Associations of overweight, obesity and osteoporosis with ankle fractures

Background: Studies exploring risk factors for ankle fractures in adults are scarce, and with diverging conclusions. This study aims to investigate whether overweight, obesity and osteoporosis may be identified as risk factors for ankle fractures and ankle fracture subgroups according to the Danis-Weber (D-W) classification. Methods: 108 patients ≥40 years with fracture of the lateral malleolus were included. Controls were 199 persons without a previous fracture history. Bone mineral density of the hips and spine was measured by dual-energy x-ray absorptiometry, and history of previous fracture, comorbidities, medication, physical activity, smoking habits, body mass index and nutritional factors were registered. Results: Higher body mass index with increments of 5 gave an adjusted odds ratio (OR) of 1.30 (95% confidence interval (CI) 1.03–1.64) for ankle fracture, and an adjusted OR of 1.96 (CI 0.99–4.41) for sustaining a D-W type B or C fracture compared to type A. Compared to patients with normal bone mineral density, the odds of ankle fracture in patients with osteoporosis was 1.53, but the 95% CI was wide (0.79–2.98). Patients with osteoporosis had reduced odds of sustaining a D-W fracture type B or C compared to type A (OR 0.18, CI 0.03–0.83). Conclusions: Overweight increased the odds of ankle fractures and the odds of sustaining an ankle fracture with possible syndesmosis disruption and instability (D-W fracture type B or C) compared to the stable and more distal fibula fracture (D-W type A). Osteoporosis did not significantly increase the odds of ankle fractures, thus suffering an ankle fracture does not automatically warrant further osteoporosis assessment.publishedVersio

Challenges in introduction of artificial intelligence in medical practice – a review of clinical trials concerning adaptation of artificial intelligence in medicine

An interest in Artificial Intelligence [AI] as science is growing in the last years. It has become gradually more used in the medicine. Methodology of development and testing of AI algorithms is generally well established. Use of AI in medicine requires elaboration of standards of its validation in clinical settings. This paper is a review of literature concerning clinical trials on AI adaptation in medicin

Detection of linear features including bone and skin areas in ultrasound images of joints.

Identifying the separate parts in ultrasound images such as bone and skin plays a crucial role in the synovitis detection task. This paper presents a detector of bone and skin regions in the form of a classifier which is trained on a set of annotated images. Selected regions have labels: skin or bone or none. Feature vectors used by the classifier are assigned to image pixels as a result of passing the image through the bank of linear and nonlinear filters. The filters include Gaussian blurring filter, its first and second order derivatives, Laplacian as well as positive and negative threshold operations applied to the filtered images. We compared multiple supervised learning classifiers including Naive Bayes, k-Nearest Neighbour, Decision Trees, Random Forest, AdaBoost and Support Vector Machines (SVM) with various kernels, using four classification performance scores and computation time. The Random Forest classifier was selected for the final use, as it gives the best overall evaluation results.publishedVersio

Detection of linear features including bone and skin areas in ultrasound images of joints.

Identifying the separate parts in ultrasound images such as bone and skin plays a crucial role in the synovitis detection task. This paper presents a detector of bone and skin regions in the form of a classifier which is trained on a set of annotated images. Selected regions have labels: skin or bone or none. Feature vectors used by the classifier are assigned to image pixels as a result of passing the image through the bank of linear and nonlinear filters. The filters include Gaussian blurring filter, its first and second order derivatives, Laplacian as well as positive and negative threshold operations applied to the filtered images. We compared multiple supervised learning classifiers including Naive Bayes, k-Nearest Neighbour, Decision Trees, Random Forest, AdaBoost and Support Vector Machines (SVM) with various kernels, using four classification performance scores and computation time. The Random Forest classifier was selected for the final use, as it gives the best overall evaluation results

Detection of linear features including bone and skin areas in ultrasound images of joints.

