AIMC Topic: Hip Fractures

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Machine learning algorithms for risk factor selection with application to 60-day sepsis morbidity risk for a geriatric hip fracture cohort.

BMC geriatrics Aug 4, 2025
BACKGROUND: Sepsis after hip fracture in elderly people is a risk factor for mortality. The purpose of this study was to screen for risk factors for 60-day sepsis morbidity after hip fracture and to establish a predictive model using various machine ...
Algorithms Female Risk Factors Aged Humans Machine Learning Cohort Studies Time Factors Morbidity Hip Fractures Aged, 80 and over Male Risk Assessment Sepsis
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Performance of Natural Language Processing versus International Classification of Diseases Codes in Building Registries for Patients With Fall Injury: Retrospective Analysis.

JMIR medical informatics Jul 14, 2025
BACKGROUND: Standardized registries, such as the International Classification of Diseases (ICD) codes, are commonly built using administrative codes assigned to patient encounters. However, patients with fall injury are often coded using subsequent i...
Retrospective Studies Hip Fractures Humans Female International Classification of Diseases Aged Aged, 80 and over Male Accidental Falls Natural Language Processing Registries
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Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cases.

Acta orthopaedica Jul 7, 2025
BACKGROUND AND PURPOSE:  Treatment-related shared decision-making (SDM) in older adults with hip fractures is complex due to the need to balance patient-specific factors such as life goals, frailty, and surgical risks. It includes considerations such...
Machine Learning Algorithms Retrospective Studies Female Humans Netherlands Aged Hip Fractures Aged, 80 and over Decision Making, Shared Male Registries
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery.

Scientific reports Jul 2, 2025
Hip fractures among the elderly population continue to present significant risks and high mortality rates despite advancements in surgical procedures. In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post...
Hip Fractures Humans Machine Learning Algorithms Female Aged Aged, 80 and over Male ROC Curve
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Automatic pain classification in older patients with hip fracture based on multimodal information fusion.

Scientific reports Jul 1, 2025
Given the limitations of unimodal pain recognition approaches, this study aimed to develop a multimodal pain recognition system for older patients with hip fractures using multimodal information fusion. The proposed system employs ResNet-50 for facia...
Aged Aged, 80 and over Male Pain Measurement Humans Databases, Factual Female Pain Hip Fractures Facial Expression
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The underlying molecular mechanisms and biomarkers of Hip fracture combined with deep vein thrombosis based on self sequencing bioinformatics analysis.

Journal of orthopaedic surgery and research May 16, 2025
BACKGROUND: Thrombus formation is a severe complication in orthopedic surgery, significantly increasing mortality in patients with fractures. Therefore, identifying feature genes to determine thrombus presence in fracture surgeries is critical.
Computational Biology Venous Thrombosis Hip Fractures Humans Biomarkers Male Female Middle Aged Aged Gene Expression Profiling Gene Regulatory Networks
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Elucidating predictors of preoperative acute heart failure in older people with hip fractures through machine learning and SHAP analysis: a retrospective cohort study.

BMC geriatrics Apr 23, 2025
BACKGROUND: Acute heart failure (AHF) has become a significant challenge in older people with hip fractures. Timely identification and assessment of preoperative AHF have become key factors in reducing surgical risks and improving outcomes.
Male Risk Assessment Heart Failure Female Cohort Studies Acute Disease Hip Fractures Risk Factors Humans Preoperative Period Aged Machine Learning Aged, 80 and over Retrospective Studies
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Screening risk factors for the occurrence of wedge effects in intramedullary nail fixation for intertrochanteric fractures in older people via machine learning and constructing a prediction model: a retrospective study.

BMC musculoskeletal disorders Apr 22, 2025
PURPOSE: The wedge effect (V-effect) is a common complication in intramedullary nailing surgery for intertrochanteric fractures and can significantly affect postoperative outcomes. The purpose of this study was to screen risk factors for the intraope...
Aged Aged, 80 and over Male Middle Aged Hip Fractures Risk Assessment Humans Machine Learning Bone Nails Postoperative Complications Retrospective Studies Intraoperative Complications China Female Fracture Fixation, Intramedullary Risk Factors
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Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis.

Scientific reports Apr 16, 2025
Hip fractures in the elderly present a significant public health challenge globally, especially among patients with hypertension, who are at an increased risk of developing preoperative deep vein thrombosis (DVT). DVT not only heightens surgical risk...
Incidence ROC Curve Logistic Models Nomograms Hypertension Venous Thrombosis Hip Fractures Preoperative Period Aged Aged, 80 and over Male Risk Assessment Machine Learning Retrospective Studies Female Risk Factors Humans
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Added value of artificial intelligence for the detection of pelvic and hip fractures.

Japanese journal of radiology Mar 5, 2025
PURPOSE: To assess the added value of artificial intelligence (AI) for radiologists and emergency physicians in the radiographic detection of pelvic fractures.
Middle Aged Pelvic Bones Fractures, Bone Hip Fractures Aged, 80 and over Adult Sensitivity and Specificity Male Humans Artificial Intelligence Retrospective Studies Female Aged
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