PCI

Application of supervised machine learning algorithms to predict in-hospital death risk in patients receiving intra-aortic balloon pump therapy during the perioperative period of cardiac surgery.

Outcomes of perioperative intra-aortic balloon pump support in patients undergoing aortic valve surgery: A single-centre, retrospective, observational study.

BACKGROUND: Patients undergoing aortic-valve surgery are prone to perioperative low-cardiac-output syndrome or progression to cardiogenic shock, which remains a challenging clinical problem. OBJECTIVE: This study aimed to investigate the efficacy of perioperative intra-aortic balloon pump (IABP) implantation following aortic valve surgery and its function in patients with severe (ejection fraction...

Decoding perioperative anesthesia-associated signature in Kawasaki disease patients with deep vein thrombosis; evidence from machine-learning driven multi-omics.

UNLABELLED: Inappropriate perioperative anesthesia (PA) drug management may lead to the detrimental clinical outcomes of Kawasaki disease (KD) patient...

Multimodal imaging in left main and bifurcation revascularization: contemporary evidence and comparative modalities review.

Left main (LM) and bifurcation coronary artery disease (CAD) are anatomically complex lesions which require detailed planning and precise execution fo...

Imaging in the diagnosis and characterization of tennis leg.

Tennis leg is a common cause of acute posteromedial calf pain and encompasses a spectrum of injuries involving the posterior calf. Although initially ...

[Comparative observation of analgesic efficacy between liposomal bupivacaine and "cocktail" therapy following artificial intelligence-assisted direct anterior approach total hip arthroplasty: A prospective randomized controlled study].

OBJECTIVE: To compare the analgesic efficacy and safety of liposomal bupivacaine (LB) versus ropivacaine for surgical incision local anesthesia after ...

Initial Multicenter Evaluation of a Novel Anchoring Exchange Device: AI-based Quantitative Distal Tip-Motion Analysis.

PURPOSE: Exchange maneuvers during intracranial angioplasty and stent deployment can cause unintended distal tip motion, potentially leading to vessel...

Neutrophil CD14 is a driver and a therapeutic target for deep vein thrombosis.

Neutrophil-mediated persistent inflammation and neutrophil extracellular trap formation (NETosis) are critical in the pathogenesis of deep vein thromb...

Development of a nomogram with machine learning-assisted feature selection for predicting left atrial appendage thrombosis and severe spontaneous echo contrast in patients with non-paroxysmal atrial fibrillation.

Thrombosis after surgical splenectomy - why, in whom and can we prevent it?

Splenectomy remains a common operation performed in the setting of trauma, haematological disease, malignancy and diagnostic purposes. Contemporary ev...

Ischaemia in tuberculous meningitis: update on pathophysiology, clinical predictors and management.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is a severe manifestation of Mycobacterium tuberculosis infection, associated with high mortality and ...

"Unpatients" in haemostasis and thrombosis. A yardstick of current paths in healthy carriers of a genetic susceptibility.

"Unpatients" are health-conscious individuals -carrying a genetic susceptibility whose impact is unclear with respect to the risk of a clinical event-...

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination because of passive, peristalsis dependent movemen...

Multimorbidity and major adverse cardiovascular events in antipsychotic users: Time-to-event prediction by explainable machine learning.

Antipsychotic treatment is associated with higher risk of major adverse cardiovascular events (MACEs), and risk may vary by multimorbidity and concomi...

Exploratory prediction model for deep vein thrombosis in intensive care patients after anticoagulation therapy: An observational study.

BACKGROUND: Despite low-molecular-weight heparin (LMWH) prophylaxis, the incidence of deep vein thrombosis (DVT) remains high in intensive care unit (...

Development and validation of an interpretable machine learning model for predicting portal vein system thrombosis following splenectomy in Wilson's disease.

Assessing the Predictive Value of Kolmogorov-Arnold Networks for the No-Reflow Phenomenon in ST-Segment Elevation Myocardial Infarction: A Comparative Machine Learning Study.

OBJECTIVE: The no-reflow phenomenon in ST-segment elevation myocardial infarction (STEMI) is a significant clinical issue associated with poor cardiov...

Machine learning survival model for personalised prevention of catheter-related thrombosis in tumour patients.

BACKGROUND: Central venous catheters for drug delivery introduce catheter-related thrombosis (CRT) and influence the survival of cancer patients. The ...

Interpretable Machine Learning for Feature-Based Classification of Platelet Activation in Rotary Blood Pumps.

BACKGROUND: Thrombosis in rotary blood pumps arises from complex flow conditions that remain difficult to translate into reliable and interpretable ri...

Multiphysics learning with graph neural networks for thrombosis prediction in intracranial aneurysms.

Intracranial aneurysms are pathological dilations of cerebral arteries affecting 3-5% of the population. Their rupture can cause subarachnoid hemorrha...