-
Gynecology and Minimally Invasive... 2024High-intensity focused ultrasound (HIFU) is commonly used to treat uterine fibroids and adenomyosis, but there is no evidence using metadata to compare fertility... (Review)
Review
High-intensity Focused Ultrasound is a Better Choice for Women with Fertility Desire: A Systematic Review and Meta-analysis of the Comparison between High-intensity Focused Ultrasound and Laparoscopic Treatment of Uterine Fibroids.
High-intensity focused ultrasound (HIFU) is commonly used to treat uterine fibroids and adenomyosis, but there is no evidence using metadata to compare fertility outcomes between conventional laparoscopic procedures and HIFU. The purpose of this study analysis is that evidence-based fertility outcomes may provide better treatment options for clinicians and patients considering fertility. The literature on fertility data for HIFU surgery versus laparoscopic myomectomy was searched in seven English language databases from January 1, 2010, to November 23, 2022. A total of 1375 articles were received in the literature, 14 of which were selected. We found that women who underwent HIFU surgery had higher rates of spontaneous pregnancy, higher rates of spontaneous delivery, and higher rates of full-term delivery but may have higher rates of miscarriage or postpartum complications than women who underwent laparoscopic myomectomy. Looking forward to future studies, it is hoped that the literature will examine endometrial differences in women who undergo HIFU and laparoscopic myomectomy to demonstrate the ability of endometrial repair. The location of fibroids in the sample should also be counted to allow for attribution statistics on the cause of miscarriage.
PubMed: 38911304
DOI: 10.4103/gmit.gmit_23_23 -
European Heart Journal. Cardiovascular... Jun 2024Direct oral anticoagulants (DOACs) are increasingly used off-label to treat patients with left ventricular thrombus (LVT). We analyzed available meta-data comparing...
AIMS
Direct oral anticoagulants (DOACs) are increasingly used off-label to treat patients with left ventricular thrombus (LVT). We analyzed available meta-data comparing DOACs and vitamin K antagonists (VKAs) for efficacy and safety.
METHODS
We conducted a systematic search and meta-analysis of observational and randomized data comparing DOACs versus VKAs in patients with LVT. Endpoints of interest were stroke or systemic embolism, thrombus resolution, all-cause death, and a composite bleeding endpoint. Estimates were pooled using a random-effect model meta-analysis, and their robustness was investigated using sensitivity and influential analyses.
RESULTS
We identified 22 articles (18 observational studies, 4 small randomized clinical trials) reporting on a total of 3,587 patients (2,489 VKA vs. 1,098 DOAC therapy). The pooled estimates for stroke or systemic embolism (OR 0.81; 95% CI [0.57, 1.15]) and thrombus resolution (OR 1.12; 95% CI [0.86; 1.46]) were comparable, and there was low heterogeneity overall across the included studies. DOAC use was associated with lower odds of all-cause death (OR 0.65; 95%CI [0.46; 0.92]) and a composite bleeding endpoint (OR 0.67; 95%CI [0.47; 0.97]). A risk of bias was evident particularly for observational reports, with some publication bias suggested in funnel plots.
CONCLUSION
In this comprehensive analysis of mainly observational data, the use of DOACs was not associated with a significant difference in stroke or systemic embolism, or thrombus resolution compared to VKA therapy. The use of DOACs was associated with a lower rate of all-cause death and fewer bleeding events. Adequately sized randomized clinical trials are needed to confirm these findings, which could allow a wider adoption of DOACs in patients with LVT.
PubMed: 38845369
DOI: 10.1093/ehjcvp/pvae042 -
BMC Medical Research Methodology May 2024Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming...
OBJECTIVE
Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening.
METHODS
This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms.
RESULTS AND CONCLUSIONS
The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.
Topics: Humans; Machine Learning; Papillomavirus Infections; Economics, Medical; Algorithms; Outcome Assessment, Health Care; Deep Learning; Abstracting and Indexing
PubMed: 38724903
DOI: 10.1186/s12874-024-02224-3 -
Frontiers in Artificial Intelligence 2024Public health policy researchers face a persistent challenge in identifying and integrating relevant data, particularly in the context of the U.S. opioid crisis, where a...
