Risk factors for infections caused by carbapenem-resistant Enterobacterales: an international matched case-control-control study (EURECA)

Cases were patients with complicated urinary tract infection (cUTI), complicated intraabdominal (cIAI), pneumonia or bacteraemia from other sources (BSI-OS) due to CRE; control groups were patients with infection caused by carbapenem-susceptible Enterobacterales (CSE), and by non-infected patients, respectively. Matching criteria included type of infection for CSE group, ward and duration of hospital admission. Conditional logistic regression was used to identify risk factors. Findings Overall, 235 CRE case patients, 235 CSE controls and 705 non-infected controls were included. The CRE infections were cUTI (133, 56.7%), pneumonia (44, 18.7%), cIAI and BSI-OS (29, 12.3% each). Carbapenemase genes were found in 228 isolates: OXA-48/like, 112 (47.6%), KPC, 84 (35.7%), and metallo-beta-lactamases, 44 (18.7%); 13 produced two. The risk factors for CRE infection in both type of controls were (adjusted OR for CSE controls; 95% CI; p value) previous colonisation/infection by CRE (6.94; 2.74-15.53; <0.001), urinary catheter (1.78; 1.03-3.07; 0.038) and exposure to broad spectrum antibiotics, as categorical (2.20; 1.25-3.88; 0.006) and time-dependent (1.04 per day; 1.00-1.07; 0.014); chronic renal failure (2.81; 1.40-5.64; 0.004) and admission from home (0.44; 0.23-0.85; 0.014) were significant only for CSE controls. Subgroup analyses provided similar results. Interpretation The main risk factors for CRE infections in hospitals with high incidence included previous coloni-zation, urinary catheter and exposure to broad spectrum antibiotics

Attributable mortality of infections caused by carbapenem-resistant Enterobacterales: results from a prospective, multinational case-control-control matched cohorts study (EURECA)

Objectives: To assess the mortality attributable to infections caused by carbapenem-resistant Enterobacterales (CRE) and to investigate the effect of clinical management on differences in observed outcomes in a multinational matched cohort study. Methods: A prospective matched -cohorts study (NCT02709408) was performed in 50 European hospitals from March 2016 to November 2018. The main outcome was 30 -day mortality with an active postdischarge follow-up when applied. The CRE cohort included patients with complicated urinary tract infections, complicated intra-abdominal infections, pneumonia, or bacteraemia from other sources because of CRE. Two control cohorts were selected: patients with infection caused by carbapenem-susceptible Enterobacterales (CSE) and patients without infection. Matching criteria included type of infection for the CSE group, hospital ward of CRE detection, and duration of hospital admission up to CRE detection. Multivariable and stratified Cox regression was applied. Results: The cohorts included 235 patients with CRE infection, 235 patients with CSE infection, and 705 non-infected patients. The 30-day mortality (95% CI) was 23.8% (18.8-29.6), 10.6% (7.2-15.2), and 8.4% (6.5-10.6), respectively. The difference in 30 -day mortality rates between patients with CRE infection when compared with patients with CSE infection was 13.2% (95% CI, 6.3-20.0), (HR, 2.57; 95% CI, 1.55 -4.26; p &lt; 0.001), and 15.4% (95% CI, 10.5-20.2) when compared with non-infected patients (HR, 3.85; 95% CI, 2.57-5.77; p &lt; 0.001). The population attributable fraction for 30 -day mortality for CRE vs. CSE was 19.28%, and for CRE vs. non -infected patients was 9.61%. After adjustment for baseline variables, the HRs for mortality were 1.87 (95% CI, 0.99-3.50; p 0.06) and 3.65 (95% CI, 2.29-5.82; p &lt; 0.001), respectively. However, when treatment -related time -dependent variables were added, the HR of CRE vs. CSE reduced to 1.44 (95% CI, 0.78-2.67; p 0.24). Discussion: CRE infections are associated with significant attributable mortality and increased adjusted hazard of mortality when compared with CSE infections or patients without infection. Underlying patient characteristics and a delay in appropriate treatment play an important role in the CRE mortality. (c) 2023 The Authors. Published by Elsevier Ltd on behalf of European Society of Clinical Microbiology and Infectious Diseases. This is an open access article under the CC BY -NC -ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/)

Attributable mortality of infections caused by carbapenem-resistant Enterobacterales: results from a prospective, multinational case-control-control matched cohorts study (EURECA)

