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1.
Am J Infect Control ; 50(4): 435-439, 2022 04.
Article in English | MEDLINE | ID: mdl-35369937

ABSTRACT

BACKGROUND: Pseudomonas aeruginosa (PA) is the third leading aetiological agent in healthcare-associated infections (HAIs) and the one most frequently found in patients with pneumonia associated with mechanical ventilation. In intensive care units (ICU), its appearance is associated with higher mortality, an increase in the days spent on ventilation, and hospital stay length and costs. Thus, evaluating strategies for preventing these infections is essential for their control. Therefore, our objective was to evaluate the effectiveness of the systematic use of antimicrobial filters in preventing PA infections in critical care units. METHODS: This was an open experimental crossover study. A total of 2,156 patients admitted for more than 24 hours in critical care units were included, 1,129 of them in units with filters, and 1,027 in units without filters. The study groups were followed-up for 24 months and HAIs were checked for the presence of PA. Chi-squared test were used to compare the rate of HAIs between groups and we calculated 95% confidence intervals adjusted by Poisson regression for the rate ratio (RR) of the association magnitude. RESULTS: Both groups were homogeneous in terms of intrinsic and extrinsic patient factors. The incidence of PA infections in the units with filters was 5.5 cases/1,000 hospitalized days and 5.4/1,000 hospitalized days for the units without water filters (RR = 1.09 [0.67-1.79]). CONCLUSIONS: Routine placing antimicrobial filters in the water taps in critical care units was not an effective means of preventing the emergence of HAIs caused by PA.


Subject(s)
Anti-Infective Agents , Pseudomonas aeruginosa , Critical Care , Cross-Over Studies , Delivery of Health Care , Humans , Intensive Care Units , Water
2.
J Patient Saf ; 17(4): 323-330, 2021 06 01.
Article in English | MEDLINE | ID: mdl-33994534

ABSTRACT

BACKGROUND: Although recommendations to prevent COVID-19 healthcare-associated infections (HAIs) have been proposed, data on their effectivity are currently limited. OBJECTIVE: The aim was to evaluate the effectivity of a program of control and prevention of COVID-19 in an academic general hospital in Spain. METHODS: We captured the number of COVID-19 cases and the type of contact that occurred in hospitalized patients and healthcare personnel (HCP). To evaluate the impact of the continuous use of a surgical mask among HCP, the number of patients with COVID-19 HAIs and accumulated incidence of HCP with COVID-19 was compared between the preintervention and intervention periods. RESULTS: Two hundred fifty-two patients with COVID-19 have been admitted to the hospital. Seven of them had an HAI origin (6 in the preintervention period and 1 in the intervention period). One hundred forty-two HCP were infected with SARS-CoV-2. Of them, 22 (15.5%) were attributed to healthcare (2 in the emergency department and none in the critical care departments), and 120 (84.5%) were attributed to social relations in the workplace or during their non-work-related personal interactions. The accumulated incidence during the preintervention period was 22.3 for every 1000 HCP and 8.2 for every 1000 HCP during the intervention period. The relative risk was 0.37 (95% confidence interval, 0.25 to 0.55) and the attributable risk was -0.014 (95% confidence interval, -0.020 to -0.009). CONCLUSIONS: A program of control and prevention of HAIs complemented with the recommendation for the continuous use of a surgical mask in the workplace and social environments of HCP effectively decreased the risk of COVID-19 HAIs in admitted patients and HCP.


Subject(s)
Academic Medical Centers , COVID-19/prevention & control , Cross Infection/prevention & control , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Adult , COVID-19/epidemiology , COVID-19/transmission , Cross Infection/epidemiology , Female , Humans , Incidence , Infectious Disease Transmission, Patient-to-Professional/statistics & numerical data , Male , Masks/statistics & numerical data , Middle Aged , Personnel, Hospital/statistics & numerical data , Program Evaluation , Risk Assessment/statistics & numerical data , SARS-CoV-2/isolation & purification , Spain/epidemiology
3.
Am J Prev Med ; 59(6): e221-e229, 2020 12.
Article in English | MEDLINE | ID: mdl-33220760

ABSTRACT

INTRODUCTION: This study examines the frequency, associated factors, and characteristics of healthcare personnel coronavirus disease 2019 cases in a healthcare department that comprises a tertiary hospital and its associated 12 primary healthcare centers. METHODS: This study included healthcare personnel that showed symptoms or were in contact with a coronavirus disease 2019 case patient from March 2, 2020 to April 19, 2020. Their evolution and characteristics (age, sex, professional category, type of contact) were recorded. Correlations between the different characteristics and risk of developing coronavirus disease 2019 and severe coronavirus disease 2019 were analyzed using chi-square tests. Their magnitudes were quantified with ORs, AORs, and their 95% CIs using a logistic regression model. RESULTS: Of the 3,900 healthcare professionals in the department, 1,791 (45.9%) showed symptoms or were part of a contact tracing study. The prevalence of those with symptoms was 20.1% (784/3,900; 95% CI=18.8, 21.4), with coronavirus disease 2019 was 4.0% (156/3,900; 95% CI=3.4, 4.6), and with severe coronavirus disease 2019 was 0.5% (18/3,900; 95% CI=0.2, 0.7). The frequency of coronavirus disease 2019 in symptomatic healthcare personnel with a nonprotected exposure was 22.8% (112/491) and 13.7% (40/293) in those with a protected exposure (AOR=2.2, 95% CI=1.2, 3.9). The service in which the healthcare personnel performed their activity was not significantly associated with being diagnosed with coronavirus disease 2019. A total of 26.3% (10/38) of male healthcare personnel with coronavirus disease 2019 required hospitalization, compared with 6.8% (8/118) among female healthcare personnel (OR=4.9, 95% CI=1.8, 13.6). CONCLUSIONS: A surveillance and monitoring program centred on healthcare personnel enables an understanding of the risk factors that lead to coronavirus disease 2019 among this population. This knowledge allows the refinement of the strategies for disease control and prevention in healthcare personnel during the coronavirus disease 2019 pandemic.


Subject(s)
Coronavirus Infections/epidemiology , Health Personnel/statistics & numerical data , Adult , Age Factors , Aged , COVID-19 , Contact Tracing/methods , Female , Humans , Male , Middle Aged , Occupations , Pandemics , Public Health Surveillance/methods , Risk Factors , SARS-CoV-2 , Severity of Illness Index , Sex Factors , Spain/epidemiology , Tertiary Care Centers
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