Zhao et al. present machine-learning models to predict intraoperative hemodynamic instability in hypertensive pheochromocytoma and paraganglioma surgery. The clinical motivation is sound and the reported discrimination and decision-curve metrics indi...
PURPOSE: To create machine learning (ML) models based on inflammatory markers and coagulation parameters for predicting intraoperative hemodynamic Instability (HI) in sustained hypertensive patients with pheochromocytomas and paragangliomas (PPGLs).
BACKGROUND AND OBJECTIVE: Adrenal incidentalomas (AIs) are predominantly adrenal adenomas (80%), with a smaller proportion (7%) being pheochromocytomas(PHEO). Adenomas are typically non-functional tumors managed through observation or medication, wit...
Pheochromocytoma (PCC) is a rare neuroendocrine tumor driven by complex molecular mechanisms, notably involving the oncogenic c-Myc/Max and c-Myc/c-Max protein complexes. Despite their pivotal role in tumor progression, the molecular interactions and...
OBJECTIVES: The purpose of this study was to explore and verify the value of various machine learning models in preoperative risk stratification of pheochromocytoma.
RATIONALE AND OBJECTIVES: Using different machine learning models CT-based radiomics to integrate clinical radiological features to discriminating the risk stratification of pheochromocytoma/paragangliomas (PPGLs).
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Feb 1, 2024
BACKGROUND: Despite recent improvements in perioperative outcomes after pheochromocytoma resection, hemodynamic instability (HI) remained of high concern. The emergence of robot-assisted surgery may bring different results to pheochromocytoma surgery...
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