Perfil asistencial del paciente con osteoporosis tributario de visita de telemedicina en la era post-COVID-19 / Care profile of susceptible patients with osteoporosis by telemedicine visits in the post-COVID-19 era

Definir el perfil del paciente con osteoporosis candidato y no candidato a la asistencia en la teleconsulta de osteoporosis, en la era post-COVID-19. Propuesta de un protocolo de manejo para su seguimiento ambulatorio. Métodos: Hemos realizado una revisión bibliográfica mediante una búsqueda sistemática en las bases de datos de Pubmed.gov de la evidencia disponible de artículos en inglés y español con fecha de inclusión hasta octubre del 2020 siguiendo las recomendaciones del sistema GRADE (Grading of Recommendations, Assessment, Development and Evaluation). Base de datos cuyo objetivo es la localización y recuperación de información relevante para esta revisión de forma actualizada. Resultados: El perfil del paciente candidato a teleconsulta sería aquel paciente con historia de osteoporosis, que conoce su enfermedad, con tratamiento y que precisa de seguimiento. La COVID-19 se ha dado en un contexto en el que las principales causas de mortalidad son las enfermedades crónicas y la necesidad de protegerse frente a la transmisión. Conclusiones: Proponemos un consenso del manejo de dicho paciente, con apartados diferenciados para las distintas etapas del proceso asistencial telemático, que ayude a la toma de decisiones clínicas y que sirva de ayuda en el proceso de seguimiento y adherencia terapéutica, y, por tanto, en la optimización de recursos asistenciales. (AU)

Objetive: Define the profile of the candidate and non-candidate osteoporosis patient for assistance in osteoporosis teleconsultation, in the post-COVID-19 era. Proposal of a management protocol for outpatient follow-up. Methods: We have carried out a bibliographic review through a systematic search in the Pubmed.gov databases of the available evidence of articles in English and Spanish with an inclusion date until October 2020, following the recommendations of the GRADE system (Grading of Recommendations, Assessment, Development and Evaluation). Database is aimed at locating and accessing relevant information for this review in an updated way. Results: The profile of the patient candidate for teleconsultation would be of those who present a history of osteoporosis, previously diagnosed, with treatment and requiring follow-up. COVID-19 has occurred in a context in which the main causes of mortality are chronic diseases and the need to protect against transmission. Conclusions: We propose a consensus for managing this patient, with differentiated sections for the different stages of the telematic care process. This will help in clinical decision-making and also in the process of follow-up and therapeutic adherence and, therefore, in optimal use of healthcare resources. (AU)

Increased survival time or better quality of life? Trade-off between benefits and adverse events in the systemic treatment of cancer.

INTRODUCTION: Primary objective of the study was to assess the relative weighting between benefit in survival time (SV), benefit in quality of life (QoL) and willingness to experience adverse events (AEs), in patient preferences for chemotherapy treatment. MATERIALS AND METHODS: We included cancer patients with current or past systemic treatment of cancer (STC) as well as physicians placed as hypothetical patients. Participants filled a choice-based conjoint analysis questionnaire with 19 choices among three STC scenarios with variable amounts of benefit in SV or QoL and different types AEs. RESULTS: One hundred patients (50 on curative and 50 on palliative intention treatment) and 114 physicians (61 oncologists and 53 non-oncologists) were included and asked about their preferred chemotherapy treatment. The relative weighting (sum 100%) of SV-QoL-AEs for making the choice in the 100 patients was SV35%-CV33%-AEs31% what was not significantly different from a random distribution (Goodness of fit Chi square P = 0.91) just as it was not for both subgroups, palliative (SV37%-QoL29%-AEs34%; GoF Chi square P = 0.55) and curative (SV34%-QoL36%-AEs30%; GoF Chi square P = 0.73) treatment. The observed distribution in the group of 114 physicians (SV46%-QoL31%-AEs23%) was significantly different from a random distribution (GoF Chi square P = 0.018) just as it was for both subgroups, medical oncologists (SV48%-QoL29%-AEs23%; GoF Chi square P = 0.006) and non-medical oncologists (SV44%-QoL33%-AEs23%; GoF Chi square P = 0.04). CONCLUSIONS: The three attributes (SV, QoL, and AEs) are considered in the same way by cancer patients to make choices on their STC. On the contrary, when placed as hypothetical patients, physicians prefer for themselves those treatments that provide more SV.