Smart Air Quality Monitoring IoT-Based Infrastructure for Industrial Environments.

Deficient air quality in industrial environments creates a number of problems that affect both the staff and the ecosystems of a particular area. To address this, periodic measurements must be taken to monitor the pollutant substances discharged into the atmosphere. However, the deployed system should also be adapted to the specific requirements of the industry. This paper presents a complete air quality monitoring infrastructure based on the IoT paradigm that is fully integrable into current industrial systems. It includes the development of two highly precise compact devices to facilitate real-time monitoring of particulate matter concentrations and polluting gases in the air. These devices are able to collect other information of interest, such as the temperature and humidity of the environment or the Global Positioning System (GPS) location of the device. Furthermore, machine learning techniques have been applied to the Big Data collected by this system. The results identify that the Gaussian Process Regression is the technique with the highest accuracy among the air quality data sets gathered by the devices. This provides our solution with, for instance, the intelligence to predict when safety levels might be surpassed.

Embedded bleeding detector into a PMMA applicator for electron intraoperative radiotherapy.

PURPOSE: The aim of this work is to present a ready to industrialize low-cost and easy-to-install bleeding detector for use in intraoperative electron radiation therapy (IOERT). The detector works in stand-alone mode and is embedded into a translucent polymethylmethacrylate (PMMA) applicator avoiding any contact with the patient, which represent a novelty compared to previous designs. The use of this detector will prevent dose misadministration during irradiation in the event of accumulation of fluids in the applicator. METHODS: The detector is based on capacitive sensor and wireless power-supply electronics. Both sensor and electronics have been embedded in the applicator, so that any contact with the patient would be avoided. Since access to the tumor can be done through different trajectories, the detector has been calibrated for different tilting angles. RESULTS: The result of the calibration provides us with a fit curve that allows the interpolation of the results at any angle. Comparison of estimated fluid height vs real height gives an error of 1 mm for tilting angles less than 10° and 2 mm for tilting angles greater than 15°. This accuracy is better than the one required by clinic. CONCLUSIONS: The performance of the bleeding detector was evaluated in situ. No interference was observed between the detector and the beam. In addition, a user-friendly mobile application has been developed to help the surgical team making decisions before and during irradiation. The measurement provided by the mobile application was stable during the irradiation process.

Simultaneous determination of four fertility-related hormones in saliva using disposable multiplexed immunoplatforms coupled to a custom-designed and field-portable potentiostat.

This work reports the first amperometric immunosensor for the simultaneous determination of four fertility-related hormones in saliva: progesterone (P4), luteinizing hormone (LH), estradiol (E2), and prolactin (PRL). The immune platform involves direct competitive (P4 and E2), and sandwich (LH and PRL) assays implemented onto functionalized magnetic microbeads (MBs). The amperometric transduction was performed upon placing the MBs-immunoconjugates onto each of the four working electrodes of the SPCE array (SP4CEs) and applying a detection potential of -0.20 V (vs. Ag pseudo-reference electrode) using the H2O2/hydroquinone (HQ) system. The achieved analytical and operational characteristics of the developed multiplexed immunoplatform showed a sensitivity that allows the determination of these hormones in saliva, and an adequate selectivity to analyse complex clinical samples. The bioplatform was employed for the determination of the set of four hormones in human saliva samples collected from individuals with different hormonal profiles. The results obtained using a conventional potentiostat were compared with those provided employing a novel low-cost custom-designed and field-portable quadruple potentiostat. Similar results were found which also agreed with those obtained by applying ELISA methods for the determination of single hormones.

An Automatized Contextual Marketing System Based on a Wi-Fi Indoor Positioning System.

A complete contextual marketing platform including an indoor positioning system (IPS) for smartphones is proposed and evaluated to later be deployed in large infrastructures, such as malls. To this end, we design and implement a novel methodology based on location-as-a-service (LAAS), comprising all the required phases of IPS generation: mall digital map creation, the tools/procedures for offline calibration fingerprint acquisition, the location algorithm, the smartphone app acquiring the fingerprint data, and a validation procedure. To select an appropriate fingerprint location algorithm, a comparison among K-nearest neighbors (KNN), support vector machine (SVM), and Freeloc is accomplished by employing a set of different smartphones in two malls and assessing different occupancy levels. We demonstrate that our solution can be quickly deployed at shop level accuracy in any new location, resulting in a robust and scalable proposal.

