Topic Modeling mediante Machine Learning no supervisado de artículos científicos sobre Salud Laboral y Servicios de Atención de Salud a Domicilio

Objective: To identify in an unsupervised manner through topic modeling the topics of greatest interest in the field of Occupational Health and Home Care Services from the scientific articles published on the subject. Method: The study used the unsupervised Machine Learning algorithm Dirichlet Latent Assignment for topic modeling and the NRC lexicon to carry out the sentiment analysis of the corpus of document files obtained from MEDLINE (via PubMed) using the descriptors “Occupational Health” and “Home Care Services”. Results: Of the total of 70 documentary files analyzed, it was obtained that the intensity of the emotions in the texts was low (ranging in values from 5 to 10), with positive feelings having a greater representation compared to negative ones in a ratio of 60/ 40. There was no variation in the proportions of emotions with respect to the study period. The four topics of greatest interest were identified in the articles analyzed: home care and caregiver satisfaction, breastfeeding period, rehabilitation programs, and physical activity to mitigate pain. Conclusions: It has been confirmed that natural language processing methodologies can be a great support tool for the analysis of scientific articles. Specifically, it has been possible to determine in a clear and unsupervised manner the topics of greatest interest in the field of Occupational Health and Home Care Services.Objetivo: Identificar de manera no supervisada mediante topic modeling los temas de mayor interés en el campo de la Salud Laboral y los Servicios de Atención a Domicilio de los artículos científicos publicados en la materia. Método: Este estudio empleó el algoritmo de Machine Learning no supervisado Asignación Latente de Dirichlet para el topic modeling y el lexicón NRC para la realización del análisis de sentimientos del corpus de las fichas documentales obtenidas de MEDLINE (vía PubMed) usando los descriptores “Salud Laboral” y “Servicios de Atención de Salud a Domicilio”. Resultados: Del total de 70 fichas documentales analizadas, se obtuvo que la intensidad de las emociones en los textos era baja (oscilando en valores de 5 a 10), teniendo una mayor representación los sentimientos positivos frente a los negativos en una relación de 60/40. No hubo una variación de las proporciones de las emociones con respecto al período del estudio. Se identificaron los cuatro temas de mayor interés en los artículos analizados: cuidado domiciliario y satisfacción de los cuidadores, período de lactancia, programas de rehabilitación, y actividad física para mitigación del dolor. Conclusiones: Se ha podido constatar que las metodologías del procesado de lenguaje natural pueden ser una gran herramienta de apoyo al análisis de artículos científicos. Concretamente, se ha logrado determinar de manera clara y no supervisada los temas de mayor interés en el campo de la Salud Laboral y la Atención de Salud a Domicilio

Use of Google Trends as an infodemiological tool in the field of Occupational Health

EditorialN

Occupational Health Applied Infodemiological Studies of Nutritional Diseases and Disorders: Scoping Review with Meta-Analysis

Objective: to identify and review existing infodemiological studies on nutritional disorders applied to occupational health and to analyse the effect of the intervention on body mass index (BMI) or alternatively body weight (BW). Methods: This study involved a critical analysis of articles retrieved from MEDLINE (via PubMed), Embase, Cochrane Library, PsycINFO, Scopus, Web of Science, Latin American, and Caribbean Health Sciences Literature (LILACS) and Medicina en Español (MEDES) using the descriptors "Nutrition Disorders, "Occupational Health" and "Infodemiology", applying the filters "Humans" and "Adult: 19+ years". The search was conducted on 29 May 2021. Results: a total of 357 references were identified from the bibliographic database searches; after applying the inclusion and exclusion criteria, a total of 11 valid studies were obtained for the review. Interventions could be categorised into (1) interventions related to lifestyle, physical activity, and dietary changes through education programmes, (2) interventions associated with lifestyle, physical activity, and dietary changes through the use of telemonitoring systems or self-help applications, (3) interventions tied to lifestyle, physical activity, and dietary changes through control and/or social network support groups, and (4) interventions linked to changes in the work environment, including behavioural change training and work environment training tasks. The meta-analysis demonstrated that the heterogeneity present when analysing the results for BMI was 72% (p < 0.01), which decreased to 0% (p = 0.57) when analysing the outcomes for weight, in which case the null hypothesis of homogeneity could be accepted. In all instances, the final summary of the effect was on the decreasing side for both BMI and BW. Conclusions: Despite the high heterogeneity of the results reported, the trend shown in all cases indicates that the intervention methodologies implemented by empowering individuals through Web 2.0 technologies are positive in terms of the problem of overweight. Further implementation of novel strategies to support individuals is needed to overcome obesity, and, at least in the early studies, these strategies seem to be making the necessary change.S

