Evaluation of Medical Subject Headings assignment in simulated patient articles.

OBJECTIVES: To evaluate human-based Medical Subject Headings (MeSH) allocation in articles about 'patient simulation'-a technique that mimics real-life patient scenarios with controlled patient responses. METHODS: A validation set of articles indexed before the Medical Text Indexer-Auto implementation (in 2019) was created with 150 combinations potentially referring to 'patient simulation'. Articles were classified into four categories of simulation studies. Allocation of seven MeSH terms (Simulation Training, Patient Simulation, High Fidelity Simulation Training, Computer Simulation, Patient-Specific Modelling, Virtual Reality, and Virtual Reality Exposure Therapy) was investigated. Accuracy metrics (sensitivity, precision, or positive predictive value) were calculated for each category of studies. KEY FINDINGS: A set of 7213 articles was obtained from 53 different word combinations, with 2634 excluded as irrelevant. 'Simulated patient' and 'standardized/standardized patient' were the most used terms. The 4579 included articles, published in 1044 different journals, were classified into: 'Machine/Automation' (8.6%), 'Education' (75.9%) and 'Practice audit' (11.4%); 4.1% were 'Unclear'. Articles were indexed with a median of 10 MeSH (IQR 8-13); however, 45.5% were not indexed with any of the seven MeSH terms. Patient Simulation was the most prevalent MeSH (24.0%). Automation articles were more associated with Computer Simulation MeSH (sensitivity = 54.5%; precision = 25.1%), while Education articles were associated with Patient Simulation MeSH (sensitivity = 40.2%; precision = 80.9%). Practice audit articles were also polarized to Patient Simulation MeSH (sensitivity = 34.6%; precision = 10.5%). CONCLUSIONS: Inconsistent use of free-text words related to patient simulation was observed, as well as inaccuracies in human-based MeSH assignments. These limitations can compromise relevant literature retrieval to support evidence synthesis exercises.

Representation of Social Determinants of Health terminology in medical subject headings: impact of added terms.

OBJECTIVES: To enhance and evaluate the quality of PubMed search results for Social Determinants of Health (SDoH) through the addition of new SDoH terms to Medical Subject Headings (MeSH). MATERIALS AND METHODS: High priority SDoH terms and definitions were collated from authoritative sources, curated based on publication frequencies, and refined by subject matter experts. Descriptive analyses were used to investigate how PubMed search details and best match results were affected by the addition of SDoH concepts to MeSH. Three information retrieval metrics (Precision, Recall, and F measure) were used to quantitatively assess the accuracy of PubMed search results. Pre- and post-update documents were clustered into topic areas using a Natural Language Processing pipeline, and SDoH relevancy assessed. RESULTS: Addition of 35 SDoH terms to MeSH resulted in more accurate algorithmic translations of search terms and more reliable best match results. The Precision, Recall, and F measures of post-update results were significantly higher than those of pre-update results. The percentage of retrieved publications belonging to SDoH clusters was significantly greater in the post- than pre-update searches. DISCUSSION: This evaluation confirms that inclusion of new SDoH terms in MeSH can lead to qualitative and quantitative enhancements in PubMed search retrievals. It demonstrates the methodology for and impact of suggesting new terms for MeSH indexing. It provides a foundation for future efforts across behavioral and social science research (BSSR) domains. CONCLUSION: Improving the representation of BSSR terminology in MeSH can improve PubMed search results, thereby enhancing the ability of investigators and clinicians to build and utilize a cumulative BSSR knowledge base.

PubChem synonym filtering process using crowdsourcing.

PubChem ( https://pubchem.ncbi.nlm.nih.gov ) is a public chemical information resource containing more than 100 million unique chemical structures. One of the most requested tasks in PubChem and other chemical databases is to search chemicals by name (also commonly called a "chemical synonym"). PubChem performs this task by looking up chemical synonym-structure associations provided by individual depositors to PubChem. In addition, these synonyms are used for many purposes, including creating links between chemicals and PubMed articles (using Medical Subject Headings (MeSH) terms). However, these depositor-provided name-structure associations are subject to substantial discrepancies within and between depositors, making it difficult to unambiguously map a chemical name to a specific chemical structure. The present paper describes PubChem's crowdsourcing-based synonym filtering strategy, which resolves inter- and intra-depositor discrepancies in synonym-structure associations as well as in the chemical-MeSH associations. The PubChem synonym filtering process was developed based on the analysis of four crowd-voting strategies, which differ in the consistency threshold value employed (60% vs 70%) and how to resolve intra-depositor discrepancies (a single vote vs. multiple votes per depositor) prior to inter-depositor crowd-voting. The agreement of voting was determined at six levels of chemical equivalency, which considers varying isotopic composition, stereochemistry, and connectivity of chemical structures and their primary components. While all four strategies showed comparable results, Strategy I (one vote per depositor with a 60% consistency threshold) resulted in the most synonyms assigned to a single chemical structure as well as the most synonym-structure associations disambiguated at the six chemical equivalency contexts. Based on the results of this study, Strategy I was implemented in PubChem's filtering process that cleans up synonym-structure associations as well as chemical-MeSH associations. This consistency-based filtering process is designed to look for a consensus in name-structure associations but cannot attest to their correctness. As a result, it can fail to recognize correct name-structure associations (or incorrect ones), for example, when a synonym is provided by only one depositor or when many contributors are incorrect. However, this filtering process is an important starting point for quality control in name-structure associations in large chemical databases like PubChem.

