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International Journal of Medical... May 2024To identify and discuss theory-based studies of large-scale health information technology programs in the UK National Health Service. (Review)
Review
OBJECTIVE
To identify and discuss theory-based studies of large-scale health information technology programs in the UK National Health Service.
MATERIALS AND METHODS
Using the PRISMA systematic review framework, we searched Scopus, PubMed and CINAHL databases from inception to March 2022 for theory-based studies of large-scale health IT implementations. We undertook detailed full-text analyses of papers meeting our inclusion criteria.
RESULTS
Forty-six studies were included after assessment for eligibility, of which twenty-five applied theories from the information systems arena (socio-technical approaches, normalization process theory, user acceptance theories, diffusion of innovation), twelve from sociology (structuration theory, actor-network theory, institutional theory), while nine adopted other theories. Most investigated England's National Program for IT (2002-2011), exploring various technologies among which electronic records predominated. Research themes were categorized into user factors, program factors, process outcomes, clinical impact, technology, and organizational factors. Most research was qualitative, often using a case study strategy with a longitudinal or cross-sectional approach. Data were typically collected through interviews, observation, and document analysis; sampling was generally purposive; and most studies used thematic or related analyses. Theories were generally applied in a superficial or fragmentary manner; and articles frequently lacked detail on how theoretical constructs and relationships aided organization, analysis, and interpretation of data.
CONCLUSION
Theory-based studies of large NHS IT programs are relatively uncommon. As large healthcare programs evolve over a long timeframe in complex and dynamic environments, wider adoption of theory-based methods could strengthen the explanatory and predictive utility of research findings across multiple evaluation studies. Our review has confirmed earlier suggestions for theory selection, and we suggest there is scope for more explicit use of such theoretical constructs to strengthen the conceptual foundations of health informatics research. Additionally, the challenges of large national health informatics programs afford wide-ranging opportunities to test, refine, and adapt sociological and information systems theories.
Topics: Humans; State Medicine; Delivery of Health Care; Technology; Qualitative Research; United Kingdom
PubMed: 38442664
DOI: 10.1016/j.ijmedinf.2024.105395 -
Human Brain Mapping Mar 2024A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and... (Review)
Review
A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.
Topics: Humans; Brain; Magnetic Resonance Imaging; Diffusion Magnetic Resonance Imaging; Brain Mapping; Neuroimaging
PubMed: 38436603
DOI: 10.1002/hbm.26620 -
BMJ Open Respiratory Research Feb 2024Mycophenolate mofetil (MMF) and azathioprine (AZA) are immunomodulatory treatments in interstitial lung disease (ILD). This systematic review aimed to evaluate the... (Meta-Analysis)
Meta-Analysis
OBJECTIVES
Mycophenolate mofetil (MMF) and azathioprine (AZA) are immunomodulatory treatments in interstitial lung disease (ILD). This systematic review aimed to evaluate the efficacy of MMF or AZA on pulmonary function in ILD.
DESIGN
Population included any ILD diagnosis, intervention included MMF or AZA treatment, outcome was delta change from baseline in per cent predicted forced vital capacity (%FVC) and gas transfer (diffusion lung capacity of carbon monoxide, %DLco). The primary endpoint compared outcomes relative to placebo comparator, the secondary endpoint assessed outcomes in treated groups only.
ELIGIBILITY CRITERIA
Randomised controlled trials (RCTs) and prospective observational studies were included. No language restrictions were applied. Retrospective studies and studies with high-dose concomitant steroids were excluded.
DATA SYNTHESIS
The systematic search was performed on 9 May. Meta-analyses according to drug and outcome were specified with random effects, I evaluated heterogeneity and Grading of Recommendations, Assessment, Development and Evaluation evaluated certainty of evidence. Primary endpoint analysis was restricted to RCT design, secondary endpoint included subgroup analysis according to prospective observational or RCT design.
RESULTS
A total of 2831 publications were screened, 12 were suitable for quantitative synthesis. Three MMF RCTs were included with no significant effect on the primary endpoints (%FVC 2.94, 95% CI -4.00 to 9.88, I=79.3%; %DLco -2.03, 95% CI -4.38 to 0.32, I=0.0%). An overall 2.03% change from baseline in %FVC (95% CI 0.65 to 3.42, I=0.0%) was observed in MMF, and RCT subgroup summary estimated a 4.42% change from baseline in %DL (95% CI 2.05 to 6.79, I=0.0%). AZA studies were limited. All estimates were considered very low certainty evidence.
