Open Access
Being born in winter-spring and at around the time of an influenza pandemic are risk factors for the development of schizophrenia: the apna study in Navarre, Spain
(MDPI, 2021) Álvarez-Mon, Miguel Ángel; Guillén Aguinaga, Sara; Pereira-Sánchez, Víctor; Onambele, Luc; Al-Rahamneh, Moad J.; Brugos Larumbe, Antonio; Guillén Grima, Francisco; Ortuño, Felipe; Ciencias de la Salud; Osasun Zientziak
Background: we analyzed the relationship between the prevalence of schizophrenia and the season of birth and gestation during a period of an influenza pandemic. Methods: cross-sectional analysis of a prospective population-based cohort of 470,942 adults. We fitted multivariant logistic regression models to determine whether the season of birth and birth in an influenza-pandemic year (1957, 1968, 1977) was associated with schizophrenia. Results: 2077 subjects had been diagnosed with schizophrenia. Logistic regression identified a significantly greater prevalence of schizophrenia in men than in women (OR = 1.516, CI 95% = 1.388–1.665); in those born in the winter or spring than in those born in the summer or autumn (OR = 1.112, CI 95% = 1.020–1.212); and in those born in a period of an influenza pandemic (OR = 1.335, CI 95% = 1.199–1.486). The increase in risk was also significant when each influenza pandemic year was analyzed separately. However, neither month of birth nor season of birth, when each of the four were studied individually, were associated with a statistically significant increase in that risk. Conclusions: the winter–spring period and the influenza pandemics are independent risk factors for developing schizophrenia. This study contradicts many previous studies and thus revitalizes a locked debate in understanding the neurodevelopmental hypothesis of this disorder.
Open Access
Infant mortality in the European Union: a time trend analysis of the 1994-2015 period
(Elsevier España, 2019) Onambele, Luc; San Martín Rodríguez, Leticia; Niu, Hao; Álvarez Álvarez, Ismael; Arnedo Pena, Alberto; Guillén Grima, Francisco; Aguinaga Ontoso, Inés; Ciencias de la Salud; Osasun Zientziak
Introducción: La mortalidad infantil es un indicador de la salud infantil y una variable explicativa del desarrollo socioeconómico. Nuestro objetivo fue examinar los cambios y tendencias de la mortalidad infantil en la Unión Europea (UE) y sus 28 países miembros en el período 1994-2015. Métodos: Se recopilaron datos de muertes de niños menores de un año entre 1994 y 2015 de la base de datos Eurostat. Estudiamos las tendencias en la UE, por países y regiones, utilizando elanálisis de regresión joinpoint. Se condujeron análisis adicionales para estudiar las tendencias de mortalidad neonatal y neonatal precoz. Resultados: La mortalidad infantil en la UE ha disminuido significativamente de 8.3 a 3.6 por 1.000 (porcentaje de cambio anual = −3.8%, intervalos de confianza del 95% −4.1; −3.6). Las tasas de mortalidad más altas se registraron en Rumanía y Bulgaria, y las tasas más bajas en países escandinavos (Finlandia, Suecia). Se encontraron tendencias descendentes significativas en los países de la UE, más pronunciadas en los países bálticos exsoviéticos y países de Europa oriental, mientras que los países de Europa occidental mostraron los descensos menos pronunciados. La mortalidad infantil ha aumentado significativamente en Grecia en los últimos años,mientras que en el Reino Unido e Irlanda las tasas se han estabilizado. Conclusiones: La mortalidad infantil ha disminuido en la UE y sus países en las últimas décadas, más pronunciadamente en los países de Europa oriental y los países bálticos exsoviéticos, mientras que en varios países de Europa occidental las tasas aumentaron o se han estabilizado enlos últimos años.
