Journal of evaluation in clinical practice · 2010
The identification of risk factors for infectious patients with acute fever and formulation of activation criteria to alert outpatient clinic doctors.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Xiao Hongli, Qi Haiyu, Li Xingwang, Wang Jing, Li Xiaoli, Ma Suxia, Diao Zongli, Wang Yan, Sun Fangfang, Yin Chenghong
Аннотация
RATIONALE, AIMS AND OBJECTIVES: Acute fever is the most common clinical symptom for infectious diseases. It is necessary to identify risk factors for infectious patients with acute fever and formulate activation criteria of early warning infectiosity score system (EWIS) to alert outpatient clinic doctors.
METHODS: Logistic regression analysis was used to determine risk factors for infectious diseases from the clinical data of 758 patients with acute fever. Risk factors were weighted and an EWIS was formulated. A receiver operator characteristic (ROC) analysis of weighted cumulative scores was performed to evaluate the diagnostic accuracy of EWIS, and the Kappa test used to confirm diagnostic reliability. A χ(2) -test for trend was applied to determine the relevance between EWIS and incidence of infectious diseases.
RESULTS: Risk factors for infections included conjunctival hyperaemia, rash, diarrhoea, increased alanine aminotransferase, splenomegaly and abnormal percentage of peripheral neutrophils (NE%). Risk factors were weighted and tabulated. The areas under the ROC curves of the EWIS was 0.929 and ≥ 4 points predicted infectious diseases, and the Kappa values were 0.750. As the score increased, the incidence of infectious diseases increased. The areas under the ROC curves of the EWIS predicting on single viral and bacterial infectious diseases were 0.961 and 0.896, and the Kappa values were 0.807 and 0.701, respectively.
CONCLUSIONS: Risk factors for infections have been identified, quantified and formulated into a table of EWIS that have high diagnostic accuracy and reliability for the early identification of contagious diseases.
METHODS: Logistic regression analysis was used to determine risk factors for infectious diseases from the clinical data of 758 patients with acute fever. Risk factors were weighted and an EWIS was formulated. A receiver operator characteristic (ROC) analysis of weighted cumulative scores was performed to evaluate the diagnostic accuracy of EWIS, and the Kappa test used to confirm diagnostic reliability. A χ(2) -test for trend was applied to determine the relevance between EWIS and incidence of infectious diseases.
RESULTS: Risk factors for infections included conjunctival hyperaemia, rash, diarrhoea, increased alanine aminotransferase, splenomegaly and abnormal percentage of peripheral neutrophils (NE%). Risk factors were weighted and tabulated. The areas under the ROC curves of the EWIS was 0.929 and ≥ 4 points predicted infectious diseases, and the Kappa values were 0.750. As the score increased, the incidence of infectious diseases increased. The areas under the ROC curves of the EWIS predicting on single viral and bacterial infectious diseases were 0.961 and 0.896, and the Kappa values were 0.807 and 0.701, respectively.
CONCLUSIONS: Risk factors for infections have been identified, quantified and formulated into a table of EWIS that have high diagnostic accuracy and reliability for the early identification of contagious diseases.