CONCLUSIONS
There were limited RCTs of MMF or AZA and their benefit in ILD was of very low certainty. MMF may support preservation of pulmonary function, yet confidence in the effect was weak. To support high certainty evidence, RCTs should be designed to directly assess MMF efficacy in ILD.
PROSPERO REGISTRATION NUMBER
CRD42023423223.
Topics: Humans; Azathioprine; Immunosuppressive Agents; Lung Diseases, Interstitial; Lung; Mycophenolic Acid; Enzyme Inhibitors; Observational Studies as Topic
PubMed: 38413120
DOI: 10.1136/bmjresp-2023-002163 -
Renewable energy sources integration via machine learning modelling: A systematic literature review.Heliyon Feb 2024The use of renewable energy sources (RESs) at the distribution level has become increasingly appealing in terms of costs and technology, expecting a massive diffusion in...
The use of renewable energy sources (RESs) at the distribution level has become increasingly appealing in terms of costs and technology, expecting a massive diffusion in the near future and placing several challenges to the power grid. Since RESs depend on stochastic energy sources -solar radiation, temperature and wind speed, among others- they introduce a high level of uncertainty to the grid, leading to power imbalance and deteriorating the network stability. In this scenario, managing and forecasting RES uncertainty is vital to successfully integrate them into the power grids. Traditionally, physical- and statistical-based models have been used to predict RES power outputs. Nevertheless, the former are computationally expensive since they rely on solving complex mathematical models of the atmospheric dynamics, whereas the latter usually consider linear models, preventing them from addressing challenging forecasting scenarios. In recent years, the advances in machine learning techniques, which can learn from historical data, allowing the analysis of large-scale datasets either under non-uniform characteristics or noisy data, have provided researchers with powerful data-driven tools that can outperform traditional methods. In this paper, a systematic literature review is conducted to identify the most widely used machine learning-based approaches to forecast RES power outputs. The results show that deep artificial neural networks, especially long-short term memory networks, which can accurately model the autoregressive nature of RES power output, and ensemble strategies, which allow successfully handling large amounts of highly fluctuating data, are the best suited ones. In addition, the most promising results of integrating the forecasted output into decision-making problems, such as unit commitment, to address economic, operational and managerial grid challenges are discussed, and solid directions for future research are provided.
PubMed: 38404865
DOI: 10.1016/j.heliyon.2024.e26088 -
Medicine Feb 2024Alopecia areata (AA) is an autoimmune disease which results in non-scarring hair loss on the scalp or any surface with hair. Several genetic polymorphisms of the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Alopecia areata (AA) is an autoimmune disease which results in non-scarring hair loss on the scalp or any surface with hair. Several genetic polymorphisms of the interleukin genes have been linked with this disease but the results are inconsistent. This systematic review and meta-analysis were done to find the association between rs3118470, rs2275913, rs3212227, and rs10889677 of the IL2RA, IL17A, IL12B, and IL23R genes, respectively, of the interleukin family with alopecia areata.
METHODS
A comprehensive search for relevant research articles was conducted in Pubmed, Google Scholar, and Embase databases. Our search yielded 8 relevant articles with 1940 cases and 1788 controls. The odds ratio with 95% confidence intervals was calculated using fixed effect and random effect models. Heterogeneity was determined using the Q-test and I2 test. Publication bias was determined and funnel plots were used to adjust the odds ratio.
RESULTS
We found a significant risk effect for rs3118470 of the IL2RA gene with alopecia areata in the dominant model (CC + CT vs TT; OR = 1.54, 95% confidence interval = 1.05-2.26, P < .05, I2 = 69.03%) and homozygous model (CC vs TT; OR = 2.00, 95% confidence interval = 1.07-3.71, P < .05, I2 = 72.84%). For the other single nucleotide polymorphisms, we could not find any statistically significant association with the disease.
CONCLUSION
Our analysis showed that mutation of rs3118470 of IL2RA gene possesses a significant risk effect for alopecia areata. Future studies with larger sample sizes and ethnic backgrounds are warranted to confirm our findings.