A bibliometric study of worldwide scientific literature on somatopsychics (1913‒2022).

OBJECTIVES: This investigation aims to analyze the characteristics and development of literature and advocate to include "Somatopsychic" as a Medical Subject Headings (MeSH) term. BACKGROUND: The interplay between physiological processes and psychological conditions, commonly referred to as "Somatopsychic," has garnered increasing attention in scientific literature over the years. METHODS: Somatopsychic-related research from the Scopus database using (Text word) and (MeSH) features. Publications were collected on Mar 22, 2023. The publication output was then analyzed using the R package's bibliometrics (Biblioshiny) and VOSviewer. RESULTS: In this study, search results for "somatopsychic" using (MeSH) resulted in a predictable return of 0 articles. Meanwhile, based on a search with (Text word), this study retrieved 306 documents for an unlimited period (and yielded published articles between 1913 and 2022). The analysis also revealed that 3,176 authors contributed to publications related to somatopsychic, with the United States ranking first in terms of authorship. In addition, the study presented a co-word network that illustrated frequent co-occurrence of particular keywords within somatopsychic research. CONCLUSION: This study reveals that somatopsychic-related publications are becoming increasingly prevalent. Adding somatopsychic as a dedicated term to the MeSH thesaurus of the National Library of Medicine would assist in indexing and retrieving the most pertinent literature on this topic (Tab. 3, Fig. 5, Ref. 51).

Influence of automated indexing in Medical Subject Headings (MeSH) selection for pharmacy practice journals.

BACKGROUND: The Medical Subject Headings (MeSH) thesaurus is the controlled vocabulary used to index articles in MEDLINE. MeSH were mainly manually selected until June 2022 when an automated algorithm, the Medical Text Indexer (MTI) automated was fully implemented. A selection of automated indexed articles is then reviewed (curated) by human indexers to ensure the quality of the process. OBJECTIVE: To describe the association of MEDLINE indexing methods (i.e., manual, automated, and automated + curated) on the MeSH assignment in pharmacy practice journals compared with medical journals. METHODS: Original research articles published between 2016 and 2023 in two groups of journals (i.e., the Big-five general medicine and three pharmacy practice journals) were selected from PubMed using journal-specific search strategies. Metadata of the articles, including MeSH terms and indexing method, was extracted. A list of pharmacy-specific MeSH terms had been compiled from previously published studies, and their presence in pharmacy practice journal records was investigated. Using bivariate and multivariate analyses, as well as effect size measures, the number of MeSH per article was compared between journal groups, geographic origin of the journal, and indexing method. RESULTS: A total of 8479 original research articles was retrieved: 6254 from the medical journals and 2225 from pharmacy practice journals. The number of articles indexed by the various methods was disproportionate; 77.8 % of medical and 50.5 % of pharmacy manually indexed. Among those indexed using the automated system, 51.1 % medical and 10.9 % pharmacy practice articles were then curated to ensure the indexing quality. Number of MeSH per article varied among the three indexing methods for medical and pharmacy journals, with 15.5 vs. 13.0 in manually indexed, 9.4 vs. 7.4 in automated indexed, and 12.1 vs. 7.8 in automated and then curated, respectively. Multivariate analysis showed significant effect of indexing method and journal group in the number of MeSH attributed, but not the geographical origin of the journal. CONCLUSIONS: Articles indexed using automated MTI have less MeSH than manually indexed articles. Articles published in pharmacy practice journals were indexed with fewer number of MeSH compared with general medical journal articles regardless of the indexing method used.

Dental bitewing radiographs segmentation using deep learning-based convolutional neural network algorithms.

