Publications by authors named "P Pillastrini"
Vestibular rehabilitation, an evidence-based physical therapy approach, plays a crucial role in managing and recovering from gaze and balance disorders, including those of central origin. This study, targeted at the community of Italian healthcare practitioners, is vital in understanding the application of vestibular rehabilitation in neurological disorders and in identifying knowledge gaps, barriers, and future directions. This is a cross-sectional study directed at healthcare professionals involved in neurorehabilitation in Italy.
View Article and Find Full Text PDFPurpose: A number of studies have explored patients' subjective experience of waiting for spinal surgery, however, they did so through an investigation conducted post-operatively. Thus, the aim of this study was to explore the experience of patients while still on the waitlist for lumbar spinal arthrodesis.
Methods: This qualitative study of semi-structured interviews was conducted at an orthopedic research institute in Italy.
Article Synopsis
- The study aimed to compare the effectiveness of tele-rehabilitation (TR) versus conventional rehabilitation (CT) in lowering pain levels in patients with knee osteoarthritis (OA), along with assessing physical function and quality of life.
- Fifty-five patients were randomly divided into the TR group, which received remote physiotherapy, and the CT group, which engaged in traditional rehabilitation, with outcomes evaluated at baseline and after three months.
- Both groups showed significant improvements in pain and quality of life measures after three months, indicating that tele-rehabilitation is a viable alternative to conventional methods for treating knee OA.
Background: Multiple Sclerosis (MS) is the most prevalent autoimmune neurological condition in the world, leading to a wide variety of symptoms, including balance disorders.
Objective: To evaluate the angular vestibulo-ocular reflex (aVOR) of all six semicircular canals (SCCs) through Head Impulse (HIMP) and Suppression HIMP (SHIMP) paradigms and any correlations with clinical balance scales.
Methods: All participants were assessed using the Expanded Disability Status Scale (EDSS), Berg Balance Scale (BBS), and Mini-BESTest (MBT).
Background: Artificial intelligence (AI) chatbots are emerging educational tools for students in healthcare science. However, assessing their accuracy is essential prior to adoption in educational settings. This study aimed to assess the accuracy of predicting the correct answers from three AI chatbots (ChatGPT-4, Microsoft Copilot and Google Gemini) in the Italian entrance standardized examination test of healthcare science degrees (CINECA test).
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