Dataset Information

Perturbation-Based Balance Training in Postoperative Individuals With Degenerative Cervical Myelopathy.

ABSTRACT: Degenerative cervical myelopathy (DCM) is a common aging condition caused by spinal cord compression. Individuals with DCM often presented with residual balance and functional impairments postoperatively. Perturbation-based balance training (PBT) has been shown to have positive effects on populations with neurological disorders but has yet to be investigated in DCM. The objective of this study was therefore to evaluate the effects of PBT on balance and functional performance in postoperative individuals with DCM. Fifteen postoperative individuals with DCM (DCM group) and 14 healthy adults (healthy control group) were recruited. The DCM group received a 4-weeks PBT using a perturbation treadmill. The outcome measures included mean velocity of center of pressure (COP) during quiet standing; center of mass (COM) variance and reaction time to balance perturbation during standing with forward and backward perturbation; gait speed during level ground walking; Timed Up and Go Test (TUG) and disability questionnaire scores including Visual Analog Scale, Neck Disability Index, and Lower Extremity Function of Japanese Orthopaedic Association Cervical Myelopathy Evaluation Questionnaire. The assessments were conducted pre- and post-training postoperatively for the DCM group but only once for the healthy control group. Significant improvements were observed in the mean velocity of COP, COM variance, reaction time, gait speed, and TUG in the DCM group. Disability questionnaire scores were not significantly different after training in DCM group. For between-group comparisons, significant differences that were observed pre-training were not observed post-training. The 4-weeks PBT is a potential rehabilitation strategy for addressing balance and functional impairment in postoperative individuals with DCM. In addition, the post-training performance in the DCM group exhibited trends comparable to those of age-matched healthy controls. Furthermore, the training regimens offer a practical reference for future studies on populations with balance disorders. Future studies complemented with neurophysiological assessments could reveal more information of the underlying mechanisms of PBT.

SUBMITTER: Cheng YS

PROVIDER: S-EPMC7044125 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Perturbation-Based Balance Training in Postoperative Individuals With Degenerative Cervical Myelopathy.

Cheng Yi-Shan YS Chien Andy A Lai Dar-Ming DM Lee Ya-Yun YY Cheng Chih-Hsiu CH Wang Shwu-Fen SF Chang Ya-Ju YJ Wang Jaw-Lin JL Hsu Wei-Li WL

Frontiers in bioengineering and biotechnology 20200220

Degenerative cervical myelopathy (DCM) is a common aging condition caused by spinal cord compression. Individuals with DCM often presented with residual balance and functional impairments postoperatively. Perturbation-based balance training (PBT) has been shown to have positive effects on populations with neurological disorders but has yet to be investigated in DCM. The objective of this study was therefore to evaluate the effects of PBT on balance and functional performance in postoperative ind ...[more]

PMID: 32154235

Similar Datasets

Project description:BackgroundDegenerative cervical myelopathy (DCM), a progressive spinal cord injury caused by spinal cord compression from degenerative pathology, often presents with neck pain, sensorimotor dysfunction in the upper or lower limbs, gait disturbance, and bladder or bowel dysfunction. Its symptomatology is very heterogeneous, making early detection as well as the measurement or understanding of the underlying factors and their consequences challenging. Increasingly, evidence suggests that DCM may consist of subgroups of the disease, which are yet to be defined.ObjectiveThis study aimed to explore whether machine learning can identify clinically meaningful groups of patients based solely on clinical features.MethodsA survey was conducted wherein participants were asked to specify the clinical features they had experienced, their principal presenting complaint, and time to diagnosis as well as demographic information, including disease severity, age, and sex. K-means clustering was used to divide respondents into clusters according to their clinical features using the Euclidean distance measure and the Hartigan-Wong algorithm. The clinical significance of groups was subsequently explored by comparing their time to presentation, time with disease severity, and other demographics.ResultsAfter a review of both ancillary and cluster data, it was determined by consensus that the optimal number of DCM response groups was 3. In Cluster 1, there were 40 respondents, and the ratio of male to female participants was 13:21. In Cluster 2, there were 92 respondents, with a male to female participant ratio of 27:65. Cluster 3 had 57 respondents, with a male to female participant ratio of 9:48. A total of 6 people did not report biological sex in Cluster 1. The mean age in this Cluster was 56.2 (SD 10.5) years; in Cluster 2, it was 54.7 (SD 9.63) years; and in Cluster 3, it was 51.8 (SD 8.4) years. Patients across clusters significantly differed in the total number of clinical features reported, with more clinical features in Cluster 3 and the least clinical features in Cluster 1 (Kruskal-Wallis rank sum test: χ22=159.46; P<.001). There was no relationship between the pattern of clinical features and severity. There were also no differences between clusters regarding time since diagnosis and time with DCM.ConclusionsUsing machine learning and patient-reported experience, 3 groups of patients with DCM were defined, which were different in the number of clinical features but not in the severity of DCM or time with DCM. Although a clearer biological basis for the clusters may have been missed, the findings are consistent with the emerging observation that DCM is a heterogeneous disease, difficult to diagnose or stratify. There is a place for machine learning methods to efficiently assist with pattern recognition. However, the challenge lies in creating quality data sets necessary to derive benefit from such approaches.

