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.

BackgroundIn Sweden, approximately one in four women aged 50 years or older will sustain a hip fracture. Patients treated for a femoral shaft fracture are likely to have an even higher risk. We hypothesized that intramedullary nails (IMN) protecting the femoral neck reduce the risk of subsequent hip fracture and allow the patient to avoid a challenging reoperation. MethodsBetween 2008 and 2010, 5,475 fractures of the femoral shaft, in patients aged ≥55 years, were registered in Sweden. Of these, 897 patients fulfilled the inclusion criteria. We used radiographs and register data to identify reasons for and types of reoperation that occurred between the index surgery and December 31, 2014. Categories of implants were determined through review of x-rays as: IMN with protection of the femoral neck (FNP) and without protection of the femoral neck (NFNP). Reoperations related to peri-implant fractures (including hip fractures), were analyzed as a subgroup of all major reoperations.Multivariable-adjusted, cause-specific hazard ratios (csHRs) were calculated to compare the risk for reoperation between nails with FNP and NFNP. ResultsAmong the 897 patients, a total of 82 reoperations were performed. In 640 patients who were treated with IMN with FNP, there were 7 peri-implant fractures (no hip fractures), and 27 major reoperations. Among the 257 patients who were treated with IMN with NFNP, 14 periimplant hip fractures and 24 major reoperations were identified. Patients who received nails with FNP had a lower hazard for any peri-implant fracture and major reoperation, with multivariable-adjusted csHR values of 0.19 (95% CI 0.07-0.5) and 0.51 (0.28-0.92), respectively. ConclusionsIntramedullary nails with femoral neck protection in the treatment of low-energy femoral shaft fractures prevent secondary hip fractures and decrease the overall risk for reoperation for 4-6 years postoperatively.

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.

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.