Background: Falls and their consequences are a serious public health problem worldwide. Each year, 37.3 million falls requiring medical attention occur. Therefore, the analysis of fall risk is of great importance for prevention. Artificial intelligence (AI) represents an innovative tool for creating predictive statistical models of fall risk through data analysis. Objective: The aim of this review was to analyze the available evidence on the applications of AI in the analysis of data related to postural control and fall risk. Methods: A literature search was conducted in 6 databases with the following inclusion criteria: the articles had to be published within the last 5 years (from 2018 to 2024), they had to apply some method of AI, AI analyses had to be applied to data from samples consisting of humans, and the analyzed sample had to consist of individuals with independent walking with or without the assistance of external orthopedic devices. Results: We obtained a total of 3858 articles, of which 22 were finally selected. Data extraction for subsequent analysis varied in the different studies: 82% (18/22) of them extracted data through tests or functional assessments, and the remaining 18% (4/22) of them extracted through existing medical records. Different AI techniques were used throughout the articles. All the research included in the review obtained accuracy values of >70% in the predictive models obtained through AI. Conclusions: The use of AI proves to be a valuable tool for creating predictive models of fall risk. The use of this tool could have a significant socioeconomic impact as it enables the development of low-cost predictive models with a high level of accuracy. Trial Registration: PROSPERO CRD42023443277; https://tinyurl.com/4sb72ssv

Objectives: Accurate prediction of fall risk in older adults is essential to prevent injuries and improve quality of life. This study evaluates the predictive performance of various machine learning models using accelerometric data, non-accelerometric data, aiming to improve predictive accuracy and identify key contributing variable. Methods: We applied random forest, XGBoost, AdaBoost, LightGBM, support vector regression (SVR), decision trees, and Bayesian ridge regression to a dataset of 146 older adults. Models were trained using accelerometric data (movement patterns) and non-accelerometric data (demographic and clinical variables). Performance was evaluated based on mean squared error (MSE) and coefficient of determination ( R 2 ), to assess how combining multiple data types influences prediction accuracy. Results: Models trained on combined accelerometric and non-accelerometric data consistently outperformed those based on single data types. Bayesian ridge regression achieved the highest accuracy (MSE = 0.6746, R 2 = 0.9941), demonstrating superior performance compared to decision trees (MSE = 0.1907, R 2 = 0.8991) and SVR (MSE = 1.5243, R 2 = − 2.2532). Non-accelerometric factors, including age and comorbidities, significantly contributed to fall risk prediction. Conclusions: Integrating accelerometric and non-accelerometric data improves fall risk prediction accuracy in older adults. Bayesian ridge regression trained on combined datasets provides superior predictive power compared to traditional models. These findings highlight the importance of multi-source data fusion for effective fall prevention strategies. Future work should validate these models in larger, more diverse populations to enhance clinical applicability.

Background: Peripheral facial paralysis (PFP) affects the facial nerve, the seventh cranial nerve. It has an incidence rate of 20–30 cases per 100,000 habitants. The diagnosis is clinical, though imaging tests may be required in some cases. The treatment protocol includes medication, physiotherapy, and, in certain cases, surgery. Proprioceptive neuromuscular facilitation (PNF) techniques and electrical stimulation have been shown to be significant for recovery. Although PFP has a high recovery rate, up to 40% of patients may experience permanent sequelae. Objective: to assess the efficacy of treatment based on electrical stimulation and/or PNF in patients affected by PFP. Methods: A systematic search was conducted across six databases (PubMed, Medline, SportDiscus, CINAHL, Scopus, and Web of Science) in November 2024. Randomized controlled trials were included. Results: Fourteen articles were analyzed, applying PNF and/or electrical stimulation methods, pharmacological treatment, low-level laser treatment, subcutaneous collagen injections, and physiotherapy protocols involving facial expression exercises, yielding evidence for the variables assessed. Conclusions: PNF and/or electrical stimulation treatment in patients with PFP can be effective when employed early with appropriate parameters, showing promising results in improving quality of life, facial movement quality, and CMAP and reducing both the incidence and degree of synkinesis.

