Prevention of Unplanned Surgery Due to Delayed Diagnosis of Occult Ipsilateral Femoral Neck Fractures Associated with Femoral Shaft Fractures

Park, Kyeong-Hyeon; Song, Hyung Keun; Yang, Kyu Hyun

doi:10.2106/jbjs.20.02033

Cited by 13 publications

(5 citation statements)

References 22 publications

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“… 2 , 3 , 5 - 7 , 13 This challenge has been noted in multiple studies and is largely due to nondisplaced or minimally displaced femoral neck fractures. 7 , 13 - 15 Owing to this rate of missed injuries, Tornetta et al 3 developed a protocol including 2-mm cut CT scan and internal rotation hip radiographs. This protocol effectively reduced the rates of delayed diagnosis by 91% compared with the previous year.…”

Section: Discussionmentioning

confidence: 99%

Characteristics of Femoral Shaft Fractures That Predict Ipsilateral Femoral Neck Fractures

Yeager,

Woodard,

Hwang

et al. 2024

JAAOS Glob Res Rev

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Introduction: This study aims to characterize radiographic features and fracture characteristics in femoral shaft fractures with associated femoral neck fractures, with the goal of establishing predictive indicators for the presence of ipsilateral femoral neck fractures (IFNFs). Methods: A retrospective cohort was collected from the electronic medical record of three level I trauma centers over a 5-year period (2017 to 2022) by current procedural terminology (CPT) codes. Current CPT codes for combined femoral shaft and IFNFs were identified to generate our study group. CPT codes for isolated femur fractures were identified to generate a control group. Results: One hundred forty patients comprised our IFNF cohort, and 280 comprised the control cohort. On univariate, there were significant differences in mechanism of injury (P < 0.001), Orthopedic Trauma Association (OTA)/Arbeitsgemeinshaft fur Osteosynthesefragen (AO) classification (P = 0.002), and fracture location (P < 0.001) between cohorts. On multivariate, motor vehicle crashes were more commonly associated with IFNFs compared with other mechanism of injuries. OTA/AO 32A fractures were more commonly associated with IFNFs when compared with OTA/AO 32B fractures (adjusted odds ratio = 0.36, P < 0.001). Fractures through the isthmus were significantly more commonly associated with IFNFs than fractures more proximal (adjusted odds ratio = 2.52, P = 0.011). Discussion: Detecting IFNFs in femoral shaft fractures is challenging. Motor vehicle crashes and motorcycle collisions, OTA/AO type 32A fractures, and isthmus fractures are predictive of IFNFs.

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Section: Discussionmentioning

confidence: 99%

Characteristics of Femoral Shaft Fractures That Predict Ipsilateral Femoral Neck Fractures

Yeager,

Woodard,

Hwang

et al. 2024

JAAOS Glob Res Rev

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“… 15 Computed tomography (CT) is a diagnosis tool for femoral neck fractures and provides preoperative evaluation for helping to choose the best treatment and provide better surgical and clinical outcomes. 16 , 17 Quantitative analysis of bone-texture features from CT scans has been actively applied to evaluate the status, quality, or microarchitecture of bones. 18 Park et al demonstrated the value of CT in prediction of avascular necrosis after femoral neck fracture.…”

Section: Introductionmentioning

confidence: 99%

Prediction Models for Prognosis of Femoral Neck–Fracture Patients 6 Months after Total Hip Arthroplasty