Topics: Humans; Alopecia Areata; Genetic Predisposition to Disease; Interleukins; Polymorphism, Single Nucleotide
PubMed: 38394507
DOI: 10.1097/MD.0000000000037300 -
International Journal of Cardiology.... Apr 2024Cardiac magnetic resonance imaging (CMR) based T1 mapping and extracellular volume fraction (ECV) are powerful tools for identifying myocardial fibrosis. This systematic...
BACKGROUND
Cardiac magnetic resonance imaging (CMR) based T1 mapping and extracellular volume fraction (ECV) are powerful tools for identifying myocardial fibrosis. This systematic review and -analysis aims to characterize the utility of native T1 mapping and ECV in patients with non-ischemic cardiomyopathy (NICM) and to clarify the prognostic significance of elevated values.
METHODS
A literature search was conducted for studies reporting on use of CMR-based native T1 mapping and ECV measurement in NICM patients and their association with major adverse cardiac events (MACE), ventricular arrhythmias (VAs), and left ventricular reverse remodeling (LVRR). Databases searched included: Ovid MEDLINE, EMBASE, Web of Science, and Google Scholar. The search was not restricted to time or publication status.
RESULTS
Native T1 and ECV were significantly higher in NICM patients compared to controls (MD 78.80, 95 % CI 50.00, 107.59; p < 0.01; MD 5.86, 95 % CI 4.55, 7.16; p < 0.01). NICM patients who experienced MACE had higher native T1 and ECV (MD 52.87, 95 % CI 26.59, 79.15; p < 0.01; MD 6.03, 95 % CI 3.79, 8.26; p < 0.01). There was a non-statistically significant trend toward higher native T1 time in NICM patients who experienced VAs. NICM patients who were poor treatment responders had higher baseline native T1 and ECV (MD 40.58, 95 % CI 12.90, 68.25; p < 0.01; MD 3.29, 95 % CI 2.25, 4.33; p < 0.01).
CONCLUSIONS
CMR-based native T1 and ECV quantification may be useful tools for risk stratification of patients with NICM. They may provide additional diagnostic utility in combination with LGE, which poorly characterizes fibrosis in patients with diffuse myocardial involvement.
PubMed: 38371310
DOI: 10.1016/j.ijcha.2024.101339 -
Cureus Jan 2024The purpose of this systematic review is to summarize all existing evidence, regarding the immunohistochemical expression of REV-7 in different human cancer pathology... (Review)
Review
The purpose of this systematic review is to summarize all existing evidence, regarding the immunohistochemical expression of REV-7 in different human cancer pathology specimens. Moreover, the association of REV-7 expression with disease severity (clinical course), patients' survival, prognosis, and response to various treatments, such as chemotherapy and irradiation, was investigated. Three databases (PubMed, Scopus, and Cochrane) were systematically screened, from inception to September 2, 2023, as suggested by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Only studies using immunohistochemical staining for REV-7 in paraffin-embedded cancer tissues were included. Nine studies met the inclusion criteria and were included in the final qualitative synthesis. All nine studies were retrospective and non-comparative ones. Selected studies reported immunohistochemical expression of REV-7 in different types of cancer, including testicular cancer, ovarian cancer, esophagus squamous cell carcinoma, prostate cancer, colorectal cancer, diffuse large B-cell lymphoma, breast cancer, lung cancer, and skin cancer. High REV-7 expression was associated with faster disease progression, resistance to available treatment options, and worse prognosis in the majority of included studies. These results indicate that immunohistochemical staining of REV-7 protein could potentially be used as a predictive tissue marker in certain cases. Promising results, arising from REV-7 inactivation experiments, render REV-7 targeting a potential therapeutic strategy for future cancer management, especially in the cases of chemoresistant or radioresistant disease.
PubMed: 38371007
DOI: 10.7759/cureus.52542 -
North American Spine Society Journal Mar 2024Subjects with ankylosing spinal disorders, including diffuse idiopathic skeletal hyperostosis (DISH) and ankylosing spondylitis (AS) are more prone to vertebral... (Review)
Review
BACKGROUND
Subjects with ankylosing spinal disorders, including diffuse idiopathic skeletal hyperostosis (DISH) and ankylosing spondylitis (AS) are more prone to vertebral fractures and frequently present with neurological deficit compared to the patients without an ankylosed spine. Moreover, prevalent vertebral fractures are an important predictor for subsequent fracture risk. However, the pooled fracture prevalence for DISH is unknown and less recent for AS. We aimed to systematically investigate the prevalence and risk of vertebral fractures in DISH and AS populations.
