Disturbance rejecting PID-FF controller design of a non-ideal buck converter using an innovative snake optimizer with pattern search algorithm.

The optimal design of a proportional-integral-derivative controller with two cascaded first-order low-pass filters (PID-FF) for non-ideal buck converters faces significant challenges, including effective disturbance rejection, robustness to parameter variations, and the mitigation of high-frequency signal noise, with existing approaches often struggling and leading to suboptimal performance in practical applications. This study addresses these challenges by introducing a constraint on the open-loop crossover frequency to mitigate high-frequency noise and ensuring the controller prioritizes maintaining constant output voltage and robust responsiveness to input voltage and load current variations. This study also introduces an innovative metaheuristic algorithm, the opposition-based snake optimizer with pattern search (OSOPS), designed to address these limitations. OSOPS enhances the Snake Optimizer (SO) by integrating opposition-based learning (OBL) and Pattern Search (PS), thereby improving its exploration and exploitation capabilities. The proposed algorithm design includes a crossover frequency constraint aimed at counteracting high-frequency noise and ensuring robust performance under diverse disturbances. The efficacy of the OSOPS algorithm is demonstrated through rigorous statistical box plot analysis and convergence response comparisons with the original SO algorithm. Additionally, we systematically compare the performance of the OSOPS-based PID-FF-controlled non-ideal buck converter system against systems utilizing the original SO algorithm and the classical pole placement (PP) method. This evaluation encompasses transient and frequency responses, disturbance rejection, and robustness analysis. The results reveal that the OSOPS-based system outperforms the SO- and PP-based systems with 14.21 % and 32.10 % faster rise times, along with 15.38 % and 84.95 % faster settling times, respectively. The OSOPS and SO systems also exhibit higher bandwidths, exceeding the PP-based system by 18.74 % and 17.03 %, respectively. By addressing the key challenges in PID-FF controller design for non-ideal buck converters, this study provides a substantial advancement in control strategy, promising enhanced performance in practical applications.

Social determinants of health in post-treatment cancer survivors: Scoping review.

PURPOSE: To identify, analyze and describe the available scientific evidence about the influence of social determinants of health on cancer survivors. METHODS: A scoping review was outlined according to the steps described by the Joanna Brigs Institute Reviewer's Manual: selection of studies, data mapping, and results grouping, synthesis and report, was conducted. PubMed, CINAHL, Scopus and LILACS databases were searched from 2011 to 2023. RESULTS: Out of a total of 1783 papers initially screened, only 19 studies met the inclusion criteria for the scoping review, focusing on the primary social determinants impacting the health of cancer survivors. These studies were categorized into six main themes: a) employment (challenges in work reintegration and work-place difficulties); b) variations among different ethnic groups; c) disparities based on sex; d) barriers and facilitators in accessing health and social security services; e) the role of support networks and social environments; and f) socioeconomic lever (influence of income and socioeconomic status). CONCLUSIONS: Understanding the impact of social determinants on the post-treatment quality of life for cancer survivors is crucial. Comprehensive survivorship care should address not just medical needs but also holistic aspects like social support, education, overall well-being, and improvements in physical and social environments. This multifaceted approach ensures the well-rounded support needed for optimal survivorship outcomes.

Job burnout, cognitive functioning, and Brain-derived neurotrophic factor expression among hospital Mexican nurses.

