Improving the ability to discriminate medical multiple-choice questions through the analysis of the competitive examination to assign residency positions in Spain.

INTRODUCTION: Psychometrics plays a vital role in evaluating educational research, including the analysis of multiple-choice exams. This study aims to improve the discriminatory ability of the "Médico Interno Residente" (MIR) medical exam in Spain, used to rank candidates for specialized healthcare training, through psychometric analysis. METHODS: We analyzed 2,890 MIR exam questions from 2009 to 2021 (totaling 147,214 exams), categorizing them based on methodology and response type. Evaluation employed classical test theory and item response theory (IRT). Classical test theory determined difficulty and discrimination indices, while IRT assessed the relationship between knowledge levels and question performance. RESULTS: Question distribution varied across categories and years. Frequently addressed knowledge areas included various medical specialties. Non-image-associated clinical cases were the easiest, while case-based clinical questions exhibited the highest discriminatory capacity, differing significantly from image-based case or negative questions. High-quality questions without images had longer stems but shorter answer choices. Adding images reduced discriminatory power and question difficulty, with image-based questions being easier. Clinical cases with images had shorter stems and longer answer choices. CONCLUSIONS: For improved exam performance, we recommend using a clinical case format followed by direct short-answer questions. Questions should be of low difficulty, providing clear and specific answers based on scientific evidence and avoiding ambiguity. Typical clinical cases with key characteristic features should be presented, excluding uncertain boundaries of medical knowledge. Questions should have lengthy stems and concise answer choices, minimizing speculation. If images are used, they should be typical, clear, consistent with the exam, and presented within clinical cases using clinical semiotics and propaedeutics.

Increased incidence of Graves' disease during the SARS-CoV2 pandemic.

INTRODUCTION: COVID-19 has a wide spectrum of clinical severity and there is evidence that SARS-Cov2 affects several organs and systems. Among the organs affected since the beginning of the pandemic, the relationship between SARS-CoV-2 infection and thyroid involvement has been demonstrated. Novel and highly effective messenger RNA and DNA-based vaccines have been rapidly developed to decrease SARS-CoV-2 morbidity and mortality. Early after mass vaccinations, cases of thyroid dysfunction mainly including episodes of subacute thyroiditis, began to be reported like adverse effects. The objective of this study is to determine the impact of the pandemic, both due to SARS-CoV2 infections and vaccinations, on the incidence of Graves' disease (GD). METHODS: Cross-sectional, observational study comparing incidence of GD in adult population (over 18 years) before (2017-2019) and after (2020-2021) Covid-19 pandemic. Only patients with new cases of GD, no relapsed diseases, were included. SARS-CoV-2 diagnosis was based on nucleic acid amplification tests on nasopharyngeal swabs or measurement of class M and class G antibodies to SARS-CoV-2 by highly specific assays. Data on incidence and vaccination related to SARS-CoV-2 infection were obtained from the public records from Castilla y León autonomous regional government. RESULTS: A total of 180 subjects were diagnosed and treated for GD during the study period. We observed a notable increase in expected GD cases in 2021 compared to 2017-19. The number of GD cases was higher in the second (Q2) quarter. Among 2021 GD cases, 42/66 patients (63.6%) had been vaccinated in the 90 days before symptom onset, but none of them in the first quarter of the year. A total of 97.7% were women with a mean age of 48.9 (SD 15.6) years. On average they were diagnosed 19.9 (SD 17.6) days after receiving the vaccine. A total of 7/42 (16.67%) had another previously diagnosed autoimmune disease and 11/42 (26.19%) were smokers. DISCUSSION: Our results show a notable increase in the incidence of GD during the year 2021, specially in women with a history of smoking. Hyper activation of the immune system induced by SARS-CoV2 and by the recently released SARS-COV-2 vaccines has been highlighted in recent months. To assess whether this observed increase in the incidence of GD is sustained in the coming years or has simply been a precipitous trigger for individuals who were already predisposed to develop the disease, future studies will be needed.

A 35-year follow-up study of patients admitted to methadone treatment between 1982-1984 in Asturias, Spain. / Estudio de seguimiento de 35 años de pacientes admitidos a tratamiento con metadona entre 1982-1984 en Asturias, España.

