Clinical Model Accurately Predicts Risk of Hip Fractures in Elderly
By HospiMedica International staff writers Posted on 15 Oct 2024 |

Each year, thousands of hip fractures occur, causing significant pain for patients and increasing their dependence on family, friends, or healthcare staff. Approximately 25% of those impacted die within the first year, resulting in a mortality rate that surpasses that of events such as strokes or heart attacks. This indicates that if clinicians can predict who is likely to be affected, they can implement preventive measures and potentially save lives. Currently, bone densitometry is the most widely utilized method for assessing fracture risk; however, it has several drawbacks. The examination is time-consuming, requires costly equipment, and is not readily accessible to all physicians. Researchers have now created a clinical model that can accurately predict the risk of hip fractures in older adults. This model can identify high-risk patients without the need for measuring skeletal strength, which can speed up the process for doctors and enable timely preventive treatment.
The new study conducted by researchers at Uppsala University (Uppsala, Sweden) is based on registry data gathered from the entire Swedish population. For five years, the researchers tracked all individuals living in Sweden aged 50 and older to identify factors that elevate the risk of hip fractures. The newly developed model relies on variables that are easier to collect in clinical environments, such as diagnoses and medical treatments. This enables healthcare personnel to perform risk assessments without needing access to bone densitometry equipment. The research model is founded on 19 variables, with the strongest predictors—apart from advanced age—being the use of home-help services and diagnoses such as Parkinson's disease and dementia. The model indicated that women utilizing home-help services face a nearly 8% risk of suffering a hip fracture within five years, while the corresponding risk for men is 5%.
A significant finding of the study was the establishment of a risk threshold for when treatment with bone-strengthening medications should be considered. If an individual has a 3% or higher risk of experiencing a hip fracture within five years, preventive medication could be advantageous. According to the model, 36 women or 52 men would therefore require treatment to avert a hip fracture. This study has also been validated among individuals from foreign backgrounds, demonstrating equal accuracy in that group. The research findings published in the journal eClinicalMedicine could inform new guidelines on how healthcare providers should approach the management of hip fracture risk in older adults.
“The most surprising result was that we could predict hip fractures so accurately without using bone density, which has traditionally been an important factor. This means that more people can be identified in time and offered preventive treatment,” said Peter Nordström, Professor and Consultant Physician who led the research group. “A major advantage of our model is that it is based on data already available in the clinic, which allows us to identify at-risk groups more quickly and easily. This in turn enables us to start preventive interventions earlier, such as medication for osteoporosis, and prevent serious complications that occur in hip fractures.”
Latest Health IT News
- Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
- Smartwatches Could Detect Congestive Heart Failure
- Versatile Smart Patch Combines Health Monitoring and Drug Delivery
- Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients
- Strategic Collaboration to Develop and Integrate Generative AI into Healthcare
- AI-Enabled Operating Rooms Solution Helps Hospitals Maximize Utilization and Unlock Capacity
- AI Predicts Pancreatic Cancer Three Years before Diagnosis from Patients’ Medical Records
- First Fully Autonomous Generative AI Personalized Medical Authorizations System Reduces Care Delay
- Electronic Health Records May Be Key to Improving Patient Care, Study Finds
- AI Trained for Specific Vocal Biomarkers Could Accurately Predict Coronary Artery Disease
Channels
Surgical Techniques
view channel
New Transcatheter Valve Found Safe and Effective for Treating Aortic Regurgitation
Aortic regurgitation is a condition in which the aortic valve does not close properly, allowing blood to flow backward into the left ventricle. This results in decreased blood flow from the heart to the... Read more
Minimally Invasive Valve Repair Reduces Hospitalizations in Severe Tricuspid Regurgitation Patients
The tricuspid valve is one of the four heart valves, responsible for regulating blood flow from the right atrium (the heart's upper-right chamber) to the right ventricle (the lower-right chamber).... Read morePatient Care
view channel
Portable Biosensor Platform to Reduce Hospital-Acquired Infections
Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more
First-Of-Its-Kind Portable Germicidal Light Technology Disinfects High-Touch Clinical Surfaces in Seconds
Reducing healthcare-acquired infections (HAIs) remains a pressing issue within global healthcare systems. In the United States alone, 1.7 million patients contract HAIs annually, leading to approximately... Read more
Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization
An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more
Game-Changing Innovation in Surgical Instrument Sterilization Significantly Improves OR Throughput
A groundbreaking innovation enables hospitals to significantly improve instrument processing time and throughput in operating rooms (ORs) and sterile processing departments. Turbett Surgical, Inc.... Read moreHealth IT
view channel
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read more
Smartwatches Could Detect Congestive Heart Failure
Diagnosing congestive heart failure (CHF) typically requires expensive and time-consuming imaging techniques like echocardiography, also known as cardiac ultrasound. Previously, detecting CHF by analyzing... Read morePoint of Care
view channel
Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour
Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Smartphone-Enabled, Paper-Based Quantitative Diagnostic Platform Transforms POC Testing
Point-of-care diagnostics are crucial for public health, offering rapid, on-site testing that enables prompt diagnosis and treatment. This is especially valuable in remote or underserved regions where... Read moreBusiness
view channel
Expanded Collaboration to Transform OR Technology Through AI and Automation
The expansion of an existing collaboration between three leading companies aims to develop artificial intelligence (AI)-driven solutions for smart operating rooms with sophisticated monitoring and automation.... Read more