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Study On Clinical Predictors Of Strength Training Effect In Patients With Chronic Ankle Instability

Posted on:2021-11-12Degree:MasterType:Thesis
Country:ChinaCandidate:J X ShaoFull Text:PDF
GTID:2504306008487664Subject:Rehabilitation Medicine & Physical Therapy
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Purpose: Strength training is one of the important treatments for patients with chronic ankle instability,but not all patients who accept strength training can benefit from it.This study will analyze and combine the individual characteristics and different test indicators of patients with chronic ankle instability who has the greatest possibility to successfully treated after strength training,and help to provide more targeted clinical treatment on the scientific basis.Methods: This study was a prospective design study.Thirty-one patients with chronic ankle instability were included according to the screening criteria,and the patient’s personal information and injury history were recorded.Each patient was then subjected to a detailed physical examination,including various test indicators related to the risk factors for chronic ankle instability development,such as balance function,range of motion in ankle and hip joint,functional movement,etc.Regardless of clinical test results,all patients received a standardized strength training intervention program which is 3 times a week for 4 weeks.Patients were then divided into successful treatment group and failed treatment group based on their response to the training intervention(whether the improvement of FAAM-sport score is detectable clinically).The factors that show significant group difference were analyzed,and the sensitivity,specificity,positive likelihood ratios of all potential predictors were calculated.stepwise logistic regression were used to determine the optimal set of variables for predicting the success of the treatment.The predictors retained in the regression model were combined to identify the CAI patients most likely to benefit from strength training.Results: Eighteen(58%)of the 31 patients achieved successful treatment with an average improvement of 21.82% ± 6.98% in FAAM-s questionnaire,they were classified into success group.The remaining 13 subjects(42%)did not reach the minimum detectable difference of FAAM-s and increased only by 0.5%±4.0% on average,they were classified into failure group.Then the different characteristics of success and failure group subjects and laboratory tests were analyzed.P < 0.10 level of significance of the variables are retained as potential prediction variables,in order to prevent the potential variable from missing.The results show nine potential predictor variables have group differences,they are then entered into the logistic regression equation and the final four clinical predictors were identified: FAAM-s questionnaire score<73.4%,age < 23.5 years old,bilateral difference of ankle varus strength > 1.03,pain score > 4.5.If a patient satisfies the four prediction variables,he has a 94% possibility that can benefit from strength training significantly,if the patient is three of the four variables,the probability of its successful treatment will be increased from 58% to 87%,if the patient is two of the four variables,the probability of its successful treatment can be increased to 74%.Conclusion: The clinical prediction rules analyze and combine the clinical indicators of CAI patients who may benefit from strength training,so as to optimize the treatment efficiency and clinical effect.It was concluded that FAAM-s questionnaire score,age,bilateral difference in ankle varus strength and pain score were the most important characteristics to ensure the success of strength training intervention.However,the sample size of this study is small and it is only the first step in the process of developing and testing clinical prediction rules.Future research needs to verify the results of the study.It should include long-term follow-up,comparison groups,etc.to further determine these predictors in predictive value.
Keywords/Search Tags:chronic ankle instability, strength training, clinical prediction rule, self-evaluation function
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