OBJECTIVES: Dental radiographs, particularly bitewing radiographs, are widely used in dental diagnosis and treatment Dental image segmentation is difficult for various reasons, such as intricate structures, low contrast, noise, roughness, and unclear borders, resulting in poor image quality. Recent developments in deep learning models have improved performance in analyzing dental images. In this research, our primary objective is to determine the most effective segmentation technique for bitewing radiographs based on different metrics: accuracy, training time, and the number of training parameters as a reflection of architectural cost. METHODS: In this research, we employ several deep learning models, namely Resnet-18, Resnet-50, Xception, Inception Resnet v2, and Mobilenetv2, to segment bitewing radiographs. The process begins by importing the radiographs into MATLAB®(MathWorks Inc), where the images are first improved, then segmented using the graph cut method based on regions to produce a binary mask that distinguishes the background from the original X-ray. RESULTS: The deep learning models were trained on 298 and 99 radiograph training and validation sets and were evaluated using 99 images from the testing set. We also compare the segmentation model using several criteria, including accuracy, speed, and size, to determine which network is superior. Furthermore, we compare our findings with prior research to provide a comprehensive understanding of the advancements made in dental image segmentation. The accurate segmentation achieved was 93.67% and 94.42% by the Resnet-18 and Resnet-50 models, respectively. CONCLUSION: This research advances dental image analysis and facilitates more accurate diagnoses and treatment planning by determining the best segmentation technique. The outcomes of this study can guide researchers and practitioners in selecting appropriate segmentation methods for practical dental image analysis.

Methodological Exploration for Global Cardiovascular Academic Performance Evaluation(CAPE)System / 中国循环杂志

Objectives:To establish a comprehensive system of Cardiovascular Academic Performance Evaluation(CAPE)and rank global TOP100 medical institutions in the fields of cardiovascular diseases(CVD). Methods:CVD-related terms were extracted from Medical Subject Headings(MeSH),Embase thesaurus(EMtrees)and International Classification of Diseases(ICD)by CVD-related professionals,as well as by librarians and information professionals.Terminology databases(named as Fuwai Subject Headings)were established,and nine sub-disciplines were proposed,including ischemic heart diseases,hypertension,vascular diseases,arrhythmia,pulmonary vascular diseases,heart failure,congenital heart diseases,cardiomyopathy,and valvular heart diseases.The mapping patterns of sub-discipline,cardiovascular terminology and entry terms were pre-defined.The CVD-related research literature published from January 1,2016 to December 31,2022 were retrieved from Web of Science,PubMed and Scopus.Based on this,metadata were fused and duplicates were excluded.Fuwai Subject Headings were searched and matched into four respects for each literature,including subject words,titles,keywords,and abstracts,which was used to generate an information table of"Position—CVD terminology—Frequency",and to calculate CVD correlation scores and sub-discipline scores.We standardized the names of medical institutions and scholars,and make a ranking system for CAPE based on original articles with strong cardiovascular correlation(correlation score≥4).When evaluating the science and technological performance for Chinese hospitals in cardiovascular diseases,National Natural Science Foundation Projects,authorized invention patents,prize achievements,research platforms,and registered data of drug clinical trials in Center for Drug Evaluation(CDE)were considered besides research papers. Results:During 2016 and 2022,1 545 103 CVD research literatures were found worldwide.After excluding meeting abstracts,books,biographies,news,videos,audio texts,retracted publications,and corrections,1 178 019 CVD research literatures were further evaluated.518 058 literatures were indexed as"strongly correlated to CVD"using Fuwai Subject Headings.Besides papers,other data sources were also collected,including 11 143 CVD-related Natural Science Foundation Projects,19 382 CVD-related effective authorized invention patents,103 CVD-related national prize achievements,24 CVD-related national research platforms,and 2 084 CDE registered data of CVD-related drug clinical trials.Research teams from nine sub-disciplines reviewed and validated research literature in respective fields,and classification rules of corresponding sub-disciplines were created and improved based on their opinions.Finally,eleven individual indexes were chosen to construct CAPE system for ranking global TOP100 medical institutions in overall CVD field and TOP30 in nine sub-disciplines.From 2016 to 2022,the number of cardiovascular disease research papers published by Chinese institutes has increased by 123.5%,with a total of approximately 76.8 thousands papers published(about 30 papers per day on average),ranked the second under the United States(approximately 114.1 thousands papers).However,the proportion of papers published by the Chinese Journal Citation Reports(JCR)and the Chinese Academy of Sciences only ranked eighth in the world.In the comprehensive academic performance of original cardiovascular research papers in global hospitals from 2020 to 2022,only two Chinese medical institutions ranked in the TOP20 as evaluated by CAPE system. Conclusions:Based on multi-source data from 2016 to 2022,CAPE initiated to establish a cardiovascular academic performance evaluation system.

