Aims To assess the functional and clinical outcome in a sizeable cohort of patients with osmotic demyelination syndrome (ODS) and to characterise the factors which could predict the final outcome. Methods Twenty five consecutive patients with ODS formed the study cohort. The diagnosis of ODS was based on clinical features with corroborating imaging findings. Two functional scales—Functional Independent Measure (FIM) and Disability Rating Scale (DRS)—were applied to assess the functional status at the time of admission, discharge and last follow-up. Patients who became independent for activities of daily living (ADL) at last follow-up were classified as favourable outcome, and those who died or became dependent for ADL were classified as a poor outcome group respectively. The Fisher exact test and Mann–Whitney U test were used to assess categorical and continuous variables respectively. Results The mean age at diagnosis was 53±14 years. Five (20%) had central pontine myelinolysis, seven (28%) had extrapontine myelinolysis, and 13 (52%) had both. Hyponatraemia and hypokalaemia were noted in 20 (80%) and 10 (40%) patients respectively. Six (24%) received intravenous methylprednisolone. Eleven (46%) had a favourable outcome at a mean follow-up of 2.2±2.5 years. Hyponatraemia ≤115 mEq (p=0.04), associated hypokalaemia (p=0.04) and low Glasgow Coma Scale (GCS) (p=0.008) at presentation were predictive of poor outcome. The mean FIM score at admission (p=0.05) and at discharge (p=0.01), and mean DRS at admission (p=0.05) were predictive of poor outcome. Conclusions Higher GCS scores, better scores in functional scales in hospital, less severe hyponatraemia and absence of superadded hypokalaemia predicted favourable outcome.

[Purpose] The acquisition of motor skills are fundamental to human life. There is a lack of research on whether knowledge of performance or knowledge of result as augmented feedback is more effective. The objective of this study was to compare the effectiveness of knowledge of result and knowledge of performance in the learning of a skilled motor activity by healthy young adults. [Subjects and Methods] A total of thirty healthy young adult males and females without any neurological or musculoskeletal impairment, between the age of 18-30 years were the subjects of the study. They were randomly allocated to 2 groups: group 1 was given knowledge of result as feedback, and knowledge of performance was given as feedback to group 2. Both the groups practiced the task of throwing a soft spongy ball for 6 days per week for 4 weeks, with 40 trials each day. The outcome measure used was the distance of the throw. [Results] The results were analyzed using the t-test. The mean distances thrown by both the groups showed highly significant improvements and throwing distance of group 2 showed better improvement than that of group 1. [Conclusion] Both types of augmented feedback were effective at improving skilled motor activity, but the knowledge of performance group showed better improvement than the knowledge of result group.

Stroke is a major cause of disability worldwide, and balance impairments are common disabling factors in patients with stroke, leading to falls. Thus, the study objectives were as follows: (i) To find the prevalence of balance impairment among patients with stroke. (ii) To find out the factors associated with balance impairment in patients with stroke. This cross-sectional retrospective case control study involved eighty-one post stroke patients with a mean age of 58.36 ± 14.06, recruited from six hospitals, who underwent an assessment of balance, walking speed, depression and isometric strength of the ankle and knee. These patients were later categorized into subjects with good balance (<45) in the Berg balance scale (BBS) and those with poor balance (≥45), as cases and controls, to assess the factors associated with balance impairment using binary logistic regression. The prevalence of balance impairment among patients with stroke was 48.1%. The reduction in power of knee flexors (OR = 0.858), knee extensors (OR = 0.880) and ankle dorsiflexors (OR = 0.820) was found to be significantly associated with balance impairment, along with speed (OR = 1.187 (95% CI = 1.100, 1.280)), depression (OR = 1.331 (95% CI = 1.055–1.679)) and activities of daily living (OR = 0.313 (95% CI = 0.150–0.650)). In summary, around half of the patients with stroke exhibited balance impairments, with females being more prone.

Background: The use of artificial intelligence (AI) in the field of rehabilitation is growing rapidly. Therefore, there is a need to understand how physical therapists (PTs) perceive AI technologies in clinical practice. Objective: This study aimed to investigate the knowledge and attitude of PTs regarding AI applications in rehabilitation based on multiple explanatory factors. Methods: A web-based Google Form survey, which was divided into 4 sections, was used to collect the data. A total of 317 PTs participated voluntarily in the study. Results: The PTs’ knowledge about AI applications in rehabilitation was lower than their knowledge about AI in general. We found a statistically significant difference in the PTs’ knowledge regarding AI applications in the rehabilitation field based on sex (odds ratio [OR] 2.43, 95% CI 1.53-3.87; P<.001). In addition, experience (OR 1.79, 95% CI 1.11-2.87; P=.02) and educational qualification (OR 1.68, 95% CI 1.05-2.70; P=.03) were found to be significant predictors of knowledge about AI applications. PTs who work in the nonacademic sector and who had <10 years of experience had positive attitudes regarding AI. Conclusions: AI technologies have been integrated into many physical therapy practices through the automation of clinical tasks. Therefore, PTs are encouraged to take advantage of the widespread development of AI technologies and enrich their knowledge about, and enhance their practice with, AI applications.

Artificial intelligence (AI) has been used in physical therapy diagnosis and management for various impairments. Physical therapists (PTs) need to be able to utilize the latest innovative treatment techniques to improve the quality of care. The study aimed to describe PTs’ views on AI and investigate multiple factors as indicators of AI knowledge, attitude, and adoption among PTs. Moreover, the study aimed to identify the barriers to using AI in rehabilitation. Two hundred and thirty-six PTs participated voluntarily in the study. A concurrent mixed-method design was used to document PTs’ opinions regarding AI deployment in rehabilitation. A self-administered survey consisting of several aspects, including demographic, knowledge, uses, advantages, impacts, and barriers limiting AI utilization in rehabilitation, was used. A total of 63.3% of PTs reported that they had not experienced any kind of AI applications at work. The major factors predicting a higher level of AI knowledge among PTs were being a non-academic worker (OR = 1.77 [95% CI; 1.01 to 3.12], p = 0.04), being a senior PT (OR = 2.44, [95%CI: 1.40 to 4.22], p = 0.002), and having a Master/Doctorate degree (OR = 1.97, [95%CI: 1.11 to 3.50], p = 0.02). However, the cost and resources of AI were the major reported barriers to adopting AI-based technologies. The study highlighted a remarkable dearth of AI knowledge among PTs. AI and advanced knowledge in technology need to be urgently transferred to PTs.