AIM: To analyze the relationship between burnout syndrome, cognitive functions, and sBDNF (Serum Brain-derived Neurotrophic Factor) in Mexican nurses. METHOD: A descriptive cross-sectional design was used. This study target staff nurses working in hospitals in Guanajuato, México. Demographic and working condition data were collected via questionnaire. The Maslach Burnout Inventory (MBI) was used to evaluate burnout. A blood sample were collected and processed by ELISA technique to measure sBDNF. Finally, the General Cognitive Assessment (CAB) of the Cognifit© neuropsychological battery was used to evaluated cognitive functions. RESULTS: Findings showed that there are sociodemographic characteristics and working conditions associated with burnout syndrome among nurses. Furthermore, the data demonstrated a significant decrease in sBDNF levels in burnout nurses and a negative correlation between BDNF levels and burnout syndrome. Additionally, these burnout nurse also revealed significant cognitive impairment in reasoning, memory, and attention as well as total scores of CAB. Interestingly, we found a positive correlation between sBDNF levels and the cognitive deficits in burnout nurse. CONCLUSION: Reduced BDNF levels could be a biological indicator or part of the pathological process of burnout, which could affect cognitive abilities. Reduced cognitive function in nurses has relevant implications and emphasizes the need for specialized preventive strategies because nurses make clinical decisions concerning their patients, whose situations are constantly changing.

Targeted delivery of temozolomide by nanocarriers based on folic acid-hollow TiO2 -nanospheres for the treatment of glioblastoma.

Glioblastoma multiforme (GBM) is a highly malignant brain tumor. Its standard treatment includes a combination of surgery, radiation, and chemotherapy. The last involves the oral delivery of free drug molecules to GBM such as Temozolomide (TMZ). However, this treatment has limited effectiveness owing to the drugs premature degradation, lack of cell selectivity, and poor control of pharmacokinetics. In this work, the development of a nanocarrier based on hollow titanium dioxide (HT) nanospheres functionalized with folic acid (HT-FA) for the targeted delivery of temozolomide (HT-TMZ-FA) is reported. This approach has the potential benefits of prolonging TMZ degradation, targeting GBM cells, and increasing TMZ circulation time. The HT surface properties were studied, and the nanocarrier surface was functionalized with folic acid as a potential targeting agent against GBM. The loading capacity, protection from degradation, and drug retention time were investigated. Cell viability was performed to assess the cytotoxicity of HT against LN18, U87, U251, and M059K GBM cell lines. The cell internalization of HT configurations (HT, HT-FA, HT-TMZ-FA) was evaluated to study targeting capabilities against GBM cancer. Results show that HT nanocarriers have a high loading capacity, retain and protect TMZ for at least 48 h. Folic acid-functionalized HT nanocarriers successfully delivered and internalized TMZ to glioblastoma cancer cells with high cytotoxicity through autophagic and apoptotic cellular mechanisms. Thus, HT-FA nanocarriers could be a promising targeted delivery platform for chemotherapeutic drugs for the treatment of GBM cancer.

Effects of Mexican Ganoderma lucidum extracts on liver, kidney, and the gut microbiota of Wistar rats: A repeated dose oral toxicity study.

Well-characterized and standardized extracts of a Mexican genotype of Ganoderma lucidum (Gl), a medicinal mushroom, cultivated on oak sawdust (Gl-1) or oak sawdust plus acetylsalicylic acid (Gl-2, ASA), have been shown to exert antioxidant, hypocholesterolemic, anti-inflammatory, prebiotic, and anticancer properties. However, toxicity analyses still need to be carried out. Different doses of these Gl-1 or Gl-2 extracts were administered to Wistar rats for 14 days in a repeated dose oral toxicity study. We assessed the external clinical signs, biochemical parameters, liver and kidney tissues, injury and inflammation biomarkers, gene expression, inflammatory responses, proinflammatory mediators, and gut microbiota. Gl extracts had no significant adverse, toxic or harmful effects on male and female rats compared to the control groups. No injury or dysfunction were recorded in the kidney or liver, as there were no significant abnormal variations in organ weight, tissue histopathology, serum biochemical parameters (C-reactive protein, creatinine, urea, glucose, ALT and AST transaminases, TC, LDL-c, TG, HDL-c), urinary parameters (creatinine, urea nitrogen, albumin, the albumin-to-creatinine ratio, glucose), injury and inflammatory biomarkers (KIM-1/TIM-1, TLR4, and NF-кB protein expression; IL-1ß, TNF-α and IL-6 gene expression), or the expression of genes linked to cholesterol metabolism (HMG-CoA, Srebp2, Ldlr). Gl-1 and Gl-2 extracts showed prebiotic effects on the gut microbiota of male and female Wistar rats. Bacterial diversity and relative bacterial abundance (BRA) increased, positively modulating the Firmicutes/Bacteroidetes ratio. The ASA (10 mM) added to the substrate used for mushroom cultivation changed properties and effects of the Gl-2 extract on Wistar rats. The no-observed-adverse-effect-level (NOAEL) was 1000 mg/kg body weight/day of Gl-1 or Gl-2 extracts. Clinical trials are recommended for further exploring the potential therapeutic applications of studied extracts.

