Publications by authors named "N M-L Cote"
Tick-borne encephalitis virus (TBEV) causes neurological disease in humans, with varied clinical severity influenced by the viral subtype. TBEV is endemic to Mongolia, where both Siberian and Far-Eastern subtypes are present. is considered the main vector of TBEV in Mongolia; although, the virus has also been detected in species.
View Article and Find Full Text PDFClinical Outcomes, Patterns of Failure, and Salvage Therapies of a Large Modern Cohort of Patients With Anal Squamous Cell Carcinoma Treated With Definitive-Intent Intensity-Modulated Radiation Therapy.
Diana A Roth O'Brien Vasilis C Hristidis Zakaria Chakrani Patrick McCann Antonio Damato Nicolas Cote
Int J Radiat Oncol Biol Phys
November 2024
Article Synopsis
- Patterns of failure and salvage treatment options for anal squamous cell carcinoma (ASCC) post-definitive IMRT were investigated, revealing limited data on patient outcomes after recurrence.
- A study of 375 ASCC patients showed significant locoregional failure (12%) and distant failure (13%) rates, with 73% progression-free survival and 80% overall survival at six years, emphasizing poorer outcomes for those with locoregional failure.
- Salvage therapies improved survival chances significantly, with 30% of patients alive after ten years, contrasting sharply with those receiving only chemotherapy or supportive care.
Article Synopsis
- Bicuspid aortic valve (BAV) shows increased progression of aorta dilation compared to tricuspid aortic valve (TAV) in patients with aortic stenosis, with a median annualized change of 0.33 mm/year for BAV versus 0.21 mm/year for TAV.
- Factors influencing the dilation rate differ by valve type; BAV patients are more affected by low-density lipoprotein (LDL) levels, while TAV patients are influenced by the apolipoprotein B/A-I ratio and baseline aortic jet velocity.
- The study highlights that men and women have different predictors for AA dilation; men’s dilation relates to baseline jet velocity and aortic diameter, while
Article Synopsis
- Aortic valve stenosis (AS) is a chronic disease that progresses at different rates among patients, making it challenging to predict its progression.* -
- This study utilized machine and deep learning algorithms on data from 303 patients to forecast AS progression over the next 2 and 5 years, showing that the LightGBM model yielded the best predictive performance.* -
- The findings suggest that using AI in clinical settings can improve the risk assessment of AS, effectively predicting the disease progression and outcomes for patients with mild-to-moderate AS.*