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BMC Emerg Med ; 16(1): 26, 2016 07 13.
Artigo em Inglês | MEDLINE | ID: mdl-27412243

RESUMO

BACKGROUND: Older people frequently attend the emergency department (ED) and have a high risk of poor outcome as compared to their younger counterparts. Our aim was to study routinely collected clinical parameters as predictors of 90-day mortality in older patients attending our ED. METHODS: We conducted a retrospective follow-up study at the Leiden University Medical Center (The Netherlands) among patients aged 70 years or older attending the ED in 2012. Predictors were age, gender, time and way of arrival, presenting complaint, consulting medical specialty, vital signs, pain score and laboratory testing. Cox regression analyses were performed to analyse the association between these predictors and 90-day mortality. RESULTS: Three thousand two hundred one unique patients were eligible for inclusion. Ninety-day mortality was 10.5 % for the total group. Independent predictors of mortality were age (hazard ratio [HR] 1.06, 95 % confidence interval [95 % CI] 1.04-1.08), referral from another hospital (HR 2.74, 95 % CI 1.22-6.11), allocation to a non-surgical specialty (HR: 1.55, 95 % CI 1.13-2.14), increased respiration rate (HR up to 2.21, 95 % CI 1.25-3.92), low oxygen saturation (HR up to 1.96, 95 % CI 1.19-3.23), hypothermia (HR 2.27, 95 % CI 1.28-4.01), fever (HR 0.43, 95 % CI 0.24-0.75), high pain score (HR 1.55, 95 % CI 1.03-2.32) and the indication to perform laboratory testing (HR 3.44, 95 % CI 2.13-5.56). CONCLUSIONS: Routinely collected parameters at the ED can predict 90-day mortality in older patients presenting to the ED. This study forms the first step towards creating a new and simple screening tool to predict and improve health outcome in acutely presenting older patients.


Assuntos
Serviço Hospitalar de Emergência/estatística & dados numéricos , Mortalidade , Alta do Paciente/estatística & dados numéricos , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Feminino , Seguimentos , Nível de Saúde , Humanos , Masculino , Países Baixos , Análise de Regressão , Estudos Retrospectivos , Fatores de Risco , Fatores Sexuais , Fatores Socioeconômicos , Fatores de Tempo
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