ABSTRACT
Purpose@#The effect of prehabilitation in patients with frailty undergoing colorectal cancer surgery remains controversial. This meta-analysis aimed to assess the impact of prehabilitation before colorectal surgery on the functional outcomes and postoperative complications in patients with frailty undergoing colorectal cancer surgery. @*Methods@#PubMed, EMBASE, Cochrane Library, and Scopus databases were searched for articles published up to November 9, 2022. We included randomized and non-randomized trials in which the effects of prehabilitation in patients with frailty undergoing colorectal cancer surgery were investigated against a control group. Data extracted for our metaanalysis included the 6-minute walk test (6MWT), postoperative incidence of complications (Clavien-Dindo classification ≥IIIa), comprehensive complication index (CCI), and length of stay (LOS) in the hospital. @*Results@#Compared with the control group, we found a significant improvement in the incidence of postoperative complications and shorter LOS in the hospital in the prehabilitation group. However, the 6MWT and CCI results showed no significant differences between the 2 groups. @*Conclusion@#Prehabilitation in patients with frailty who underwent colorectal cancer surgery improved the incidence of postoperative complications and LOS in the hospital. Hence, clinicians should consider conducting or recommending prehabilitation exercises prior to colorectal cancer surgery in patients with frailty.
ABSTRACT
A narrative review was conducted of machine learning applications and research in the field of stroke rehabilitation. The machine learning models commonly used in medical research include random forest, logistic regression, and deep neural networks. Convolutional neural networks (CNNs), a type of deep neural network, are typically used for image analysis.Machine learning has been used in stroke rehabilitation to predict recovery of motor function using a large amount of clinical data as input. Recent studies on predicting motor function have trained CNN models using magnetic resonance images as input data together with clinical data to increase the accuracy of motor function prediction models. Additionally, a model interpreting videofluoroscopic swallowing studies was developed and investigated. In the future, we anticipate that machine learning will be actively used to treat stroke patients, such as predicting the occurrence of depression and the recovery of language, cognitive, and sensory function, as well as prescribing appropriate rehabilitation treatments.
ABSTRACT
Background@#Videofluoroscopic swallowing study (VFSS) is currently considered the gold standard to precisely diagnose and quantitatively investigate dysphagia. However, VFSS interpretation is complex and requires consideration of several factors. Therefore, considering the expected impact on dysphagia management, this study aimed to apply deep learning to detect the presence of penetration or aspiration in VFSS of patients with dysphagia automatically. @*Methods@#The VFSS data of 190 participants with dysphagia were collected. A total of 10 frame images from one swallowing process were selected (five high-peak images and five low-peak images) for the application of deep learning in a VFSS video of a patient with dysphagia. We applied a convolutional neural network (CNN) for deep learning using the Python programming language. For the classification of VFSS findings (normal swallowing, penetration, and aspiration), the classification was determined in both high-peak and lowpeak images. Thereafter, the two classifications determined through high-peak and low-peak images were integrated into a final classification. @*Results@#The area under the curve (AUC) for the validation dataset of the VFSS image for the CNN model was 0.942 for normal findings, 0.878 for penetration, and 1.000 for aspiration. The macro average AUC was 0.940 and micro average AUC was 0.961. @*Conclusion@#This study demonstrated that deep learning algorithms, particularly the CNN, could be applied for detecting the presence of penetration and aspiration in VFSS of patients with dysphagia.
ABSTRACT
Objectives@#Sarcopenia is a common disease in the elderly population that causes disability, poor quality of life, and a high risk of death. In the current study, we conducted a meta-analysis to report basic knowledge about the prevalence of sarcopenia in the elderly in Korea. @*Methods@#We searched for articles in the MEDLINE, Cochrane Library, Embase, and Scopus databases published until December 28, 2020. Studies investigating the prevalence of sarcopenia in elderly Koreans aged ≥65 years were included. The methodological quality of the studies was evaluated using the Newcastle-Ottawa scale. Publication bias was evaluated using the Egger test and funnel plots. @*Results@#In total, 3 studies and 2922 patients were included in the meta-analysis. All 3 studies used the European Working Group on Sarcopenia in Older People criteria for the diagnosis of sarcopenia. The total prevalence of sarcopenia was 13.1-14.9% in elderly men and 11.4% in elderly women. @*Conclusions@#This meta-analysis is the first to estimate the pooled prevalence of sarcopenia in elderly Koreans, and its findings suggest that sarcopenia is common in this population. Therefore, attention should be paid to the prevention and control of sarcopenia.
ABSTRACT
Objectives@#Sarcopenia is a common disease in the elderly population that causes disability, poor quality of life, and a high risk of death. In the current study, we conducted a meta-analysis to report basic knowledge about the prevalence of sarcopenia in the elderly in Korea. @*Methods@#We searched for articles in the MEDLINE, Cochrane Library, Embase, and Scopus databases published until December 28, 2020. Studies investigating the prevalence of sarcopenia in elderly Koreans aged ≥65 years were included. The methodological quality of the studies was evaluated using the Newcastle-Ottawa scale. Publication bias was evaluated using the Egger test and funnel plots. @*Results@#In total, 3 studies and 2922 patients were included in the meta-analysis. All 3 studies used the European Working Group on Sarcopenia in Older People criteria for the diagnosis of sarcopenia. The total prevalence of sarcopenia was 13.1-14.9% in elderly men and 11.4% in elderly women. @*Conclusions@#This meta-analysis is the first to estimate the pooled prevalence of sarcopenia in elderly Koreans, and its findings suggest that sarcopenia is common in this population. Therefore, attention should be paid to the prevention and control of sarcopenia.
ABSTRACT
Spinal pain is a common patient complaint in clinical practice. Conservative treatment methods include oral medication, physical therapy, injections, and spinal orthoses. The clinical application of orthoses is debated because of potential complications associated with long-term use, such as muscle weakness and joint contracture. We reviewed the orthoses most frequently used to manage spinal pain. We review the use of soft cervical and Philadelphia collars, lumbosacral corsets, and thoracolumbosacral orthosis to manage spinal pain. Spinal orthoses can help reduce pain by protecting the muscles and joints of the injured spinal region, preventing or correcting malformations, and limiting trunk flexion, extension, lateral flexion, and rotation. The short-term use of spinal orthoses is known to improve pain and disability during the treatment period without significant adverse effects. Spinal orthoses are expected to alleviate pain and improve patients’ lifestyle.