The objective was to evaluate outcomes in a heroin-dependent population 35 years after first enrolment in methadone maintenance treatment (MMT).  An ad hoc protocol was used to assess drug misuse, treatment, and drug-related morbidity in the survivor sample. The standardized mortality ratio (SMR) and 95% confidence interval (CI) were calculated.  A total of 214 heroin-dependent patients entered MMT between 1982 and 1984 in the Asturias Public Health Service. Information was received on 195 subjects, of whom 146 were deceased.  Men accounted for 77.5% of the study cohort. Over the 35-year follow-up period, the SMR was 11.75 (95% CI = 9.95 - 13.77). In the survivor sample, 5.7% were still enrolled in MMT; human immunodeficiency virus (HIV) was diagnosed in 38.77% and hepatitis B/C in 73.46%. No differences were found between sexes in mortality or HIV and hepatitis B/C status. None of the female survivors were using heroin at the 35-year follow-up compared with 5.26% of males. In conclusion, our study confirms the high long-term mortality rate of heroin addicts, even after enrollment in MMT.

El objetivo fue evaluar el estado de una población dependiente a la heroína 35 años después de su primera inscripción en un tratamiento de mantenimiento con metadona (TMM). Se utilizó un protocolo ad hoc para evaluar morbilidad, consumo y tratamiento de la adicción en la muestra de supervivientes. Se calculó la razón de mortalidad estandarizada (RME) con un intervalo de confianza (IC) del 95%. Un total de 214 pacientes ingresaron en TMM entre 1982 y 1984 en el Servicio de Salud Pública de Asturias. Se recibió información sobre 195 sujetos, de los cuales 146 habían fallecido. Los hombres representaron el 77,5% de la cohorte del estudio. Durante el período de seguimiento de 35 años, la RME fue de 11,75 (IC 95% = 9,95 ­ 13,77). En la muestra de supervivientes, el 5,7% todavía estaba inscrito en TMM; el virus de inmunodeficiencia humana (VIH) se diagnosticó en un 38,77% y la hepatitis B/C en un 73,46%; el consumo actual de heroína se informó en un 4,1%. No hubo diferencias de género en la mortalidad o la condición de VIH y hepatitis B/C. Ninguna de las mujeres consumía heroína en el seguimiento de 35 años en comparación con el 5,26% de los hombres. En conclusión, nuestro estudio confirma la alta tasa de mortalidad a largo plazo, incluso después de la inscripción en TMM.

Computer vision syndrome in healthcare workers using video display terminals: an exploration of the risk factors.

AIMS: To estimate the prevalence of computer vision syndrome (CVS) in healthcare workers and its relationship to video display terminal (VDT) exposure, sociodemographic, optical correction and work characteristics, and to analyse whether there are differences among occupational groups. DESIGN: Cross-sectional study. METHODS: A sample of 1179 physicians and surgeons, nurses, and nursing assistants from two hospitals in Spain between January 2017 and February 2018 were invited to participate in this study. Of these, 622 workers from both hospitals were finally included. CVS was measured using a questionnaire, the CVS-Q© . Logistic regression was used to identify the factors associated with CVS. All the results were stratified by occupational group. RESULTS: The prevalence of CVS was 56.75% with nurses being the most affected occupational group (61.75%). It was associated significantly with female sex (aOR = 2.57; 95% CI 1.36-4.88) and morning shifts plus on-call (aOR = 2.33; 95% CI 1.11-4.88) in the physicians and surgeons group. Among the nurses, it was associated with female sex (aOR = 2.35; 95% CI 1.03-5.37), seniority between 10 and 20 years (aOR = 2.17; 95% CI 1.03-4.59), VDT exposure at work of 2-4 h/day (aOR = 6.14; 95% CI 1.08-35.02), VDT exposure at work >4 h/day (aOR = 7.14; 95% CI 1.29-39.62) and self-perception that using the software application was not easy (aOR = 2.49; 95% CI 1.23-5.01). CONCLUSIONS: A high prevalence of CVS among healthcare workers was observed. The risk factors that increased the likelihood of suffering from this syndrome depended on the occupation. IMPACT: The findings may be used as a reference for occupational health services to implement specific preventive measures to reduce CVS for each occupational group. Such measures should consider both individual factors and the working conditions.