METHODS
Publications in Medline and EMBASE were searched from January 1980 until July 2023 for cohort studies reporting vertebral fractures in AS and DISH. Data on prevalence were pooled with random effects modeling after double arcsine transformation. Heterogeneity was assessed with I statistics and we performed subgroup analysis and meta-regression to explore sources of heterogeneity.
RESULTS
We included 7 studies on DISH (n = 1,193, total fractures = 231) with a pooled vertebral fracture prevalence of 22.6% (95%CI: 13.4%-33.4%). For AS, 26 studies were included (n = 2,875, total fractures = 460) with a pooled vertebral fracture prevalence of 15.2% (95%CI: 11.6%-19.1%). In general, fracture prevalence for AS remained similar for several study-level and clinically relevant characteristics, including study design, diagnostic criteria, spine level, and patient characteristics in subgroup analysis. AS publications from 2010 to 2020 showed higher fracture prevalence compared to 1990 to 2010 (18.6% vs. 11.6%). Fractures in DISH were most common at the thoracolumbar junction, whereas for AS, the most common location was the mid-thoracic spine.
CONCLUSIONS
Vertebral fractures are prevalent in AS and DISH populations. Differences in fracture distribution along the spinal axis exist between the 2 disorders. Additional longitudinal studies are needed for incident fracture assessment in patients with ankylosing spinal disorders.
PubMed: 38370336
DOI: 10.1016/j.xnsj.2024.100312 -
Dermatology Practical & Conceptual Jan 2024Diffuse Melanosis Cutis (DMC) is a rare and late complication of metastatic malignant melanoma (MM) characterized by progressive pigmentation of skin and sometimes... (Review)
Review
INTRODUCTION
Diffuse Melanosis Cutis (DMC) is a rare and late complication of metastatic malignant melanoma (MM) characterized by progressive pigmentation of skin and sometimes mucous membranes. The distinctive feature is the widespread and progressive deposition of melanin precursors in the dermis.
OBJECTIVES
The purpose of this review is to define the clinical and demographic features of DMC and to promote a deeper insight into the clinical manifestation, histological findings, and pathophysiology behind DMC.
METHODS
We have conducted a systematic review of the literature on published DMC in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. We also reported a case of DMC secondary to low-risk melanoma.
RESULTS
Overall, including our case report, we reported 53 articles described 62 DMC patients. Breslow level of primary melanoma was reported having a mean value of 3.3 mm. The mean survival rate from onset of DMC resulted being 4.36 months.
CONCLUSIONS
Among the most widely accepted etiopathogenetic hypotheses are deposition of melanic precursors in the dermis following tumor lysis, melanocyte proliferation induced by neoplastic growth factors, and the presence of diffuse dermal micro-metastases of MM. However, unanimous consensus on the proposed etiopathogenetic models of DMC is still lacking.
PubMed: 38364426
DOI: 10.5826/dpc.1401a8 -
Critical Reviews in Oncology/hematology Apr 2024Models based on risk stratification are increasingly reported for Diffuse large B cell lymphoma (DLBCL). Due to a rising interest in nomograms for cancer patients, we... (Review)
Review
Models based on risk stratification are increasingly reported for Diffuse large B cell lymphoma (DLBCL). Due to a rising interest in nomograms for cancer patients, we aimed to review and critically appraise prognostic models based on nomograms in DLBCL patients. A literature search in PubMed/Embase identified 59 articles that proposed prognostic models for DLBCL by combining parameters of interest (e.g., clinical, laboratory, immunohistochemical, and genetic) between January 2000 and 2024. Of them, 40 studies proposed different gene expression signatures and incorporated them into nomogram-based prognostic models. Although most studies assessed discrimination and calibration when developing the model, many lacked external validation. Current nomogram-based models for DLBCL are mainly developed from publicly available databases, lack external validation, and have no applicability in clinical practice. However, they may be helpful in individual patient counseling, although careful considerations should be made regarding model development due to possible limitations when choosing nomograms for prognostication.
Topics: Humans; Nomograms; Lymphoma, Large B-Cell, Diffuse; Prognosis
PubMed: 38346460
DOI: 10.1016/j.critrevonc.2024.104293