Publications by authors named "Thanh Bui Duc"
Objective: The study aimed to characterize serum immunoglobulin (Ig) concentrations and their relationship with clinical and paraclinical features in patients with COPD group E in the stable stage. Additionally, the study focused on evaluating the relationship between serum Ig levels and the risk of exacerbations over the next 12 months, thereby clarifying the role of serum Ig deficiency in affecting the future risk for these patients.
Methods: A prospective observational study assessed IgG, IgA, IgM, and IgE levels in 67 COPD patients and 30 healthy controls at Military Hospital 103 from October 2017 to August 2020.
Article Synopsis
- A study was conducted to develop an early prognostic tool to identify hospitalized COVID-19 patients at high risk of mortality, emphasizing the importance of accurate patient management.
- Researchers analyzed 375 patients and identified six key clinical factors correlated with mortality: age over 50, multiple underlying diseases, dyspnea, acute confusion, low oxygen saturation, and high oxygen demand.
- The newly created Military Hospital 175 scale (MH175) proved effective in predicting mortality risk with high sensitivity (96.1%) and a good overall discriminative ability (AUC of 0.87), enabling healthcare providers to optimize treatment strategies.
Background: The B-type rafkinase (BRAF) V600E gene mutation plays an important role in the pathogenesis, diagnosis, and prognosis of thyroid carcinoma. This study was conducted to investigate the rate of the BRAF V600E mutation, the relationships between the BRAF V600E gene mutation and some immunohistochemical markers, and recurrence rate in patients with differentiated thyroid cancer.
Method: The study was conducted by a descriptive and longitudinal follow-up method on 102 thyroid carcinoma patients at 103 Military Hospital, Hanoi, Vietnam.
Introduction: Artificial Intelligence (AI) and machine learning (ML) are used extensively in HICs to detect and control antibiotic resistance (AMR) in laboratories and clinical institutions. ML is designed to predict outcome variables using an algorithm to enable "machines" to learn the "rules" from the data. ML is increasingly being applied in intensive care units to identify AMR and to assist empiric antibiotic therapy.
View Article and Find Full Text PDFBackground: After coronary artery bypass graft (CABG) surgery, heart failure is still major problem. The valuable marker for it is needed.
Aim: Evaluating the role of serial NT-proBNP level in prognosis and follow-up treatment of acute heart failure after CABG surgery.