Prediction of Computer Vision Syndrome in Health Personnel by Means of Genetic Algorithms and Binary Regression Trees.

One of the major consequences of the digital revolution has been the increase in the use of electronic devices in health services. Despite their remarkable advantages, though, the use of computers and other visual display terminals for a prolonged time may have negative effects on vision, leading to a greater risk of Computer Vision Syndrome (CVS) among their users. In this study, the importance of ocular and visual symptoms related to CVS was evaluated, and the factors associated with CVS were studied, with the help of an algorithm based on regression trees and genetic algorithms. The performance of this proposed model was also tested to check its ability to predict how prone a worker is to suffering from CVS. The findings of the present research confirm a high prevalence of CVS in healthcare workers, and associate CVS with a longer duration of occupation and higher daily computer usage.

The MIR 2018 Exam: Psychometric Study and Comparison with the Previous Nine Years.

Background and Objectives: The aim of the present research is to study the questions used in the 2018 MIR exam (a test that allows access to specialized medical training in Spain), describe their psychometric properties, and evaluate their quality. Materials and Methods: This analysis is performed with the help of classical test theory (CTT) and item response theory (IRT). The answers given to the test questions by a total of 3868 physicians are analyzed. Results: According to CTT, the average difficulty index for all of the test questions was 0.629, which falls into the acceptable category. The average difficulty index with correction for random effects was 0.515, which corresponds to a value within the optimal range. The mean discrimination index was 0.277, which is in the good category, while the mean point biserial correlation coefficient, with a value of 0.275 fits in the regular category. The values of difficulty and discrimination calculated according to the model of two parameters of the IRT seem adequate with average values of -0.389 and 0.677. The Cronbach alpha score obtained for the overall test was 0.944. This value is considered as very good. Conclusions: A decrease was observed in the average values of discrimination in the last three calls, which may be related to the greater proportion of Spanish graduates that take the exam in the same year of finalization of their studies in Medicine.

Stress distribution in the transitional peri-implant bone in a single implant-supported prosthesis with platform-switching under different angulated loads.

A 3D finite element analysis was conducted to evaluate and compare the stress distribution in the peri-implant bone (transitional cortical and trabecular bone) of one single implant-supported crown with platform switching and another without platform switching, under a vertical and an oblique load. Two models were created, simulating an osseointegrated implant (4 × 13 mm, platform 4.1 mm) embedded in the jaw bone. One model simulated a 4.1-mm diameter abutment connection (conventional model) and the other a 3.8-mm diameter abutment connection (platform-switching model). A crown with a Co-Cr alloy framework and feldspathic porcelain veneering was applied over the titanium abutment. Static, vertical and oblique loads (0°, 15°, 30°, 45°) with a maximum value of 150 N were applied to the crown. For any inclination of the applied load, the stress values in the transitional cortical bone were lower in the platform-switching model than in the conventional model. However, the stress in the transitional trabecular bone was higher in the platform-switching model than in the conventional model. Stress values increased when the load was more oblique at the transitional cortical bone in both models and was slightly reduced at the transitional trabecular bone of the conventional model. The platform-switching technique reduces the stress at the transitional cortical bone. In both models, this stress gradually increases as the load becomes more inclined. The transitional trabecular bone shows lower stress values than the transitional cortical bone. The location of stress is similar in both models.

Gastroenterology - Evolution of specialty choice in recent years.