Eyes-Open Versus Eyes-Closed Somatosensory Motor Balance in Professional Soccer Players With Chronic Ankle Instability: A Case-Control Study.

BACKGROUND: Chronic ankle instability (CAI) is a condition defined by certain structural and functional deficits in the ankle joint complex after acute ankle injury. These deficits include pathological joint laxity, impaired postural control, and decreased strength and neuromuscular control. PURPOSE: To compare an eyes-open versus an eyes-closed balance training protocol in professional soccer players with CAI. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: For this study, we evaluated 19 players from 2 professional soccer teams in Madrid, Spain, all of whom had CAI. Participants from both teams were randomly assigned to an eyes-open group (n = 9) or eyes-closed group (n = 10). All participants completed 4 weeks of a supervised exercise protocol consisting of 3 sessions per week. Members of both the eyes-open and eyes-closed groups performed the same exercise protocol in the same order of execution. At the end of the protocol, the participants were assessed for pain (visual analog scale), ankle dorsiflexion range of motion (weightbearing lunge test), dynamic stability (Star Excursion Balance Test), and fear of movement and reinjury (Tampa Scale for Kinesiophobia). We compared results both before and after balance training and between the eyes-open and eyes-closed balance training groups. RESULTS: Statistically significant differences were found for all of the assessed variables before and after balance training. No statistically significant differences were found between the eyes-closed and eyes-open groups on any variable. CONCLUSION: In the current study, eyes-closed balance training was not more effective than eyes-open balance training for CAI in professional soccer players.

Phantom development for daily checks in electron intraoperative radiotherapy with a mobile linac.

PURPOSE: IORT with mobile linear accelerators is a well-established modality where the dose rate and, therefore, the dose per pulse are very high. The constancy of the dosimetric parameters of the accelerator has to be checked daily. The aim of this work is to develop a phantom with embedded detectors to improve both accuracy and efficiency in the daily test of an IORT linac at the surgery room. METHODS: The developed phantom is manufactured with transparent polymethyl methacrylate (PMMA), allocating 6 parallel-plate chambers: a central one to evaluate the on-axis beam output, another on-axis one placed at a fixed depth under the previous one to evaluate the energy constancy and four off-axis chambers to evaluate the flatness and symmetry. To analyse the readings a specific application has been developed. RESULTS: For all chambers and energies, the mean saturation and polarization corrections were smaller than 0.7%. The beam is monitored at different levels of the clinical beam. Output, energy constancy and flatness correlate very well with the correspondent values with the complete applicator. During the first six months of clinical use the beam dosimetric parameters showed excellent stability. CONCLUSIONS: A phantom has been developed with embedded parallel plate chambers attached to the upper applicator part of an IORT linac. The phantom allows a very efficient setup reducing the time to check the parameters. It provides complete dosimetric information (output, energy and flatness) with just one shot and using ionization chambers with minimum saturation effect, as this highly pulsed beam requires.

An Analytical Approach to Flow-Guided Nanocommunication Networks.

Continuous progress of nanocommunications and nano-networking is opening the door to the development of innovative yet unimaginable services, with a special focus on medical applications. Among several nano-network topologies, flow-guided nanocommunication networks have recently emerged as a promising solution to monitoring, gathering information, and data communication inside the human body. In particular, flow-guided nano-networks display a number of specific characteristics, such as the type of nodes comprising the network or the ability of a nano-node to transmit successfully, which significantly differentiates them from other types of networks, both at the nano and larger scales. This paper presents the first analytical study on the behavior of these networks, with the objective of evaluating their metrics mathematically. To this end, a theoretical framework of the flow-guided nano-networks is developed and an analytical model derived. The main results reveal that, due to frame collisions, there is an optimal number of nano-nodes for any flow-guided network, which, as a consequence, limits the maximum achievable throughput. Finally, the analytical results obtained are validated through simulations and are further discussed.

A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor.

