Prediction of Cervical Lymph Node Metastasis in Clinically Node-Negative T1 and T2 Papillary Thyroid Carcinoma Using Supervised Machine Learning Approach

Papillary thyroid carcinoma (PTC) is generally considered an indolent cancer. However, patients with cervical lymph node metastasis (LNM) have a higher risk of local recurrence. This study evaluated and compared four machine learning (ML)-based classifiers to predict the presence of cervical LNM in clinically node-negative (cN0) T1 and T2 PTC patients. The algorithm was developed using clinicopathological data from 288 patients who underwent total thyroidectomy and prophylactic central neck dissection, with sentinel lymph node biopsy performed to identify lateral LNM. The final ML classifier was selected based on the highest specificity and the lowest degree of overfitting while maintaining a sensitivity of 95%. Among the models evaluated, the k-Nearest Neighbor (k-NN) classifier was found to be the best fit, with an area under the receiver operating characteristic curve of 0.72, and sensitivity, specificity, positive and negative predictive values, F1 and F2 scores of 98%, 27%, 56%, 93%, 72%, and 85%, respectively. A web application based on a sensitivity-optimized kNN classifier was also created to predict the potential of cervical LNM, allowing users to explore and potentially build upon the model. These findings suggest that ML can improve the prediction of LNM in cN0 T1 and T2 PTC patients, thereby aiding in individual treatment planning

Anticoagulation Strategies during Extracorporeal Membrane Oxygenation: A Narrative Review

The development of extracorporeal life support technology has added a new dimension to the care of critically ill patients who fail conventional treatment options. Extracorporeal membrane oxygenation (ECMO)—specialized temporary life support for patients with severe cardiac or pulmonary failure—plays a role in bridging the time for organ recovery, transplant, or permanent assistance. The overall patient outcome is dependent on the underlying disease, comorbidities, patient reaction to critical illness, and potential adverse events during ECMO. Moreover, the contact of the blood with the large artificial surface of an extracorporeal system circuit triggers complex inflammatory and coagulation responses. These processes may further lead to endothelial injury and disrupted microcirculation with consequent end-organ dysfunction and the development of adverse events like thromboembolism. Therefore, systemic anticoagulation is considered crucial to alleviate the risk of thrombosis and failure of ECMO circuit components. The gold standard and most used anticoagulant during extracorporeal life support is unfractionated heparin, with all its benefits and disadvantages. However, therapeutic anticoagulation of a critically ill patient carries the risk of clinically relevant bleeding with the potential for permanent injury or death. Similarly, thrombotic events may occur. Therefore, different anticoagulation strategies are employed, while the monitoring and the balance of procoagulant and anticoagulatory factors is of immense importance. This narrative review summarizes the most recent considerations on anticoagulation during ECMO support, with a special focus on anticoagulation monitoring and future directions