INTRODUCTION: Gastroenterology is one of the medical specialties offered to residency training candidates each year. This project analyzes the data associated with the choice of a Gastroenterology residency program in recent years. MATERIAL AND METHODS: Data related to specialty selection were obtained from official reports with regard to the allocation of residency places by the Spanish Ministry of Health, Social Services and Equality. Information was collected from various teaching centers via their training guides, the Spanish National Catalogue of Hospitals and the National Transplant Organization. RESULTS: The median consecutive number involved in the choice of Gastroenterology training has decreased year after year, and this specialty is now positioned among the five most commonly selected residency programs in 2015. The median number of hospitals with a higher number of beds, adult liver transplantation activities and dedicated GI bleeding units is significantly lower. This is also true when centers are analyzed according to the presence of specific Gastroenterology on-call shifts for residents or their association with medical schools. Data from the past five years highlight Madrid, Aragón and the Basque Country as the autonomous communities where Gastroenterology is the most popular. Centers selected by candidates with the lowest median consecutive numbers from 2011-2015 included the university hospitals Ramón y Cajal, Santiago de Compostela and Gregorio Marañón. CONCLUSIONS: Gastroenterology has gradually escalated in the ranking of residency choices and is now one of the five most popular options. Potential residents prefer larger centers with complex-care patients and more research activity.

A Hybrid Algorithm for Missing Data Imputation and Its Application to Electrical Data Loggers.

The storage of data is a key process in the study of electrical power networks related to the search for harmonics and the finding of a lack of balance among phases. The presence of missing data of any of the main electrical variables (phase-to-neutral voltage, phase-to-phase voltage, current in each phase and power factor) affects any time series study in a negative way that has to be addressed. When this occurs, missing data imputation algorithms are required. These algorithms are able to substitute the data that are missing for estimated values. This research presents a new algorithm for the missing data imputation method based on Self-Organized Maps Neural Networks and Mahalanobis distances and compares it not only with a well-known technique called Multivariate Imputation by Chained Equations (MICE) but also with an algorithm previously proposed by the authors called Adaptive Assignation Algorithm (AAA). The results obtained demonstrate how the proposed method outperforms both algorithms.

A New Missing Data Imputation Algorithm Applied to Electrical Data Loggers.

Nowadays, data collection is a key process in the study of electrical power networks when searching for harmonics and a lack of balance among phases. In this context, the lack of data of any of the main electrical variables (phase-to-neutral voltage, phase-to-phase voltage, and current in each phase and power factor) adversely affects any time series study performed. When this occurs, a data imputation process must be accomplished in order to substitute the data that is missing for estimated values. This paper presents a novel missing data imputation method based on multivariate adaptive regression splines (MARS) and compares it with the well-known technique called multivariate imputation by chained equations (MICE). The results obtained demonstrate how the proposed method outperforms the MICE algorithm.

A hybrid PCA-CART-MARS-based prognostic approach of the remaining useful life for aircraft engines.

Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS) technique with the principal component analysis (PCA), dendrograms and classification and regression trees (CARTs). Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL) with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.). Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks) also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

Effects of the economic crisis on demand due to mental disorders in Asturias: data from the Asturias Cumulative Psychiatric Case Register (2000-2010).

INTRODUCTION: The economic crisis has negative effects on the population's physical and mental health. Our objective has been to study the association between socioeconomic status and number of people demanding mental health services. METHODS: We performed a correlation analysis of administrative morbidity data (incidence and prevalence) of mental illness (obtained from the Asturias Cumulative Psychiatric Case Register) and three economic indicators (unemployment, consumer price index and gross domestic product). RESULTS: The increase in the unemployment rate is associated with a clear decrease in both new and prevalent mental health demand. CPI has a minor weak positive correlation with the administrative incidence of some mental disorders (Neurotic disorders, Schizophrenia and addictions). GDP does not show a significant correlation with the administrative incidence and it is strongly associated with an increased administrative prevalence that is more intense in the case of alcoholism, neurotic disorders, mental retardation and Z codes (ICD-10). CONCLUSION: The variation of the socioeconomic indicated observed in the economic crisis period in Asturias was not associated with increased care demand for any mental disorders. There is a negative correlation of unemployment rate with care demand.

Biomechanical Effects of Ti-Base Abutment Height on the Dental Implant System: A Finite Element Analysis.