Cardiovascular diseases are the leading cause of death around the world. As a result, low-cost biomedical sensors have been gaining importance in business and research over the last few decades. Their main benefits include their small size, light weight, portability and low power consumption. Despite these advantages, they are not generally used for clinical monitoring mainly because of their low accuracy in data acquisition. In this emerging technological context, this paper contributes by discussing a methodology to help practitioners build a prototype framework based on a low-cost commercial sensor. The resulting application consists of four modules; namely, a digitalization module whose input is an electrocardiograph signal in portable document format (PDF) or joint photographic expert group format (JPEG), a module to further process and filter the digitalized signal, a selectable data calibration module and, finally, a module implementing a classification algorithm to distinguish between individuals with normal sinus rhythms and those with atrial fibrillation. This last module employs our recently published symbolic recurrence quantification analysis (SRQA) algorithm on a time series of RR intervals. Moreover, we show that the algorithm applies to any biomedical low-cost sensor, achieving good results without requiring.

Quick and Cost-Effective Estimation of Vitamin C in Multifruit Juices using Voltammetric Methods.

Ascorbic Acid (AA) is a natural and powerful water-soluble antioxidant associated with long-lasting food products. As time passes, the AA content in products sharply decreases, and they become increasingly degraded. There are several techniques to precisely quantify AA concentrations. However, most of them employ costly laboratory instruments, such as High-Performance Liquid Chromatography (HPLC) or complex electrochemical methods, which make unfeasible recurrent AA measurements along the entire supply chain. To address this issue, we contribute with an in-field and real-time voltammetric method, carried out with a low-cost, easy-to-use, and portable device. An unmodified Screen-Printed Electrode (SPE) is used together with the device to achieve short reading times. Our method has been extensively tested in two multifruit juices using three different SPEs. Calibration curves and Limit of Detection were derived for each SPE. Furthermore, periodic experiments were conducted to study the shelf life of juices under consideration. During the analysis, a set of assays for each SPE were implemented to determine the remaining AA amount per juice and compare it with that obtained using HPLC under the same conditions. Results revealed that our cost-effective device is fully comparable to the HPLC equipment, as long as the juice does not include certain interferents; a scenario also contemplated in this article.

Machine Learning Techniques Applied to Dose Prediction in Computed Tomography Tests.

Increasingly more patients exposed to radiation from computed axial tomography (CT) will have a greater risk of developing tumors or cancer that are caused by cell mutation in the future. A minor dose level would decrease the number of these possible cases. However, this framework can result in medical specialists (radiologists) not being able to detect anomalies or lesions. This work explores a way of addressing these concerns, achieving the reduction of unnecessary radiation without compromising the diagnosis. We contribute with a novel methodology in the CT area to predict the precise radiation that a patient should be given to accomplish this goal. Specifically, from a real dataset composed of the dose data of over fifty thousand patients that have been classified into standardized protocols (skull, abdomen, thorax, pelvis, etc.), we eliminate atypical information (outliers), to later generate regression curves employing diverse well-known Machine Learning techniques. As a result, we have chosen the best analytical technique per protocol; a selection that was thoroughly carried out according to traditional dosimetry parameters to accurately quantify the dose level that the radiologist should apply in each CT test.

Symbolic Recurrence Analysis of RR Interval to Detect Atrial Fibrillation.

Atrial fibrillation (AF) is a sustained cardiac arrhythmia associated with stroke, heart failure, and related health conditions. Though easily diagnosed upon presentation in a clinical setting, the transient and/or intermittent emergence of AF episodes present diagnostic and clinical monitoring challenges that would ideally be met with automated ambulatory monitoring and detection. Current approaches to address these needs, commonly available both in smartphone applications and dedicated technologies, combine electrocardiogram (ECG) sensors with predictive algorithms to detect AF. These methods typically require extensive preprocessing, preliminary signal analysis, and the integration of a wide and complex array of features for the detection of AF events, and are consequently vulnerable to over-fitting. In this paper, we introduce the application of symbolic recurrence quantification analysis (SRQA) for the study of ECG signals and detection of AF events, which requires minimal pre-processing and allows the construction of highly accurate predictive algorithms from relatively few features. In addition, this approach is robust against commonly-encountered signal processing challenges that are expected in ambulatory monitoring contexts, including noisy and non-stationary data. We demonstrate the application of this method to yield a highly accurate predictive algorithm, which at optimal threshold values is 97.9% sensitive, 97.6% specific, and 97.7% accurate in classifying AF signals. To confirm the robust generalizability of this approach, we further evaluated its performance in the implementation of a 10-fold cross-validation paradigm, yielding 97.4% accuracy. In sum, these findings emphasize the robust utility of SRQA for the analysis of ECG signals and detection of AF. To the best of our knowledge, the proposed model is the first to incorporate symbolic analysis for AF beat detection.

