The association between peripheral arterial disease and risk for hip fractures in elderly men is not explained by low hip bone mineral density. Results from the MrOS Sweden study

The Importance of a Hierarchical Approach in Investigating the Connection Between Peripheral Artery Disease and Risk for Developing Low-Trauma Fractures: A Narrative Literature Review

Considering that skeletal changes are often asymptomatic during routine clinical examination, these disorders are frequently overlooked in patients with peripheral artery disease (PAD). Keeping in mind the inclining prevalence of PAD and bone fragility, especially in older individuals, this narrative literature review aimed to provide a comprehensive overview of skeletal alterations in patients with PAD, focusing on the importance of the multi-scale and multidisciplinary approach in the assessment of the bone hierarchical organization. Several observational studies have shown a connection between PAD and the risk of developing low-trauma fractures, but numerous ambiguities remain to be solved. Recent data indicate that evaluating additional bone properties at various levels of bone hierarchical structure may help in understanding the factors contributing to bone fragility in individuals with PAD. Further research on bone structural alterations (especially on micro- and nano-scale) may enhance the understanding of the complex etiopathogenesis of skeletal disorders in patients with PAD, which may lead to advancements in optimizing the clinical management of these individuals. Since osteoporosis and PAD have numerous overlapping risk factors, it is meaningful to evaluate vascular status in individuals with osteoporosis and examine bone health in individuals with PAD to identify individuals who require treatment for both diseases.

Random forest predictive modeling of prolonged hospital length of stay in elderly hip fracture patients

Background

In elderly individuals suffering from hip fractures, a prolonged hospital length of stay (PLOS) not only heightens the probability of patient complications but also amplifies mortality risks. Yet, most elderly hip fracture patients present compromised baseline health conditions. Additionally, PLOS leads to increased expenses for patient treatment and care, while also diminishing hospital turnover rates. This, in turn, jeopardizes the prompt allocation of beds for urgent cases.

Methods

A retrospective study was carried out from October 2021 to November 2023 on 360 elderly hip fracture patients who underwent surgical treatment at West China Hospital. The 75th percentile of the total patient cohort's hospital stay duration, which was 12 days, was used to define prolonged hospital length of stay (PLOS). The cohort was divided into training and testing datasets with a 70:30 split. A predictive model was developed using the random forest algorithm, and its performance was validated and compared with the Lasso regression model.

Results

Out of 360 patients, 103 (28.61%) experienced PLOS. A Random Forest classification model was developed using the training dataset, identifying 10 essential variables. The Random Forest model achieved perfect performance in the training set, with an area under the curve (AUC), balanced accuracy, Kappa value, and F1 score of 1.000. In the testing set, the model's performance was assessed with an AUC of 0.846, balanced accuracy of 0.7294, Kappa value of 0.4325, and F1 score of 0.6061.

Conclusion

This study aims to develop a prognostic model for predicting delayed discharge in elderly patients with hip fractures, thereby improving the accuracy of predicting PLOS in this population. By utilizing machine learning models, clinicians can optimize the allocation of medical resources and devise effective rehabilitation strategies for geriatric hip fracture patients. Additionally, this method can potentially improve hospital bed turnover rates, providing latent benefits for the healthcare system.

FRAX predicts cardiovascular risk in women undergoing osteoporosis screening: the Manitoba bone mineral density registry

Osteoporosis and cardiovascular disease (CVD) are highly prevalent in older women, with increasing evidence for shared risk factors and pathogenesis. Although FRAX was developed for the assessment of fracture risk, we hypothesized that it might also provide information on CVD risk. To test the ability of the FRAX tool and FRAX-defined risk factors to predict incident CVD in women undergoing osteoporosis screening with DXA, we performed a retrospective prognostic cohort study which included women aged 50 yr or older with a baseline DXA scan in the Manitoba Bone Mineral Density Registry between March 31, 1999 and March 31, 2018. FRAX scores for major osteoporotic fracture (MOF) were calculated on all participants. Incident MOF and major adverse CV events (MACE; hospitalized acute myocardial infarction [AMI], hospitalized non-hemorrhagic cerebrovascular disease [CVA], or all-cause death) were ascertained from linkage to population-based healthcare data. The study population comprised 59 696 women (mean age 65.7 ± 9.4 yr). Over mean 8.7 yr of observation, 6021 (10.1%) had MOF, 12 277 women (20.6%) had MACE, 2274 (3.8%) had AMI, 2061 (3.5%) had CVA, and 10 253 (17.2%) died. MACE rates per 1000 person-years by FRAX risk categories low (10-yr predicted MOF <10%), moderate (10%-19.9%) and high (≥20%) were 13.5, 34.0, and 64.6, respectively. Although weaker than the association with incident MOF, increasing FRAX quintile was associated with increasing risk for MACE (all P-trend <.001), even after excluding prior CVD and adjusting for age. HR for MACE per SD increase in FRAX was 1.99 (95%CI, 1.96-2.02). All FRAX-defined risk factors (except parental hip fracture and lower BMI) were independently associated with higher non-death CV events. Although FRAX is intended for fracture risk prediction, it has predictive value for cardiovascular risk.