Preoperative factors predict prolonged length of stay, serious adverse complications, and readmission following operative intervention of proximal humerus fractures: a machine learning analysis of a national database

Hornung, Alexander L.; Rudisill, Samuel S.; McCormick, Johnathon R.; Streepy, John T.; Harkin, William E.; Bryson, Noah; Simcock, Xavier; Garrigues, Grant E.

doi:10.1016/j.jseint.2024.02.005

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2024

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Cited by 2 publications

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Can Machine Learning Identify Patients Who are Appropriate for Outpatient Open Reduction and Internal Fixation of Distal Radius Fractures?

Hornung,

Rudisill,

Smith

et al. 2024

Journal of Hand Surgery Global Online

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Can Machine Learning Identify Patients Who are Appropriate for Outpatient Open Reduction and Internal Fixation of Distal Radius Fractures?

Hornung,

Rudisill,

Smith

et al. 2024

Journal of Hand Surgery Global Online

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Volume Rendering Techniques in Computerized Tomography for the Evaluation of Proximal Humerus Fractures: A Case report

Zarakovitis,

Karametos

2024

Preprint

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Background: Proximal Humerus Fracture (PHF) is the third most common type of fracture, commonly occurring in older people, with a higher incidence in those over 50 years of age. Diagnostic imaging includes X-rays of the shoulder and a CT scan to aid surgical treatment and pre-operative surgical planning. The CT scan is performed in combination with the new applications of artificial intelligence in image reconstruction. Cost is a major limitation when it comes to AI technology, therefore public hospitals in Greece cannot afford it. The novelty of our article is that we investigate a practical way to reconstruct CT images of proximal humerus fractures by using the Volume Rendering Technique algorithm to generate images of great accuracy and detail, especially in the absence of Deep Learning Reconstruction systems. Case presentation: We present the case of a 48-year-old worker who was injured after falling from a ladder and was diagnosed with a PHF and a scapula fracture. Three-dimensional (3D) image reconstruction of the shoulder joint showed a fracture line with high accuracy. The surgeons were supported in the decision to transfer the patient to a specialized hospital for treatment of severe fractures. Conclusions: The Volume Rendering Technique algorithm is a helpful tool that allows physicians to create three-dimensional images of proximal humerus fractures with great accuracy. The process is performed in a very short time and allows surgeons to proceed with preoperative planning of the shoulder.

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Preoperative factors predict prolonged length of stay, serious adverse complications, and readmission following operative intervention of proximal humerus fractures: a machine learning analysis of a national database

Cited by 2 publications

References 52 publications

Can Machine Learning Identify Patients Who are Appropriate for Outpatient Open Reduction and Internal Fixation of Distal Radius Fractures?

Can Machine Learning Identify Patients Who are Appropriate for Outpatient Open Reduction and Internal Fixation of Distal Radius Fractures?

Volume Rendering Techniques in Computerized Tomography for the Evaluation of Proximal Humerus Fractures: A Case report

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