Biblioteca virtual em saúde homeopatia Brasil Dr. Matheus Marim: o ingresso da homeopatia na literatura científica mundial / Virtual library in health homeopathy Brazil Dr. Matheus Marim: the entrance of homeopathy in scientific literature worldwide

A Biblioteca Virtual em Saúde (BVS) Homeopatia Brasil(1) personifica o ingresso da Homeopatia na literatura médica oficial, sendo o resultado de décadas de um trabalho voluntário de vários homeopatas, tendo uma história de mais 40 anos a qual se mescla de maneira indissociável com a história da Biblioteca Regional de Medicina (BIREME)(2), que adotou posteriormente o nome de Centro Latino-Americano e do Caribe de Informação em Ciências da Saúde(3). É também um testemunho da transformação tecnológica do paradigma das bibliotecas físicas seculares(4), para as atuais bibliotecas digitais online. A BVS é um patrimônio da Homeopatia brasileira, evidenciando a Homeopatia perante as ciências da saúde como sendo uma especialidade médica em nosso país. Ela teve como marco inicial a base de dados HOMEOINDEX, pioneira e exclusiva da literatura homeopática, construída na década de 90, que será abordada mais adiante. Esta biblioteca virtual homeopática faz parte da rede de bibliotecas virtuais em saúde(5), e da rede BVS Brasil(6) operacionalizadas pela BIREME, órgão regional da OPAS(7) (Organização Panamericana de Saúde) e da OMS(8) (Organização Mundial de Saúde). A BIREME tem como missão contribuir para o desenvolvimento da saúde nos países da América Latina e Caribe por meio da democratização do acesso, publicação e uso de informação, conhecimento e evidência científica. A BIREME abriga atualmente mais de 60 BVSs, entre temáticas, nacionais e regionais, que abordam os mais variados aspectos de informações de cada área, com acesso online eficiente, gratuito, universal e eqüitativo à informação Para entendermos a origem da BVS Homeopatia é necessário que seja abordada também a história da BIREME(9). Desde a sua criação no ano de 1967, a BIREME sempre considerou a colaboração das bibliotecas para desenvolver e oferecer seus serviços e produtos de informação. Nos anos iniciais a primeira tarefa foi o serviço colaborativo de comutação bibliográfica (fornecimento de cópias de documentos), já considerando que apenas a coleção de revistas da então Biblioteca Regional de Medicina não seria suficientemente completa para atender a todos os pedidos dos usuários da América Latina e do Caribe. Os primeiros acordos de cooperação da BIREME com as bibliotecas foram estabelecidos no início dos anos 70, com a Faculdade de Odontologia e a Escola de Medicina Veterinária, ambas da Universidade de São Paulo, com o Instituto de Nutrição da América Central e do Panamá (INCAP), com o Centro Latino-Americano de Perinatologia e Desenvolvimento Humano, e com o Centro Pan-Americano de Engenharia Sanitária e Ciências Ambientais (CEPIS).

The Virtual Health Library (VHL) Homeopathy Brazil embodies the inclusion of Homeopathy in the official medical literature, being the result of decades of voluntary work by several homeopaths, having a history of more than 40 years, which is inseparably intertwined with the history of the Regional Library of Medicine (BIREME), which later adopted the name of the Latin American and Caribbean Center on Health Sciences Information. It is also a testament to the technological transformation from the paradigm of centuries-old physical libraries to today's online digital libraries. The VHL is a heritage of Brazilian Homeopathy, highlighting Homeopathy before the health sciences as a medical specialty in our country. Its initial milestone was the HOMEOINDEX database, a pioneer and exclusive database of homeopathic literature, built in the 1990s, which will be discussed later. This virtual homeopathic library is part of the network of virtual health libraries, and the VHL Brazil network operated by BIREME, a regional body of PAHO (Pan American Health Organization) and WHO (World Health Organization). BIREME's mission is to contribute to the health development in Latin American and Caribbean countries through the democratization of access, publication, and use of information, knowledge, and scientific evidence. BIREME currently houses more than 60 VHLs, including thematic, national, and regional, covering the most varied aspects of information in each area, with efficient, free, universal, and equitable online access to information. To understand the origin of the VHL Homeopathy, it is also necessary to address the history of BIREME. Since its creation in 1967, BIREME has always considered the collaboration of libraries to develop and offer its information services and products. In the early years, the first task was the collaborative bibliographic exchange service (provision of document copies), already considering that the journal collection of the then Regional Library of Medicine would not be sufficiently complete to meet all the requests from users in Latin America and the Caribbean. The first cooperation agreements between BIREME and libraries were established in the early 1970s, with the Faculty of Dentistry and the School of Veterinary Medicine, both from the University of São Paulo, with the Institute of Nutrition of Central America and Panama (INCAP), with the Latin American Center for Perinatology and Human Development, and with the Pan-American Center for Sanitary Engineering and Environmental Sciences (CEPIS).