This study aims to analyse, using a finite element analysis, the effects of Ti-base abutment height on the distribution and magnitude of transferred load and the resulting bone microstrain in the bone-implant system. A three-dimensional bone model of the mandibular premolar section was created with an implant placed in a juxta-osseous position. Three prosthetic models were designed: a 1 mm-high titanium-base (Ti-base) abutment with an 8 mm-high cemented monolithic zirconia crown was designed for model A, a 2 mm-high Ti-base abutment with a 7 mm-high crown for model B, and a 3 mm-high abutment with a 6 mm-high crown for model C. A static load of 150 N was applied to the central fossa at a six-degree angle with respect to the axial axis of the implant to evaluate the magnitude and distribution of load transfer and microstrain. The results showed a trend towards a direct linear association between the increase in the height of the Ti-base abutments and the increase in the transferred stress and the resulting microstrain to both the prosthetic elements and the bone/implant system. An increase in transferred stress and deformation of all elements of the system, within physiological ranges, was observed as the size of the Ti-base abutment increased.

PsiOvi Staging Model for Schizophrenia (PsiOvi SMS): A New Internet Tool for Staging Patients with Schizophrenia.

BACKGROUND: One of the challenges of psychiatry is the staging of patients, especially those with severe mental disorders. Therefore, we aim to develop an empirical staging model for schizophrenia. METHODS: Data were obtained from 212 stable outpatients with schizophrenia: demographic, clinical, psychometric (PANSS, CAINS, CDSS, OSQ, CGI-S, PSP, MATRICS), inflammatory peripheral blood markers (C-reactive protein, interleukins-1RA and 6, and platelet/lymphocyte [PLR], neutrophil/lymphocyte [NLR], and monocyte/lymphocyte [MLR] ratios). We used machine learning techniques to develop the model (genetic algorithms, support vector machines) and applied a fitness function to measure the model's accuracy (% agreement between patient classification of our model and the CGI-S). RESULTS: Our model includes 12 variables from 5 dimensions: 1) psychopathology: positive, negative, depressive, general psychopathology symptoms; 2) clinical features: number of hospitalizations; 3) cognition: processing speed, visual learning, social cognition; 4) biomarkers: PLR, NLR, MLR; and 5) functioning: PSP total score. Accuracy was 62% (SD = 5.3), and sensitivity values were appropriate for mild, moderate, and marked severity (from 0.62106 to 0.6728). DISCUSSION: We present a multidimensional, accessible, and easy-to-apply model that goes beyond simply categorizing patients according to CGI-S score. It provides clinicians with a multifaceted patient profile that facilitates the design of personalized intervention plans.

Effect of Applying 1% Metformin on Guided Bone Regeneration Processes with Bovine-Derived Xenografts.

Background: Although xenografts have shown successful results in GBR procedures due to their osteoconductive properties, many authors have opted to add co-adjuvant drugs to favor osteogenesis and differentiate cells into an osteoblastic lineage. Metformin has been shown to have bone-protective properties, regulating osteoclast differentiation, as well as the ability to promote osteoblast mineralization and differentiation. The present study aimed to evaluate the effect of the local application of a 1% metformin solution on bone neoformation in the treatment of an experimental bone defect in a guided bone regeneration animal model with a particulated bovine hydroxyapatite xenograft with hyaluronate. Methods: With this purpose in mind, two critical defects with 8 mm diameter and 0.5 mm depth were created in eight male New Zealand rabbit calvarias. Titanium cylinders were fixed in each defect and filled with particulate hydroxyapatite of bovine origin and sodium hyaluronate, with sterile injectable saline added to the control group and sterile 1% metformin solution added to the test group. At 6 weeks, the animals were euthanized, and samples were obtained and prepared for histomorphometric analysis. Results: A higher percentage of new bone formation was observed in the metformin samples than in the control samples, both in the region closest to the animal's calvaria and in the most distal region analyzed. A higher average bone-biomaterial contact percentage was observed in the samples, with metformin in both the proximal and distal regions. There was no statistically significant difference in the mean value in either region in both parameters. Conclusion: The local application of a 1% metformin solution in an animal model of guided bone regeneration with particulate bovine hydroxyapatite and hyaluronate resulted in greater bone neoformation and xenograft osseointegration than in the control group.

An ANN-based smart tomographic reconstructor in a dynamic environment.

In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A).

Work-related overexertion injuries in cleaning occupations: An exploration of the factors to predict the days of absence by means of machine learning methodologies.

