaluate PDMPs, 2) summarise existing evidence on outcomes and factors that influence PDMP success or benefit realisation.
METHODS
MEDLINE, EMBASE, Scopus, Cochrane Database of Systematic Reviews, and PROSPERO were used to identify systematic reviews on PDMPs. Twelve papers met the inclusion criteria. Data extracted included review aim, study designs, settings, outcome measures, and key findings. Quality was assessed using AMSTAR 2 quality assessment tool.
RESULTS
Review papers were categorised as outcome or process evaluation reviews. Process evaluation reviews described implementation processes, barriers and facilitators to PDMP use and/or implementation. Most (57%) papers described barriers which frequently included usability and data integration. Outcome evaluation papers reported impact of PDMPs on outcomes, which were opioid-focused, and findings were highly variable. Most reviews (67%) were rated as low quality, limiting the conclusions that can be drawn.
CONCLUSIONS
Inconsistent methods and outcome measures were used to evaluate PDMPs. No economic evaluations of PDMPs were found. Standardising assessment and reporting of results may improve the quality and confidence in an evidence-base to inform future roll-out and evaluation of PDMPs. Targeting barriers such as system-related challenges and negative end-user perceptions could improve sustained uptake of PDMPs, and potentially facilitate benefits realisation, including mitigating harms of high-risk prescription medicines.
Topics: Humans; Analgesics, Opioid; Drug Overdose; Opioid-Related Disorders; Prescription Drug Misuse; Prescription Drug Monitoring Programs; Systematic Reviews as Topic
PubMed: 37126936
DOI: 10.1016/j.drugalcdep.2023.109887 -
The Ocular Surface Apr 2023Societal factors associated with ocular surface diseases were mapped using a framework to characterize the relationship between the individual, their health and...
Societal factors associated with ocular surface diseases were mapped using a framework to characterize the relationship between the individual, their health and environment. The impact of the COVID-19 pandemic and mitigating factors on ocular surface diseases were considered in a systematic review. Age and sex effects were generally well-characterized for inflammatory, infectious, autoimmune and trauma-related conditions. Sex and gender, through biological, socio-economic, and cultural factors impact the prevalence and severity of disease, access to, and use of, care. Genetic factors, race, smoking and co-morbidities are generally well characterized, with interdependencies with geographical, employment and socioeconomic factors. Living and working conditions include employment, education, water and sanitation, poverty and socioeconomic class. Employment type and hobbies are associated with eye trauma and burns. Regional, global socio-economic, cultural and environmental conditions, include remoteness, geography, seasonality, availability of and access to services. Violence associated with war, acid attacks and domestic violence are associated with traumatic injuries. The impacts of conflict, pandemic and climate are exacerbated by decreased food security, access to health services and workers. Digital technology can impact diseases through physical and mental health effects and access to health information and services. The COVID-19 pandemic and related mitigating strategies are mostly associated with an increased risk of developing new or worsening existing ocular surface diseases. Societal factors impact the type and severity of ocular surface diseases, although there is considerable interdependence between factors. The overlay of the digital environment, natural disasters, conflict and the pandemic have modified access to services in some regions.
Topics: Male; Female; Humans; Pandemics; COVID-19; Socioeconomic Factors; Poverty; Life Style
PubMed: 37062429
DOI: 10.1016/j.jtos.2023.04.006 -
Pain Jul 2021We report a systematic review and meta-analysis of studies that assessed the antinociceptive efficacy of cannabinoids, cannabis-based medicines, and endocannabinoid... (Meta-Analysis)
Meta-Analysis
Systematic review and meta-analysis of cannabinoids, cannabis-based medicines, and endocannabinoid system modulators tested for antinociceptive effects in animal models of injury-related or pathological persistent pain.
We report a systematic review and meta-analysis of studies that assessed the antinociceptive efficacy of cannabinoids, cannabis-based medicines, and endocannabinoid system modulators on pain-associated behavioural outcomes in animal models of pathological or injury-related persistent pain. In April 2019, we systematically searched 3 online databases and used crowd science and machine learning to identify studies for inclusion. We calculated a standardised mean difference effect size for each comparison and performed a random-effects meta-analysis. We assessed the impact of study design characteristics and reporting of mitigations to reduce the risk of bias. We meta-analysed 374 studies in which 171 interventions were assessed for antinociceptive efficacy in rodent models of pathological or injury-related pain. Most experiments were conducted in male animals (86%). Antinociceptive efficacy was most frequently measured by attenuation of hypersensitivity to evoked limb withdrawal. Selective cannabinoid type 1, cannabinoid type 2, nonselective cannabinoid receptor agonists (including delta-9-tetrahydrocannabinol) and peroxisome proliferator-activated receptor-alpha agonists (predominantly palmitoylethanolamide) significantly attenuated pain-associated behaviours in a broad range of inflammatory and neuropathic pain models. Fatty acid amide hydrolase inhibitors, monoacylglycerol lipase inhibitors, and cannabidiol significantly attenuated pain-associated behaviours in neuropathic pain models but yielded mixed results in inflammatory pain models. The reporting of criteria to reduce the risk of bias was low; therefore, the studies have an unclear risk of bias. The value of future studies could be enhanced by improving the reporting of methodological criteria, the clinical relevance of the models, and behavioural assessments. Notwithstanding, the evidence supports the hypothesis of cannabinoid-induced analgesia.
Topics: Analgesics; Animals; Cannabinoids; Cannabis; Endocannabinoids; Male; Models, Animal; Neuralgia
PubMed: 33729209
DOI: 10.1097/j.pain.0000000000002269 -
Expert Systems With Applications Apr 2021The pandemic caused by the novel coronavirus occurred unexpectedly in China in December 2019. Tens of millions of confirmed cases and more than hundreds of thousands... (Review)
Review
The pandemic caused by the novel coronavirus occurred unexpectedly in China in December 2019. Tens of millions of confirmed cases and more than hundreds of thousands of confirmed deaths are reported worldwide according to the World Health Organisation. News about the virus is spreading all over social media websites. Consequently, these social media outlets are experiencing and presenting different views, opinions and emotions during various outbreak-related incidents. For computer scientists and researchers, big data are valuable assets for understanding people's sentiments regarding current events, especially those related to the pandemic. Therefore, analysing these sentiments will yield remarkable findings. To the best of our knowledge, previous related studies have focused on one kind of infectious disease. No previous study has examined multiple diseases via sentiment analysis. Accordingly, this research aimed to review and analyse articles about the occurrence of different types of infectious diseases, such as epidemics, pandemics, viruses or outbreaks, during the last 10 years, understand the application of sentiment analysis and obtain the most important literature findings. Articles on related topics were systematically searched in five major databases, namely, ScienceDirect, PubMed, Web of Science, IEEE Xplore and Scopus, from 1 January 2010 to 30 June 2020. These indices were considered sufficiently extensive and reliable to cover our scope of the literature. Articles were selected based on our inclusion and exclusion criteria for the systematic review, with a total of articles selected. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature in accordance with four main categories: lexicon-based models, machine learning-based models, hybrid-based models and individuals. The obtained articles were categorised into motivations related to disease mitigation, data analysis and challenges faced by researchers with respect to data, social media platforms and community. Other aspects, such as the protocol being followed by the systematic review and demographic statistics of the literature distribution, were included in the review. Interesting patterns were observed in the literature, and the identified articles were grouped accordingly. This study emphasised the current standpoint and opportunities for research in this area and promoted additional efforts towards the understanding of this research field.
PubMed: 33139966
DOI: 10.1016/j.eswa.2020.114155