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1.
Front Public Health ; 11: 1274047, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-38035291

RESUMO

Introduction: Reliable and valid assessment tools are needed to evaluate and predict physical function in older hospitalized patients. The aim of this study is to develop the Italian version of the Elderly Mobility Scale (I-EMS) and to evaluate its validity and inter-rater reliability for use with geriatric inpatients. Methods: The study consists of two phases: (i) translation, where EMS version 2 was translated into Italian by two teams, each comprising 2 bilingual physiotherapists; translations were back translated by 2 native English speakers, and a committee of 2 physiotherapists and 1 physician refined the initial I-EMS version, which was pilot-tested for clarity in a group of ten experienced geriatric physiotherapists; (ii) an observational study assessed I-EMS metrics (reliability, validity) in older Italian inpatients at IRCCS INRCA (Ancona, Italy) between September 2022 and April 2023. Results: No statistically significant differences were found between the scores of individual items and the total score assigned by different raters. The ICC for total I-EMS was 0.951, SEM was 1.10 and MDC95 was 3.06. The absolute agreement and weighted kappa for individual items ranged 80.32-100% and 8.2-1, respectively. The validity of I-EMS was supported by a significant (p < 0.05) correlation with the Barthel Index (r = 0.827 and 0.834 for the I-EMS administered by rater A and rater B, respectively). Conclusion: I-EMS showed good internal consistency and inter-rater reliability, and confirmed construct validity with respect to BI. Therefore, it can safely be used as an assessment tool for hospitalized Italian geriatric patients. Clinical trial registration: [ClinicalTrials.gov], [NCT05806242].


Assuntos
Reprodutibilidade dos Testes , Humanos , Idoso , Itália
2.
Front Neurol ; 13: 964454, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36034306

RESUMO

Introduction: Alzheimer's disease is a neurodegenerative syndrome characterized by cognitive deficits, loss of daily functions, and mental and behavioral disorders, which cause stress and negatively affect the quality of life. Studies in the field suggest that combining cognitive training with physical activity can reduce the risk of developing the disease and, once neurodegeneration has begun, it slows its progress. In particular, virtual reality and augmented reality administer cognitive stimulation while providing a link to autobiographical memory through reminiscence, enabling the improvement of the person's quality of life. The present protocol aims to evaluate the effectiveness of cognitive and physical treatments, integrated with the addition of virtual reality and reminiscence elements, using the Brainer software, in which people will find cognitive training, and the jDome® BikeAround™ system, which will allow participants to pedal along a personalized path projected on a schematic, using an exercise bike connected to the system. Methods and analysis: For this study, 78 patients with mild Alzheimer's dementia were recruited and divided into the Experimental Group (EG) and Control Group (CG). Sixteen treatment sessions of 60 min each were conducted for both groups (2 training sessions per week, for 8 weeks), including 1 patient at a time. The EG received cognitive treatment with Brainer and physical training with jDome, while the CG received cognitive treatment with Brainer and physical training with a classic bicycle. The evaluation mainly focused on the assessment of the person's cognitive status. Other analyses were conducted on the quality of life, mood, behavioral disorders, and physical function, which were considered secondary outcomes. Discussions: The ultimate goal of the present study is to test the effectiveness of a treatment for people with mild Alzheimer's focused on the integration of cognitive training and aerobic physical activity, using an exercise bike, with the addition of virtual reality and reminiscence elements. Ethics and dissemination: The study was approved by the Ethics Committee of the IRCCS INRCA. It was recorded in ClinicalTrials.gov on 2 June 2022 with the number NCT05402423. The study findings will be used for publication in peer-reviewed scientific journals and presentations in scientific meetings.

3.
Trials ; 22(1): 400, 2021 Jun 14.
Artigo em Inglês | MEDLINE | ID: mdl-34127032

RESUMO

BACKGROUND: Stroke is a leading cause of disability, injury, and death in elderly people and represents a major public health problem with substantial medical and economic consequences. The incidence of stroke rapidly increases with age, doubling for each decade after age 55 years. Gait impairment is one of the most important problems after stroke, and improving walking function is often a key component of any rehabilitation program. To achieve this goal, a robotic gait trainer seems to be promising. In fact, some studies underline the efficacy of robotic gait training based on end-effector technology, for different diseases, in particular in stroke patients. In this randomized controlled trial, we verify the efficacy of the robotic treatment in terms of improving the gait and reducing the risk of falling and its long-term effects. METHODS: In this single-blind randomized controlled trial, we will include 152 elderly subacute stroke patients divided in two groups to receive a traditional rehabilitation program or a robotic rehabilitation using G-EO system, an end-effector device for the gait rehabilitation, in addition to the traditional therapy. Twenty treatment sessions will be conducted, divided into 3 training sessions per week, for 7 weeks. The control group will perform traditional therapy sessions lasting 50 min. The technological intervention group, using the G-EO system, will carry out 30 min of traditional therapy and 20 min of treatment with a robotic system. The primary outcome of the study is the evaluation of the falling risk. Secondary outcomes are the assessment of the gait improvements and the fear of falling. Further evaluations, such as length and asymmetry of the step, walking and functional status, and acceptance of the technology, will be carried. DISCUSSION: The final goal of the present study is to propose a new approach and an innovative therapeutic plan in the post-stroke rehabilitation, focused on the use of a robotic device, in order to obtain the beneficial effects of this treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT04087083 . Registered on September 12, 2019.


Assuntos
Reabilitação do Acidente Vascular Cerebral , Acidente Vascular Cerebral , Acidentes por Quedas , Idoso , Terapia por Exercício , Medo , Marcha , Humanos , Pessoa de Meia-Idade , Ensaios Clínicos Controlados Aleatórios como Assunto , Método Simples-Cego , Acidente Vascular Cerebral/diagnóstico , Acidente Vascular Cerebral/terapia , Resultado do Tratamento
4.
Data Brief ; 27: 104793, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31788519

RESUMO

Sport Database is a collection of 126 cardiorespiratory data, acquired through wearable sensors from 81 subjects while practicing 10 different sports. Each cardiorespiratory dataset consists of demographic info (gender, age, weight, height, smoking habit, alcohol consumption and weekly training rate), cardiorespiratory signals (electrocardiogram, heart-rate series, RR-interval series and breathing-rate series) and training notes. Demographic info was collected by survey. Cardiorespiratory signals were acquired through the chest strap BioHarness 3.0 by Zephyr. Eventually, training notes including the sport-dependent training protocol, were manually annotated. Sport Database may be useful to support: 1) the investigation of cardiorespiratory system adaptations to different types of physical exercise; 2) the development of automatic algorithms finalized to real-time health monitoring of athletes and preventive identification of subjects at increased risk of sport-related sudden cardiac death; and, 3) clinical testing of the BioHarness 3.0 by Zephyr. Further acquisitions could involve other sports, other cardiovascular signals and/or parameters, data from different biological systems, and other acquisition devices.

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