The COVID-19 pandemic is expected to worsen the global problem of antimicrobial resistance (AMR). There is a heightened interest in understanding this effect and to develop antimicrobial stewardship (AMS) interventions accordingly to curb this threat. Our paper aims to evaluate the potential magnitude of COVID-19 on AMR and AMS with a focus on the countries of the Arab league, given the social, political, and economic environments. We also evaluate obstacles in applying the rational use of antibiotics, monitoring resistance trends in the midst of the pandemic, and evaluating the impact of the economic crisis in some countries. We aim to raise awareness about the potential effects of antibiotic overuse during the pandemic and to propose practical approaches to tackle this issue.

Challenges to Antimicrobial Stewardship in the Countries of the Arab League: Concerns of Worsening Resistance during the COVID-19 Pandemic and Proposed Solutions

During the COVID-19 pandemic hospitals reorganized their resources and delivery of care, which may have affected the number of healthcare-associated infections (HAIs). We aimed to quantify changes in trends in the number of HAIs in Dutch hospitals during the COVID-19 pandemic.National surveillance data from 2016 to 2020 on the prevalence of HAIs measured by point prevalence surveys, and the incidence of surgical site infections (SSIs) and catheter-related bloodstream infections (CRBSIs) were used to compare rates between the pre-pandemic (2016-February 2020) and pandemic (March 2020-December 2020) period.The total HAI prevalence among hospitalised patients was higher during the pandemic period (7.4%) compared to pre-pandemic period (6.4%), mainly because of an increase in ventilator-associated pneumonia (VAP), gastro-intestinal infections (GIs) and central nervous system (CNS) infections. No differences in SSI rates were observed during the pandemic, except for a decrease after colorectal surgeries (6.3% (95%-CI 6.0-6.6%) pre-pandemic versus 4.4% (95%-CI 3.9-5.0%) pandemic). The observed CRBSI incidence in the pandemic period (4.0/1,000 CVC days (95%-CI 3.2-4.9)) was significantly higher than predicted based on pre-pandemic trends (1.4/1000 (95%-CI 1.0-2.1)), and was increased in both COVID-19 patients and non-COVID-19 patients at the intensive care unit (ICU).Rates of CRBSIs, VAPs, GIs and CNS infections among hospitalised patients increased during the first year of the pandemic. Higher CRBSI rates were observed in both COVID-19 and non-COVID-19 ICU population. The full scope and influencing factors of the pandemic on HAIs needs to be studied in further detail. 

/pdf/healthcare-associated-infections-in-dutch-hospitals-during-1i5q2emk.pdf

Healthcare-associated infections in Dutch hospitals during the COVID-19 pandemic

Background and Objectives: In Coronavirus Disease 2019 (COVID-19), which is caused by the infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the clinical manifestations are primarily related to the pulmonary system. Under 10% of cases also develop gastrointestinal events such as diarrhea, nausea, vomiting and abdominal pain. Materials and Methods: We conducted an observational, retrospective study in the Infectious Diseases Clinic of “Victor Babes” Hospital, Timis County, in order to assess the incidence, outcome and risk factors for clostridium difficile infection (CDI) in COVID-19 patients. Results: Out of 2065 COVID-19 cases, hospitalized between 1st September 2020 and 30th April 2021, 40 cases of CDI were identified with 32 cases of hospital-onset of CDI and eight cases of community-onset and healthcare-associated CDI. By randomization, polymerase chain reaction ribotyping of Clostridium Difficile was performed in six cases. All the randomized cases tested positive for ribotype 027. The percentage of cases recovered with complications at discharge was higher among COVID-19 patients and CDI (p = 0.001). The in-hospital stay, 36 days versus 28 days, was longer among COVID-19 patients and CDI (p = 0.01). The presence of previous hospitalization (p = 0.004) and administration of antibiotics during the hospital stay, increased the risk of CDI among COVID-19 patients. The mean adjusted CCI at admission was lower among controls (p = 0.01). In two cases, exitus was strictly CDI-related, with one case positive for 027 ribotype. Conclusions: CDI has complicated the outcome of COVID-19 patients, especially for those with comorbidities or previously exposed to the healthcare system. In the face of the COVID-19 pandemic and the widespread, extensive use of antibiotics, clinicians should remain vigilant for possible CDI and SARS-CoV-2 co-infection.

Clostridium Difficile and COVID-19: General Data, Ribotype, Clinical Form, Treatment-Our Experience from the Largest Infectious Diseases Hospital in Western Romania.