BACKGROUND
Public health policy researchers face a persistent challenge in identifying and integrating relevant data, particularly in the context of the U.S. opioid crisis, where a comprehensive approach is crucial.
PURPOSE
To meet this new workforce demand health policy and health economics programs are increasingly introducing data analysis and data visualization skills. Such skills facilitate data integration and discovery by linking multiple resources. Common linking strategies include individual or aggregate level linking (e.g., patient identifiers) in primary clinical data and conceptual linking (e.g., healthcare workforce, state funding, burnout rates) in secondary data. Often, the combination of primary and secondary datasets is sought, requiring additional skills, for example, understanding metadata and constructing interlinkages.
METHODS
To help improve those skills, we developed a 2-step process using a scoping method to discover data and network visualization to interlink metadata. Results: We show how these new skills enable the discovery of relationships among data sources pertinent to public policy research related to the opioid overdose crisis and facilitate inquiry across heterogeneous data resources. In addition, our interactive network visualization introduces (1) a conceptual approach, drawing from recent systematic review studies and linked by the publications, and (2) an aggregate approach, constructed using publicly available datasets and linked through crosswalks.
CONCLUSIONS
These novel metadata visualization techniques can be used as a teaching tool or a discovery method and can also be extended to other public policy domains.
PubMed: 38646414
DOI: 10.3389/frai.2024.1208874 -
Frontiers in Psychiatry 2024Recent developments in the fields of natural language processing (NLP) and machine learning (ML) have shown significant improvements in automatic text processing. At the... (Review)
Review
Recent developments in the fields of natural language processing (NLP) and machine learning (ML) have shown significant improvements in automatic text processing. At the same time, the expression of human language plays a central role in the detection of mental health problems. Whereas spoken language is implicitly assessed during interviews with patients, written language can also provide interesting insights to clinical professionals. Existing work in the field often investigates mental health problems such as depression or anxiety. However, there is also work investigating how the diagnostics of eating disorders can benefit from these novel technologies. In this paper, we present a systematic overview of the latest research in this field. Our investigation encompasses four key areas: (a) an analysis of the metadata from published papers, (b) an examination of the sizes and specific topics of the datasets employed, (c) a review of the application of machine learning techniques in detecting eating disorders from text, and finally (d) an evaluation of the models used, focusing on their performance, limitations, and the potential risks associated with current methodologies.
PubMed: 38596627
DOI: 10.3389/fpsyt.2024.1319522 -
European Child & Adolescent Psychiatry Feb 2024Several interventions have been developed to support families living with parental mental illness (PMI). Recent evidence suggests that programmes with whole-family...
Several interventions have been developed to support families living with parental mental illness (PMI). Recent evidence suggests that programmes with whole-family components may have greater positive effects for families, thereby also reducing costs to health and social care systems. This review aimed to identify whole-family interventions, their common characteristics, effectiveness and acceptability. A systematic review was conducted according to PRISMA 2020 guidelines. A literature search was conducted in ASSIA, CINAHL, Embase, Medline, and PsycINFO in January 2021 and updated in August 2022. We double screened 3914 abstracts and 212 papers according to pre-set inclusion and exclusion criteria. The Mixed Methods Appraisal Tool was used for quality assessment. Quantitative and qualitative data were extracted and synthesised. Randomised-control trial data on child and parent mental health outcomes were analysed separately in random-effects meta-analyses. The protocol, extracted data, and meta-data are accessible via the Open Science Framework ( https://osf.io/9uxgp/ ). Data from 66 reports-based on 41 independent studies and referring to 30 different interventions-were included. Findings indicated small intervention effects for all outcomes including children's and parents' mental health (dā=ā-0.017, -027; dā=ā-0.14, -0.16) and family outcomes. Qualitative evidence suggested that most families experienced whole-family interventions as positive, highlighting specific components as helpful, including whole-family components, speaking about mental illness, and the benefits of group settings. Our findings highlight the lack of high-quality studies. The present review fills an important gap in the literature by summarising the evidence for whole-family interventions. There is a lack of robust evidence coupled with a great need in families affected by PMI which could be addressed by whole-family interventions. We recommend the involvement of families in the further development of these interventions and their evaluation.
