Risk prediction of second hip fracture by bone and muscle density of the hip varies with time after first hip fracture: A prospective cohort study

Wang, Ling; Yang, Minghui; Ge, Yufeng; Liu, Yandong; Wang, Gang; Su, Yongbin; Guo, Zhe; Yin, Lu; Huang, Pengju; Geng, Jian; Blake, Glen M.; He, Bo; Zhu, Shiwen; Cheng, Xiaoguang; Wu, Xinbao; Aro, Hannu T.; Vlug, Annegreet; Engelke, Klaus

doi:10.1016/j.bonr.2023.101732

Cited by 3 publications

(3 citation statements)

References 30 publications

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“…The key to preventing contralateral hip fracture is to identify and control the relevant predictive risk factors. The results showed that BMD, Singh index, concomitant internal medical diseases, type of first fracture, and age were the most significant risk factors for contralateral hip fracture, with BMD, the Singh index, and age being the most dangerous, which is partially consistent with previous studies 19,20 , and that both lower Singh index and The advantage of the study was that it provides data that could be beneficial in the identification of risk factors that can be treated and corrected to reduce the frequency of contralateral fractures within three years. However, the study has several limitations.…”

Section: Discussionsupporting

confidence: 90%

“…The key to preventing contralateral hip fracture is to identify and control the relevant predictive risk factors. The results showed that BMD, Singh index, concomitant internal medical diseases, type of first fracture, and age were the most significant risk factors for contralateral hip fracture, with BMD, the Singh index, and age being the most dangerous, which is partially consistent with previous studies 19 , 20 , and that both lower Singh index and BMD were positively correlated with the risk of contralateral hip fracture. We discovered that senior patients with osteoporosis, basic internal medicine diseases, and a first hip fracture, were more likely to sustain a contralateral hip fracture.…”

Section: Discussionsupporting

confidence: 88%

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Analysis of the clinical characteristics and risk factors associated with contralateral hip fracture after initial hip fracture in elderly patients: a retrospective cohort study

Zhao,

Tian,

Sha

et al. 2024

Sci Rep

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Fractures of the contralateral hip may easily occur in elderly patients after an initial hip fracture. The aim of this study was to investigate the clinical characteristics and major predisposing risk factors of contralateral hip fracture after initial hip fracture in the elderly, to provide a clinical basis for preventing contralateral hip fracture. The data of 1586 patients who had sustained first or second hip fractures and had been surgically treated in our department were retrospectively analyzed. Potential predictive factors for contralateral hip fracture and descriptive statistics associated with surgery (such as blood loss, operation time, and length of hospital stay) were recorded. Of these patients, 133 (8.4%) suffered contralateral hip fracture. The rates of contralateral fracture after femoral neck and intertrochanteric fracture were 5.4% and 10.7% respectively (P < 0.01). Fifty-four cases of contralateral hip fracture occurred within one year, an incidence of 40.6%, while 95 cases (71.4%) and 105 cases (78.9%) occurred within two and three years, respectively, with a interval duration of 21.6 months. The risk factors for contralateral hip fracture were found to be age, type of first fracture, bone mineral density, the Singh index, and concomitant internal medical diseases, which were found to be significantly associated with an increased risk of contralateral hip fracture in multivariate logistic regression analysis (P < 0.05). In conclusion, the presence of concomitant internal diseases, type of first fracture, bone mineral density, the Singh index, and age were found to be significant predictors of the risk of contralateral hip fracture in elderly patients after a first hip fracture.

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Section: Discussionsupporting

confidence: 90%

“…The key to preventing contralateral hip fracture is to identify and control the relevant predictive risk factors. The results showed that BMD, Singh index, concomitant internal medical diseases, type of first fracture, and age were the most significant risk factors for contralateral hip fracture, with BMD, the Singh index, and age being the most dangerous, which is partially consistent with previous studies 19 , 20 , and that both lower Singh index and BMD were positively correlated with the risk of contralateral hip fracture. We discovered that senior patients with osteoporosis, basic internal medicine diseases, and a first hip fracture, were more likely to sustain a contralateral hip fracture.…”

Section: Discussionsupporting

confidence: 88%

Analysis of the clinical characteristics and risk factors associated with contralateral hip fracture after initial hip fracture in elderly patients: a retrospective cohort study