Sleep Disturbances and Mental Well-Being of Preschool Children during the COVID-19 Pandemic in Mexico.

COVID-19 pandemic confinement caused changes in families and children's routines worldwide. Studies conducted at the beginning of the pandemic have examined the harmful effects of these changes on mental health, including sleep disturbances. As sleep is essential for optimal childhood development, this study was designed to determine preschool-aged (3-6 years old) children's sleep parameters and mental well-being during the COVID-19 pandemic in Mexico. Using a cross-sectional design, a survey was applied to parents of preschool children, inquiring about their children's confinement status, routine changes, and electronics use. The parents responded to the Children's Sleep Habits Questionnaire and the Strengths and Difficulties Questionnaire to assess children's sleep and mental well-being. To provide objective sleep data, the children wore wrist actigraphy for seven days. Fifty-one participants completed the assessment. The children's mean age was 5.2 years, and the prevalence of sleep disturbances was 68.6%. The use of electronic tablets in the bedroom near bedtime and symptoms of mental health deterioration (i.e., emotional distress and behavioral difficulties) were associated with sleep disturbances and their severity. The COVID-19 pandemic's confinement-related routine changes greatly impacted preschool children's sleep and well-being. We recommend establishing age-tailored interventions to manage children at higher risk.

Scale, context, and heterogeneity: the complexity of the social space.

The social space refers to physical or virtual places where people interact with one another. It decisively influences the emergence of human behaviors. However, little is known about the nature and complexity of the social space, nor its relationship to context and spatial scale. Recently, the science of complex systems has bridged between fields of knowledge to provide quantitative responses to fundamental sociological questions. In this paper, we analyze the shifting behavior of social space in terms of human interactions and wealth distribution across multiple scales using fine-grained data collected from both official (US Census Bureau) and unofficial data sources (social media). We use these data to unveil how patterns strongly depend upon the observation scale. Therefore, it is crucial for any analysis to be framed within the appropriate context to avoid biased results and/or misleading conclusions. Biased data analysis may lead to the adoption of fragile and poor decisions. Including context and a proper understanding of the spatial scale are essential nowadays, especially with the pervasive role of data-driven tools in decision-making processes.

Psychosocial factors in adherence to pharmacological treatment and diabetes mellitus control in patients over 65.

AIM: To explore the influence of anxiety/depression symptoms and social risk in patients older than 65 years with type 2 diabetes mellitus (T2DM) both in non-adherence to pharmacological treatment (Non-AdhT) and in poor control of T2DM. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: Adults over 65 years of age with T2DM treated at the Madrid Primary Care Service. MAIN MEASUREMENTS: Data collection: Electronic Health Record database. VARIABLES: Poor control of T2DM (HBA1c) and Non-AdhT (Morisky-Green test); main clinical variables: symptoms of depression/anxiety and social risk. Global multivariate logistic regression models and disaggregated by sex were used to Non-AdhT and poor T2DM control. RESULTS: Data were obtained on 884 subjects. Non-AdhT prevalence: 4.4%; prevalence of poor T2DM control: 37.2%. Multivariate logistic regression models for No-AdhT in men showed a higher risk if they had symptoms of anxiety/depression (OR: 3.88; 95%CI: 1.15-13.07); and in women, if they had social risk (OR: 5.61; 95%CI: 1.86-16.94). Multivariate logistic regression models for poor control of T2DM in men revealed a higher risk if they did not have AdhT (OR: 3.53; 95%CI: 1.04-12.02). CONCLUSIONS: In people over 65 years with T2DM, although Non-AdhT is low, the prevalence of poor T2DM control is high. Symptoms of depression or anxiety are a risk factor to Non-AdhT in men, while social risk has the same effect in women. Non-AdhT in men increases the risk of poor T2DM control. From a gender perspective, it is important to detect social and mental health problems in older adults with diabetes and to reinforce strategies to improve their adherence to drug treatment in these patients.