Project description:BackgroundDegenerative cervical myelopathy (DCM) is widely accepted as the most common cause of adult myelopathy worldwide. Despite this, there is no specific term or diagnostic criteria in the International Classification of Diseases 11th Revision and no Medical Subject Headings (MeSH) or an equivalent in common literature databases. This makes searching the literature and thus conducting systematic reviews or meta-analyses imprecise and inefficient. Efficient research synthesis is integral to delivering evidence-based medicine and improving research efficiency.ObjectiveThis study aimed to illustrate the difficulties encountered when attempting to carry out a comprehensive and accurate evidence search in the field of DCM by identifying the key sources of imprecision and quantifying their impact.MethodsTo identify the key sources of imprecision and quantify their impact, an illustrative search strategy was developed using a validated DCM hedge combined with contemporary strategies used by authors in previous systematic reviews and meta-analyses. This strategy was applied to Medical Literature Analysis and Retrieval System Online (MEDLINE) and Excerpta Medica dataBASE (EMBASE) databases looking for relevant DCM systematic reviews and meta-analyses published within the last 5 years.ResultsThe MEDLINE via PubMed search strategy returned 24,166 results, refined to 534 papers after the application of inclusion and exclusion criteria. Of these, 32.96% (176/534) results were about DCM, and 18.16% (97/534) of these were DCM systematic reviews or meta-analyses. Non-DCM results were organized into imprecision categories (spinal: 268/534, 50.2%; nonspinal: 84/534, 15.5%; and nonhuman: 8/534, 1.5%). The largest categories were spinal cord injury (75/534, 13.67%), spinal neoplasms (44/534, 8.24%), infectious diseases of the spine and central nervous system (18/534, 3.37%), and other spinal levels (ie, thoracic, lumbar, and sacral; 18/534, 3.37%). Counterintuitively, the use of human and adult PubMed filters was found to exclude a large number of relevant articles. Searching a second database (EMBASE) added an extra 12 DCM systematic reviews or meta-analyses.ConclusionsDCM search strategies face significant imprecision, principally because of overlapping and heterogenous search terms, and inaccurate article indexing. Notably, commonly employed MEDLINE filters, human and adult, reduced search sensitivity, whereas the related articles function and the use of a second database (EMBASE) improved it. Development of a MeSH labeling and a standardized DCM definition would allow comprehensive and specific indexing of DCM literature. This is required to support a more efficient research synthesis.

Project description:OBJECTIVES:No intervention has been shown to prevent falls poststroke. We aimed to determine if perturbation-based balance training (PBT) can reduce falls in daily life among individuals with chronic stroke. DESIGN:Assessor-blinded randomised controlled trial. SETTING:Two academic hospitals in an urban area. INTERVENTIONS:Participants were allocated using stratified blocked randomisation to either 'traditional' balance training (control) or PBT. PBT focused on improving responses to instability, whereas traditional balance training focused on maintaining stability during functional tasks. Training sessions were 1 hour twice/week for 6 weeks. Participants were also invited to complete 2 'booster' training sessions during the follow-up. PARTICIPANTS:Eighty-eight participants with chronic stroke (>6 months poststroke) were recruited and randomly allocated one of the two interventions. Five participants withdrew; 42 (control) and 41 (PBT group) were included in the analysis. PRIMARY AND SECONDARY OUTCOME MEASURES:The primary outcome was rate of falls in the 12 months post-training. Negative binomial regression was used to compare fall rates between groups. Secondary outcomes were measures of balance, mobility, balance confidence, physical activity and social integration. RESULTS:PBT participants reported 53 falls (1.45 falls/person-year) and control participants reported 64 falls (1.72 falls/person-year; rate ratio: 0.85(0.42 to 1.69); p=0.63). Per-protocol analysis included 32 PBT and 34 control participants who completed at least 10/12 initial training sessions and 1 booster session. Within this subset, PBT participants reported 32 falls (1.07 falls/person-year) and control participants reported 57 falls (1.75 falls/person-year; rate ratio: 0.62(0.29 to 1.30); p=0.20). PBT participants had greater improvement in reactive balance control than the control group, and these improvements were sustained 12 months post-training. There were no intervention-related serious adverse effects. CONCLUSIONS:The results are inconclusive. PBT may help to prevent falls in daily life poststroke, but ongoing training may be required to maintain the benefits. TRIAL REGISTRATION NUMBER:ISRCTN05434601; Results.

Dataset Information

Perturbation-Based Balance Training in Postoperative Individuals With Degenerative Cervical Myelopathy.

Publications

Perturbation-Based Balance Training in Postoperative Individuals With Degenerative Cervical Myelopathy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets