Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews.

BACKGROUND: Artificial intelligence is fueling a new revolution in medicine and in the healthcare sector. Despite the growing evidence on the benefits of artificial intelligence there are several aspects that limit the measure of its impact in people's health. It is necessary to assess the current status on the application of AI towards the improvement of people's health in the domains defined by WHO's Thirteenth General Programme of Work (GPW13) and the European Programme of Work (EPW), to inform about trends, gaps, opportunities, and challenges. OBJECTIVE: To perform a systematic overview of systematic reviews on the application of artificial intelligence in the people's health domains as defined in the GPW13 and provide a comprehensive and updated map on the application specialties of artificial intelligence in terms of methodologies, algorithms, data sources, outcomes, predictors, performance, and methodological quality. METHODS: A systematic search in MEDLINE, EMBASE, Cochrane and IEEEXplore was conducted between January 2015 and June 2021 to collect systematic reviews using a combination of keywords related to the domains of universal health coverage, health emergencies protection, and better health and wellbeing as defined by the WHO's PGW13 and EPW. Eligibility criteria was based on methodological quality and the inclusion of practical implementation of artificial intelligence. Records were classified and labeled using ICD-11 categories into the domains of the GPW13. Descriptors related to the area of implementation, type of modeling, data entities, outcomes and implementation on care delivery were extracted using a structured form and methodological aspects of the included reviews studies was assessed using the AMSTAR checklist. RESULTS: The search strategy resulted in the screening of 815 systematic reviews from which 203 were assessed for eligibility and 129 were included in the review. The most predominant domain for artificial intelligence applications was Universal Health Coverage (N = 98) followed by Health Emergencies (N = 16) and Better Health and Wellbeing (N = 15). Neoplasms area on Universal Health Coverage was the disease area featuring most of the applications (21.7 %, N = 28). The reviews featured analytics primarily over both public and private data sources (67.44 %, N = 87). The most used type of data was medical imaging (31.8 %, N = 41) and predictors based on regions of interest and clinical data. The most prominent subdomain of Artificial Intelligence was Machine Learning (43.4 %, N = 56), in which Support Vector Machine method was predominant (20.9 %, N = 27). Regarding the purpose, the application of Artificial Intelligence I is focused on the prediction of the diseases (36.4 %, N = 47). With respect to the validation, more than a half of the reviews (54.3 %, N = 70) did not report a validation procedure and, whenever available, the main performance indicator was the accuracy (28.7 %, N = 37). According to the methodological quality assessment, a third of the reviews (34.9 %, N = 45) implemented methods for analysis the risk of bias and the overall AMSTAR score below was 5 (4.01 ± 1.93) on all the included systematic reviews. CONCLUSION: Artificial intelligence is being used for disease modelling, diagnose, classification and prediction in the three domains of GPW13. However, the evidence is often limited to laboratory and the level of adoption is largely unbalanced between ICD-11 categoriesand diseases. Data availability is a determinant factor on the developmental stage of artificial intelligence applications. Most of the reviewed studies show a poor methodological quality and are at high risk of bias, which limits the reproducibility of the results and the reliability of translating these applications to real clinical scenarios. The analyzed papers show results only in laboratory and testing scenarios and not in clinical trials nor case studies, limiting the supporting evidence to transfer artificial intelligence to actual care delivery.

Nursing students faced with organ donation: Multicenter stratified national study.

AIM: To analyze the attitude of university nursing students at Spanish universities toward organ donation and transplantation and the factors affecting to their attitude. BACKGROUND: The opinion of future nurses toward organ transplant donation could have an important influence on the population. Knowing that opinion and what factors influence it is important to improve the attitude towards organ donation and transplantation. DESIGN: A multicenter, sociological, interdisciplinary and observational study including university nursing diploma students in a complete academic year. METHODS: Selected and randomized sample was taken of students from 52 of the 111 faculties and nursing schools and faculties in Spain with teaching activity PARTICIPANTS: A sample of 10,566 students was selected stratified by geographical area and year. MEASUREMENT INSTRUMENT: The instrument used was a validated questionnaire of attitude toward organ donation and transplantation, self-administered and completed anonymously. RESULTS: Completion rate: 85 % (n = 9001). Of the students surveyed, 78 % (n = 7040) would donate their organs after dying. Variables related to a favourable attitude: (1) Interest in listening to a talk about organ donation and transplantation [Odds ratio 1.66, 95 % confidence interval 2.05-1.35]; (2) Family discussion [Odds ratio 2.30, 95 % confidence interval 2.79-1.90] or discussion with friends about organ donation and transplantation [Odds ratio 1.56, 95 % confidence interval 1.86-1.31]; (3) Knowing that one's father [Odds ratio 1.54, 95 % confidence interval 1.94-1.22], mother's [Odds ratio 1.44, 95 % confidence interval 1.82-1.13] or partner [Odds ratio 1.28, 95 % confidence interval 1.60-1.03] has a favourable opinion; (4) Having a good self-assessment of information about organ donation and transplantation [Odds ratio 2.94, 95 % confidence interval 4.90-1.78]; (5) Not being worried about possible mutilation of the body after donation [Odds ratio 2.73, 95 % confidence interval 3.36-1.72]. CONCLUSIONS: Nursing students in Spain tend to have a favourable attitude toward organ donation and transplantation although more than 20 % of those surveyed are not in favour. TWEETABLE ABSTRACT: To maintain a high rate of organ donation for organ transplantation, it is necessary to improve the social awareness of future generations of nurses towards organ donation.