Flood impact on the Spanish Mediterranean coast since 1960 based on the prevailing synoptic patterns.

In a changing climate and in social context, tools and databases with high spatiotemporal resolution are needed for increasing the knowledge on the relationship between meteorological events and flood impacts; hence, analysis of high-resolution spatiotemporal databases with detailed information on the frequency, intensity, and impact of floods is necessary. However, the methodological nature of flood databases hinders relating specific flood events to the weather events that cause them; hence, methodologies for classifying flood cases according to the synoptic patterns that generate them are also necessary. Knowing which synoptic patterns are likely to generate risk situations allows for a probabilistic approach with high spatial resolution regarding the timing of occurrence, affected area, and expected damage from floods. To achieve these objectives, we use the SMC-Flood Database, a high-resolution spatiotemporal flood database covering the 1960-2015 period for all municipalities along the Spanish Mediterranean coast. To relate floods with the synoptic conditions that generated them, we used a multivariate analysis method on the corrected daily anomalies of the surface pressure fields, 850 hPa temperature, and 500 hPa geopotential height, all of which were obtained from the 20th Century Reanalysis Project V2. Results show that 12 atmospheric synoptic patterns can statistically explain the 3608 flood cases that occurred in the study area between 1960 and 2015. These flood cases were classified into 847 atmospherically induced flood events. These results reduce the uncertainty during decision making because of the classification of potential risk situations. The Mediterranean Basin is a region where floods have serious socioeconomic impacts; hence, this work helps improving prevention measures and providing information for policymakers, mainly regarding land use planning and early warning systems.

Comparative Study on the Quality of Microcrystalline and Epitaxial Silicon Films Produced by PECVD Using Identical SiF4 Based Process Conditions.

Hydrogenated microcrystalline silicon (µc-Si:H) and epitaxial silicon (epi-Si) films have been produced from SiF4, H2 and Ar mixtures by plasma enhanced chemical vapor deposition (PECVD) at 200 °C. Here, both films were produced using identical deposition conditions, to determine if the conditions for producing µc-Si with the largest crystalline fraction (XC), will also result in epi-Si films that encompass the best quality and largest crystalline silicon (c-Si) fraction. Both characteristics are of importance for the development of thin film transistors (TFTs), thin film solar cells and novel 3D devices since epi-Si films can be grown or etched in a selective manner. Therefore, we have distinguished that the H2/SiF4 ratio affects the XC of µc-Si, the c-Si fraction in epi-Si films, and the structure of the epi-Si/c-Si interface. Raman and UV-Vis ellipsometry were used to evaluate the crystalline volume fraction (Xc) and composition of the deposited layers, while the structure of the films were inspected by high resolution transmission electron microscopy (HRTEM). Notably, the conditions for producing µc-Si with the largest XC are different in comparison to the fabrication conditions of epi-Si films with the best quality and largest c-Si fraction.

Use of herbal medicine for diabetes mellitus in adults from the central-western region of Mexico.