Bacterial resistance to antibiotics has proven difficult to control over the past few decades. The large group of multidrug-resistant bacteria includes carbapenemase-producing bacteria (CPB), for which limited therapeutic options and infection control measures are available. Furthermore, carbapenemases associate with high-risk clones that are defined by the sequence type (ST) to which each bacterium belongs. The objectives of this cross-sectional and retrospective study were to describe the CPB population isolated in a third-level hospital in Southern Spain between 2015 and 2020 and to establish the relationship between the ST and the epidemiological situation defined by the hospital. CPB were microbiologically studied in all rectal and pharyngeal swabs and clinical samples received between January 2015 and December 2020, characterizing isolates using MicroScan and mass spectrometry. Carbapenemases were detected by PCR and Sanger sequencing, and STs were assigned by multilocus sequence typing (MLST). Isolates were genetically related by pulsed-field gel electrophoresis using Xbal, Spel, or Apal enzymes. The episodes in which each CPB was isolated were recorded and classified as involved or non-involved in an outbreak. There were 320 episodes with CPB during the study period: 18 with K. pneumoniae, 14 with Klebisella oxytoca, 9 with Citrobacter freundii, 11 with Escherichia coli, 46 with Enterobacter cloacae, 70 with Acinetobacter baumannii, and 52 with Pseudomonas aeruginosa. The carbapenemase groups detected were OXA, VIM, KPC, and NDM with various subgroups. Synchronous relationships were notified between episodes of K. pneumoniae and outbreaks for ST15, ST258, ST307, and ST45, but not for the other CPB. There was a major increase in infections with CPB over the years, most notably during 2020, coinciding with the COVID-19 pandemic. This study highlights the usefulness of gene sequencing techniques to control the spread of these microorganisms, especially in healthcare centers. These techniques offer faster results, and a reduction in their cost may make their real-time application more feasible. The combination of epidemiological data with real-time molecular sequencing techniques can provide a major advance in the transmission control of these CPB and in the management of infected patients. Real-time sequencing is essential to increase precision and thereby control outbreaks and target infection prevention measures in a more effective manner.

/pdf/a-study-in-a-regional-hospital-of-a-mid-sized-spanish-city-4et4qzycwm.pdf

A Study in a Regional Hospital of a Mid-Sized Spanish City Indicates a Major Increase in Infection/Colonization by Carbapenem-Resistant Bacteria, Coinciding with the COVID-19 Pandemic.

Using Artificial Intelligence to Reduce Orthopedic Surgical Site Infection Surveillance Workload: Algorithm Design, Validation, and Implementation in Four Spanish Hospitals.

The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections in 2020: A summary of data reported to the National Healthcare Safety Network - CORRIGENDUM.

Abstract Objective: Automated surveillance methods increasingly replace or support conventional (manual) surveillance; the latter is labor intensive and vulnerable to subjective interpretation. We sought to validate 2 previously developed semiautomated surveillance algorithms to identify deep surgical site infections (SSIs) in patients undergoing colorectal surgeries in Dutch hospitals. Design: Multicenter retrospective cohort study. Methods: From 4 hospitals, we selected colorectal surgery patients between 2018 and 2019 based on procedure codes, and we extracted routine care data from electronic health records. Per hospital, a classification model and a regression model were applied independently to classify patients into low- or high probability of having developed deep SSI. High-probability patients need manual SSI confirmation; low-probability records are classified as no deep SSI. Sensitivity, positive predictive value (PPV), and workload reduction were calculated compared to conventional surveillance. Results: In total, 672 colorectal surgery patients were included, of whom 28 (4.1%) developed deep SSI. Both surveillance models achieved good performance. After adaptation to clinical practice, the classification model had 100% sensitivity and PPV ranged from 11.1% to 45.8% between hospitals. The regression model had 100% sensitivity and 9.0%–14.9% PPV. With both models, <25% of records needed review to confirm SSI. The regression model requires more complex data management skills, partly due to incomplete data. Conclusions: In this independent external validation, both surveillance models performed well. The classification model is preferred above the regression model because of source-data availability and less complex data-management requirements. The next step is implementation in infection prevention practices and workflow processes.

/pdf/semiautomated-surveillance-of-deep-surgical-site-infections-2ue7w0of.pdf

Semiautomated surveillance of deep surgical site infections after colorectal surgeries: A multicenter external validation of two surveillance algorithms

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Semiautomated surveillance of deep surgical site infections after colorectal surgeries: A multicenter external validation of two surveillance algorithms - ERRATUM.

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The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections in 2020: A summary of data reported to the National Healthcare Safety Network - CORRIGENDUM.

Semiautomated surveillance of deep surgical site infections after colorectal surgeries: A multicenter external validation of two surveillance algorithms

Semiautomated surveillance of deep surgical site infections after colorectal surgeries: A multicenter external validation of two surveillance algorithms - ERRATUM.