Correlation between classification in risk categories and clinical aspects and outcomes

• Autor(a) principal: Oliveira, Gabriella Novelli [UNIFESP]
• Data de Publicação: 2016
• Outros Autores: Vancini-Campanharo, Cassia Regina [UNIFESP], Lopes, Maria Carolina Barbosa Teixeira [UNIFESP], Barbosa, Dulce Aparecida [UNIFESP], Okuno, Meiry Fernanda Pinto [UNIFESP], Batista, Ruth Ester Assayag [UNIFESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNIFESP
• dARK ID: ark:/48912/0013000006gdd
• DOI: 10.1590/1518-8345.1284.2842
• Texto Completo: http://dx.doi.org/10.1590/1518-8345.1284.2842; http://repositorio.unifesp.br/handle/11600/49261
• topic: Triage; Emergency Medical Services; Emergency Nursing; Clinical Evolution; Protocols; User EmbracementEmergency; Pain

Objective: to correlate classification in risk categories with the clinical profiles, outcomes and origins of patients. Method: analytical cross-sectional study conducted with 697 medical forms of adult patients. The variables included: age, sex, origin, signs and symptoms, exams, personal antecedents, classification in risk categories, medical specialties, and outcome. The Chi-square and likelihood ratio tests were used to associate classifications in risk categories with origin, signs and symptoms, exams, personal antecedents, medical specialty, and outcome. Results: most patients were women with an average age of 44.5 years. Pain and dyspnea were the symptoms most frequently reported while hypertension and diabetes mellitus were the most common comorbidities. Classifications in the green and yellow categories were the most frequent and hospital discharge the most common outcome. Patients classified in the red category presented the highest percentage of ambulance origin due to surgical reasons. Those classified in the orange and red categories also presented the highest percentage of hospitalization and death. Conclusion: correlation between clinical aspects and outcomes indicate there is a relationship between the complexity of components in the categories with greater severity, evidenced by the highest percentage of hospitalization and death.