Nursing Students' Knowledge About Organ Donation and Transplantation: A Spanish Multicenter Study.

Health care professionals and the information that they provide to the public on organ donation and transplantation (ODT) influence attitudes toward this option. OBJECTIVE: The objective was to analyze the knowledge of university nursing students at Spanish universities toward ODT and the factors affecting it. METHODS AND DESIGN: The methods and design included a multicenter, sociologic, and observational study including university nursing diploma students in a complete academic year. PARTICIPANTS: A sample of 10,566 students was selected stratified by geographic area and year. INSTRUMENT: A validated questionnaire of knowledge toward ODT (PCID-DTO RIOS), self-administered and completed anonymously. RESULTS: Questionnaire completion rate: 85% (n = 9001). Only 18% (n = 1580) believed that their knowledge about ODT was good, 40% (n = 3578) believed that the information they had was normal, and 39% believed that their knowledge was sparse. Of the students, 96% believed that organ needs are not covered and 79% that they might need a transplant in the future. Only 39% (n = 3493) had attended a talk about ODT. Furthermore, 83% (n = 7435) believed that attending a talk would be interesting. The following variables were associated with having a more adequate knowledge: gender (62% men vs 57% women; P < .001); academic year (P < .001); knowing a donor (P < .001); knowing a transplant patient (P < .001); believing the possibility of needing a transplant oneself in the future (P < .001); attitude toward deceased donation (P < .001); and interest in receiving an informative talk about ODT (P < .001). CONCLUSION: Only 18% of nursing students in Spain believed that their knowledge about ODT was adequate. These results must be considered for possible training plans for these future professionals.

Student nurses at Spanish universities and their attitude toward xenotransplantation.

INTRODUCTION: Recent immunological and transgenic advances are a promising alternative using limited materials of human origin for transplantation. However, it is essential to achieve social acceptance of this therapy. OBJECTIVE: To analyze the attitude of nursing students from Spanish universities toward organ xenotransplantation (XTx) and to determine the factors affecting their attitude. MATERIALS AND METHODS: Type of study: A sociological, multicentre, and observational study. STUDY POPULATION: Nursing students enrolled in Spain (n = 28,000). SAMPLE SIZE: A sample of 10 566 students estimating a proportion of 76% (99% confidence and precision of ±1%), stratified by geographical area and year of study. Instrument of measurement: A validated questionnaire (PCID-XenoTx-RIOS) was handed out to every student in a compulsory session. This survey was self-administered and self-completed voluntarily and anonymously by each student in a period of 5-10 min. STATISTICAL ANALYSIS: descriptive analysis, Student's t test, the chi-square test, and a logistic regression analysis. RESULTS: A completion rate: 84% (n = 8913) was obtained. If the results of XTx were as good as in human donation, 74% (n = 6564) would be in favor and 22% (n = 1946) would have doubts. The following variables affected this attitude: age (P < 0.001); sex (P < 0.001); geographical location (P < 0.001); academic year of study (P < 0.001); attitude toward organ donation (P < 0.001); belief in the possibility of needing a transplant (P < 0.001); discussion of transplantation with one's family (P < 0.001) and friends (P < 0.001); and the opinion of one's partner (P < 0.001). The following variables persisted in the multivariate analysis: being a male (OR = 1.436; P < 0.001); geographical location (OR = 1.937; P < 0.001); an attitude in favor of donation (OR = 1.519; P < 0.001); belief in the possibility of needing a transplant (OR = 1.497; P = 0.036); and having spoken about the issue with family (OR = 1.351; P < 0.001) or friends (OR = 1.240; P = 0.001). CONCLUSIONS: The attitude of nursing students toward organ XTx is favorable and is associated with factors of general knowledge about organ donation and transplantation and social interaction.

Size-resolved particle number emission patterns under real-world driving conditions using positive matrix factorization.

A novel on-board system was tested to characterize size-resolved particle number emission patterns under real-world driving conditions, running in a EURO4 diesel vehicle and in a typical urban circuit in Madrid (Spain). Emission profiles were determined as a function of driving conditions. Source apportionment by Positive Matrix Factorization (PMF) was carried out to interpret the real-world driving conditions. Three emission patterns were identified: (F1) cruise conditions, with medium-high speeds, contributing in this circuit with 60% of total particle number and a particle size distribution dominated by particles >52 nm and around 60 nm; (F2) transient conditions, stop-and-go conditions at medium-high speed, contributing with 25% of the particle number and mainly emitting particles in the nucleation mode; and (F3) creep-idle conditions, representing traffic congestion and frequent idling periods, contributing with 14% to the total particle number and with particles in the nucleation mode (<29.4 nm) and around 98 nm. We suggest potential approaches to reduce particle number emissions depending on particle size and driving conditions. Differences between real-world emission patterns and regulatory cycles (NEDC) are also presented, which evidence that detecting particle number emissions <40 nm is only possible under real-world driving conditions.