Optimization of CT protocols using cause-and-effect analysis of outliers.

The aim of this study was to implement an outlier marking and analysis methodology to optimize CT examination protocols. CT Head examination data, including dose metrics along with technical parameters, were stored in an automatic dose registry system. Reference dose metrics distribution was obtained throughout a 1-year period. Outlier thresholds were calculated taking into account the specific shape of the distribution, by using a robust measure of the skewness; the medcouple parameter. Subsequently, outliers from a 4-month period were marked and Cause-and-Effect analysis was carried out by a multidisciplinary dose committee. Reference Dose metrics distributions were obtained from 3690 CT Head examinations. Both CTDIvol and DLP showed a certain degree of skewness, with a medcouple value of 0.05 and 0.11, respectively. All of the upper-outliers fell within 3 identifiable groups of causes, ordered by relative importance: i) inadequate protocol selection, ii) arms or objects in the field-of-view, and iii) abnormal scanning region diameter. Regarding the lower-outliers, 90% were attributable to the inclusion of additional series in the original head protocol and the remaining 10% to unknown causes. Also, a general Cause-and-Effect diagram for outliers was elaborated. While the Dose Reference Level method applies to the general performance of a CT protocol and allows comparison with other centers, the outlier method represents a step further in the optimization process. The proposed method focuses on detecting incorrect utilization of the CT, which mainly arises from inadequate knowledge of CT technology.

Efficacy of Cognitive Behavioral Therapy in Adherence to the Mediterranean Diet in Metabolic Syndrome Patients: A Randomized Controlled Trial.

OBJECTIVE: Verify the efficacy of cognitive behavioral therapy (CBT) in adherence to the Mediterranean diet (MedDiet) in metabolic syndrome (MetS) patients. DESIGN, SETTING, PARTICIPANTS, AND INTERVENTION: In the Multimodal Intervention Program for Patients with Metabolic Syndrome clinical trial, 79 MetS patients completed the intervention. Of those, 48 belonged to the experimental group and 31 to the control group. The intervention received by the experimental group was CBT; the control group followed usual care and attended a workshop on healthy lifestyle. MAIN OUTCOME MEASURE(S) AND ANALYSIS: Anthropometric, biochemical, psychological, and lifestyle measures were taken before and after the intervention at 3 and 6 months. Analyses included paired t tests, ANOVA, and ANCOVA. RESULTS: The ANOVA results showed a statistically significant interaction between the 2 groups in waist circumference (P = .009), triglycerides (P = .015), and adherence to the MedDiet (P = .026). The ANCOVA results indicated between-group difference in waist circumference (P = .026 and .062 at 3 and 6months, respectively), in triglycerides (P = .009 and .860 at 3 and 6 months, respectively), and in MedDiet (P = .024 and .273 at 3 and 6 months, respectively). CONCLUSIONS AND IMPLICATIONS: In interventions in which CBT was applied, significant improvements were observed in MetS patients, especially in adherence to the MedDiet.

On the Nature of Energy-Feasible Wireless Nanosensor Networks.

Electromagnetic nanocommunications, understood as the communication between electronic nanoscale devices through electromagnetic waves in the terahertz band, has attracted increasing attention in recent years. In this regard, several solutions have already been proposed. However, many of them do not sufficiently capture the significance of the limitations in nanodevice energy-gathering and storing capacity. In this paper, we address key factors affecting the energy consumption of nanodevices, highlighting the effect of the communication scheme employed. Then, we also examine how nanodevices are powered, focusing on the main parameters governing the powering nanosystem. Different mathematical expressions are derived to analyze the impact of these parameters on its performance. Based on these expressions, the functionality of a nanogenerator is evaluated to gain insight into the conditions under which a wireless nanosensor network (WNSN) is viable from the energetic point of view. The results reveal that a micrometer-sized piezoelectric system in high-lossy environments (exceeding 100 dB/mm) becomes inoperative for transmission distances over 1.5 mm by its inability to harvest and store the amount of energy required to overcome the path loss.

A COTS-Based Portable System to Conduct Accurate Substance Concentration Measurements.

