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Title: Infection probability score, apache II and karnofsky scoring systems as predictors of infection onset in haematology-oncology patients
Authors: Apostolopolou, Eleni
Terzis, Konstantinos 
Pissaki, Kiriaki
Pagoni, Maria
Delibasi, Sossana
Raftopoulos, Vasilios 
Keywords: Hematology;Nursing;Infection
Category: Clinical Medicine
Field: Medical and Health Sciences
Issue Date: 2010
Publisher: Wiley
Source: Journal of Clinical Nursing, 2010, Volume 19, Issue 11-12, Pages 1560-1568
Abstract: Aim: To assess the predictive power of three systems: Infection Probability Score, APACHE II and KARNOFSKY score to the onset of healthcare-associated infections in haematology-oncology patients. Background: The high incidence of healthcare-associated infections is a frequent problem in haematology-oncology patients that affects morbidity and mortality of these patients. Design: A retrospective surveillance survey. Method: The survey was conducted for seven months in the haematology unit of a general hospital in Greece to assess the predictive power of Infection Probability Score, APACHE II and KARNOFSKY score to the onset of healthcare-associated infections. The sample consisted of 102 hospitalised patients. The diagnosis of healthcare-associated infections was based on the definitions proposed by CDC. Results: Among the participants, 53 (52%) were males and 49 (48%) were females with a mean age of 53·30 (SD 18·59) years old (range, 17-85 years). The incidence density of healthcare-associated infections (the number of new cases of healthcare-associated infections per 1000 patient-days) was 21·8 infections per 1000 patient-days. Among the 102 patients, healthcare-associated infections occurred in 32 (31·4%) patients who had a total of 48 healthcare-associated infections (47·5%). Among the 38 patients with neutropenia, 26 (68·4%) had more than one healthcare-associated infection. Of the 48 detected healthcare-associated infections, the most frequent type was blood-stream infection (n = 17, 35·4%), followed by Clostridium difficile infection (n = 11, 22·9%) and respiratory tract infection (n = 8, 3·4%). The best cut-off value of Infection Probability Score (IPS) for the prediction of a healthcare-associated infection was 10 with sensitivity of 59·4% and specificity of 74·3%. Conclusions: Between the three different prognostic scoring systems, IPS had the best sensitivity in predicting healthcare-associated infections. Relevance to clinical practice: IPS is an effective tool and should be used from nurses for the early detection of haematology-oncology patients who are susceptible to the onset of a healthcare-associated infection.
ISSN: 0962-1067 (print)
1365-2702 (online)
DOI: 10.1111/j.1365-2702.2009.03011.x
Rights: © 2010 Blackwell Publishing Ltd.
Type: Article
Appears in Collections:Άρθρα/Articles

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