Objective To discuss the association between the length of stay at the intensive care unit (ICU) and sarcopenia among hemiplegic stroke patients.
Methods This study evaluated 66 hemiplegic stroke patients with history of ICU admission using handgrip strength and bioelectrical impedance analysis to obtain height-adjusted appendicular skeletal muscle mass. The diagnosis of sarcopenia was made according to the muscle mass based on the Asian Working Group for Sarcopenia. The patients were divided into sarcopenic and non-sarcopenic groups. The two groups were statistically analyzed, and the significant factors with differences were studied. A multivariate logistic regression analysis was performed to examine the association between length of stay in the ICU and sarcopenia, after adjusting for potential confounders.
Results Among 66 hemiplegic patients with an ICU admission history, 12 patients were diagnosed with sarcopenia. Sarcopenia patients showed lower scores on the Korean version of the Modified Barthel Index and the Korean version of the Mini-Mental State Examination. Additionally, patients with sarcopenia had a longer length of stay in the ICU, and univariate and multivariate analyses confirmed that the ICU length of stay was significantly related to sarcopenia (adjusted odds ratio=1.187; 95% confidence interval, 1.019–1.382; p=0.028).
Conclusion The length of stay in the ICU was significantly associated with sarcopenia in hemiplegic stroke patients.
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Objective To evaluate the gait pattern of patients with gait disturbances without consideration of defilades due to assistive devices. This study focuses on gait analysis using the inertial measurement unit (IMU) system, which can also be used to determine the most appropriate assistive device for patients with gait disturbances.
Methods Records of 18 disabled patients who visited the Department of Rehabilitation from May 2018 to June 2018 were selected. Patients’ gait patterns were analyzed using the IMU system with different assistive devices to determine the most appropriate device depending on the patient’s condition. Evaluation was performed using two or more devices, and the appropriate device was selected by comparing the 14 parameters of gait evaluation. The device showing measurements nearer or the nearest to the normative value was selected for rehabilitation.
Results The result of the gait evaluation in all 18 patients was analyzed using the IMU system. According to the records, the patients were evaluated using various assistive devices without consideration of defilades. Moreover, this gait analysis was effective in determining the most appropriate device for each patient. Increased gait cycle time and swing phase and decreased stance phase were observed in devices requiring significant assistance.
Conclusion The IMU-based gait analysis system is beneficial in evaluating gait in clinical fields. Specifically, it is useful in evaluating patients with gait disturbances who require assistive devices. Furthermore, it allows the establishment of an evidence-based decision for the most appropriate assistive walking devices for patients with gait disturbances.
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