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Emerg Med J ; 25(10): 635-9, 2008 Oct.
Article in English | MEDLINE | ID: mdl-18843058

ABSTRACT

INTRODUCTION: Sickle cell patients commonly present to the emergency department (ED). Identifying those requiring admission and those who can safely be discharged is difficult. It was hypothesised that ED variables predictive of 96-h adverse sickle cell patient outcomes are identifiable. METHODS: This observational cohort study included all adult sickle cell patient visits (1 June 2004-31 May 2005) to two ED. Patients were identified by ICD-9 codes of vaso-occlusive crisis and lists from treating haematologists. ED charts were abstracted for history, physical examination, laboratory/imaging data and outcomes. Outcomes were hospitalisation within 96 h of ED presentation for transfusion/antibiotic treatment, acute chest syndrome, or aplastic or sequestration crisis. Logistic regression was used to derive a risk score, which was tested in a validation cohort. The area under the receiver operating curve (AUC) was used to measure score performance. RESULTS: There were 884 ED visits by 125 patients (mean age 36 years/55% female/58% homozygous sickle cell disease). 199 ED visits had one or more outcome (197 transfusion/antibiotic treatment, 71 acute chest syndrome, and one aplastic crisis). The risk score included sickle variant, chest pain, chills, pain dissimilar to past, temperature (<36 degrees C/>38 degrees C), oxygen saturation (<95%), haemoglobin (<10 g/dl), urine nitrites and chest x ray abnormality. The score had an AUC of 0.816 (95% CI 0.778 to 0.854) in the derivation cohort, 0.824 (95% CI 0.760 to 0.889) in the validation cohort. CONCLUSION: Those ED variables predictive of 96-h adverse sickle cell patient outcomes can be identified and combined into a risk score. Prospective validation is necessary before any clinical decision-making based on this score.


Subject(s)
Anemia, Sickle Cell/therapy , Emergency Service, Hospital , Hospitalization , Risk Assessment/methods , Adult , Aged , Decision Making , Epidemiologic Methods , Female , Humans , Male , Middle Aged , Patient Discharge , Risk Assessment/standards , Young Adult
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