Trends and Seasonality of Information Searches Carried Out through Google on Nutrition and Healthy Diet in Relation to Occupational Health: Infodemiological Study

This study aimed to analyze and relate the population interest through information search trends on Nutrition and Healthy Diet (HD) with the Occupational Health (OH). Ecological and correlational study of the Relative Search Volume (RSV) obtained from Google Trends query, segmented in two searched periods concerning antiquity; date of query: 20 April 2021. The RSV trends for the analyzed three Topics were: Nutrition (R2 = 0.02), HD (R2 = 0.07) and OH (R2 = -0.72). There was a good positive correlation between Nutrition and OH (R = 0.56, p 0.05). There was only a significant relationship between the RSV Topic HD (p < 0.05) for the Developing and Least Developed countries. The data on the analyzed RSV demonstrated diminishing interest in the search information on HD and OH as well as a clearly positive trend change in recent years for Nutrition. A good positive correlation was observed between the RSV of nutrition and OH whereas the correlation between HD and OH was moderate. There were no milestones found that may report a punctual event leading to the improvement of information searches. Temporal dependence was corroborated in the RSV on Nutrition, but not in the other two Topics. Strangely, only an association was found on HD searches between the Developing and Least Developed Countries. The study of information search trends may provide useful information on the population's interest in the disease data, as well as would gradually allow the analysis of differences in popularity, or interest even between different countries. Thus, this information might be used as a guide for public health approaches regarding nutrition and a healthy diet at work.S

Tendencias y estacionalidad de las búsquedas de información, realizadas a través de Google, sobre síndrome metabólico y salud laboral: estudio infodemiológico

Acknowledgements: In to Habiba Chbab, master’s degree in English and Spanish for Specific Purposes and doctoral student in Professional and Audiovisual Translation (Research branch: medical translation), for her inestimable collaboration in the translation of this document.Objective: This study aimed to analyse and relate the population interest through information search trends, on Metabolic Syndrome (MS) with the Occupational Health (OH). Method: Ecological and correlational study of the Relative Search Volume (RSV) obtained from Google Trends query, segmented into 3 searched periods concerning antiquity; date of query: September 30, 2023. Results: The lowest mean of the RSV was for the MS Topic (2.23 ± 0.87), albeit there was a positive correlation in the RSV amid MS and OH (R = 0.56; p 0.05), and significant differences were demonstrated in the information search between developed and undeveloped countries (p > 0.05). Conclusions: Through their information searches, the whole population showed to have a dearth of knowledge of MS than of its component diseases. A relationship was found between the information searches carried out on MS and OH. The study of information search trends may provide useful information on the population’s interest in the disease data, as well as would gradually allow the analysis of differences in popularity, or interest even between different countries.Objetivo: Este estudio tuvo como objetivo analizar y relacionar el interés de la población, a través de tendencias de búsqueda de información, sobre el Síndrome Metabólico (MS) con la Salud Laboral (OH). Método: Estudio ecológico y correlacional del Volumen Relativo de Búsqueda (RSV) obtenido de la consulta de Google Trends, segmentado en 3 períodos buscados relacionados con la antigüedad; fecha de consulta: 30 de septiembre de 2023. Resultados: La media más baja del RSV fue para el tema MS (2,23 ± 0,87), aunque hubo una correlación positiva en el RSV entre MS y OH (R = 0,56; p 0,05), y se demostraron diferencias significativas en la búsqueda de información entre países desarrollados y no desarrollados (p > 0,05). Conclusiones: A través de sus búsquedas de información, toda la población demostró tener un menor conocimiento sobre la MS que sobre las enfermedades que la componen. Se encontró relación entre las búsquedas de información realizadas sobre MS y OH. El estudio de las tendencias de búsqueda de información puede proporcionar información útil sobre el interés de la población por los datos de enfermedades, así como permitiría gradualmente analizar diferencias en popularidad, o interés incluso entre distintos países