OBJECTIVE: This study aims to assess the prevalence of herbal medicine (HM) use and factors influencing HM usage including the identification of the main plants consumed by patients with type 2 diabetes mellitus (T2DM) in central-western Mexico. DESIGN: A total of 1862 patients with diabetes were surveyed in public and private hospitals in four states (Guanajuato, Jalisco, Michoacan, and San Luis Potosi) of the central-western region of Mexico. The chi-square test was used to assess associations between HM use and demographic characteristics, such as glucose levels, presence of complications and comorbidities, as well as the selected therapy to treat T2DM. RESULTS: The prevalence of HM use (59.2%) in patients with T2DM was mainly associated with education level (p = 0.001), time of diagnosis of T2DM (p = 0.004), presence of complications (p < 0.001) and comorbidities (p = 0.018) and the use of insulin (p < 0.001). These patients report a higher consumption of herbal medicine compared to those on glycemic control (p < 0.001). The most frequently used medicinal plants to treat T2DM were nopal (54.9%), moringa (26.7%), and aloe (22.1%). CONCLUSION: The prevalence of HM use to treat T2DM in west-central Mexico is high (59.2%) and its consumption is mostly carried out without the recommendation of a health professional (91.9%). The use of HM increases mainly when the patient uses insulin, during complications of the disease or in patients with an inadequate glycemic control.

Socioeconomic Patterns of Twitter User Activity.

Stratifying behaviors based on demographics and socioeconomic status is crucial for political and economic planning. Traditional methods to gather income and demographic information, like national censuses, require costly large-scale surveys both in terms of the financial and the organizational resources needed for their successful collection. In this study, we use data from social media to expose how behavioral patterns in different socioeconomic groups can be used to infer an individual's income. In particular, we look at the way people explore cities and use topics of conversation online as a means of inferring individual socioeconomic status. Privacy is preserved by using anonymized data, and abstracting human mobility and online conversation topics as aggregated high-dimensional vectors. We show that mobility and hashtag activity are good predictors of income and that the highest and lowest socioeconomic quantiles have the most differentiated behavior across groups.

Icephobic Performance of Multi-Scale Laser-Textured Aluminum Surfaces for Aeronautic Applications.

Ice-building up on the leading edge of wings and other surfaces exposed to icing atmospheric conditions can negatively influence the aerodynamic performances of aircrafts. In the past, research activities focused on understanding icing phenomena and finding effective countermeasures. Efforts have been dedicated to creating coatings capable of reducing the adhesion strength of ice to a surface. Nevertheless, coatings still lack functional stability, and their application can be harmful to health and the environment. Pulsed laser surface treatments have been proven as a viable technology to induce icephobicity on metallic surfaces. However, a study aimed to find the most effective microstructures for reducing ice adhesion still needs to be carried out. This study investigates the variation of the ice adhesion strength of micro-textured aluminum surfaces treated using laser-based methods. The icephobic performance is tested in an icing wind tunnel, simulating realistic icing conditions. Finally, it is shown that optimum surface textures lead to a reduction of the ice adhesion strength from originally 57 kPa down to 6 kPa, corresponding to a relative reduction of ~90%. Consequently, these new insights will be of great importance in the development of functionalized surfaces, permitting an innovative approach to prevent the icing of aluminum components.

Geographical fragmentation of the global network of Twitter communications.

Understanding the geography of society represents a challenge for social and economic sciences. The recent availability of data from social media enables the observation of societies at a global scale. In this paper, we study the geographical structure of the Twitter communication network at the global scale. We find a complex structure where self-organized patches with clear cultural, historical, and administrative boundaries are manifested and first-world economies centralize information flows. These patches unveil world regions that are socially closer to each other with direct implications for processes of collective learning and identity creation.

Segregation dynamics with reinforcement learning and agent based modeling.

