AIMC Topic: Reoperation

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Predicting early return to the operating room in early-onset scoliosis patients using machine learning techniques.

Spine deformity
PURPOSE: Surgical treatment of early-onset scoliosis (EOS) is associated with high rates of complications, often requiring unplanned return to the operating room (UPROR). The aim of this study was to create and validate a machine learning model to pr...

Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.

Clinical orthopaedics and related research
BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling a...

Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort.

Medical & biological engineering & computing
Revision total knee arthroplasty (TKA) is associated with a higher risk of readmission than primary TKA. Identifying individual patients predisposed to readmission can facilitate proactive optimization and increase care efficiency. This study develop...

Deep Learning Prediction of Cervical Spine Surgery Revision Outcomes Using Standard Laboratory and Operative Variables.

World neurosurgery
BACKGROUND: Cervical spine procedures represent a major proportion of all spine surgery. Mitigating the revision rate following cervical procedures requires careful patient selection. While complication risk has successfully been predicted, revision ...

Prediction of 30-Day Morbidity and Mortality After Conversion of Sleeve Gastrectomy to Roux-en-Y Gastric Bypass: Use of an Artificial Neural Network.

The American surgeon
BACKGROUND: Conversion of sleeve gastrectomy to Roux-en-Y gastric bypass is indicated primarily for unsatisfactory weight loss or gastroesophageal reflux disease (GERD). This study aimed to use a comprehensive database to define predictors of 30-day ...

Deep-Learning Automation of Preoperative Radiographic Parameters Associated With Early Periprosthetic Femur Fracture After Total Hip Arthroplasty.

The Journal of arthroplasty
BACKGROUND: The radiographic assessment of bone morphology impacts implant selection and fixation type in total hip arthroplasty (THA) and is important to minimize the risk of periprosthetic femur fracture (PFF). We utilized a deep-learning algorithm...

Using Machine Learning to Select Breast Implant Volume.

Plastic and reconstructive surgery
BACKGROUND: In breast augmentation surgery, selection of the appropriate breast implant size is a crucial step that can greatly affect patient satisfaction and the outcome of the procedure. However, this decision is often based on the subjective judg...

Impact of heart failure on reoperation in adult congenital heart disease: An innovative machine learning model.

The Journal of thoracic and cardiovascular surgery
OBJECTIVES: The study objectives were to evaluate the association between preoperative heart failure and reoperative cardiac surgical outcomes in adult congenital heart disease and to develop a risk model for postoperative morbidity/mortality.