Indización y uso de los Descriptores MeSH en Hospitalización a Domicilio

Objective: To perform an indexing study with MeSH descriptors on Home Hospitalization.Method: Cross-sectional descriptive study with records from MEDLINE database (PubMed to current date (2016)). The term used as the main descriptor for the search was «Home Care Services, Hospital-Based»The sampling method was simple randomization without replacement, based on the total number of references obtained.Result: The resulting sample size was 386 references. Significant differences were observed in the use of descriptors associated with home hospitalization. The comparison between descriptors gives a p &lt;0.004 and a likelihood ratio of 727.52 with 460 degrees of freedom.Discussion: The descriptors used are appropriate to the subject studied, Hospital at Home. An increase in the incidence of neoplasms generates the appearance of “Neoplasms” as the second most indexed descriptor and the rise of computer science and technology makes “Telemedicine” appears as the third descriptor, with “Home Care Services, Hospital-Based» the first, since it is the one used to perform the search.Objetivo: Analizar la utilización de los Descriptores, como Major Topic, en la indización de los artículos sobre Hospitalización Domiciliaria en la base de datos MEDLINE.Método: Estudio descriptivo transversal de los registros de indización recogidos en la base de datos MEDLINE (vía PubMed) hasta 2016. El término utilizado, como descriptor principal para la búsqueda fue «Home Care Services, Hospital-Based».El método de muestreo fue la aleatorización simple sin reemplazo, tomando como base el número total de referencias obtenidas (tamaño muestral 386).Resultados: Se observaron diferencias significativas en la utilización de los Descriptores asociados a hospitalización a domicilio. La comparativa entre descriptores dio una p&lt;0,004 y una razón de verosimilitudes de 727,52 con 460 grados de libertad.Conclusiones: Los descriptores utilizados son adecuados a la temática estudiada, Hospital a Domicilio. Lógicamente, «Home Care Services, Hospital-Based» es el Descriptor con mayor frecuencia de uso, ya que es el utilizado para realizar la búsqueda. El aumento en el diagnóstico de las neoplasias genera la aparición de «Neoplasms» como el segundo descriptor más usado y el auge de la informática y la tecnología hace que «Telemedicine» aparezca como tercer descriptor

Perception of risk of exposure in the management of hazardous drugs in home hospitalization and hospital units.

To assess the perception of risk of exposure in the management of hazardous drugs (HDs) through home hospitalization and hospital units. A questionnaire was released, at the national level, to health professionals with HD management expertise. Questionnaire included 21 questions that were scored using a Likert scale: 0 (null probability) to 4 (very high probability). The internal consistency and reliability of the questionnaire were calculated using Cronbach's alpha and the intraclass correlation coefficient, respectively. 144 questionnaires (response rate 70.2%) were obtained: 65 (45.1%) were nurses, 42 (28.9%) occupational physicians, and 37 (26.1%) were pharmacists. Cronbach's alpha was 0.93, and intraclass correlation coefficient was 0.94 (95% CI 0.91-0.97; p-value < 0.001). The mean probability was 1.95 ± 1.02 (median 1.9; minimum: 0.05; 1st quartile 1.1; 3rd quartile 2.6; and maximum 4). Differences were observed in scoring among professional groups (occupational physicians versus nurses (1.6/2.1, p = 0.044); pharmacists versus nurses (1.7/2.1, p = 0.05); and occupational physicians versus pharmacists (1.6/1.7, p = 0.785), due mainly to the administration stage (p = 0.015). The perception of risk of exposure was moderate, being higher for nurses. It would be advisable to integrate HDs into a standardized management system (risk management model applicable to any healthcare center) to improve the safety of health professionals.The research leading to these results received funding from Carlos III Health Institute (Instituto de Salud Carlos III) of Madrid, Spain, through Health Research Project (Proyecto de Investigación en Salud), reference PI16/00788.S

Germline Predisposition to Pediatric Cancer, from Next Generation Sequencing to Medical Care

Knowledge about genetic predisposition to pediatric cancer is constantly expanding. The categorization and clinical management of the best-known syndromes has been refined over the years. Meanwhile, new genes for pediatric cancer susceptibility are discovered every year. Our current work shares the results of genetically studying the germline of 170 pediatric patients diagnosed with cancer. Patients were prospectively recruited and studied using a custom panel, OncoNano V2. The well-categorized predisposing syndromes incidence was 9.4%. Likely pathogenic variants for predisposition to the patient's tumor were identified in an additional 5.9% of cases. Additionally, a high number of pathogenic variants associated with recessive diseases was detected, which required family genetic counseling as well. The clinical utility of the Jongmans MC tool was evaluated, showing a high sensitivity for detecting the best-known predisposing syndromes. Our study confirms that the Jongmans MC tool is appropriate for a rapid assessment of patients; however, the updated version of Ripperger T criteria would be more accurate. Meaningfully, based on our findings, up to 9.4% of patients would present genetic alterations predisposing to cancer. Notably, up to 20% of all patients carry germline pathogenic or likely pathogenic variants in genes related to cancer and, thereby, they also require expert genetic counseling. The most important consideration is that the detection rate of genetic causality outside Jongmans MC et al. criteria was very low

