ABSTRACT
The objectives of this study are to develop a predictive model of hospital admission for COVID-19 to help in the activation of emergency services, early referrals from primary care, and the improvement of clinical decision-making in emergency room services. The method is the retrospective cohort study of 49,750 patients with microbiological confirmation of SARS-CoV-2 infection. The sample was randomly divided into two subsamples, for the purposes of derivation and validation of the prediction rule (60% and 40%, respectively). Data collected for this study included sociodemographic data, baseline comorbidities, baseline treatments, and other background data. Multilevel analyses with generalized estimated equations were used to develop the predictive model. Male sex and the gradual effect of age were the main risk factors for hospital admission. Regarding baseline comorbidities, coagulopathies, cancer, cardiovascular diseases, diabetes with organ damage, and liver disease were among the five most notable. Flu vaccination was a risk factor for hospital admission. Drugs that increased risk were chronic systemic steroids, immunosuppressants, angiotensin-converting enzyme inhibitors, and NSAIDs. The AUC of the risk score was 0.821 and 0.828 in the derivation and validation samples, respectively. Based on the risk score, five risk groups were derived with hospital admission ranging from 2.94 to 51.87%. In conclusion, we propose a classification system for people with COVID-19 with a higher risk of hospitalization, and indirectly with it a greater severity of the disease, easy to be completed both in primary care, as well as in emergency services and in hospital emergency room to help in clinical decision-making.Registration: ClinicalTrials.gov Identifier: NCT04463706.
Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Hospitalization , Hospitals , Humans , Male , Primary Health Care , Retrospective StudiesABSTRACT
OBJETIVOS: (1) Conocer la percepción de Satisfacción y Fatiga por Compasión del personal de Enfermería de oncología; (2) estudiar la correlación entre variables sociodemográficas, profesionales y adaptativas (resiliencia, actitudes ante la muerte y personalidad) y la Satisfacción y Fatiga por Compasión y, (3) identificar variables predictoras para ambas dimensiones. MÉTODO: Estudio descriptivo, correlacional, de corte transversal. 69 enfermeras (62.7%) y 41 técnicos en cuidados auxiliares de Enfermería (37.3%) de los servicios de Oncología de Bizkaia (Servicio Vasco de Salud) dieron respuesta al ProQOL-V, CD-RISC-10, PRAM y NEO-FFI-3. Los datos se recogieron entre septiembre 2018 y marzo 2019. El estudio estadístico con el SPSS.22 implicó pruebas chi cuadrado, comparación de medias, correlación de Pearson y regresión logística multivariante. RESULTADOS: El 66.4% (n=73) presentó alta Satisfacción, y el 41.8% (n=46) se situó en niveles moderados de Fatiga por Compasión. Las personas con estudios previos sobre la muerte y/o duelo se percibieron más satisfechas. La Satisfacción estableció correlaciones más fuertes con resiliencia y extroversión, y la Fatiga lo hizo con neuroticismo y resiliencia. Emergieron 4 variables predictoras para la Satisfacción: edad, formación, resiliencia, y amabilidad; y 4 para la Fatiga: evitación y aceptación de escape ante la muerte, neuroticismo y apertura. CONCLUSIONES: La alta relación hallada entre la formación y la resiliencia con la Satisfacción por Compasión puede servir de guía a las instituciones académicas y asistenciales para orientar estrategias formativas, preventivas e interventivas que permitan dotar a los equipos de enfermería oncológica de recursos que les permitan optimizar la percepción sobre su rol de cuidado
OBJECTIVES: (1) To determine the perception of Compassion Satisfaction and Fatigue of oncology nursing staff; (2) to study the correlation between Compassion Satisfaction and Fatigue and sociodemographic, professional and adaptive variables (resilience, attitudes toward death, personality); and (3) to identify predictors of the two dimensions. METHOD: Descriptive, correlational, cross-sectional study. 69 nurses (62.7%) and 41 auxiliary care technicians (37.3%) from the Oncology Services in Biscay (Basque Health Service) completed the ProQOL-V, CD-RISC-10, DAP-R, and NEO-FFI-3. Data were collected between September 2018 and March 2019. The statistical analysis with SPSS.22 included chi-square tests, comparison of means, Pearson's correlation, and multivariate logistic regression. RESULTS: 66.4% (n=73) showed high Compassion Satisfaction, and 41.8% (n=46) were at moderate levels of Compassion Fatigue. People with prior studies related to death and/or grief were more satisfied. Compassion Satisfaction had stronger correlations with resilience and extroversion, and Compassion Fatigue did so with neuroticism and resilience. Four predictor variables emerged for Compassion Satisfaction: age, prior learning, resilience, and agreeableness; and four for Compassion Fatigue: attitudes of avoidance and escape concerning death, neuroticism, and openness. CONCLUSIONS: The high relationship found between training and resilience with Compassion Satisfaction can serve as a guide for academic and health care institutions to orient training, preventive and interventional strategies to provide oncology nursing teams with resources that allow them to optimize their care role
