Long-Term Risk of Hip Fracture After Ischemic Stroke

Impact of Stroke History on the Risk of Recurrent Hip Fracture or Major Osteoporotic Fractures among Patients with Incident Hip Fracture: A Nationwide Cohort Study

Considerable uncertainty prevails regarding risk factors for recurrent fracture among older patients with hip fracture. We aimed to investigate the relationship between prefracture stroke history, baseline mobility, and the risk of recurrent hip fracture. This cohort study was based on the Danish Multidisciplinary Hip Fracture Registry, 2011-2018 (n = 48,230). We estimated cumulative incidence (competing risk of death) of recurrent hip fracture and major osteoporotic fractures within 1 and 2 years comparing patients with/without prefracture stroke history. Analyses were performed overall and stratified on baseline mobility status (good mobility: Cumulated Ambulation Score ≥ 5 versus poor mobility: Cumulated Ambulation Score < 5). Using Cox regression, adjusted cause-specific hazard ratios (HRs) with 95% confidence intervals (CIs) were obtained. The 1-year cumulative incidence was 4.6% (95% CI: 3.9-5.4) among patients with stroke history and 4.3% (95% CI: 4.1-4.5) among patients without stroke history. For patients with good mobility, the cumulative incidence of recurrent hip fracture was 5.8% (95% CI: 4.3-7.5) versus 3.7% (95% CI: 3.4-4.0) for patients with versus without stroke history. Corresponding numbers for patients with poor mobility were 4.4% (95% CI: 3.6-5.5) and 5.0% (95% CI: 4.7-5.3). Stroke history was associated with an adjusted HR of 1.55 (95% CI: 1.15-2.10) for recurrent fracture among patients with good mobility. In contrast, no association was observed among patients with poor mobility (adjusted HR 0.88 [95% CI: 0.70-1.10]). The associations were attenuated after 2 years of follow-up and for major osteoporotic fractures. In conclusion, stroke history was associated with slightly higher risk of recurrent fracture among patients with first-time hip fracture in the overall analysis, although the CI included a null result. The association was modified by baseline mobility: Patients with stroke history and good mobility had a markedly higher risk, whereas patients with stroke and poor mobility did not. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Development and validation of a machine learning-based model for postoperative ischemic stroke in middle-aged and elderly patients with hip or knee arthroplasty

Postoperative ischemic stroke in middle-aged and elderly patients with hip or knee arthroplasty remains a major postoperative challenge, little is known about its incidence and risk factors. This study sought to create a nomogram for precise prediction of ischemic stroke after hip or knee arthroplasty. Discharge data of all middle-aged and elderly patients undergoing primary hip or knee arthroplasty from May 2013 to October 2020 were queried. These patients were then followed up over time to determine their risk of ischemic stroke. Clinical parameters and blood biochemical features were analyzed by the use of univariable and multivariable generalized logistic regression analysis. A nomogram to predict the risk of ischemic stroke was constructed and validated with bootstrap resampling. Eight hundred twenty-eight patients were included for analysis; Fifty-one were diagnosed with ischemic stroke. After final regression analysis, age, the neutrophil-to-lymphocyte ratio (NLR), a standard deviation of red blood cell distribution width, American Society of Anesthesiologists, low-density lipoprotein, and diabetes were identified and were entered into the nomogram. The nomogram showed an area under the receiver operating characteristic curve of 0. 841 (95% confidence interval [CI], 0.809-0.871). The calibration curves for the probability of ischemic stroke showed optimal agreement between the probability as predicted by the nomogram and the actual probability (Hosmer-Lemeshow test: P = .818). We developed a practical nomogram that can predict the risk of ischemic stroke for middle-aged and elderly patients with hip or knee arthroplasty. This model has the potential to assist clinicians in making treatment recommendations.

Utilization of screening and treatment for osteoporosis among stroke survivors

BACKGROUND

Stroke survivors are prone to osteoporosis and fractures. However, bone mineral density (BMD) testing and osteoporosis treatment were underutilized in patients with recent stroke. We aimed to examine whether stroke has an impact on the utilization of BMD testing and osteoporosis treatment as well as the determinants of their utilization in stroke patients using nationwide population-based data in Taiwan.

METHODS

We identified patients aged 55 years and older who were hospitalized for hemorrhagic or ischemic stroke as the stroke cohort, and age- and sex-matched patients hospitalized for reasons other than stroke, fracture, or fall as the non-stroke cohort. We used the Fine-Gray sub-distribution hazard competing risk regression model to determine the predictors for BMD testing and osteoporosis treatment.

RESULTS

A total of 32997 stroke patients and 32997 age- and sex-matched controls comprised the stroke and non-stroke cohorts, respectively. BMD testing and osteoporosis treatment were performed in 1.0% and 5.2% of the stroke patients, respectively, within one year after hospitalization while these measures were performed in 0.8% and 4.7% of the controls. Stroke patients were more likely to receive BMD testing (adjusted hazard ratio [HR] 1.33; 95% confidence interval [CI] 1.11-1.58) and osteoporosis treatment (adjusted HR 1.19; 95% CI 1.11-1.29). Female sex, osteoporosis, prior BMD testing, and low-trauma fractures after stroke increased the likelihood of using BMD testing and osteoporosis treatment whereas greater stroke severity reduced the likelihood of receiving both measures.

CONCLUSIONS

Both BMD testing and osteoporosis treatment were underutilized among stroke survivors even though they had a higher chance of receiving both measures than non-stroke patients.

Associations between stroke type, stroke severity, and pre-stroke osteoporosis with the risk of post-stroke fracture: A nationwide population-based study

Background Recognizing the post-stroke fracture risk factors is crucial for targeted intervention and primary fracture prevention. We aimed to investigate whether stroke types, stroke severity, and pre-stroke osteoporosis are associated with post-stroke fracture. Methods In a nationwide cohort, we identified previously fracture-free patients who suffered from first-ever stroke, either acute ischemic stroke (AIS) or intracerebral hemorrhage (ICH), between 2003 and 2015. Information regarding stroke severity, osteoporosis, comorbidity, and medication information was collected. The outcomes analyzed included hip fracture, spine fracture, and other fractures. Cumulative incidence functions (CIFs) were used to estimate the cumulative incidence of fractures over time after accounting for competing risk of death. Multivariable Fine and Gray models were used to determine the adjusted hazard ratio (HR) and 95% confidence interval (CI). Results Of the 41,895 patients with stroke, the 5-year CIFs of any incident fracture, hip fracture, spine fracture, and other fractures were 8.03%, 3.42%, 1.87%, and 3.05%, respectively. The fracture risk did not differ between patients with AIS and ICH. While osteoporosis increased the risk of post-stroke fracture (adjusted HR [95% CI],1.42 [1.22-1.66]), stroke severity was inversely associated with post-stroke fracture (moderate, 0.88 [0.81-0.96] and severe, 0.39 [0.34-0.44], compared with mild stroke severity). Conclusions Stroke survivors had an over 8% fracture risk at 5 years after stroke. Mild stroke severity and osteoporosis were significantly associated with post-stroke fracture risk, whereas stroke type was not. Our results call for effective measures for bone health screening and fracture prevention in patients with stroke.