Identifying the separate parts in ultrasound images such as bone and skin plays a crucial role in the synovitis detection task. This paper presents a detector of bone and skin regions in the form of a classifier which is trained on a set of annotated images. Selected regions have labels: skin or bone or none. Feature vectors used by the classifier are assigned to image pixels as a result of passing the image through the bank of linear and nonlinear filters. The filters include Gaussian blurring filter, its first and second order derivatives, Laplacian as well as positive and negative threshold operations applied to the filtered images. We compared multiple supervised learning classifiers including Naive Bayes, k-Nearest Neighbour, Decision Trees, Random Forest, AdaBoost and Support Vector Machines (SVM) with various kernels, using four classification performance scores and computation time. The Random Forest classifier was selected for the final use, as it gives the best overall evaluation results

Positive IgA against transglutaminase 2 in patients with distal radius and ankle fractures compared to community-based controls

Background: Patients with celiac disease (CD), including adults with subclinical disease, have low bone mineral density (BMD), deteriorated bone microarchitecture and meta-analysis show an increased risk of fracture. Immunoglobulin A (IgA) against transglutaminase 2 (IgA TG2) is a highly reliable marker to detect CD. Main objective: To explore the prevalence of positive IgA TG2 and CD in patients with distal radius and ankle fracture compared to community-based controls. Methods: Four hundred patients aged 40 years or above with distal fractures were included in a case–control study. About 197 controls were identified from the National Population Registry, those included had never suffered a fracture. BMD was measured, and comorbidities, medications, physical activity, smoking habits, body mass index (BMI) and nutritional factors were registered. Blood analysis to detect common causes of secondary osteoporosis was performed. Results: About 2.5% of the fracture patients had positive IgA TG2, compared to 1% in the control group. The odds ratio, adjusted for sex and age, of having positive IgA TG2 was 2.50 (95% CI 0.54–11.56). Conclusions: There were no significantly increased odds of CD in adult patients with fractures compared to controls; however, results imply that positive IgA TG2 is more prevalent in fracture patients than in controls. This study indicates that universal screening for CD in fracture patients is not warranted, but supports current clinical practice in Norway to suspect and investigate for CD in patients with fracture, osteoporosis and other risk factors for CD

No association between osteoporosis and AO classification of distal radius fractures: an observational study of 289 patients

Background It is mechanically plausible that osteoporosis leads to more severe peripheral fractures, but studies investigating associations between BMD and radiographically verified complexity of distal radius fractures are scarce. This study aims to study the association between osteoporosis, as well as other risk factors for fracture, and the AO classification of distal radius fractures. Methods In this observational study, 289 consecutive patients aged ≥40 years with a distal radius fracture were included. Bone mineral density (BMD) of the hips and spine was measured by dual-energy x-ray absorptiometry (DXA), and comorbidities, medication, physical activity, smoking habits, body mass index (BMI), and history of previous fracture were registered. The distal radius fractures were classified according to the Müller AO system (AO) (type B and C regarded as most complex). Results Patients with osteoporosis (n = 130) did not have increased odds of a more complex distal radius fracture (type B + C, n = 192)) (n = vs type A (n = 92) (OR 1.1 [95% CI 0.5 to 2.3]) compared to those with osteopenia /normal BMD (n = 159). Patients with AO fracture types A or C had a higher prevalence of osteoporosis than patients with type B fracture. Conclusions Distal radius fracture patients with osteoporosis did not sustain more complex fractures than those with osteopenia/normal BMD according to the AO classification system. The AO classification of distal radius fracture cannot be used to decide which patients should be referred to DXA scan and considered for secondary fracture prevention

No association between osteoporosis and AO classification of distal radius fractures: an observational study of 289 patients