Societies are complex. Properties of social systems can be explained by the interplay and weaving of individual actions. Rewards are key to understand people's choices and decisions. For instance, individual preferences of where to live may lead to the emergence of social segregation. In this paper, we combine Reinforcement Learning (RL) with Agent Based Modeling (ABM) in order to address the self-organizing dynamics of social segregation and explore the space of possibilities that emerge from considering different types of rewards. Our model promotes the creation of interdependencies and interactions among multiple agents of two different kinds that segregate from each other. For this purpose, agents use Deep Q-Networks to make decisions inspired on the rules of the Schelling Segregation model and rewards for interactions. Despite the segregation reward, our experiments show that spatial integration can be achieved by establishing interdependencies among agents of different kinds. They also reveal that segregated areas are more probable to host older people than diverse areas, which attract younger ones. Through this work, we show that the combination of RL and ABM can create an artificial environment for policy makers to observe potential and existing behaviors associated to rules of interactions and rewards.

Fabrication of Microbolometer Arrays Based on Polymorphous Silicon-Germanium.

This work reports the development of arrays of infrared sensors (microbolometers) using a hydrogenated polymorphous silicon-germanium alloy (pm-SixGe1-x:H). Basically, polymorphous semiconductors consist of an amorphous semiconductor matrix with embedded nanocrystals of about 2-3 nm. The pm-SixGe1-x:H alloy studied has a high temperature coefficient of resistance (TCR) of 4.08%/K and conductivity of 1.5 × 10-5 S∙cm-1. Deposition of thermosensing film was made by plasma-enhanced chemical vapor deposition (PECVD) at 200 °C, while the area of the devices is 50 × 50 µm2 with a fill factor of 81%. Finally, an array of 19 × 20 microbolometers was packaged for electrical characterization. Voltage responsivity values were obtained in the range of 4 × 104 V/W and detectivity around 2 × 107 cm∙Hz1/2/W with a polarization current of 70 µA at a chopper frequency of 30 Hz. A minimum value of 2 × 10-10 W/Hz1/2 noise equivalent power was obtained at room temperature. In addition, it was found that all the tested devices responded to incident infrared radiation, proving that the structure and mechanical stability are excellent.

Development of an Analytical Model for Optimization of Direct Laser Interference Patterning.

Direct laser interference patterning (DLIP) has proven to be a fast and, at the same time, high-resolution process for the fabrication of large-area surface structures. In order to provide structures with adequate quality and defined morphology at the fastest possible fabrication speed, the processing parameters have to be carefully selected. In this work, an analytical model was developed and verified by experimental data, which allows calculating the morphological properties of periodic structures as a function of most relevant laser-processing parameters. The developed model permits to improve the process throughput by optimizing the laser spot diameter, as well as pulse energy, and repetition rate. The model was developed for the structures formed by a single scan of the beam in one direction. To validate the model, microstructures with a 5.5 µm spatial period were fabricated on stainless steel by means of picosecond DLIP (10 ps), using a laser source operating at a 1064 nm wavelength. The results showed a difference of only 10% compared to the experimental results.

Segregation and polarization in urban areas.

Social behaviours emerge from the exchange of information among individuals-constrained by and reciprocally influencing the structure of information flows. The Internet radically transformed communication by democratizing broadcast capabilities and enabling easy and borderless formation of new acquaintances. However, actual information flows are heterogeneous and confined to self-organized echo-chambers. Of central importance to the future of society is understanding how existing physical segregation affects online social fragmentation. Here, we show that the virtual space is a reflection of the geographical space where physical interactions and proximity-based social learning are the main transmitters of ideas. We show that online interactions are segregated by income just as physical interactions are, and that physical separation reflects polarized behaviours beyond culture or politics. Our analysis is consistent with theoretical concepts suggesting polarization is associated with social exposure that reinforces within-group homogenization and between-group differentiation, and they together promote social fragmentation in mirrored physical and virtual spaces.

US social fragmentation at multiple scales.