Descriptores para la enseñanza y el aprendizaje del inglés con fines específicos en Medicina

Fundamento: la lengua inglesa es la más utilizada en la comunicación internacional. Las universidades médicas desarrollan procesos del inglés con fines específicos basados en el Marco Común Europeo de Referencia para las Lenguas. Objetivo: diseñar los descriptores del inglés con fines específicos de la carrera de Medicina para el perfeccionamiento de su proceso enseñanza aprendizaje. Métodos: se realizó un estudio experimental de corte pedagógico en la Facultad de Ciencias Médicas de Mayabeque, de enero 2020 a enero 2022. Se aplicaron métodos teóricos: histórico-lógico, analítico-sintético, inductivo-deductivo y modelación; empíricos: revisión documental, cuestionario, entrevista a profesores y una prueba pedagógica a estudiantes. Se utilizó el porcentaje como unidad de resumen, la técnica IADOV para criterio de usuarios y el método Delphi a especialistas. Resultados: la revisión documental mostró carencias de descriptores del inglés con fines específicos de la carrera de Medicina. Los instrumentos aplicados revelaron insuficiencias en conocimientos y utilización de elementos sugeridos en el Marco Común Europeo de Referencia para las Lenguas, que incluye los descriptores. La prueba pedagógica reveló bajo nivel de competencia comunicativa; por lo que se diseñaron descriptores para el perfeccionamiento de su proceso enseñanza aprendizaje. Conclusiones: los descriptores diseñados para el inglés con fines específicos fueron valorados por usuarios a través de la técnica IADOV, quienes mostraron alto nivel de satisfacción en su aplicación a la docencia, y fueron valorados por especialistas como pertinentes a través del método Delphi.

Background: the English language is the most used in international communication. Medical universities develop English processes for specific purposes based on the Common European Framework of Reference for Languages. Objective: to design English descriptors for specific purposes of the Medicine degree to improve its teaching-learning process. Method: an experimental pedagogical study was carried out at Mayabeque, Faculty of Medical Sciences from January 2020 to January 2022. Theoretical methods were applied: historical-logical, analytical-synthetic, inductive-deductive and modeling; empirical: documentary review, questionnaire, interview with teachers and a pre-test and post-test test with students. The percentage was used as a summary unit, the IADOV technique was used for user criteria, and the Delphi method was used for specialists. Results: the documentary review showed deficiencies in English descriptors for specific purposes of the Medicine degree. The instruments applied revealed deficiencies in knowledge and use of elements suggested in the Common European Framework of Reference for Languages, which includes the descriptors. The pre-test and post-test revealed a low level of communicative competence; Therefore, descriptors were designed to improve the teaching-learning process. Conclusions: the descriptors designed for English for specific purposes were evaluated by users through the IADOV technique, who showed a high level of satisfaction in their application to teaching, and were evaluated by specialists as relevant through the Delphi method.

Terminology focused on design and retention methods used for anterior resin-bonded fixed partial dentures in English literature: A scoping review.

Purpose: Novel terms describing several designs of resin-bonded fixed partial dentures (RBFPDs) continue to appear. Indeed, a variety of terms are used in the English scientific literature The use of a standard terminology is important for a fair and efficient understanding. This study aimed to investigate if the terminology used to describe designs and retention methods for anterior RBFPDs is standard. Methods: An electronic search in the English literature was conducted in PubMed/Medline to identify all publications reporting RBFPDs in the anterior region until August 2022. This search was completed by hand searching. Terms indicating different designs of RBFPDs were listed and then classified. Percentages of their use were calculated to determine the commonly used terms. Analysis of the use of these terms was performed based on the standards determined by the latest edition of the Glossary of Prosthodontic Terms (GPT). The impacts of the MeSH Thesaurus and GPT on the nomenclature used for RBFPDs was assessed. Results: A total of 125 articles were eligible for this review. In the retained articles, 86 terms were found. Among them, thirty-nine terms were classified into three groups. Only six terms were defined in the latest edition of GPT (GPT-9). Several classified terms that are commonly used were not identified in the GPT-9. Conversely to the GPT-9 which impact was insignificant, the MeSH Thesaurus had an important impact on the nomenclature used for RBFPDs. Conclusion: The terminology used to describe designs and retention methods for anterior RBFPDs was non-standard. The GPT-9, constituting an important reference, defined a limited number of terms related to RBFPDs and had no significant impact on the standardization of the terminology used for RBFPDs. Efforts should therefore be continued to standardize the terminology. A specialized mini-glossary grouping and defining all the terms found in this study will helpful in clarifying the terminology used for the anterior RBFPDs.

Development and validation of search filters to retrieve medication discontinuation articles in Medline and Embase.

BACKGROUND: Medication discontinuation studies explore the outcomes of stopping a medication compared to continuing it. Comprehensively identifying medication discontinuation articles in bibliographic databases remains challenging due to variability in terminology. OBJECTIVES: To develop and validate search filters to retrieve medication discontinuation articles in Medline and Embase. METHODS: We identified medication discontinuation articles in a convenience sample of systematic reviews. We used primary articles to create two reference sets for Medline and Embase, respectively. The reference sets were equally divided by randomization in development sets and validation sets. Terms relevant for discontinuation were identified by term frequency analysis in development sets and combined to develop two search filters that maximized relative recalls. The filters were validated against validation sets. Relative recalls were calculated with their 95% confidences intervals (95% CI). RESULTS: We included 316 articles for Medline and 407 articles for Embase, from 15 systematic reviews. The Medline optimized search filter combined 7 terms. The Embase optimized search filter combined 8 terms. The relative recalls were respectively 92% (95% CI: 87-96) and 91% (95% CI: 86-94). CONCLUSIONS: We developed two search filters for retrieving medication discontinuation articles in Medline and Embase. Further research is needed to estimate precision and specificity of the filters.

