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- Bögl, Hans Peter, 1969-
(author)
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Atypical femoral fractures: Another brick in the wall : On aspects of healing, treatment strategies and surveillance
- 2021
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Doctoral thesis (other academic/artistic)abstract
- Atypical femoral fractures are stress fractures of the femoral subtrochanteric and diaphyseal region. It is a common notion that these fractures heal poorly, if at all. In this thesis we show that patients with atypical femoral fractures have a good capacity to generate bone and therefore heal fractures. In daily practice, these patients have a higher risk for reoperation when compared with patients with a normal femoral fracture. However, this risk is less likely to be dependent on the type of fracture than other factors such as age, gender, comorbidities and survival. Using an implant that protects the fragile proximal femur, the risk for reoperations can be attenuated dramatically. An intramedullary nail with fixation of the femoral neck protects the femur from subsequent hip fractures – the most common complication in elderly patients with any type of femoral shaft fracture.Atypical femoral fractures are difficult to identify in the population. Erroneous diagnosis coding, poor reporting of adverse drug reactions and low accuracy of radiology reports make the identification and surveillance a difficult task. The Swedish Fracture Register has provided the option to register this special fracture since 2015. With its physician-based registration process, it enables researchers and treating physicians to identify and follow these rare fractures longitudinally.
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| 2. |
- Bögl, Hans Peter, 1969-, et al.
(author)
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Increased rate of reoperation in atypical femoral fractures is related to patient characteristics and not fracture type : A nationwide cohort study
- 2020
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In: Osteoporosis International. - : SPRINGER LONDON LTD. - 0937-941X .- 1433-2965. ; 31:5, s. 951-959
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Journal article (peer-reviewed)abstract
- Atypical femoral fractures are burdened with a high rate of reoperation. In our nationwide analysis, the increased rate of reoperation was related to patient background characteristics, such as age and health status, rather than fracture type. Introduction Patients with atypical fractures are complex to treat and burdened with a high risk of reoperation. We hypothesized that patients with surgically treated, complete atypical fractures have a higher risk of any reoperation and reoperation related to healing complications than patients with common femoral shaft fractures but that this increase would become insignificant when adjusted for predefined characteristics. Methods A cohort of 163 patients with atypical fractures and 862 patients with common femoral shaft or subtrochanteric fractures treated from 2008 to 2010 and who had follow-up radiographs and register data available until 31 December 2014 was included. Reoperations were identified by a complementary review of radiographs and register data and were used to calculate risks for any reoperation and reoperations related to healing complications. Results Patients with atypical fractures were more likely to be reoperated for any reason, age-adjusted OR 1.76 (95% CI, 1.08 to 2.86). However, patients with common fractures had a shorter follow-up due to a threefold higher death rate. Accordingly, in a multivariable-adjusted time-to-event model, the increased risk lost statistical significance for any reoperations, cause-specific HR 1.34 (95% CI, 0.85 to 2.13), and for reoperations related to healing complications, HR 1.32 (95% CI, 0.58 to 3.0). Continued use of bisphosphonate in the first year after the fracture did not affect the reoperation rate. Conclusions Our findings suggest that the increased risk of reoperation after an atypical femur fracture is largely explained by patient characteristics and not fracture type.
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| 3. |
- Bögl, Hans Peter, 1969-, et al.
(author)
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Surveillance of atypical femoral fractures in a nationwide fracture register
- 2022
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In: Acta Orthopaedica. - Uppsala : Medical Journals Sweden AB. - 1745-3682 .- 1745-3674. ; 93, s. 229-233
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Journal article (peer-reviewed)abstract
- Background and purpose - To continuously assess the incidence of atypical femoral fractures (AFFs) in the population is important, to allow the evaluation of the risks and benefits associated with osteoporosis treatment. Therefore, we investigated the possibility to use the Swedish Fracture Register (SFR) as a surveillance tool for AFFs in the population and to explore means of improvement. Patients and methods - All AFF registrations in the SFR from January 1, 2015 to December 31, 2018 were enrolled in the study. For these patients, radiographs were obtained and combined with radiographs from 176 patients with normal femoral fractures, to form the study cohort. All images were reviewed and classified into AFFs or normal femur fractures by 2 experts in the field (gold-standard classification) and 1 orthopedic resident educated on the specific radiographic features of AFF (educated-user classification). Furthermore, we estimated the incidence rate of AFFs in the population captured by the register through comparison with a previous cohort and calculated the positive predictive value (PPV) and, where possible, the inter-observer agreement (Cohen's kappa) between the different classifications. Results - Of the 178 available patients with AFF in the SFR, 104 patients were classified as AFF using the goldstandard classification, and 89 using the educated-user classification. The PPV increased from 0.58 in the SFR classification to 0.93 in the educated-user classification. The interobserver agreement between the gold-standard classification and the educated-user classification was 0.81. Interpretation - With a positive predictive value of 0.58 the Swedish Fracture Register outperforms radiology reports and reports to the Swedish Medical Products Agency on adverse drug reactions as a diagnostic tool to identify atypical femoral fractures.
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| 4. |
- Zdolsek, Georg, et al.
(author)
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Deep neural networks with promising diagnostic accuracy for the classification of atypical femoral fractures
- 2021
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In: Acta Orthopaedica. - : Medical Journals Sweden AB. - 1745-3674 .- 1745-3682. ; 92:4, s. 394-400
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Journal article (peer-reviewed)abstract
- Background and purpose — A correct diagnosis is essential for the appropriate treatment of patients with atypical femoral fractures (AFFs). The diagnostic accuracy of radiographs with standard radiology reports is very poor. We derived a diagnostic algorithm that uses deep neural networks to enable clinicians to discriminate AFFs from normal femur fractures (NFFs) on conventional radiographs. Patients and methods — We entered 433 radiographs from 149 patients with complete AFF and 549 radiographs from 224 patients with NFF into a convolutional neural network (CNN) that acts as a core classifier in an automated pathway and a manual intervention pathway (manual improvement of image orientation). We tested several deep neural network structures (i.e., VGG19, InceptionV3, and ResNet) to identify the network with the highest diagnostic accuracy for distinguishing AFF from NFF. We applied a transfer learning technique and used 5-fold cross-validation and class activation mapping to evaluate the diagnostic accuracy. Results — In the automated pathway, ResNet50 had the highest diagnostic accuracy, with a mean of 91% (SD 1.3), as compared with 83% (SD 1.6) for VGG19, and 89% (SD 2.5) for InceptionV3. The corresponding accuracy levels for the intervention pathway were 94% (SD 2.0), 92% (2.7), and 93% (3.7), respectively. With regards to sensitivity and specificity, ResNet outperformed the other networks with a mean AUC (area under the curve) value of 0.94 (SD 0.01) and surpassed the accuracy of clinical diagnostics. Interpretation — Artificial intelligence systems show excellent diagnostic accuracies for the rare fracture type of AFF in an experimental setting.
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