Introducción: Las tendinopatías son altamente prevalentes, especialmente entre los atletas. Este estudio analiza la evidencia científica sobre los efectos del entrenamiento con volante de inercia en los factores de riesgo de la tendinopatía. Métodos: Se realizó una revisión sistemática siguiendo las directrices PRISMA, con búsquedas en CINAHL, Medline, PubMed, Scopus y Web of Science. Se incluyeron ensayos clínicos aleatorizados y estudios clínicos que evaluaban ejercicios de resistencia con volante de inercia para la tendinopatía. Se excluyeron estudios que no valorasen cambios funcionales, morfológicos o fisiológicos en el tendón. Tres revisores extrajeron y evaluaron la calidad de los datos de manera independiente. Resultados: Cinco estudios cumplieron los criterios de inclusión, con adultos deportistas en riesgo o diagnosticados con tendinopatía rotuliana, así como atletas sanos. Los protocolos de entrenamiento duraron entre seis y 24 semanas. La mayoría de los estudios reportaron mejoras significativas en fuerza y potencia, además de cambios estructurales como aumento del área transversal del tendón y reducción de su temperatura. Conclusiones: El entrenamiento con volante de inercia mejora la fuerza, la potencia y la adaptación del tendón en individuos físicamente activos. No obstante, se requieren estudios a gran escala y con mayor seguimiento para confirmar su efectividad en poblaciones más amplias y en la prevención de tendinopatías.

Background/Objectives: During the Coronavirus Disease 2019 (COVID-19) pandemic, various safety measures were implemented in elderly care facilities in Spain. These measures led to a reduction in physical activity and increased supervision of residents, often resulting in the suspension of outings from the facility. The objective of this study was to assess the influence of COVID-19 preventive measures on the number and characteristics of falls among elderly individuals living in a residential care facility in Spain. Methods: A retrospective longitudinal observational study was conducted from 2018 to 2021. Over these four years, data related to falls were collected from a residential care facility for the elderly. Both patient characteristics and fall characteristics were recorded. Results: The average age of the 48 residents continuously institutionalized between 2018 and 2021 was 85.8 ± 5.1 years. A total of 364 falls occurred during the study period, with 68% of them taking place in 2019 and 2020. Although the number of falls increased during the COVID-19 pandemic, the characteristics of the falls did not change. However, residents who experienced falls were increasingly accompanied at the time of the event. Conclusions: Based on the data collected from the elderly care facility analyzed in this study, falls increased during the COVID-19 pandemic, but the measures implemented in residential care facilities do not appear to have altered the characteristics of the falls, except for the greater presence of companionship.

Introducción: Esta revisión sistemática se realizó debido a la alta incidencia de prolapso de órganos pélvicos entre mujeres primíparas y multíparas. Se evaluó la efectividad de los tratamientos conservadores para el prolapso en mujeres postparto, centrándose en el entrenamiento muscular del suelo pélvico y en terapias complementarias como la estimulación eléctrica y vibratoria. Métodos: Siguiendo las directrices PRISMA y registrada en PROSPERO, se realizó una búsqueda exhaustiva en siete bases de datos (incluyendo PubMed, PEDro, Cochrane Library y ClinicalTrials.gov) utilizando términos relacionados con prolapso, terapéutica y salud de la mujer. Se seleccionaron ensayos controlados aleatorizados publicados desde el 2013. Dos revisores independientes evaluaron la calidad Metodológica utilizando la escala PEDro y la herramienta RoB 2. Objetivo: Comparar la eficacia de los tratamientos conservadores en el prolapso de órganos pélvicos en mujeres primíparas y/o multíparas. Resultados: Se incluyeron cinco estudios (n = 1305 mujeres). La calidad metodológica fue buena (puntuación PEDro media de siete). Los ensayos demostraron mejoras significativas a corto plazo en la fuerza muscular del suelo pélvico con el entrenamiento muscular solo o combinado con estimulación eléctrica o vibratoria. Sólo un estudio abordó específicamente el dolor y la función sexual, e informó una reducción del dolor y una mejoría de la función sexual con los dispositivos vibratorios. Conclusiones: Los tratamientos conservadores, en particular el entrenamiento muscular solo o en combinación, ofrecen beneficios a corto plazo en la fuerza muscular y el alivio de los síntomas. Se necesita más investigación sobre resultados a largo plazo y la calidad de vida.