PubMed: 38393370
DOI: 10.1007/s00787-024-02380-3 -
Translational Vision Science &... Feb 2024Retinal images contain rich biomarker information for neurodegenerative disease. Recently, deep learning models have been used for automated neurodegenerative disease...
PURPOSE
Retinal images contain rich biomarker information for neurodegenerative disease. Recently, deep learning models have been used for automated neurodegenerative disease diagnosis and risk prediction using retinal images with good results.
METHODS
In this review, we systematically report studies with datasets of retinal images from patients with neurodegenerative diseases, including Alzheimer's disease, Huntington's disease, Parkinson's disease, amyotrophic lateral sclerosis, and others. We also review and characterize the models in the current literature which have been used for classification, regression, or segmentation problems using retinal images in patients with neurodegenerative diseases.
RESULTS
Our review found several existing datasets and models with various imaging modalities primarily in patients with Alzheimer's disease, with most datasets on the order of tens to a few hundred images. We found limited data available for the other neurodegenerative diseases. Although cross-sectional imaging data for Alzheimer's disease is becoming more abundant, datasets with longitudinal imaging of any disease are lacking.
CONCLUSIONS
The use of bilateral and multimodal imaging together with metadata seems to improve model performance, thus multimodal bilateral image datasets with patient metadata are needed. We identified several deep learning tools that have been useful in this context including feature extraction algorithms specifically for retinal images, retinal image preprocessing techniques, transfer learning, feature fusion, and attention mapping. Importantly, we also consider the limitations common to these models in real-world clinical applications.
TRANSLATIONAL RELEVANCE
This systematic review evaluates the deep learning models and retinal features relevant in the evaluation of retinal images of patients with neurodegenerative disease.
Topics: Humans; Algorithms; Alzheimer Disease; Deep Learning; Machine Learning; Neurodegenerative Diseases; Datasets as Topic; Retina
PubMed: 38381447
DOI: 10.1167/tvst.13.2.16 -
Comprehensive Reviews in Food Science... Jan 2024Among descriptive sensory evaluation methods, temporal methods have a wide audience in food science because they make it possible to follow perception as close as...
Among descriptive sensory evaluation methods, temporal methods have a wide audience in food science because they make it possible to follow perception as close as possible to the moment when sensations are perceived. The aim of this work was to describe 30 years of research involving temporal methods by mapping the scientific literature using a systematic scoping review. Thus, 363 research articles found from a search in Scopus and Web of Science from 1991 to 2022 were included. The extracted data included information on the implementation of studies referring to the use of temporal methods (details related to subjects, products, descriptors, research design, data analysis, etc.), reasons why they were used and the conclusions they allowed to be drawn. Metadata analysis and critical appraisal were also carried out. A quantitative and qualitative synthesis of the results allowed the identification of trends in the way in which the methods were developed, refined, and disseminated. Overall, a large heterogeneity was noted in the way in which the temporal measurements were carried out and the results presented. Some critical research gaps in establishing the validity and reliability of temporal methods have also been identified. They were mostly related to the details of implementation of the methods (e.g., almost no justification for the number of consumers included in the studies, absence of report on panel repeatability) and data analysis (e.g., prevalence of use of exploratory data analysis, only 20% of studies using confirmatory analyses considering the dynamic nature of the data). These results suggest the need for general guidelines on how to implement the method, analyze and interpret data, and report the results. Thus, a template and checklist for reporting data and results were proposed to help increase the quality of future research.
