Purpose: Response Evaluation Criteria in Solid Tumours (RECIST) determines partial response (PR) and progressive disease (PD) as a 30 % reduction and 20 % increase in the longest diameter (LD), respectively. Tumour volume analysis (TVA) utilises three diameters to calculate response parameters.
Patients And Methods: We conducted a pilot investigation of patients who underwent neoadjuvant breast cancer treatment and evaluation using RECIST with LD measurements and TVA with three diametric measurements, using the parameters PR (>30 % tumour regression), PD (>20 % tumour growth), and intermediate stable disease (SD).
Objectives: We aimed to describe the characteristics of Clostridioides difficile infection (CDI) in cancer patients, analysing risk factors for 90-day recurrence and attributable mortality.
Methods: Retrospective analysis on all CDI episodes from 2020 to 2022 in three Australian hospitals and one Spanish hospital. Logistic regression analyses were performed.
Oral and maxillofacial surgery (OMS) is a field that straddles knowledge and clinical experience from both medical and dental specialties. In the small island nation of Singapore, the rapidly and constantly changing needs of its diverse and aging population, as well as changes in the mindsets of both students and educators have led to many developments in the local OMS program. Tied to the only dental school in the country, the curriculum of the training program has kept up with the changes in the demographics and attitudes of the local patient pool, which comprises a multicultural population with both traditional and modern mindsets.
View Article and Find Full Text PDFIntroduction: The population is heterogeneous with varying levels of healthcare needs. Clustering individuals into health segments with more homogeneous healthcare needs allows for better understanding and monitoring of health profiles in the population, which can support data-driven resource allocation.
Methods: Using the developed criteria, data from several of Singapore's national administrative datasets were used to classify individuals into the various health segments.