Methods of Evidence-based medicine for patients after stroke with early Spasticity
Bibliographic record
Abstract
аcute cerebrovascular accident is the main cause of disability. Stroke has different clinical characteristics and consequences that require individual rehabilitation examination and approach. Adverse neurological disorders are accompanied by motor, cognitive, and psycho-emotional consequences. Over the past 20 years, the treatment of acute cerebrovascular accidents has significantly increased the recovery rates of patients. This is due to the progress of international clinical protocols, randomized evidence-based medicine, adequate medication, step-by-step and individualized physical therapy, and occupational therapy strategies for patients. One of the most important contributions to rehabilitation for stroke patients is made by evidence-based medicine. The literature review highlights current evidence and critical appraisal to confirm the effectiveness of evidence-based medicine in rehabilitation interventions to improve movement control, activity, participation, and functioning. The benefits of rehabilitation interventions on spasticity after stroke in the early period have been proven. However, even after medical and rehabilitation, the restoration of motor function remains insufficient to achieve the patient's request, due to inconsistent application of evidence-based medicine. The purpose of the literature review is to analyze the effectiveness of evidence-based medicine in rehabilitation interventions for people after early stroke with spasticity to improve quality of life and motor function. Materials and methods. In this review, we analyzed rehabilitation interventions and evidence-based medicine in physical therapy. We substantiated the materials of the Canadian Clinician's Guide to Stroke Rehabilitation for 2020. The review includes scientific publications in English. Articles and research by scientists published over the past 15 years. A computer search was conducted through the PubMed database. We considered 63 publications that were evaluated according to the following criteria: reliability, validity, and measurability. The changes that have occurred during the research have been analyzed. Conclusions. Spasticity in the late period after acute cerebrovascular accident has significant negative consequential difficulties that patients are unable to cope with on their own. We have found that rehabilitation measures and physical therapy techniques improve the motor functions of patients with spasticity in the early period, provided that the recommendations of evidence-based medicine are followed. The timely use of methods, tools, and an individualized approach to each patient gives positive results. After all, the purpose of physical therapy is not to convince patients that the consequences of stroke are not subject to rehabilitation, but to help and teach patients to be independent and improve the quality of life of people with spasticity in the early or late period. It was also determined that the topic of recovery of patients with late-onset spasticity after stroke is not sufficiently covered. To date, more than half of people after stroke remain limited in everyday activities and have negative consequences - motor disorders, and activity limitations that significantly affect the quality of life and independence. Further research is needed to determine whether it is possible to reduce late-onset spasticity and improve the motor function of patients after stroke with the possibility of further use of the affected limb.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".