Open Access
Trends, projections, and regional disparities of maternal mortality in Africa (1990-2030): an ARIMA forecasting approach
(MDPI, 2023) Onambele, Luc; Guillén Aguinaga, Sara; Guillén Aguinaga, Laura; Ortega-Leon, Wilfrido; Montejo, Rocío; Alas Brun, Rosa María; Aguinaga Ontoso, Enrique; Aguinaga Ontoso, Inés; Guillén Grima, Francisco; Ciencias de la Salud; Osasun Zientziak
With the United Nations Sustainable Development Goals (SDG) (2015–2030) focused on the reduction in maternal mortality, monitoring and forecasting maternal mortality rates (MMRs) in regions like Africa is crucial for health strategy planning by policymakers, international organizations, and NGOs. We collected maternal mortality rates per 100,000 births from the World Bank database between 1990 and 2015. Joinpoint regression was applied to assess trends, and the autoregressive integrated moving average (ARIMA) model was used on 1990–2015 data to forecast the MMRs for the next 15 years. We also used the Holt method and the machine-learning Prophet Forecasting Model. The study found a decline in MMRs in Africa with an average annual percentage change (APC) of −2.6% (95% CI −2.7; −2.5). North Africa reported the lowest MMR, while East Africa experienced the sharpest decline. The region-specific ARIMA models predict that the maternal mortality rate (MMR) in 2030 will vary across regions, ranging from 161 deaths per 100,000 births in North Africa to 302 deaths per 100,000 births in Central Africa, averaging 182 per 100,000 births for the continent. Despite the observed decreasing trend in maternal mortality rate (MMR), the MMR in Africa remains relatively high. The results indicate that MMR in Africa will continue to decrease by 2030. However, no region of Africa will likely reach the SDG target.
Open Access
Maternal mortality in Africa: regional trends (2000-2017)
(MDPI, 2022) Onambele, Luc; Ortega-Leon, Wilfrido; Guillén Aguinaga, Sara; Forjaz, Maria Joao; Yoseph, Amanuel; Guillén Aguinaga, Laura; Alas Brun, Rosa María; Arnedo Pena, Alberto; Aguinaga Ontoso, Inés; Guillén Grima, Francisco; Ciencias de la Salud; Osasun Zientziak
Background: United Nations Sustainable Development Goals state that by 2030, the global maternal mortality rate (MMR) should be lower than 70 per 100,000 live births. MMR is still one of Africa’s leading causes of death among women. The leading causes of maternal mortality in Africa are hemorrhage and eclampsia. This research aims to study regional trends in maternal mortality (MM) in Africa. Methods: We extracted data for maternal mortality rates per 100,000 births from the United Nations Children’s Fund (UNICEF) databank from 2000 to 2017, 2017 being the last date available. Joinpoint regression was used to study the trends and estimate the annual percent change (APC). Results: Maternal mortality has decreased in Africa over the study period by an average APC of −3.0% (95% CI −2.9; −3,2%). All regions showed significant downward trends, with the greatest decreases in the South. Only the North African region is close to the United Nations’ sustainable development goals for Maternal mortality. The remaining Sub-Saharan African regions are still far from achieving the goals. Conclusions: Maternal mortality has decreased in Africa, especially in the South African region. The only region close to the United Nations’ target is the North African region. The remaining Sub-Saharan African regions are still far from achieving the goals. The West African region needs more extraordinary efforts to achieve the goals of the United Nations. Policies should ensure that all pregnant women have antenatal visits and give birth in a health facility staffed by specialized personnel.
Open Access
Covid-19 impact on DTP vaccination trends in Africa: a joinpoint regression análisis
(MDPI, 2023) Aguinaga Ontoso, Inés; Guillén Aguinaga, Sara; Guillén Aguinaga, Laura; Alas Brun, Rosa María; Onambele, Luc; Aguinaga Ontoso, Enrique; Guillén Grima, Francisco; Ciencias de la Salud; Osasun Zientziak
Background: deaths due to vaccine-preventable diseases are one of the leading causes of death among African children. Vaccine coverage is an essential measure to decrease infant mortality. The COVID-19 pandemic has affected the healthcare system and may have disrupted vaccine coverage. Methods: DTP third doses (DTP3) Vaccine Coverage was extracted from UNICEF databases from 2012 to 2021 (the last available date). Joinpoint regression was performed to detect the point where the trend changed. The annual percentage change (APC) with 95% confidence intervals (95% CI) was calculated for Africa and the regions. We compared DTP3 vaccination coverage in 2019–2021 in each country using the Chi-square test. Result: During the whole period, the vaccine coverage in Africa increased with an Annual Percent change of 1.2% (IC 95% 0.9–1.5): We detected one joinpoint in 2019. In 2019–2021, there was a decrease in DTP3 coverage with an APC of −3.5 (95% −6.0; −0,9). (p < 0.001). Vaccination rates decreased in many regions of Sub-Saharan Africa, especially in Eastern and Southern Africa. There were 26 countries (Angola, Cabo Verde, Comoros, Congo, Côte d’Ivoire, Democratic Republic of the Congo, Djibouti, Ethiopia, Eswatini, The Gambia, Guinea-Bissau, Liberia, Madagascar, Malawi, Mauritania, Mauritius, Mozambique, Rwanda, Senegal, Seychelles, Sierra Leone, Sudan, Tanzania, Togo, Tunisia, Uganda, and Zimbabwe) where the vaccine coverage during the two years decreased. There were 10 countries (Angola, Cabo Verde, Comoros, Democratic Republic of the Congo, Eswatini, The Gambia, Mozambique, Rwanda, Senegal, and Sudan) where the joinpoint regression detected a change in the trend. Conclusions. COVID-19 has disrupted vaccine coverage, decreasing it all over Africa.
Open Access
Evaluating the efficacy of ChatGPT in navigating the spanish medical residency entrance examination (MIR): promising horizons for AI in clinical medicine
(MDPI, 2023) Guillén Grima, Francisco; Guillén Aguinaga, Sara; Guillén Aguinaga, Laura; Alas Brun, Rosa María; Onambele, Luc; Ortega-Leon, Wilfrido; Montejo, Rocío; Aguinaga Ontoso, Enrique; Barach, Paul; Aguinaga Ontoso, Inés; Ciencias de la Salud; Osasun Zientziak
The rapid progress in artificial intelligence, machine learning, and natural language processing has led to increasingly sophisticated large language models (LLMs) for use in healthcare. This study assesses the performance of two LLMs, the GPT-3.5 and GPT-4 models, in passing the MIR medical examination for access to medical specialist training in Spain. Our objectives included gauging the model’s overall performance, analyzing discrepancies across different medical specialties, discerning between theoretical and practical questions, estimating error proportions, and assessing the hypothetical severity of errors committed by a physician. Material and methods: We studied the 2022 Spanish MIR examination results after excluding those questions requiring image evaluations or having acknowledged errors. The remaining 182 questions were presented to the LLM GPT-4 and GPT-3.5 in Spanish and English. Logistic regression models analyzed the relationships between question length, sequence, and performance. We also analyzed the 23 questions with images, using GPT-4’s new image analysis capability. Results: GPT-4 outperformed GPT-3.5, scoring 86.81% in Spanish (p < 0.001). English translations had a slightly enhanced performance. GPT-4 scored 26.1% of the questions with images in English. The results were worse when the questions were in Spanish, 13.0%, although the differences were not statistically significant (p = 0.250). Among medical specialties, GPT-4 achieved a 100% correct response rate in several areas, and the Pharmacology, Critical Care, and Infectious Diseases specialties showed lower performance. The error analysis revealed that while a 13.2% error rate existed, the gravest categories, such as “error requiring intervention to sustain life” and “error resulting in death”, had a 0% rate. Conclusions: GPT-4 performs robustly on the Spanish MIR examination, with varying capabilities to discriminate knowledge across specialties. While the model’s high success rate is commendable, understanding the error severity is critical, especially when considering AI’s potential role in real-world medical practice and its implications for patient safety.