Producción científica europea sobre los cuidados de salud a domicilio indizada en la base de datos bibliográfica Scopus / European scientific production on home health care indexed in the Scopus bibliographic database

Objetivo: Analizar, mediante técnicas bibliomé-tricas, la producción científica europea sobre cuidados de salud a domicilio (HaD) indizada en la base de datos bibliográfica Scopus.Método: Estudio descriptivo transversal. Los datos se obtuvieron de la base de datos Sco-pus, interrogando con el término “Home Care”los campos de registro de título, resumen y pa-labras clave; fecha final de búsqueda septiem-bre 2023.Resultados: Se obtuvo un total de 90830 refe-rencias a nivel mundial, teniendo 27251 (30,0%) de ellas filiación europea. La relación anual del número de publicaciones mostró un modelo de regresión lineal directo (R2 = 0,6; p < 0,001). La tipología documental más frecuente fue el artículo original con 20225 (74,2%) referencias, siendo el índice de productividad de 4,3. El se-miperiodo de Burton-Kebler fue de 53,5 años, con máximo de 110 y mínimo de 0 años, con índice de Price (IP) del 4,6%. Se identificaron trabajos publicados en 32 distintos idiomas, siendo el inglés la lengua predominante en las publicaciones sobre HaD con 22391 (82,2%) trabajos.Conclusiones: Se observó un incremento progresivo, no exponencial, de la producción científica sobre HaD, siendo el artículo original la tipología documental principal, si bien la ob-solescencia mostró resultados superiores a lo esperado. Existió predominio del idioma inglés y de la filiación anglosajona. La temática publi-cada estuvo en consonancia con el área de las ciencias de la salud y el campo de HaD. (AU)

Objective: To analize by means of bibliometric technics the European scientific production on home health care (HaD) indexed in Scopus bib-liographical database.Method: Cross-sectional descriptive study. Data were obtained from Scopus database. The term “Home Care” was used to interrogate the fields of title, abstract and keywords. Search fi-nal date September 2023.Results: A total of 90830 references were ob-tained worldwide. 27251 (30%) of the referenc-es had European affiliation. The annual relation of the number of publications showed a direct linear regression model (R2 = 0,6; p < 0,001). The original article was the most frequent docu-mentary typology founded with 20225 (74.2%) references. The productivity index was 4.3 and the Burton-Kebler index was 53.5 years with a máximum of 110 and a mínimum of 0 years. The Price index was 4.6%. Articles published in 32 different languages were identified being Eng-lish the predominant language in publications on HaD with 22391 (82.2%) works.Conclusions: A progressive, non-exponential increase in scientific production on HaD was observed with the original article being the main documentary typology, although obsolescence showed results higher than expected. There was a predominance of the English language and Anglo-Saxon affiliation. Topics were in line with the area of health sciences and the field of HaD. (AU)

Magnitude of undernutrition and its association with dietary diversity among older persons in Ethiopia: a systematic review and meta-analysis, 2023.

Undernutrition in elders remains under-detected, under-treated, and under-resourced and leads to further weight loss, increased infections, and delay in recovery from illness as well as increased hospital admissions and length of stay. The reports of the findings were fragmented and inconsistent in Ethiopia. Therefore, the main objective of this meta-analysis was to estimate the pooled prevalence of undernutrition and its association with dietary diversity among older persons in Ethiopia. Online databases (Medline, PubMed, Scopus, and Science Direct), Google, Google Scholar, and other grey literature were used to search articles until the date of publication. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline was followed. The random effect model was used to estimate the pooled prevalence; whereas subgroup analysis and meta-regression were performed to identify the probable source of heterogeneity using Stata version 14.0 software. Out of 522 studies accessed, 14 met our criteria and were included in the study. A total of 7218 older people (aged above 60 years old) were included in the study. The pooled proportion of undernutrition among older persons in Ethiopia was 20⋅6 % (95 % CI 17⋅3, 23⋅8). Elders who consumed low dietary diversity scores were strongly associated with undernutrition among older persons. Therefore, promoting appropriate intervention strategies for elders to improve dietary diversity practices and nutritional status is crucial.

Large-scale investigation of weakly-supervised deep learning for the fine-grained semantic indexing of biomedical literature.

