Objective: We aimed to develop of a risk stratification model for the pharmaceutical care (PC) of patients with solid or hematologic neoplasms who required antineoplastic agents or supportive treatments.
Method: The risk stratification model was collaboratively developed by oncology pharmacists from the Spanish Society of Hospital Pharmacy (SEFH). It underwent refinement through three workshops and a pilot study. Variables were defined, grouped into four dimensions, and assigned relative weights. The pilot study collected and analyzed data from participating centers to determine priority levels and evaluate variable contributions. The study followed the Kaiser Permanente pyramid model, categorizing patients into three priority levels: Priority 1 (intensive PC, 90th percentile), Priority 2 (60th-90th percentiles), and Priority 3 (60th percentile). Cut-off points were determined based on this stratification. Participating centers recorded variables in an Excel sheet, calculating mean weight scores for each priority level and the total risk score.
Results: The participants agreed to complete a questionnaire that comprised 22 variables grouped into 4 dimensions: demographic (maximum score =11); social and health variables and cognitive and functional status (maximum = 19); clinical and health services utilization (maximum = 25); and treatment-related (maximum = 41). From the results of applying the model to the 199 patients enrolled, the cutoff points for categorization were 28 or more points for priority 1, 16 to 27 points for priority 2 and less than 16 for priority 3; more than 80% of the total score was based on the dimensions of 'clinical and health services utilization' and 'treatment-related'. Interventions based on the pharmaceutical care model were recommended for patients with solid or hematological neoplasms, according to their prioritization level.
Conclusion: This stratification model enables the identification of cancer patients requiring a higher level of pharmaceutical care and facilitates the adjustment of care capacity. Validation of the model in a representative population is necessary to establish its effectiveness.
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http://dx.doi.org/10.1016/j.farma.2023.12.001 | DOI Listing |
Eur J Prev Cardiol
January 2025
Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
Aim: Primary prevention of cardiovascular disease (CVD) relies on effective risk stratification to guide interventions. Current models, primarily developed using regression analysis, can lead to inaccurate estimates when applied to external populations. This study evaluates the utility of cluster analysis as an alternative method for developing CVD risk stratification models, comparing its performance with established CVD risk prediction models.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Background: Patients undergoing liver transplantation (LT) are at risk of perioperative neurocognitive dysfunction (PND), which significantly affects the patients' prognosis.
Objective: This study used machine learning (ML) algorithms with an aim to extract critical predictors and develop an ML model to predict PND among LT recipients.
Methods: In this retrospective study, data from 958 patients who underwent LT between January 2015 and January 2020 were extracted from the Third Affiliated Hospital of Sun Yat-sen University.
J Neurol
January 2025
Department of Neuroscience, Central Clinical School, Faculty of Medicine, Nursing and Health Science, Monash University, Melbourne, VIC, Australia.
Background: Idiopathic intracranial hypertension (IIH) is increasingly prevalent, yet longitudinal outcome data are scarce. This study aimed to characterise demographic and longitudinal clinical changes in a cohort of patients with IIH.
Methods: Retrospective cohort analysis on adult patients diagnosed with IIH (Friedman criteria) enrolled in the neuro-ophthalmology database (NODE) across two tertiary centres.
Gastro Hep Adv
September 2024
Division of Gastroenterology and Hepatology, Duke University, Durham, North Carolina.
Background And Aims: Alcohol-related liver disease is a leading cause of liver transplantation (LT) in the United States; however, alcohol relapse remains a risk, and real-world assessment of relapse prediction scores is lacking. The primary aim of this study was to assess risk factors for alcohol relapse and compare effectiveness of pre-existing risk scores (e.g.
View Article and Find Full Text PDFSoc Forces
March 2025
National Women's Law Center, Washington, DC 20005, United States.
Drawing on a unique survey of US workers with information about their employers' policies on pay discussions and whether workers engage in such talk with their coworkers, we provide the most comprehensive investigation into pay talk in workplaces to date. Unlike existing treatments, we focus on core organizational and relational factors that influence whether workers talk about pay. We theorize pay talk as a challenge to managerial discretion, and we hypothesize that organizational attributes related to pay-setting influence workers' willingness to discuss wages and salaries with colleagues.
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