Open Access
The impact of COVID-19 on DTP3 vaccination coverage in Europe (2012-2023)
(MDPI, 2025-12-24) Aguinaga Ontoso, Inés; Guillén Aguinaga, Sara; Guillén Aguinaga, Laura; Alas Brun, Rosa María; Guillén-Aguinaga, Miriam; Onambele, Luc; Aguinaga Ontoso, Enrique; Rayón Valpuesta, Esperanza; Guillén Grima, Francisco; Ciencias de la Salud; Osasun Zientziak
Background: The COVID-19 pandemic disrupted routine child immunization efforts, threatening to reverse progress in controlling vaccine-preventable diseases. Materials and Methods: We analyzed the impact of COVID-19 on DTP3 vaccination in Europe by comparing trends before and after the pandemic using time series data from 2000 to 2023. Employing joinpoint regression, chi-square tests, and segmented regression analysis, we assessed DTP3 vaccination trends and coverage changes. Results: The findings revealed significant regional disparities across Europe. Statistical models indicated reductions in DTP3 coverage in countries such as Ireland, Sweden, and Switzerland, whereas Ukraine and San Marino showed improvements. Conclusions: There are variations in the effect of COVID-19 on DTP3 coverage rates, indicating the need for targeted public health strategies to address vaccine hesitancy, logistical barriers, and systemic inequities.
Open Access
Tendances internationales de la mortalité maternelle et infantile en Afrique de 1990-2016
(2020) Onambele, Luc; Guillén Grima, Francisco; Ciencias de la Salud; Osasun Zientziak
Objectif général: savoir la tendance annuelle de réduction du taux de mortalité maternelle et infantile entre 1990 à 2015 et 2016 respectivement. Objectifs spécifiques: savoir les tendances annuelles de réduction de la mortalité maternelle dans les cinq régions de l‘Afrique; savoir les pays africains qui ont atteint le quatrième Objectif du Millénaire pour le Développement (OMD4); savoir les tendances annuelles de mortalité infantile dans les cinq régions de l‘Afrique; savoir les pays africains ayant atteint le cinquième Objectif du Millénaire pour le Développement(OMD5); savoir la région dont les pays ont les meilleures tendances annuelles de réduction de la mortalité maternelle et infantile.
Open Access
Mixed reality in undergraduate nursing education: a systematic review and meta-analysis of benefits and challenges
(MDPI, 2025-04-22) Guillén Aguinaga, Laura; Rayón Valpuesta, Esperanza; Guillén Aguinaga, Sara; Rodríguez-Díaz, Blanca; Montejo, Rocío; Alas Brun, Rosa María; Aguinaga Ontoso, Enrique; Onambele, Luc; Guillén-Aguinaga, Miriam; Guillén Grima, Francisco; Aguinaga Ontoso, Inés; Ciencias de la Salud; Osasun Zientziak
Background: Nursing Schools are incorporating Mixed Reality (MR) into student training to enable them to confront challenging or infrequently encountered scenarios in their practice and ensure their preparedness. This systematic review evaluates the benefits and challenges of implementing MR in nursing curricula. Materials and Methods: A search was conducted in PubMed, WOS, Scopus, Embase, and CINAHL for studies published between 2011 and 2023. The search strategy used was (nurses OR nurse OR nursing) AND mixed reality AND simulation. Inclusion criteria required that studies focus on undergraduate nursing students and be written in English or Spanish. Exclusion criteria included reviews, bibliometric studies, and articles that did not separately report undergraduate nursing student results. Quality was evaluated with the JBI Critical Appraisal Checklist for Qualitative Research and the Newcastle-Ottawa Scale. A meta-analysis was conducted on studies with control groups to compare MR's effectiveness against traditional teaching methods. Results: Thirty-three studies met the inclusion criteria. MR was widely used to improve clinical judgment, patient safety, technical skill acquisition, and student confidence. The meta-analysis found that MR reduced anxiety (Cohen's d = -0.73, p < 0.001). However, its impact on knowledge acquisition and skill development was inconsistent. There was no improvement over traditional methods (p = 0.466 and p = 0.840). Despite positive qualitative findings, methodological variability, small sample sizes, and publication bias contributed to mixed quantitative results. The main challenges were cybersickness, usability, high costs, and limited institutional access to MR technology. Conclusions: Although MR can help nursing education by decreasing students' anxiety, its efficacy remains inconclusive. Future research should use larger, randomized controlled trials to validate MR's role in nursing education.