AIMC Topic: Postoperative Complications

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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 Jan 13, 2025
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,...
Aged, 80 and over Male Middle Aged Postoperative Complications Treatment Outcome Humans Female Sweden Aged Bone Cements Prosthesis Failure Hip Prosthesis Periprosthetic Fractures Cementation Elective Surgical Procedures Registries Propensity Score Reoperation Arthroplasty, Replacement, Hip
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Machine learning algorithms for predicting delayed hyponatremia after transsphenoidal surgery for patients with pituitary adenoma.

Scientific reports Jan 9, 2025
This study aimed to develop and validate machine learning (ML) models to predict the occurrence of delayed hyponatremia after transsphenoidal surgery for pituitary adenoma. We retrospectively collected clinical data on patients with pituitary adenoma...
Hyponatremia Postoperative Complications ROC Curve Pituitary Neoplasms Adenoma Machine Learning Algorithms Prospective Studies Retrospective Studies Female Aged Adult Male Middle Aged Humans
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Mortality prediction after major surgery in a mixed population through machine learning: a multi-objective symbolic regression approach.

Anaesthesia Jan 8, 2025
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...
Humans Machine Learning Databases, Factual Female Regression Analysis Elective Surgical Procedures Surgical Procedures, Operative Aged Aged, 80 and over Male Middle Aged Postoperative Complications
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Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review.

BMC musculoskeletal disorders Jan 4, 2025
BACKGROUND: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical p...
Humans Machine Learning Reoperation Risk Factors Anterior Cruciate Ligament Injuries Risk Assessment Anterior Cruciate Ligament Reconstruction Postoperative Complications Predictive Value of Tests
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Application of machine learning in predicting postoperative arrhythmia following transcatheter closure of perimembranous ventricular septal defects.

Kardiologia polska Jan 2, 2025
BACKGROUND: Arrhythmia is a frequent complication following transcatheter device closure of perimembranous ventricular septal defects (pmVSD). However, there is currently a lack of a convenient tool for predicting postoperative arrhythmia.
Retrospective Studies Female Male Humans Postoperative Complications Machine Learning Infant Child, Preschool Child Arrhythmias, Cardiac Cardiac Catheterization Heart Septal Defects, Ventricular
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Assessing the value of deep neural networks for postoperative complication prediction in pancreaticoduodenectomy patients.

PloS one Dec 30, 2024
INTRODUCTION: Pancreaticoduodenectomy (PD) for patients with pancreatic ductal adenocarcinoma (PDAC) is associated with a high risk of postoperative complications (PoCs) and risk prediction of these is therefore critical for optimal treatment plannin...
Male Humans Pancreatic Neoplasms Neural Networks, Computer Carcinoma, Pancreatic Ductal Middle Aged Pancreaticoduodenectomy Risk Assessment Female Postoperative Complications Aged Deep Learning
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Predicting lack of clinical improvement following varicose vein ablation using machine learning.

Journal of vascular surgery. Venous and lymphatic disorders Dec 26, 2024
OBJECTIVE: Varicose vein ablation is generally indicated in patients with active/healed venous ulcers. However, patient selection for intervention in individuals without venous ulcers is less clear. Tools that predict lack of clinical improvement (LC...
Predictive Value of Tests Ablation Techniques Varicose Veins Middle Aged Risk Assessment Postoperative Complications Time Factors Treatment Outcome Female Risk Factors Aged Male Machine Learning Decision Support Techniques Databases, Factual Humans Retrospective Studies Clinical Decision-Making
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Protocol for the impact of machine learning-based clinician decision support algorithims in perioperative care (IMAGINATIVE) in Singapore general hospital : a large prospective randomised controlled trial.

BMJ open Dec 20, 2024
INTRODUCTION: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early id...
Middle Aged Risk Assessment Postoperative Complications Decision Support Systems, Clinical Humans Randomized Controlled Trials as Topic Elective Surgical Procedures Aged, 80 and over Machine Learning Singapore Young Adult Prospective Studies Hospitals, General Adult Intensive Care Units Perioperative Care Male Female Aged
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Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

BMC cardiovascular disorders Dec 20, 2024
INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalies, constitutes a significant contributor to the burden of non-communicable diseases, highlighting the critical need for improved risk assessment tools...
Humans Artificial Intelligence Decision Support Techniques Female Infant, Newborn Risk Factors Young Adult Treatment Outcome Predictive Value of Tests Infant Cardiac Surgical Procedures Adolescent Heart Defects, Congenital Time Factors Adult Child, Preschool Male Child Risk Assessment Postoperative Complications
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Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy.

BMC nephrology Dec 18, 2024
BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy in patients with renal cancer. The timely and accurate prediction of the long-term progression of renal function post-surgery is crucial for early inte...
Support Vector Machine Kidney Neoplasms Carcinoma, Renal Cell Nephrectomy Middle Aged Humans Postoperative Complications Machine Learning Disease Progression Retrospective Studies Renal Insufficiency, Chronic Female Aged Male
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