2 research outputs found
MikrobiolĂłgiai Ă©rtĂ©ktöbblet az infekciĂłkontroll-centrum kialakĂtásához
Az egĂ©szsĂ©gĂĽgyi ellátással kapcsolatos fertĹ‘zĂ©sek hatĂ©kony megelĹ‘zĂ©se elkĂ©pzelhetetlen intenzĂv mikrobiolĂłgiai rĂ©szvĂ©tel nĂ©lkĂĽl. A szerzĹ‘k a Semmelweis Egyetemen 2008 vĂ©gĂ©n megvalĂłsult infekciĂłkontroll-centrum modelljĂ©t ismertetik. A felĂĽgyelet Ăşj modellje a diagnosztikai Ă©s kĂsĂ©rletes mikrobiolĂłgiai eredmĂ©nyeken alapul. A klinikai mikrobiolĂłgiai laboratĂłrium ugyanazokkal a mĂłdszerekkel vĂ©gzi a járványĂĽgyi cĂ©lĂş vizsgálatokat is. A leletek kĂ©t feladatot látnak el: közlik a klinikussal a kimutatott kĂłrokozĂłt Ă©s annak antibiotikum-Ă©rzĂ©kenysĂ©gĂ©t, továbbá Ă©rtesĂtĂ©st kĂĽldenek a járványĂĽgyi szakembereknek a nosocomialis jelentĹ‘sĂ©gű mikroorganizmusok megjelenĂ©sĂ©rĹ‘l. A legfontosabb kĂłrokozĂłk kimutatása klinikai Ă©s szűrĹ‘mintákbĂłl egyaránt nagy Ă©rzĂ©kenysĂ©gű specifikus automatizált PCR-mĂłdszerrel törtĂ©nik. Az izolátumok biotipizálásának alapja a kiterjedt szubsztráthasznosĂtási spektrum, a genotipizálás Ă©s ennek alapján a rokonság szerinti clusterbesorolás a repetitĂv DNS-szekvenciák polimorfizmusát kimutatĂł DNS-csip-mĂłdszerrel valĂłsul meg. Az OSIRIS Epidemiology több szempontĂş keresĹ‘programjai segĂtik az adatok statisztikai elemzĂ©sĂ©t. Orv. Hetil., 2011, 152, 437–442.
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An effective control of healthcare-associated infections is not realized without an intensive participation of microbiologic activities. Authors present the model of a centre for healthcare-associated infection control established in 2008 at Semmelweis University. The new model of the surveillance system is based on diagnostic and experimental microbiologic data. Clinical and epidemiological microbiologic examinations are performed in the same laboratory using identical methods, and the results are continually compared. Reports consist of two functional parts; namely list of pathogens isolated and antibiotic sensitivity patterns for clinicians and messages especially for epidemiologists including abbreviated information on bacteria of nosocomial importance. Rapid detection of the most important pathogens both from clinical samples and from those obtained for detecting nasal carriage is carried out by a sensitive and specific method of an automated real time PCR. Biotyping of isolates by detailed biochemical substrate spectrum, genotyping by ready-to-use kits depending on polymorphism of repetitive DNA sequences, and cluster analysis of data are used for up-to-date survey of nosocomial situation. Statistical analysis of reports is performed by the multifactorial software OSIRIS Epidemiology. Orv. Hetil., 2011, 152, 437–442
2015/16 seasonal vaccine effectiveness against hospitalisation with influenza a(H1N1)pdm09 and B among elderly people in Europe: Results from the I-MOVE+ project
We conducted a multicentre test-negative caseâ\u80\u93control study in 27 hospitals of 11 European countries to measure 2015/16 influenza vaccine effectiveness (IVE) against hospitalised influenza A(H1N1)pdm09 and B among people aged â\u89¥ 65 years. Patients swabbed within 7 days after onset of symptoms compatible with severe acute respiratory infection were included. Information on demographics, vaccination and underlying conditions was collected. Using logistic regression, we measured IVE adjusted for potential confounders. We included 355 influenza A(H1N1)pdm09 cases, 110 influenza B cases, and 1,274 controls. Adjusted IVE against influenza A(H1N1)pdm09 was 42% (95% confidence interval (CI): 22 to 57). It was 59% (95% CI: 23 to 78), 48% (95% CI: 5 to 71), 43% (95% CI: 8 to 65) and 39% (95% CI: 7 to 60) in patients with diabetes mellitus, cancer, lung and heart disease, respectively. Adjusted IVE against influenza B was 52% (95% CI: 24 to 70). It was 62% (95% CI: 5 to 85), 60% (95% CI: 18 to 80) and 36% (95% CI: -23 to 67) in patients with diabetes mellitus, lung and heart disease, respectively. 2015/16 IVE estimates against hospitalised influenza in elderly people was moderate against influenza A(H1N1)pdm09 and B, including among those with diabetes mellitus, cancer, lung or heart diseases