Traditionally, electrochemical procedures aimed at determining substance concentrations have required a costly and cumbersome laboratory environment. Specialized equipment and personnel obtain precise results under complex and time-consuming settings. Innovative electrochemical-based sensors are emerging to alleviate this difficulty. However, they are generally scarce, proprietary hardware and/or software, and focused only on measuring a restricted range of substances. In this paper, we propose a portable, flexible, low-cost system, built from commercial off-the-shelf components and easily controlled, using open-source software. The system is completed with a wireless module, which enables the transmission of measurements to a remote database for their later processing. A well-known PGSTAT100 Autolab device is employed to validate the effectiveness of our proposal. To this end, we select ascorbic acid as the substance under consideration, evaluating the reliability figure and obtaining the calibration curves for both platforms. The final outcomes are shown to be feasible, accurate, and repeatable.

Ionizing Radiation Measurement Solution in a Hospital Environment.

Ionizing radiation is one of the main risks affecting healthcare workers and patients worldwide. Special attention has to be paid to medical staff in the vicinity of radiological equipment or patients undergoing radioisotope procedures. To measure radiation values, traditional area meters are strategically placed in hospitals and personal dosimeters are worn by workers. However, important drawbacks inherent to these systems in terms of cost, detection precision, real time data processing, flexibility, and so on, have been detected and carefully detailed. To overcome these inconveniences, a low cost, open-source, portable radiation measurement system is proposed. The goal is to deploy devices integrating a commercial Geiger-Muller (GM) detector to capture radiation doses in real time and to wirelessly dispatch them to a remote database where the radiation values are stored. Medical staff will be able to check the accumulated doses first hand, as well as other statistics related to radiation by means of a smartphone application. Finally, the device is certified by an accredited calibration center, to later validate the entire system in a hospital environment.

Concentration of uranium in the soils of the west of Spain.

While determining the uranium concentration in the rock (background level) and soils on the Iberian Massif of western Spain, several geochemical anomalies were observed. The uranium concentration was much higher than the geochemical levels at these locations, and several uranium minerals were detected. The proposed uranium background levels for natural soils in the west of Salamanca Province (Spain) are 29.8 mg kg-1 in granitic rock and 71.2 mg kg-1 in slate. However, the soil near the tailings of abandoned mines exhibited much higher concentrations, between 207.2 and 542.4 mg kg-1. The calculation of different pollution indexes (Pollution Factor and Geo-accumulation Index), which reveal the conditions in the superficial horizons of the natural soils, indicated that a good percentage of the studied samples (16.7-56.5%) are moderately contaminated. The spatial distribution of the uranium content in natural soils was analysed by applying the inverse distance weighted method. The distribution of uranium through the horizons of the soils shows a tendency to accumulate in the horizons with the highest clay content. The leaching of uranium from the upper horizons and accumulation in the lower horizons of the soil could be considered a process for natural attenuation of the surface impacts of this radiogenic element in the environment. Environmental restoration is proposed in the areas close to the abandoned mining facilities of this region, given the high concentration of uranium. First, all the tailings and other mining waste would be covered with a layer of impermeable material to prevent leaching by runoff. Then, a layer of topsoil with organic amendments would be added, followed by revegetation with herbaceous plants to prevent surface erosion.

Geochemical Background and Baseline Values Determination and Spatial Distribution of Heavy Metal Pollution in Soils of the Andes Mountain Range (Cajamarca-Huancavelica, Peru).

Concentrations of seven heavy metals (Cd, Cr, Cu, Hg, Ni, Pb, and Zn) and one metalloid (As) as well as various parameters (pH, organic carbon, granulometric analysis and cation exchange capacity) were analyzed in 77 soil samples collected in the mining areas of La Zanja and Colquirrumi (Department of Cajamarca) and Julcani (Department of Huancavelica). Our study proposed geochemical baseline values for heavy metals in a natural region (La Zanja) from samples collected during the period of the environmental impact study (2006), that is, from an earlier period which occurred at the beginning of the exploitation of the current gold mine. The baseline values obtained were as follows: 8.26 mg kg-1 for Cr; 56.97 mg kg-1 for Ni; 22, 20 mg kg-1 for the Cu; 47.42 mg kg-1 for Zn; 27.50 mg kg-1 for As; 4.36 mg kg-1 for Cd; 4.89 mg kg-1 for Hg, and 44.87 mg kg-1 for Pb. Through the use of different indices of heavy metal contamination (geo-accumulation index (Igeo), improved Nemerow index (IIN) and potential ecological risk index (RI)), the degree of pollution caused by mining activities in two areas, Colquirrumi and Julcani, which have a high density of mining sites in operation, was determined. The values obtained from these indices indicated that the Colquirrumi region was the most contaminated, followed by Julcani. The area of La Zanja, despite being free of mining operations, presented slight diffuse pollution. Several positive correlations were obtained, with a high level of significance, between pH, organic carbon content, cation exchange capacity, and the Cr, Pb and Ni concentrations of the soils. The spatial distribution of the heavy metals was realized by means of the interpolation method of ordinary kriging. The results obtained and the experience gained in this work were necessary to facilitate the identification of soil contamination processes in high altitude areas of the Andes Western Cordillera (Peru) as a basis for taking appropriate measures when restoring soils, during mine closure processes, and to protect the quality of soil resources.