The special characteristics of the cleaning industry have an important impact on the health and safety of its workforce. Making use of data from more than 79,000 occupational accidents, the aim of the present research is to use machine learning techniques to develop a model to predict incapacity for work (expressed in days of absence) due to work-related overexertion injuries among service sector cleaners in Spain. The severity of accidents caused by overexertion depends on several factors that can be classified into the following categories: injury typology, individual factors, employment conditions, accident circumstances and health and safety management and standards in the company.

A Biomechanical Analysis of the Influence of the Morfology of the Bone Blocks Grafts on the Transfer of Tension or Load to the Soft Tissue by Means of the Finite Elements Method.

Edentulism produces resorption of alveolar bone processes, which can complicate placement of dental implants. Guided bone regeneration techniques aim to recover the volume of bone. These treatments are susceptible to the surgical technique employed, the design of the autologous block or the tension of the suture. These factors can relate to major complications as the lack of primary closure and dehiscence. The present study, using finite element analysis, aimed to determine differences in terms of displacement of the oral mucosa, transferred stress according to Von Mises and deformation of soft tissue when two block graft designs (right-angled and rounded) and two levels of suture tension (0.05 and 0.2 N) were combined. The results showed that all the variables analyzed were greater with 0.2 N. Regarding the design of the block, no difference was found in the transferred stress and deformation of the soft tissue. However, displacement was related to a tendency to dehiscence (25% greater in the right-angled/chamfer design). In conclusion different biomechanical behavior was observed in the block graft depending on the design and suture tension, so it is recommended to use low suture tension and rounded design. A novel finite element analysis model is presented for future investigations.

Zirconia vs. Titanium Dental Implants: Primary Stability In-Vitro Analysis.

The present experimental trial uses two types of dental implants, one made of titanium (Ti6Al4V) and the other one of zirconia (ZrO2), but both of identical design, to compare their stability and micro-movements values under load. One of each type of implant (n = 42) was placed into 21 cow ribs, recording the insertion torque and the resonance frequency using a specific transducer. Subsequently, a prosthetic crown made of PMMA was screwed onto each of the implants in the sample. They were then subjected to a static compression load on the vestibular cusp of the crown. The resulting micromovements were measured. The zirconia implants obtained a higher mean of both IT and RFA when compared with those of titanium, with statistically significant differences in both cases (p = 0.0483 and p = 0.0296). However, the micromovement values when load was applied were very similar for both types, with the differences between them (p = 0.3867) not found to be statistically significant. The results show that zirconia implants have higher implant stability values than titanium implants. However, the fact that there are no differences in micromobility values implies that caution should be exercised when applying clinical protocols for zirconia based on RFA, which only has evidence for titanium.

Detection of outliers in pollutant emissions from the Soto de Ribera coal-fired power plant using functional data analysis: a case study in northern Spain.

For more than a century, air pollution has been one of the most important environmental problems in cities. Pollution is a threat to human health and is responsible for many deaths every year all over the world. This paper deals with the topic of functional outlier detection. Functional analysis is a novel mathematical tool employed for the recognition of outliers. This methodology is applied here to the emissions of a coal-fired power plant. This research uses two different methods, called functional high-density region (HDR) boxplot and functional bagplot. Please note that functional bagplots were developed using bivariate bagplots as a starting point. Indeed, they are applied to the first two robust principal component scores. Both methodologies were applied for the detection of outliers in the time pollutant emission curves that were built using, as inputs, the discrete information available from an air quality monitoring data record station and the subsequent smoothing of this dataset for each pollutant. In this research, both new methodologies are tested to detect outliers in pollutant emissions performed over a long period of time in an urban area. These pollutant emissions have been treated in order to use them as vectors whose components are pollutant concentration values for each observation made. Note that although the recording of pollutant emissions is made in a discrete way, these methodologies use pollutants as curves, identifying the outliers by a comparison of curves rather than vectors. Then, the concept of outlier goes from being a point to a curve that employs the functional depth as the indicator of curve distance. In this study, it is applied to the detection of outliers in pollutant emissions from a coal-fired power plant located on the outskirts of the city of Oviedo, located in the north of Spain and capital of the Principality of Asturias. Also, strengths of the functional methods are explained.