OBJECTIVES: To assess the mortality attributable to infections caused by carbapenem-resistant Enterobacterales (CRE) and to investigate the effect of clinical management on differences in observed outcomes in a multinational matched cohort study. METHODS: A prospective matched-cohorts study (NCT02709408) was performed in 50 European hospitals from March 2016 to November 2018. The main outcome was 30-day mortality with an active post-discharge follow-up when applied. The CRE cohort included patients with complicated urinary tract infections, complicated intra-abdominal infections, pneumonia, or bacteraemia from other sources because of CRE. Two control cohorts were selected: patients with infection caused by carbapenem-susceptible Enterobacterales (CSE) and patients without infection. Matching criteria included type of infection for the CSE group, hospital ward of CRE detection, and duration of hospital admission up to CRE detection. Multivariable and stratified Cox regression was applied. RESULTS: The cohorts included 235 patients with CRE infection, 235 patients with CSE infection, and 705 non-infected patients. The 30-day mortality (95% CI) was 23.8% (18.8-29.6), 10.6% (7.2-15.2), and 8.4% (6.5-10.6), respectively. The difference in 30-day mortality rates between patients with CRE infection when compared with patients with CSE infection was 13.2% (95% CI, 6.3-20.0), (HR, 2.57; 95% CI, 1.55-4.26; p < 0.001), and 15.4% (95% CI, 10.5-20.2) when compared with non-infected patients (HR, 3.85; 95% CI, 2.57-5.77; p < 0.001). The population attributable fraction for 30-day mortality for CRE vs. CSE was 19.28%, and for CRE vs. non-infected patients was 9.61%. After adjustment for baseline variables, the HRs for mortality were 1.87 (95% CI, 0.99-3.50; p 0.06) and 3.65 (95% CI, 2.29-5.82; p < 0.001), respectively. However, when treatment-related time-dependent variables were added, the HR of CRE vs. CSE reduced to 1.44 (95% CI, 0.78-2.67; p 0.24). DISCUSSION: CRE infections are associated with significant attributable mortality and increased adjusted hazard of mortality when compared with CSE infections or patients without infection. Underlying patient characteristics and a delay in appropriate treatment play an important role in the CRE mortality

Risk factors for infections caused by carbapenem-resistant Enterobacterales: an international matched case-control-control study (EURECA)

© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).[Background] Data on risk factors for carbapenem-resistant Enterobacterales (CRE) with wider applicability are needed to inform preventive measures and efficient design of randomised trials.[Methods] An international matched case-control-control study was performed in 50 hospitals with high CRE incidence from March 2016 to November 2018 to investigate different aspects of infections caused by CRE (NCT02709408). Cases were patients with complicated urinary tract infection (cUTI), complicated intraabdominal (cIAI), pneumonia or bacteraemia from other sources (BSI-OS) due to CRE; control groups were patients with infection caused by carbapenem-susceptible Enterobacterales (CSE), and by non-infected patients, respectively. Matching criteria included type of infection for CSE group, ward and duration of hospital admission. Conditional logistic regression was used to identify risk factors.[Findings] Overall, 235 CRE case patients, 235 CSE controls and 705 non-infected controls were included. The CRE infections were cUTI (133, 56.7%), pneumonia (44, 18.7%), cIAI and BSI-OS (29, 12.3% each). Carbapenemase genes were found in 228 isolates: OXA-48/like, 112 (47.6%), KPC, 84 (35.7%), and metallo-β-lactamases, 44 (18.7%); 13 produced two. The risk factors for CRE infection in both type of controls were (adjusted OR for CSE controls; 95% CI; p value) previous colonisation/infection by CRE (6.94; 2.74–15.53; <0.001), urinary catheter (1.78; 1.03–3.07; 0.038) and exposure to broad spectrum antibiotics, as categorical (2.20; 1.25–3.88; 0.006) and time-dependent (1.04 per day; 1.00–1.07; 0.014); chronic renal failure (2.81; 1.40–5.64; 0.004) and admission from home (0.44; 0.23–0.85; 0.014) were significant only for CSE controls. Subgroup analyses provided similar results.[Interpretation] The main risk factors for CRE infections in hospitals with high incidence included previous colonization, urinary catheter and exposure to broad spectrum antibiotics.The study was funded by the Innovative Medicines Initiative Joint Undertaking (https://www.imi.europa.eu/) under Grant Agreement No. 115620 (COMBACTE-CARE).Peer reviewe

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century