M Barchitta1, A Maugeri1, G Favara2, P M Riela3, C La Mastra2, M C La Rosa2, R Magnano San Lio2, G Gallo3, I Mura4, A Agodi5. 1. Department of Medical and Surgical Sciences and Advanced Technologies 'GF Ingrassia', University of Catania, Catania, Italy; Italian Study Group of Hospital Hygiene, Italian Society of Hygiene, Preventive Medicine and Public Health, Italy. 2. Department of Medical and Surgical Sciences and Advanced Technologies 'GF Ingrassia', University of Catania, Catania, Italy. 3. Department of Mathematics and Informatics, University of Catania, Catania, Italy. 4. Italian Study Group of Hospital Hygiene, Italian Society of Hygiene, Preventive Medicine and Public Health, Italy; Department of Biomedical Sciences, University of Sassari, Sassari, Italy. 5. Department of Medical and Surgical Sciences and Advanced Technologies 'GF Ingrassia', University of Catania, Catania, Italy; Italian Study Group of Hospital Hygiene, Italian Society of Hygiene, Preventive Medicine and Public Health, Italy. Electronic address: agodia@unict.it.
Abstract
BACKGROUND: Although preventive strategies have been proposed against catheter-associated urinary tract infections (CAUTIs) in intensive care units (ICUs), more efforts are needed to control the incidence rate. AIM: To distinguish patients according to their characteristics at ICU admission, and to identify clusters of patients at higher risk for CAUTIs. METHODS: A two-step cluster analysis was conducted on 9656 patients from the Italian Nosocomial Infections Surveillance in Intensive Care Units project. FINDINGS: Three clusters of patients were identified. Type of admission, patient origin and administration of antibiotics had the greatest weight on the clustering model. Cluster 1 comprised more patients with a medical type of ICU admission who came from the community. Cluster 2 comprised patients who were more likely to come from other wards/hospitals, and to report administration of antibiotics 48 h before or after ICU admission. Cluster 3 was similar to Cluster 2 but was characterized by a lower percentage of patients with administration of antibiotics 48 h before or after ICU admission. Patients in Clusters 1 and 2 had a longer duration of urinary catheterization [median 7 days, interquartile range (IQR) 12 days for Cluster 1; median 7 days, IQR 11 days for Cluster 2] than patients in Cluster 3 (median 6 days, IQR 8 days; P<0.001). Interestingly, patients in Cluster 1 had a higher incidence of CAUTIs (3.5 per 100 patients) compared with patients in the other two clusters (2.5 per 100 patients in both clusters; P=0.033). CONCLUSION: To the authors' knowledge, this is the first study to use cluster analysis to identify patients at higher risk of CAUTIs who could gain greater benefit from preventive strategies.
BACKGROUND: Although preventive strategies have been proposed against catheter-associated urinary tract infections (CAUTIs) in intensive care units (ICUs), more efforts are needed to control the incidence rate. AIM: To distinguish patients according to their characteristics at ICU admission, and to identify clusters of patients at higher risk for CAUTIs. METHODS: A two-step cluster analysis was conducted on 9656 patients from the Italian Nosocomial Infections Surveillance in Intensive Care Units project. FINDINGS: Three clusters of patients were identified. Type of admission, patient origin and administration of antibiotics had the greatest weight on the clustering model. Cluster 1 comprised more patients with a medical type of ICU admission who came from the community. Cluster 2 comprised patients who were more likely to come from other wards/hospitals, and to report administration of antibiotics 48 h before or after ICU admission. Cluster 3 was similar to Cluster 2 but was characterized by a lower percentage of patients with administration of antibiotics 48 h before or after ICU admission. Patients in Clusters 1 and 2 had a longer duration of urinary catheterization [median 7 days, interquartile range (IQR) 12 days for Cluster 1; median 7 days, IQR 11 days for Cluster 2] than patients in Cluster 3 (median 6 days, IQR 8 days; P<0.001). Interestingly, patients in Cluster 1 had a higher incidence of CAUTIs (3.5 per 100 patients) compared with patients in the other two clusters (2.5 per 100 patients in both clusters; P=0.033). CONCLUSION: To the authors' knowledge, this is the first study to use cluster analysis to identify patients at higher risk of CAUTIs who could gain greater benefit from preventive strategies.
Authors: Martina Barchitta; Andrea Maugeri; Maria Clara La Rosa; Claudia La Mastra; Giuseppe Murolo; Antonella Agodi Journal: Antibiotics (Basel) Date: 2020-12-22
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