Zhao,

Tian,

Sha

et al. 2024

Sci Rep

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“…This study aims to evaluate gait stability improvement among hip fracture patients in response to clinical treatment, physical therapies, and rehabilitation interventions. Clinically, such evaluation of gait performance has been reported as important to monitor fracture healing complications and risks associated with overloading [40,41]. This study introduces N&B methods to evaluate gait dynamic stability in joint fracture patients.…”

Section: Discussionmentioning

confidence: 99%

Gait dynamic stability evaluation in patients undergoing hip joint fractures – tools to measure rehabilitation effectiveness

Mahmood,

Maqbool,

Raza

et al. 2024

Biomed. Phys. Eng. Express

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A hip joint fracture includes a break in the thigh (femur) or coxa bone near the pelvis. During fracture healing, stability and weight bearing by the affected limb are key indicators to measure patients’ improvement. Conventionally, the rehabilitation effectiveness is monitored through clinical examinations, patients’ feedback, and few studies also reported instrumented gait evaluations. A gap remains there to numerically quantify the recovery in patients’ stability and weight bearing in response to rehabilitation therapies. This study introduces Nyquist and Bode (N&B) methods to analyse the instrumented gait signals further and evaluate gait stability in hip fracture patients during weight loading and unloading transitions. The centre of pressure (CoP) data was recorded using force plates for conditions: coxa hip fracture (HC), femur hip fracture (HF), and normal hip joint (NH). The time rate of CoP signals illustrated two major impulses during the loading and unloading phases which were modelled in time and frequency domains. The frequency models were further analysed by applying N&B methods and stability margins were computed for both impaired and healthy conditions. Results illustrated a significant decrease (Kruskal–Wallis’s test, p < 0.001) in the intralimb walking stability of both fracture conditions. Further, Spearman’s correlation between CoP velocities of fractured and intact limbs illustrated significant interlimb dependencies to maintain walking stability (p < 0.001) during weight loading and unloading transitions. Overall, the HF impairment illustrated the least intralimb walking stability and relatively greater interlimb dependencies. Clinically, these methods and findings are important to measure the recovery in patients undergoing rehabilitation after a hip joint or other lower limb impairments.

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Association between physical function and parameters of hip structural analysis in patients with hip fracture

Umehara,

Kaneguchi,

Watanabe

et al. 2024

HIP International

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Objectives: The current study sought to investigate whether physical function and activity were associated with hip structural analysis (HSA) parameters on the non-fracture side of patients with hip fractures. Methods: Participants were patients with unilateral hip fracture treated by surgery. HSA of the proximal femur was conducted based on dual-energy x-ray absorptiometry data. HSA parameters in the narrow neck region included cross-sectional area (CSA), cross-sectional moment of inertia (CSMI), section modulus (SM), and buckling ratio (BR). Hierarchical multiple regression analysis was conducted to identify predictors of HSA. Results: Except for the adjustment variables, age, gender and BMI, other variables were extracted. Hierarchical multiple regression analysis (standardised partial regression coefficients) identified movement control during one-leg standing on the non-fractured side (0.15) as factors associated with CSA. Hierarchical multiple regression analysis (standardised partial regression coefficients) identified hand grip (0.12, 0.23) as factors associated with CSMI and SM, respectively. Hierarchical multiple regression analysis (standardised partial regression coefficients) identified presence of steroid (0.23) and cerebrovascular disease (0.19) as factors associated with BR. The coefficients of determination adjusted for degrees of freedom ( R2) were 0.545, 0.331, 0.401, and 0.148 for CSA, CSMI, SM, and BR, respectively. Conclusions: Our results indicate that movement control during 1-leg standing and muscle strength may be important for maintaining and improving bone strength.

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Risk prediction of second hip fracture by bone and muscle density of the hip varies with time after first hip fracture: A prospective cohort study

Cited by 3 publications

References 30 publications

Analysis of the clinical characteristics and risk factors associated with contralateral hip fracture after initial hip fracture in elderly patients: a retrospective cohort study

Analysis of the clinical characteristics and risk factors associated with contralateral hip fracture after initial hip fracture in elderly patients: a retrospective cohort study

Gait dynamic stability evaluation in patients undergoing hip joint fractures – tools to measure rehabilitation effectiveness

Association between physical function and parameters of hip structural analysis in patients with hip fracture

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