Zheng¹,

Xiao²,

Xie³

et al. 2022

IJGM

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Purpose To establish prediction models for 6-month prognosis in femoral neck–fracture patients receiving total hip arthroplasty (THA). Patients and Methods In total, 182 computed tomography image pairs from 85 patients were collected and divided into a training set (n=127) and testing set (n=55). Least absolute shrinkage–selection operator regression was used for selecting optimal predictors. A random-forest algorithm was used to establish the prediction models, which were evaluated for accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC). Results The best model in this study was constructed based on demographic data, preoperative laboratory indicators, and three preoperative radiomic features. In the random-forest model, activated partial thromboplastin time, a preoperative radiomic feature (maximum diameter), and fibrinogen were important variables correlating with patient outcomes. The AUC, sensitivity, specificity, PPV, NPV, and accuracy in the training set were 0.986 (95% CI 0.971–1), 0.925 (95% CI 0.862–0.988), 0.983 (95% CI 0.951–1.016), 0.984 (95% CI 0.953–1.014), 0.922 (95% CI 0.856–0.988), and 0.953 (95% CI 0.916–0.990), respectively. The AUC, sensitivity, specificity, PPV, NPV, and accuracy in the testing set were 0.949 (95% CI 0.885–1), 0.767 (95% CI 0.615–0.918), 1 (95% CI 1–1), 1 (95% CI 1–1), 0.781 (95% CI 0.638–0.924), and 0.873 (95% CI 0.785–0.961), respectively. Conclusion The model based on demographic, preoperative clinical, and preoperative radiomic data showed the best predictive ability for 6-month prognosis in the femoral neck–fracture patients receiving THA.

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“…Totally 4.5 million elderly people worldwide become disabled due to hip fractures every year, including about 1.7 million patients with FNF [ 1 , 2 ]. Such fractures are rarely treated conservatively, but usually treated by cannulated screw internal fixation, femoral head arthroplasty or total hip arthroplasty [ 3 , 4 ]. The type of fractures is one of the important factors determining the treatment programs.…”

Section: Introductionmentioning

confidence: 99%

Does Garden type I incomplete femoral neck fracture really exist in older adults? To evaluate the stability and consistency of Garden classification

et al. 2022

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Background Accurate classification of femoral neck fracture (FNF) is crucial for treatment plan and therapeutic outcomes. Garden classification is commonly used in the clinic, but its stability and consistency remain controversial. The aim of this study was to evaluate the stability and consistency of Garden classification based on X and CT images, and to analyze whether it is valid for Garden I in the elderly. Methods X-ray and CT images from 886 elderly patients with FNF were collected, four orthopaedic surgeons and four radiologists evaluated these images independently, and determined the fracture type based on Garden classification. Three months later, The exercise was repeated and the results were compared based on 4 types Garden classification (I, II, III and IV) and 3 types Garden classification (I + II, III and IV). Kappa was used to measure inter- and intraobserver agreement. The patients with Garden I incomplete FNF confirmed by 8 observers together based on images combined with medical history were compared with the intraoperative results. Results Four types Garden classification, there was little consistency inter- and intraobservers (Kappa from 0.18 to 0.43) based on X-ray images, while professors consistency (0.56 to 0.76) was higher than residents (0.28 to 0.35) based on CT. 3 types Garden classification showed almost perfect agreement inter- and intraobservers, which ranged from 0.76 to 0.90. Totally 52 patients were diagnosed as Garden I, 38 of whom underwent arthroplasty. All surgical cases showed complete fracture during operation. Conclusions There was low consistency and repeatability in 4 types Garden classification (I, II, III and IV), while 3 types Garden classification (I + II, III and IV) had high consistency among observers. In the elderly, all undisplaced femoral neck fracture may be Garden II, no Garden I.

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Prevention of Unplanned Surgery Due to Delayed Diagnosis of Occult Ipsilateral Femoral Neck Fractures Associated with Femoral Shaft Fractures

Cited by 13 publications

References 22 publications

Characteristics of Femoral Shaft Fractures That Predict Ipsilateral Femoral Neck Fractures

Characteristics of Femoral Shaft Fractures That Predict Ipsilateral Femoral Neck Fractures

Prediction Models for Prognosis of Femoral Neck–Fracture Patients 6 Months after Total Hip Arthroplasty

Does Garden type I incomplete femoral neck fracture really exist in older adults? To evaluate the stability and consistency of Garden classification

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