Background: It is mechanically plausible that osteoporosis leads to more severe peripheral fractures, but studies investigating associations between BMD and radiographically verified complexity of distal radius fractures are scarce. This study aims to study the association between osteoporosis, as well as other risk factors for fracture, and the AO classification of distal radius fractures. Methods: In this observational study, 289 consecutive patients aged ≥40 years with a distal radius fracture were included. Bone mineral density (BMD) of the hips and spine was measured by dual-energy x-ray absorptiometry (DXA), and comorbidities, medication, physical activity, smoking habits, body mass index (BMI), and history of previous fracture were registered. The distal radius fractures were classified according to the Müller AO system (AO) (type B and C regarded as most complex). Results: Patients with osteoporosis (n = 130) did not have increased odds of a more complex distal radius fracture (type B + C, n = 192)) (n = vs type A (n = 92) (OR 1.1 [95% CI 0.5 to 2.3]) compared to those with osteopenia /normal BMD (n = 159). Patients with AO fracture types A or C had a higher prevalence of osteoporosis than patients with type B fracture. Conclusions: Distal radius fracture patients with osteoporosis did not sustain more complex fractures than those with osteopenia/normal BMD according to the AO classification system. The AO classification of distal radius fracture cannot be used to decide which patients should be referred to DXA scan and considered for secondary fracture prevention

Associations of overweight, obesity and osteoporosis with ankle fractures

Background: Studies exploring risk factors for ankle fractures in adults are scarce, and with diverging conclusions. This study aims to investigate whether overweight, obesity and osteoporosis may be identified as risk factors for ankle fractures and ankle fracture subgroups according to the Danis-Weber (D-W) classification. Methods: 108 patients ≥40 years with fracture of the lateral malleolus were included. Controls were 199 persons without a previous fracture history. Bone mineral density of the hips and spine was measured by dual-energy x-ray absorptiometry, and history of previous fracture, comorbidities, medication, physical activity, smoking habits, body mass index and nutritional factors were registered. Results: Higher body mass index with increments of 5 gave an adjusted odds ratio (OR) of 1.30 (95% confidence interval (CI) 1.03–1.64) for ankle fracture, and an adjusted OR of 1.96 (CI 0.99–4.41) for sustaining a D-W type B or C fracture compared to type A. Compared to patients with normal bone mineral density, the odds of ankle fracture in patients with osteoporosis was 1.53, but the 95% CI was wide (0.79–2.98). Patients with osteoporosis had reduced odds of sustaining a D-W fracture type B or C compared to type A (OR 0.18, CI 0.03–0.83). Conclusions: Overweight increased the odds of ankle fractures and the odds of sustaining an ankle fracture with possible syndesmosis disruption and instability (D-W fracture type B or C) compared to the stable and more distal fibula fracture (D-W type A). Osteoporosis did not significantly increase the odds of ankle fractures, thus suffering an ankle fracture does not automatically warrant further osteoporosis assessment

No association between osteoporosis and AO classification of distal radius fractures: an observational study of 289 patients

Background It is mechanically plausible that osteoporosis leads to more severe peripheral fractures, but studies investigating associations between BMD and radiographically verified complexity of distal radius fractures are scarce. This study aims to study the association between osteoporosis, as well as other risk factors for fracture, and the AO classification of distal radius fractures. Methods In this observational study, 289 consecutive patients aged ≥40 years with a distal radius fracture were included. Bone mineral density (BMD) of the hips and spine was measured by dual-energy x-ray absorptiometry (DXA), and comorbidities, medication, physical activity, smoking habits, body mass index (BMI), and history of previous fracture were registered. The distal radius fractures were classified according to the Müller AO system (AO) (type B and C regarded as most complex). Results Patients with osteoporosis (n = 130) did not have increased odds of a more complex distal radius fracture (type B + C, n = 192)) (n = vs type A (n = 92) (OR 1.1 [95% CI 0.5 to 2.3]) compared to those with osteopenia /normal BMD (n = 159). Patients with AO fracture types A or C had a higher prevalence of osteoporosis than patients with type B fracture. Conclusions Distal radius fracture patients with osteoporosis did not sustain more complex fractures than those with osteopenia/normal BMD according to the AO classification system. The AO classification of distal radius fracture cannot be used to decide which patients should be referred to DXA scan and considered for secondary fracture prevention