Identification of high-risk patients for referral through machine learning assisting the decision making to manage minor ailments in community pharmacies

Background: Data analysis techniques such as machine learning have been used for assisting in triage and the diagnosis of health problems. Nevertheless, it has not been used yet to assist community pharmacists with services such as the Minor Ailment Services These services have been implemented to reduce the burden of primary care consultations in general medical practitioners (GPs) and to allow a better utilization of community pharmacists’ skills. However, there is a need to refer high-risk patients to GPs.Aim: To develop a predictive model for high-risk patients that need referral assisting community pharmacists’ triage through a minor ailment service.Method: An ongoing pragmatic type 3 effectiveness-implementation hybrid study was undertaken at a national level in Spanish community pharmacies since October 2020. Pharmacists recruited patients presenting with minor ailments and followed them 10 days after the consultation. The main outcome measured was appropriate medical referral (in accordance with previously co-designed protocols). Nine machine learning models were tested (three statistical, three black box and three tree models) to assist pharmacists in the detection of high-risk individuals in need of referral.Results: Over 14′000 patients were included in the study. Most patients were female (68.1%). With no previous treatment for the specific minor ailment (68.0%) presented. A percentage of patients had referral criteria (13.8%) however, not all of these patients were referred by the pharmacist to the GP (8.5%). The pharmacists were using their clinical expertise not to refer these patients. The primary prediction model was the radial support vector machine (RSVM) with an accuracy of 0.934 (CI95 = [0.926,0.942]), Cohen’s kappa of 0.630, recall equal to 0.975 and an area under the curve of 0.897. Twenty variables (out of 61 evaluated) were included in the model. radial support vector machine could predict 95.2% of the true negatives and 74.8% of the true positives. When evaluating the performance for the 25 patient’s profiles most frequent in the study, the model was considered appropriate for 56% of them.Conclusion: A RSVM model was obtained to assist in the differentiation of patients that can be managed in community pharmacy from those who are at risk and should be evaluated by GPs. This tool potentially increases patients’ safety by increasing pharmacists’ ability to differentiate minor ailments from other medical conditions

Serological response and breakthrough infection after COVID-19 vaccination in patients with cirrhosis and post-liver transplant

BACKGROUND: Vaccine hesitancy and lack of access remain major issues in disseminating COVID-19 vaccination to liver patients globally. Factors predicting poor response to vaccination and risk of breakthrough infection are important data to target booster vaccine programs. The primary aim of the current study was to measure humoral responses to 2 doses of COVID-19 vaccine. Secondary aims included the determination of factors predicting breakthrough infection. METHODS: COVID-19 vaccination and Biomarkers in cirrhosis And post-Liver Transplantation is a prospective, multicenter, observational case-control study. Participants were recruited at 4-10 weeks following first and second vaccine doses in cirrhosis [n = 325; 94% messenger RNA (mRNA) and 6% viral vaccine], autoimmune liver disease (AILD) (n = 120; 77% mRNA and 23% viral vaccine), post-liver transplant (LT) (n = 146; 96% mRNA and 3% viral vaccine), and healthy controls (n = 51; 72% mRNA, 24% viral and 4% heterologous combination). Serological end points were measured, and data regarding breakthrough SARS-CoV-2 infection were collected. RESULTS: After adjusting by age, sex, and time of sample collection, anti-Spike IgG levels were the lowest in post-LT patients compared to cirrhosis (p < 0.0001), AILD (p < 0.0001), and control (p = 0.002). Factors predicting reduced responses included older age, Child-Turcotte-Pugh B/C, and elevated IL-6 in cirrhosis; non-mRNA vaccine in AILD; and coronary artery disease, use of mycophenolate and dysregulated B-call activating factor, and lymphotoxin-α levels in LT. Incident infection occurred in 6.6%, 10.6%, 7.4%, and 15.6% of cirrhosis, AILD, post-LT, and control, respectively. The only independent factor predicting infection in cirrhosis was low albumin level. CONCLUSIONS: LT patients present the lowest response to the SARS-CoV-2 vaccine. In cirrhosis, the reduced response is associated with older age, stage of liver disease and systemic inflammation, and breakthrough infection with low albumin level