OBJECTIVE: Semantic indexing of biomedical literature is usually done at the level of MeSH descriptors with several related but distinct biomedical concepts often grouped together and treated as a single topic. This study proposes a new method for the automated refinement of subject annotations at the level of MeSH concepts. METHODS: Lacking labelled data, we rely on weak supervision based on concept occurrence in the abstract of an article, which is also enhanced by dictionary-based heuristics. In addition, we investigate deep learning approaches, making design choices to tackle the particular challenges of this task. The new method is evaluated on a large-scale retrospective scenario, based on concepts that have been promoted to descriptors. RESULTS: In our experiments concept occurrence was the strongest heuristic achieving a macro-F1 score of about 0.63 across several labels. The proposed method improved it further by more than 4pp. CONCLUSION: The results suggest that concept occurrence is a strong heuristic for refining the coarse-grained labels at the level of MeSH concepts and the proposed method improves it further.

Sleep disturbance and fatigue in multiple sclerosis: A systematic review and meta-analysis.

Sleep disturbance is common in people with multiple sclerosis and may worsen fatigue; however, the assessment of sleep-fatigue relationships varies across studies. To better understand sleep-fatigue relationships in this population, we conducted a systematic review and random effects meta-analyses for the associations between fatigue and 10 sleep variables: Sleep-disordered breathing, daytime sleepiness, sleep quality, insomnia, restless legs, number of awakenings, sleep efficiency, sleep latency, sleep duration, and wake after sleep onset. Of the 1062 studies screened, 46 met inclusion criteria and provided sufficient data for calculating Hedges' g. Study quality was assessed using the Newcastle-Ottawa Scale. Sample characteristics did not differ between the 10 analyses. Results indicated that sleep quality and insomnia (assessed via self-report or diagnostic criteria) were strongly associated with fatigue (all gs ≥ 0.80 and all ps < .001). In contrast, the number of awakenings and sleep duration (assessed objectively) were not significantly associated with fatigue. Remaining sleep variables yielded moderate, significant effects. Most effects did not vary based on study quality or sample demographics. Results highlight that insomnia and perceptions of poor sleep have a stronger link than objective sleep duration to fatigue in multiple sclerosis and may represent a more effective target for intervention.

Writing strategies for improving the access of medical literature.

When conducting a literature review, medical authors typically search for relevant keywords in bibliographic databases or on search engines like Google. After selecting the most pertinent article based on the title's relevance and the abstract's content, they download or purchase the article and cite it in their manuscript. Three major elements influence whether an article will be cited in future manuscripts: the keywords, the title, and the abstract. This indicates that these elements are the "key dissemination tools" for research papers. If these three elements are not determined judiciously by authors, it may adversely affect the manuscript's retrievability, readability, and citation index, which can negatively impact both the author and the journal. In this article, we share our informed perspective on writing strategies to enhance the searchability and citation of medical articles. These strategies are adopted from the principles of search engine optimization, but they do not aim to cheat or manipulate the search engine. Instead, they adopt a reader-centric content writing methodology that targets well-researched keywords to the readers who are searching for them. Reputable journals, such as Nature and the British Medical Journal, emphasize "online searchability" in their author guidelines. We hope that this article will encourage medical authors to approach manuscript drafting from the perspective of "looking inside-out." In other words, they should not only draft manuscripts around what they want to convey to fellow researchers but also integrate what the readers want to discover. It is a call-to-action to better understand and engage search engine algorithms, so they yield information in a desired and self-learning manner because the "Cloud" is the new stakeholder.

WeakMeSH: Leveraging provenance information for weakly supervised classification of biomedical articles with emerging MeSH descriptors.

Medical Subject Headings (MeSH) is a hierarchically structured thesaurus created by the National Library of Medicine of USA. Each year the vocabulary gets revised, bringing forth different types of changes. Those of particular interest are the ones that introduce new descriptors in the vocabulary either brand new or those who come up as a product of a complex change. These new descriptors often lack ground truth articles and rendering learning models that require supervision not applicable. Furthermore, this problem is characterized by its multi label nature and the fine-grained character of the descriptors that play the role of classes, requiring expert supervision and a lot of human resources. In this work, we alleviate these issues through retrieving insights from provenance information about those descriptors present in MeSH to create a weakly labeled train set for them. At the same time, we make use of a similarity mechanism to further filter the weak labels obtained through the descriptor information mentioned earlier. Our method, called WeakMeSH, was applied on a large-scale subset of the BioASQ 2018 data set consisting of 900 thousand biomedical articles. The performance of our method was evaluated on BioASQ 2020 against several other approaches that had given competitive results in similar problems in the past, or apply alternative transformations against the proposed one, as well as some variants that showcase the importance of each different component of our proposed approach. Finally, an analysis was performed on the different MeSH descriptors each year to assess the applicability of our method on the thesaurus.

