RESUMO
Introduction: Perception and relief of pain exhibit variability among individuals. Age, gender, ethnicity, educational level, actual stress level, mood, or medical conditions can modify the personal interpretation of pain and responses to pharmacological treatment. These differences may play a significant role in the effects, sometimes unwanted, of analgesic treatment. Objectives: Define patient typologies with Failed Back Syndrome regarding attitudes toward the disease, treatment, healthcare, and the follow-up they receive from their healthcare professionals. Create a tool for patient profile identification. Materials and Methods: A clinical case series study, observational, descriptive, and cross-sectional. Study population: patients from the Pain Unit of Nuestra Señora de La Candelaria University Hospital (HUNSC) in Tenerife, conducted in three phases: collection of medical history data (F0), initial visit (F1), and personal interview (F2). Results: Five patient typologies are obtained based on responses to 17 items. Regression equations are calculated from these responses to predict the patient type. They are grouped into "Classics," "Dependents," "Critics," "Unconscious," and "Responsible." Additionally, two tools with 17 items and another with 7 optimized items are developed to simplify the process. Conclusions: These tools enable Community Pharmacy (CP) to identify patients based on their characteristics to direct personalized strategies for each of them.
RESUMO
We introduce the FunAndes database, a compilation of functional trait data for the Andean flora spanning six countries. FunAndes contains data on 24 traits across 2,694 taxa, for a total of 105,466 entries. The database features plant-morphological attributes including growth form, and leaf, stem, and wood traits measured at the species or individual level, together with geographic metadata (i.e., coordinates and elevation). FunAndes follows the field names, trait descriptions and units of measurement of the TRY database. It is currently available in open access in the FIGSHARE data repository, and will be part of TRY's next release. Open access trait data from Andean plants will contribute to ecological research in the region, the most species rich terrestrial biodiversity hotspot.