Necrosis del cuero cabelludo / Scalp necrosis

No disponible

Eficacia a 2 años de tocilizumab en pacientes con artritis reumatoide activa en la práctica clínica habitual / Two-year efficacy of tocilizumab in patients with active rheumatoid arthritis in clinical practice

Objetivos. Evaluar la eficacia del tratamiento con tocilizumab (TCZ) en pacientes con artritis reumatoide (AR) en práctica clínica, las tasas de supervivencia del fármaco y variables clínicas predictoras de respuesta. Métodos. Es un estudio descriptivo, prospectivo, longitudinal y abierto en el que se incluyó a pacientes en condiciones de práctica clínica que recibieron TCZ (8mg/kg/cada 4 semanas). Las respuestas clínicas se midieron utilizando los criterios de respuesta de la European League Against Rheumatism (EULAR), las tasas de actividad baja y remisión según el Disease activity score-28 (DAS28-VSG) y Clinical Disease Activity Index (CDAI). Resultados. La tasa de respuesta EULAR fue del 86,63%, con una tasa de remisión DAS28 del 53,7% a los 6 meses de tratamiento. El 52,9% de los pacientes presentaron baja actividad de la enfermedad a los 24 meses según CDAI y 47,1% según DAS28. No hubo diferencias significativas en cuanto a respuesta EULAR, baja actividad y remisión DAS28 entre pacientes en tratamiento con TCZ en monoterapia y terapia combinada, ni entre pacientes positivos y negativos para factor reumatoide (FR) y/o anticuerpo antipéptido cíclico citrulinado (anti-PCC). Los pacientes que recibieron TCZ de primera línea presentaron mejores tasas de remisión y baja actividad a los 6 meses. La tasa de supervivencia fue del 61% a los 24 meses, siendo una de las causas de discontinuación más frecuente los efectos adversos. Conclusión. El TCZ es efectivo en pacientes con AR, tiene eficacia similar cuando se utiliza en monoterapia o en combinación con fármacos antirreumáticos modificadores de la enfermedad (FAME) sintéticos y presenta altas tasas de supervivencia (AU)

Objectives. To evaluate the efficacy of tocilizumab (TCZ) in patients with rheumatoid arthritis (RA) in clinical practice, retention rates of the drug and predictors of response. Methods. We performed a descriptive, prospective, longitudinal, open-label study in patients receiving TCZ (8mg/kg/4 weeks) in a clinical practice setting. The clinical responses were evaluated using the European League Against Rheumatism (EULAR) response criteria, and the low activity and remission rates according to the Disease Activity Score 28-erythrocyte sedimentation rate (DAS28-ESR) and the Clinical Disease Activity Index (CDAI). Results. The EULAR response rate was 86.63% and the DAS28 remission rate was 53.7% after 6 months of treatment; rates of low disease activity were 52.9% on CDAI and 47.1% on DAS28 at month 24. There were no statistically significant differences in EULAR response, rates of low activity and remission on DAS28 between patients receiving TCZ alone and those receiving TCZ in combination therapy, or between patients positive or negative for rheumatoid factor (RF) and/or anti-cyclic citrullinated peptide (anti-CCP) antibodies. The naïve biological therapy patients showed better remission and low activity rates after 6 months of treatment. The retention rate was 61% at month 24. Adverse events were among the most frequent causes of discontinuation. Conclusions. Tocilizumab is effective in RA, has a similar efficacy when used alone or in combination with synthetic disease-modifying antirheumatic drugs (DMARDs) and shows high retention rates (AU)