Despite global connectivity, societies seem to be increasingly polarized and fragmented. This phenomenon is rooted in the underlying complex structure and dynamics of social systems. Far from homogeneously mixing or adopting conforming views, individuals self-organize into groups at multiple scales, ranging from families up to cities and cultures. In this paper, we study the fragmented structure of American society using mobility and communication networks obtained from geo-located social media data. We find self-organized patches with clear geographical borders that are consistent between physical and virtual spaces. The patches have multi-scale structure ranging from parts of a city up to the entire nation. Their significance is reflected in distinct patterns of collective interests and conversations. Finally, we explain the patch emergence by a model of network growth that combines mechanisms of geographical distance gravity, preferential attachment and spatial growth. Our observations are consistent with the emergence of social groups whose separated association and communication reinforce distinct identities. Rather than eliminating borders, the virtual space reproduces them as people mirror their offline lives online. Understanding the mechanisms driving the emergence of fragmentation in hyper-connected social systems is imperative in the age of the Internet and globalization.

Ejercicio Físico en el Paciente con Falla Renal / Physical Exercise in the Patient with Renal Failure

Resumen La enfermedad renal es una patología que afecta gravemente a los riñones, generando alteraciones en la capacidad de filtrar toxinas y otras sustancias de desecho en la sangre. Evidenciar los efectos y el rol de la intervención fisioterapéutica en pacientes con enfermedad renal. Se realizó una revisión sistemática, con análisis retrospectivo y descriptivo, de artículos científicos publicados en bases de datos indexadas entre enero del 2007 a noviembre del 2018. Se realizó la búsqueda de estudios en las bases de datos EBSCO, SciELO, MEDLINE, Medscape, PubMed Central, EMBASE, REDALYC, DOAJ, OVID y diferentes revistas sobre el tema. Se utilizaron los criterios de inclusión de estudios para revisiones sistemáticas de la Declaración PRISMA, y la evaluación del riesgo de sesgo se realizó mediante la evaluación de la Colaboración Cochrane y la escala de PEDro. Se recuperaron 68.620 artículos científicos antes de aplicar los filtros correspondientes. Luego de ellos, se obtuvieron 20 artículos que fundamentan la existencia de una mejoría en la calidad de vida, fuerza, capacidad física, consumo de oxígeno, bienestar físico, mental y social, en pacientes con falla renal. La realización de ejercicio físico en pacientes con falla renal mejora la respuesta física, social y mental, como también, las actividades de la vida diaria. Estos efectos se obtienen con una evaluación, prescripción y monitoreo adecuado del ejercicio. Por esto, concluimos que resulta indispensable que un profesional en fisioterapia participe en el equipo interdisciplinario necesario para el tratamiento de la enfermedad renal.

Abstract Kidney disease is a pathology where the kidneys are seriously damaged, generating alterations in the ability to filter toxins and other waste substances in the blood. The aim of this study was to evidence the effects and role of physiotherapeutic intervention in patients with kidney disease. A systematic review was conducted, with retrospective and descriptive analysis, of scientific articles published in indexed databases between January 2007 and November 2018. The search was performed for studies in the EBSCO, SciELO, MEDLINE, Medscape, PubMed databases, as well as in Central, EMBASE, REDALYC, DOAJ, OVID and several journals on the subject. The criteria for inclusion of studies were used for systematic reviews of the PRISMA Statement, and a risk-of-bias assessment was performed through the evaluation of the Cochrane Collaboration and the PEDro scale. 68,620 scientific articles were recovered before applying the corresponding filters. After that, 20 articles were obtained which support the existence of an improvement in the quality of life, strength, physical capacity, oxygen consumption, physical, mental and social well-being in patients with renal failure. The performance of physical exercise in patients with renal failure improves the physical, social and mental response, as well as the activities of daily living. These effects are the result of an evaluation, prescription and adequate monitoring of the exercise. Therefore, we conclude it is essential that a professional in physiotherapy should participate in the interdisciplinary team necessary for the treatment of kidney disease.