Topics: Humans; Reproducibility of Results; Food Technology
PubMed: 38284596
DOI: 10.1111/1541-4337.13294 -
Journal of Neuro-oncology Dec 2023Surgical resection of glioblastoma (GBM) remains a cornerstone in the current treatment paradigm. The postoperative evolution of hydrocephalus necessitating... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Surgical resection of glioblastoma (GBM) remains a cornerstone in the current treatment paradigm. The postoperative evolution of hydrocephalus necessitating ventriculoperitoneal shunting (VPS) continues to be defined. Correspondingly the objective of this study was to aggregate pertinent metadata to better define the clinical course of VPS for hydrocephalus following glioblastoma surgery in light of contemporary management.
METHODS
Searches of multiple electronic databases from inception to November 2023 were conducted following PRISMA guidelines. Articles were screened against pre-specified criteria. Outcomes were pooled by random-effects meta-analyses where possible.
RESULTS
A total of 12 cohort studies satisfied all selection criteria, describing a total of 6,098 glioblastoma patients after surgery with a total of 261 (4%) of patients requiring postoperative VPS for hydrocephalus. Meta-analysis demonstrated the estimated pooled rate of symptomatic improvement following VPS was 78% (95% CI 66-88), and the estimated pooled rate of VPS revision was 24% (95% CI 16-33). Pooled time from index glioblastoma surgery to VPS surgery was 4.1 months (95% CI 2.8-5.3), and pooled survival time for index VPS surgery was 7.3 months (95% CI 5.4-9.4). Certainty of these outcomes were limited by the heterogenous and palliative nature of postoperative glioblastoma management.
CONCLUSIONS
Of the limited proportion of glioblastoma patients requiring VPS surgery for hydrocephalus after index surgery, 78% patients are expected to show symptom improvement, and 24% can expect to undergo revision surgery. An individualized approach to each patient is required to optimize both index glioblastoma and VPS surgeries to account for anatomy and goals of care given the poor prognosis of this tumor overall.
Topics: Humans; Glioblastoma; Hydrocephalus; Ventriculoperitoneal Shunt; Cohort Studies; Disease Progression; Retrospective Studies; Treatment Outcome
PubMed: 38112893
DOI: 10.1007/s11060-023-04538-6 -
PLOS Global Public Health 2023Enteric and parasitic infections such as soil-transmitted helminths cause considerable mortality and morbidity in low- and middle-income settings. Earthen household...
Enteric and parasitic infections such as soil-transmitted helminths cause considerable mortality and morbidity in low- and middle-income settings. Earthen household floors are common in many of these settings and could serve as a reservoir for enteric and parasitic pathogens, which can easily be transmitted to new hosts through direct or indirect contact. We conducted a systematic review and meta-analysis to establish whether and to what extent improved household floors decrease the odds of enteric and parasitic infections among occupants compared with occupants living in households with unimproved floors. Following the PRISMA guidelines, we comprehensively searched four electronic databases for studies in low- and middle-income settings measuring household flooring as an exposure and self-reported diarrhoea or any type of enteric or intestinal-parasitic infection as an outcome. Metadata from eligible studies were extracted and transposed on to a study database before being imported into the R software platform for analysis. Study quality was assessed using an adapted version of the Newcastle-Ottawa Quality Assessment Scale. In total 110 studies were eligible for inclusion in the systematic review, of which 65 were eligible for inclusion in the meta-analysis after applying study quality cut-offs. Random-effects meta-analysis suggested that households with improved floors had 0.75 times (95CI: 0.67-0.83) the odds of infection with any type of enteric or parasitic infection compared with household with unimproved floors. Improved floors gave a pooled protective OR of 0.68 (95CI: 0.58-0.8) for helminthic infections and 0.82 OR (95CI: 0.75-0.9) for bacterial or protozoan infections. Overall study quality was poor and there is an urgent need for high-quality experimental studies investigating this relationship. Nevertheless, this study indicates that household flooring may meaningfully contribute towards a substantial portion of the burden of disease for enteric and parasitic infections in low- and middle-income settings.
PubMed: 38039279
DOI: 10.1371/journal.pgph.0002631