Principales tecnologías de indización en las ciencias de la salud que se emplean en Occidente / Main indexing healthcare technologies used in West

En la actualidad, las tecnologías de indización en las ciencias de la salud están aportando mu-chos beneficios para el ámbito biomédico y la estandarización de su correspondiente termino-logía, puesto que esta cuestión es fundamental para lograr un diagnóstico médico más preciso e inequívoco Por esta razón, en este artículo se ha explicado con detalle cómo funcionan estas tecnologías: Terminología Anatómica In-ternacional (TAI), Medical Subject Headings y el Systematized Nomenclature of Medicine Cli-nical terminology (SNOMED CT), así como, las razones de la importancia de su uso para los sanitarios y los terminólogos.(AU)

Nowadays, healthcare indexing technologies are profiting the biomedical field and the stand-ardization of its corresponding terminology, since this is essential to achieve a more pre-cise and unequivocal medical diagnosis. Thus, in this article it has been performed a thorough explanation on how these healthcare technolo-gies work: International Anatomical Terminology (TAI), Medical Subject Headings and the Sys-tematised Nomenclature of Medicine Clinical terminology (SNOMED CT), as well as it was elucidated the reasons of its use for healthcare professionals and terminologists.(AU)

A Digital Health Initiative (COVIDsmart) for Remote Data Collection and Study of COVID-19's Impact on the State of Virginia: Prospective Cohort Study.

BACKGROUND: The COVID-19 pandemic has affected people's lives beyond severe and long-term physical health symptoms. Social distancing and quarantine have led to adverse mental health outcomes. COVID-19-induced economic setbacks have also likely exacerbated the psychological distress affecting broader aspects of physical and mental well-being. Remote digital health studies can provide information about the pandemic's socioeconomic, mental, and physical impact. COVIDsmart was a collaborative effort to deploy a complex digital health research study to understand the impact of the pandemic on diverse populations. We describe how digital tools were used to capture the effects of the pandemic on the overall well-being of diverse communities across large geographical areas within the state of Virginia. OBJECTIVE: The aim is to describe the digital recruitment strategies and data collection tools applied in the COVIDsmart study and share the preliminary study results. METHODS: COVIDsmart conducted digital recruitment, e-Consent, and survey collection through a Health Insurance Portability and Accountability Act-compliant digital health platform. This is an alternative to the traditional in-person recruitment and onboarding method used for studies. Participants in Virginia were actively recruited over 3 months using widespread digital marketing strategies. Six months of data were collected remotely on participant demographics, COVID-19 clinical parameters, health perceptions, mental and physical health, resilience, vaccination status, education or work functioning, social or family functioning, and economic impact. Data were collected using validated questionnaires or surveys, completed in a cyclical fashion and reviewed by an expert panel. To retain a high level of engagement throughout the study, participants were incentivized to stay enrolled and complete more surveys to further their chances of receiving a monthly gift card and one of multiple grand prizes. RESULTS: Virtual recruitment demonstrated relatively high rates of interest in Virginia (N=3737), and 782 (21.1%) consented to participate in the study. The most successful recruitment technique was the effective use of newsletters or emails (n=326, 41.7%). The primary reason for contributing as a study participant was advancing research (n=625, 79.9%), followed by the need to give back to their community (n=507, 64.8%). Incentives were only reported as a reason among 21% (n=164) of the consented participants. Overall, the primary reason for contributing as a study participant was attributed to altruism at 88.6% (n=693). CONCLUSIONS: The COVID-19 pandemic has accelerated the need for digital transformation in research. COVIDsmart is a statewide prospective cohort to study the impact of COVID-19 on Virginians' social, physical, and mental health. The study design, project management, and collaborative efforts led to the development of effective digital recruitment, enrollment, and data collection strategies to evaluate the pandemic's effects on a large, diverse population. These findings may inform effective recruitment techniques across diverse communities and participants' interest in remote digital health studies.

Updated generic search filters for finding studies of adverse drug effects in Ovid medline and Embase may retrieve up to 90% of relevant studies.

BACKGROUND: The most current objectively derived search filters for adverse drug effects are 15 years old and other strategies have not been developed and tested empirically. OBJECTIVE: To develop and validate search filters to retrieve evidence on adverse drug effects from Ovid medline and Ovid Embase. METHODS: We identified systematic reviews of adverse drug effects in Epistemonikos. From these reviews, we collated their included studies which we then randomly divided into three tests and one validation set of records. We constructed a search strategy to maximise relative recall using word frequency analysis with test set one. This search strategy was then refined using test sets two and three and validated on the final set of records. RESULTS: Of 107 systematic reviews which met our inclusion criteria, 1948 unique included studies were available from medline and 1980 from Embase. Generic adverse drug effects searches in medline and Embase achieved 90% and 89% relative recall, respectively. When specific adverse effects terms were added recall was improved. CONCLUSION: We have derived and validated search filters that retrieve around 90% of records with adverse drug effects data in medline and Embase. The addition of specific adverse effects terms is required to achieve higher recall.