The intertwining of healthcare-associated infections and COVID-19 in Italian intensive care units: an analysis of the SPIN-UTI project from 2006 to 2021.

BACKGROUND: Although healthcare-associated infections (HAIs) pose an extraordinary burden on public health, the impact of coronavirus disease 2019 (COVID-19) is still a matter of debate. AIM: To describe trends of HAIs in Italian intensive care units (ICUs) from 2006 to 2021, and to compare characteristics and outcomes of patients with or without COVID-19. METHODS: We evaluated patients participating in the 'Italian Nosocomial Infections Surveillance in Intensive Care Units' (SPIN-UTI) project, who were admitted to ICUs for more than 48 h. Data regarding diagnosis, clinical conditions, therapies, treatments and outcomes of COVID-19 patients were also collected. FINDINGS: From a total of 21,523 patients from 2006 to 2021, 3485 (16.2%) presented at least one HAI. We observed an increasing trend for both the incidence of patients with HAI and the incidence density of HAIs (P-trend <0.001). Compared with the pre-pandemic period, the incidence density of HAIs increased by about 15% in 2020-2021, with pneumoniae being the greatest contributors to this increase (P-trend <0.001). Moreover, incidence of HAIs was higher in ICUs dedicated to COVID-19 patients (P<0.001), who showed a greater risk of HAIs and death than patients without COVID-19 (P-values <0.001). Accordingly, the mortality in ICUs increased over the years and doubled during the pandemic (P-trend <0.001). Notably, co-infected patients had higher mortality (75.2%) than those with COVID-19 (66.2%) or HAI (39.9%) alone, and those without any infection (23.2%). CONCLUSIONS: Our analysis provides useful insight into whether and how the COVID-19 pandemic influenced HAI incidence and death in Italian ICUs, highlighting the need for evaluation of the long-term effects of the pandemic.

A machine learning approach to predict healthcare-associated infections at intensive care unit admission: findings from the SPIN-UTI project.

BACKGROUND: Identifying patients at higher risk of healthcare-associated infections (HAIs) in intensive care units (ICUs) represents a major challenge for public health. Machine learning could improve patient risk stratification and lead to targeted infection prevention and control interventions. AIM: To evaluate the performance of the Simplified Acute Physiology Score (SAPS) II for HAI risk prediction in ICUs, using both traditional statistical and machine learning approaches. METHODS: Data for 7827 patients from the 'Italian Nosocomial Infections Surveillance in Intensive Care Units' project were used in this study. The Support Vector Machines (SVM) algorithm was applied to classify patients according to sex, patient origin, non-surgical treatment for acute coronary disease, surgical intervention, SAPS II at admission, presence of invasive devices, trauma, impaired immunity, and antibiotic therapy in 48 h preceding ICU admission. FINDINGS: The performance of SAPS II for predicting HAI risk provides a receiver operating characteristic curve with an area under the curve of 0.612 (P<0.001) and accuracy of 56%. Considering SAPS II along with other characteristics at ICU admission, the SVM classifier was found to have accuracy of 88% and an AUC of 0.90 (P<0.001) for the test set. The predictive ability was lower when considering the same SVM model but with the SAPS II variable removed (accuracy 78%, AUC 0.66). CONCLUSIONS: This study suggested that the SVM model is a useful tool for early prediction of patients at higher risk of HAIs at ICU admission.

Cluster analysis identifies patients at risk of catheter-associated urinary tract infections in intensive care units: findings from the SPIN-UTI Network.

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.

Dietary patterns and school performance: evidence from a sample of adolescents in Sicily, Italy.

BACKGROUND: Academic success in adolescence is a strong predictor of future wealth, productivity and health. While unhealthy dietary habits might be detrimental for academic outcomes, a positive association between healthy diet and school performance was found in adolescents worldwide. STUDY DESIGN: A total of 213 adolescents (15 to 18 years old; 48% boys), attending three high schools in the urban area of Eastern Sicily, were enrolled in a cross-sectional study. METHODS: Dietary data and informations about weekly consumption of main meals were collected administering a Food Frequency Questionnaire. The Mediterranean Diet Score and Principal Component Analysis were used to identify a priori and a posteriori dietary patterns, respectively. School performance was assessed through school marks, using the previous year as reference. RESULTS: The Mediterranean Diet Score was weakly but positively correlated with performance in Italian, Science and Physical Education (p-values < 0.05). Similarly, the adherence to the prudent dietary pattern weakly positively correlated with marks in Mathematics. In contrast, we demonstrated a weak but significant negative correlation between adherence to the western dietary pattern and the performance in several subjects. The energy dense dietary pattern was instead negatively correlated with mark in Italian. We also showed that adolescents regularly eating all main meals have a better performance in several subjects, when compared to those who skipped at least one meal. CONCLUSION: The promotion of healthy diet in youth should be a priority for Public Health, in order to improve adolescents' quality of life and prevent negative health and social outcomes later in life.

The impact of social determinants and lifestyles on dietary patterns during pregnancy: evidence from the "Mamma & Bambino" study.

BACKGROUND: During pregnancy, maternal dietary patterns play a critical role in determining maternal and new-born health. Recent evidence highlighted the influence of either social determinants and lifestyles on the adherence to different dietary patterns. STUDY DESIGN: In this cross-sectional analysis, we evaluated the association of social determinants and lifestyles with maternal dietary patterns in the "Mother & Child" cohort, a prospective study that enrols mother-child pairs from Catania, Italy. METHODS: Dietary patterns were derived using Food Frequency Questionnaire and Principal Component Analysis. Logistic regression models were used to evaluate the association between socio-demographic factors (i.e., age, educational level and employment status), lifestyles (i.e., smoking status, body mass index, use of folic acid, multivitamin and multi-mineral supplements) and dietary patterns. RESULTS: Overall, 332 women were enrolled and the following dietary patterns were derived: the "western" dietary pattern, characterized by high intake of red meat, fries, dipping sauces, salty snacks and alcoholic drinks; the second one, named "prudent", characterized by high intake of potatoes, raw and cooked vegetables, legumes, rice and soup. Multivariable analysis showed that young age, low educational level and smoking were positively associated with the adherence to the western dietary pattern. In contrast, pre-gestational body mass index was negatively associated with the adherence to the prudent dietary pattern. CONCLUSION: Our results raise the need of strategies for promoting healthy dietary habits among women in their reproductive age, which might also help control their body weight before and during pregnancy. These strategies should be prioritized to young women of low educational level, who generally share other unhealthy behaviours.