Association between movement control during one-leg standing and femoral BMD in patients with hip fractures.

INTRODUCTION: Prior studies have focused only on the temporal component of one-leg standing, no reports have examined the relationship between the qualitative components of one-leg standing and femoral BMD. Thus, this study investigated whether quality (i.e., movement control) of one-leg standing also associated femoral BMD. MATERIALS AND METHODS: A total of 80 patients with unilateral hip fracture were included in a cross-sectional study. Basic and medical information and physical functions including movement control during one-leg standing were assessed at admission and 2 weeks after surgery, respectively. Hierarchical multiple regression analysis was performed to identify predictors of femoral BMDs on the non-fractured side. Dependent variables included femoral neck and total hip BMDs in models 1 and 2, respectively. RESULTS: Hierarchical multiple regression analysis (standardized partial regression coefficients) in model 1 identified age (- 0.18), sex (0.38), body mass index (BMI) (0.41), movement control during one-leg standing on the non-fractured side (0.19), and life-space assessment (0.17) as factors associating femoral neck BMD. Meanwhile, hierarchical multiple regression analysis (standardized partial regression coefficients) in model 2 identified age (- 0.12), sex (0.36), BMI (0.37), and movement control during one-leg standing on the non-fractured side (0.25) as factors associating total hip BMD. The coefficients of determination adjusted for degrees of freedom (R2) were 0.529 and 0.470 for models 1 and 2, respectively. CONCLUSION: Our results suggest that improving movement control during one-leg standing may be important for maintaining and improving femoral BMD on the non-fractured side.

Factors Affecting Quality of Life at Discharge among Patients with Osteoporotic Vertebral Fractures.

OBJECTIVES: This study aimed to identify factors, including physical functions and activities that affect quality of life (QOL) at discharge among patients with osteoporotic vertebral fractures. METHODS: Patients with osteoporotic vertebral fractures were included in our prospective cohort study. Multiple regression analysis was performed to determine the predictors of QOL at discharge using two models: model 1, basic medical information and physical functions at admission, and model 2, basic medical information, physical function, and activity after 4 weeks of admission. RESULTS: Multiple regression analysis (standard partial regression coefficients) using model 1 identified L2 to L4 bone mineral density (-0.2), Visual Analog Scale for pain during activity at admission (-0.31), and Revised Hasegawa Dementia Scale (HDS-R) score at admission (0.64) as factors affecting QOL at discharge. Multiple regression analysis using model 2 identified HDS-R at admission (0.64), Pain Catastrophizing Scale score at 4 weeks (-0.34), and knee extension muscle strength at 4 weeks (0.28) as factors affecting QOL at discharge. CONCLUSIONS: Our results suggest that if patients have high bone mineral density, intense pain, and low cognitive function at admission, then low QOL at discharge will be predicted; however, improvement of pain catastrophizing and knee extension muscle strength during first the 4 weeks of admission may be able to improve QOL at discharge. Because patients in this study were Japanese only, it is important to exercise caution when applying our results to other populations.

Physical Functions and Comorbidity Affecting Collapse at 4 or More Weeks after Admission in Patients with Osteoporotic Vertebral Fractures: A Prospective Cohort Study.

STUDY DESIGN: A prospective cohort study. PURPOSE: This study aimed to reveal physical functions and comorbidity affecting collapse at ≥4 weeks after hospital admission of patients with osteoporotic vertebral fracture. OVERVIEW OF LITERATURE: Only a few studies have investigated the influence of physical function and activity on collapse in patients with osteoporotic vertebral fractures. METHODS: This prospective cohort study analyzed patients with osteoporotic vertebral fractures admitted to the hospital between March 2018 and October 2019. Logistic regression analysis was performed to explore the predictors of vertebral collapse at >4 weeks after admission. Model 1 used basic medical information and physical functions at admission; model 2 used basic medical information and physical function and activity at >4 weeks after admission. RESULTS: In the model 1 results of logistic regression analysis, cardiovascular disease (odds ratio [OR], 12.27; 95% confidence interval [CI], 1.28-117.91) was extracted as a factor affecting vertebral collapse at ≥4 weeks after admission. In the model 2 results of logistic regression analysis, cardiovascular disease (OR, 34.57; 95% CI, 2.53-471.74), movement control during one leg standing at 4 weeks (OR, 7.25; 95% CI, 1.36-38.71), and Pain Catastrophizing Scale score at 4 weeks (OR, 1.11; 95% CI, 1.01-1.21) were extracted as factors affecting vertebral collapse at ≥4 weeks after admission. CONCLUSIONS: Our results indicate that physical functions and comorbidity affect collapse at ≥4 weeks after admission in patients with osteoporotic vertebral fractures.

Validity of simplified, calibration-less exercise intensity measurement using resting heart rate during sleep: a method-comparison study with respiratory gas analysis.

BACKGROUND: The recent development of wearable devices has enabled easy and continuous measurement of heart rate (HR). Exercise intensity can be calculated from HR with indices such as percent HR reserve (%HRR); however, this requires an accurate measurement of resting HR, which can be time-consuming. The use of HR during sleep may be a substitute that considers the calibration-less measurement of %HRR. This study examined the validity of %HRR on resting HR during sleep in comparison to percent oxygen consumption reserve (%VO2R) as a gold standard. Additionally, a 24/7%HRR measurement using this method is demonstrated. METHODS: Twelve healthy adults aged 29 ± 5 years underwent treadmill testing using the Bruce protocol and a 6-min walk test (6MWT). The %VO2R during each test was calculated according to a standard protocol. The %HRR during each exercise test was calculated either from resting HR in a sitting position (%HRRsitting), when lying awake (%HRRlying), or during sleep (%HRRsleeping). Differences between %VO2R and %HRR values were examined using Bland-Altman plots. A 180-day, 24/7%HRR measurement with three healthy adults was also conducted. The %HRR values during working days and holidays were compared. RESULTS: In the treadmill testing, the mean difference between %VO2R and %HRRsleeping was 1.7% (95% confidence interval [CI], - 0.2 to 3.6%). The %HRRsitting and %HRRlying values were 10.8% (95% CI, 8.8 to 12.7%) and 7.7% (95% CI, 5.4 to 9.9%), respectively. In the 6MWT, mean differences between %VO2R and %HRRsitting, %HRRlying and %HRRsleeping were 12.7% (95% CI, 10.0 to 15.5%), 7.0% (95% CI, 4.0 to 10.0%) and - 2.9% (95% CI, - 5.0% to - 0.7%), respectively. The 180-day, 24/7%HRR measurement presented significant differences in %HRR patterns between working days and holidays in all three participants. CONCLUSIONS: The results suggest %HRRsleeping is valid in comparison to %VO2R. The results may encourage a calibration-less, 24/7 measurement model of exercise intensity using wearable devices. TRIAL REGISTRATION: UMIN000034967.Registered 21 November 2018 (retrospectively registered).