AIMC Topic: Elective Surgical Procedures

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Maternal and umbilical cord plasma purine concentrations after oral carbohydrate loading prior to elective Cesarean delivery under spinal anesthesia: a randomized controlled trial.

BMC pregnancy and childbirth
OBJECTIVE: To evaluate the effect of preoperative intake of oral carbohydrates versus standard preoperative fasting prior to elective cesarean delivery on plasma purine levels (hypoxanthine, xanthine, and uric acid) and beta-hydroxybutyrate (β-HB) in...

90-day mortality prediction in elective visceral surgery using machine learning: a retrospective multicenter development, validation, and comparison study.

International journal of surgery (London, England)
BACKGROUND: Machine Learning (ML) is increasingly being adopted in biomedical research, however, its potential for outcome prediction in visceral surgery remains uncertain. This study compares the potential of ML methods for preoperative 90-day morta...

Statistical models versus machine learning approach for competing risks in proctological surgery.

Updates in surgery
Clinical risk prediction models are ubiquitous in many surgical domains. The traditional approach to develop these models involves the use of regression analysis. Machine learning algorithms are gaining in popularity as an alternative approach for pr...

Adverse Outcomes after Cemented and Cementless Primary Elective Total Hip Arthroplasty in 60,064 Matched Patients: A Study of Data from the Swedish Arthroplasty Register.

The Journal of arthroplasty
BACKGROUND: The choice between cemented and cementless fixation in primary elective total hip arthroplasty (THA) remains a subject of ongoing debate. However, comparisons between the two are subject to limited adjustments for patient characteristics,...

Mortality prediction after major surgery in a mixed population through machine learning: a multi-objective symbolic regression approach.

Anaesthesia
INTRODUCTION: Understanding 1-year mortality following major surgery offers valuable insights into patient outcomes and the quality of peri-operative care. Few models exist that predict 1-year mortality accurately. This study aimed to develop a predi...

Prediction of Two Year Survival Following Elective Repair of Abdominal Aortic Aneurysms at A Single Centre Using A Random Forest Classification Algorithm.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...

Development and validation of an artificial intelligence system for surgical case length prediction.

Surgery
BACKGROUND: Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for ...

Bowel preparation before elective right colectomy: Multitreatment machine-learning analysis on 2,617 patients.

Surgery
BACKGROUND: In the worldwide, real-life setting, some candidates for right colectomy still receive no bowel preparation, some receive oral antibiotics alone, some receive mechanical bowel preparation alone, and some receive mechanical bowel preparati...

Identifying Elective Induction of Labor among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Health Care System.

American journal of perinatology
OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...