AIMC Topic: Postoperative Complications

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Development, validation, and clinical evaluation of a machine-learning based model for diagnosing early infection after cardiovascular surgery (DEICS): a multi-center cohort study.

International journal of surgery (London, England)
BACKGROUND: This study addresses the critical need for timely and accurate diagnosis of early postoperative infection (EPI) following cardiac surgery. EPI significantly impacts patient outcomes and healthcare costs, making its early detection vital.

Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach.

PloS one
BACKGROUND: Non-small-cell lung cancer (NSCLC) and its surgery significantly increase the venous thromboembolism (VTE) risk. This study explored the VTE risk factors and established a machine-learning model to predict a failure of postoperative throm...

Artificial Intelligence Risk Prediction Tools for Alloplastic Breast Reconstruction.

Plastic and reconstructive surgery
BACKGROUND: Accurate risk prediction for patients undergoing breast reconstruction with tissue expanders (TEs) can improve patient counseling and shared decision-making. This study aimed to develop and evaluate traditional statistical and machine lea...

Application of machine learning models to identify predictors of good outcome after laparoscopic fundoplication.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Laparoscopic fundoplication remains the gold standard treatment for gastroesophageal reflux disease. However, 10% to 20% of patients experience new, persistent, or recurrent symptoms warranting further treatment. Potential predictors for ...

Perioperative risk assessment for emergency general surgery in those with multimorbidity or frailty.

Current opinion in critical care
PURPOSE OF REVIEW: This review explores advances in risk stratification tools and their applicability in identifying and managing high-risk emergency general surgery (EGS) patients.

Predicting postoperative pulmonary infection in elderly patients undergoing major surgery: a study based on logistic regression and machine learning models.

BMC pulmonary medicine
BACKGROUND: Postoperative pulmonary infection (POI) is strongly associated with a poor prognosis and has a high incidence in elderly patients undergoing major surgery. Machine learning (ML) algorithms are increasingly being used in medicine, but the ...

Predicting complications after laparoscopic surgery for ureteropelvic junction obstruction using machine learning models: a retrospective cohort study.

World journal of urology
PURPOSES: Postoperative complications in patients with ureteropelvic junction obstruction (UPJO) negatively impact surgical outcomes and may necessitate redo surgery. We aimed to predict the occurrence of postoperative complications in these patients...

Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers.

Annals of clinical and translational neurology
OBJECTIVE: Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervention. Herein, we constructed a multidimensional postoperative delirium risk-prediction model incorpor...

Querying the capability of the post-HoLEP endoscopic aspect of the membranous urethral mucosa in predicting urinary incontinence: a prospective AI-based analysis.

World journal of urology
INTRODUCTION: Transient stress urinary incontinence (SUI) after holmium laser enucleation of prostate (HoLEP) is commonly linked to intraoperative injury of the external urethral sphincter (EUS). We assessed the reliability of the post-HoLEP endoscop...

Post-Bariatric Hypoglycemia After Gastric Bypass: Clinical Characteristics, Risk Factors, and Future Directions-A Response to Grover et al.

Clinical endocrinology
BACKGROUND: Post-bariatric hypoglycemia (PBH) after Roux-en-Y gastric bypass (RYGB) is a complex complication, often characterized by potentially severe hypoglycemic episodes and reduced hypoglycemia awareness. Recent findings suggest that autonomic ...