Naslov
Scoring Systems for Predicting Postoperative Infection

Autori
Skurić, Jadranka

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Book of Abstracts - KDSA 2008, Workshop on Knowledge Discovery in Scientific Applications / Gamberger, Dragan - Zagreb : Institut Ruđer Bošković, 2008

Skup
KDSA 2008, Workshop on Knowledge Discovery in Scientific Applications

Mjesto i datum
Poreč, Hrvatska, 17.10.2008. - 19.10.2008

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
predictive models; scoring systems; postoperative infection
(prediktivni modeli; skoring sustavi; postoperativne infekcije)

Sažetak
Nosocomial infections represent a major cause of morbidity and mortality among hospitalized patients, especially in the surgical intensive care units, where the rates are approximately 35%. Therefore, the identification of predictors of these infections is helpful in implementing early diagnostic, therapeutic and preventive measures. A large number of scoring systems for assessing the perioperative risk and quantifying the severity of illnesses has been developed over recent years. However, only a few studies showed a predictive value of these scoring systems in determining the risk of developing nosocomial infections. In addition to existing scoring systems for diagnosing and following certain types of infection, like the Clinical pulmonary infection score (CPIS) and Sepsis-related organ failure assessment score (SOFA score), in 2003. the Infection Probability Score (IPS) was developed to predict infection in adult intensive care units patients. The aim of our work was to apply existing systems, evaluate and compare their predictive values, as well as analyze risk factors for developing nosocomial infection in our patients, and to develop a simple score to help assess the presence or absence of infection using routinely available variables. Risk evaluation and prognostication has become a science in its own, and further research and introduction of new scoring systems to assist clinicians in their decision making regarding the risk of an individual patient is needed.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti, Javno zdravstvo i zdravstvena zaštita

POVEZANOST RADA