Associated factors for mortality in a COVID-19 colombian cohort: is the third wave relevant when Mu variant was predominant epidemiologically?

OBJECTIVES: To evaluate the association between Colombia's third wave when the Mu variant was predominant epidemiologically (until 75%) in Colombia and COVID-19 all-cause in-hospital mortality. METHODS: In this retrospective cohort, we included hospitalized patients ≥18 years with SARS-CoV-2 infection between March 2020 to September 2021 in ten hospitals from three cities in Colombia. Description analysis, survival, and multivariate Cox regression analyses were performed to evaluate the association between the third epidemic wave and in-hospital mortality. RESULTS: A total of 25,371 patients were included. The age-stratified time-to-mortality curves showed differences according to epidemic waves in patients ≥75 years (log-rank test p = 0.012). In the multivariate Cox analysis, the third wave was not associated with increased mortality relative to the first wave (aHR 0.95; 95%CI 0.84-1.08), but there was an interaction between age ≥75 years and the third wave finding a lower HR for mortality (aHR 0.56, 95%CI 0.36-0.86). CONCLUSIONS: We did not find an increase in in-hospital mortality during the third epidemic wave in which the Mu variant was predominant in Colombia. The reduced hazard in mortality in patients ≥75 years hospitalized in the third wave could be explained by the high coverage of SARS-CoV-2 vaccination in this population and patients with underlying conditions.

Antibiotic resistance associated with the COVID-19 pandemic: a systematic review and meta-analysis.

BACKGROUND: COVID-19 and antimicrobial resistance (AMR) are two intersecting global public health crises. OBJECTIVE: We aimed to describe the impact of the COVID-19 pandemic on AMR across health care settings. DATA SOURCE: A search was conducted in December 2021 in WHO COVID-19 Research Database with forward citation searching up to June 2022. STUDY ELIGIBILITY: Studies evaluating the impact of COVID-19 on AMR in any population were included and influencing factors were extracted. Reporting of enhanced infection prevention and control and/or antimicrobial stewardship programs was noted. METHODS: Pooling was done separately for Gram-negative and Gram-positive organisms. Random-effects meta-analysis was performed. RESULTS: Of 6036 studies screened, 28 were included and 23 provided sufficient data for meta-analysis. The majority of studies focused on hospital settings (n = 25, 89%). The COVID-19 pandemic was not associated with a change in the incidence density (incidence rate ratio 0.99, 95% CI: 0.67-1.47) or proportion (risk ratio 0.91, 95% CI: 0.55-1.49) of methicillin-resistant Staphylococcus aureus or vancomycin-resistant enterococci cases. A non-statistically significant increase was noted for resistant Gram-negative organisms (i.e. extended-spectrum beta-lactamase, carbapenem-resistant Enterobacterales, carbapenem or multi-drug resistant or carbapenem-resistant Pseudomonas aeruginosa or Acinetobacter baumannii, incidence rate ratio 1.64, 95% CI: 0.92-2.92; risk ratio 1.08, 95% CI: 0.91-1.29). The absence of reported enhanced infection prevention and control and/or antimicrobial stewardship programs initiatives was associated with an increase in gram-negative AMR (risk ratio 1.11, 95% CI: 1.03-1.20). However, a test for subgroup differences showed no statistically significant difference between the presence and absence of these initiatives (p 0.40). CONCLUSION: The COVID-19 pandemic may have hastened the emergence and transmission of AMR, particularly for Gram-negative organisms in hospital settings. But there is considerable heterogeneity in both the AMR metrics used and the rate of resistance reported across studies. These findings reinforce the need for strengthened infection prevention, antimicrobial stewardship, and AMR surveillance in the context of the COVID-19 pandemic.

Antimicrobial resistance in patients with COVID-19: a systematic review and meta-analysis.

BACKGROUND: Frequent use of antibiotics in patients with COVID-19 threatens to exacerbate antimicrobial resistance. We aimed to establish the prevalence and predictors of bacterial infections and antimicrobial resistance in patients with COVID-19. METHODS: We did a systematic review and meta-analysis of studies of bacterial co-infections (identified within ≤48 h of presentation) and secondary infections (>48 h after presentation) in outpatients or hospitalised patients with COVID-19. We searched the WHO COVID-19 Research Database to identify cohort studies, case series, case-control trials, and randomised controlled trials with populations of at least 50 patients published in any language between Jan 1, 2019, and Dec 1, 2021. Reviews, editorials, letters, pre-prints, and conference proceedings were excluded, as were studies in which bacterial infection was not microbiologically confirmed (or confirmed via nasopharyngeal swab only). We screened titles and abstracts of papers identified by our search, and then assessed the full text of potentially relevant articles. We reported the pooled prevalence of bacterial infections and antimicrobial resistance by doing a random-effects meta-analysis and meta-regression. Our primary outcomes were the prevalence of bacterial co-infection and secondary infection, and the prevalence of antibiotic-resistant pathogens among patients with laboratory-confirmed COVID-19 and bacterial infections. The study protocol was registered with PROSPERO (CRD42021297344). FINDINGS: We included 148 studies of 362 976 patients, which were done between December, 2019, and May, 2021. The prevalence of bacterial co-infection was 5·3% (95% CI 3·8-7·4), whereas the prevalence of secondary bacterial infection was 18·4% (14·0-23·7). 42 (28%) studies included comprehensive data for the prevalence of antimicrobial resistance among bacterial infections. Among people with bacterial infections, the proportion of infections that were resistant to antimicrobials was 60·8% (95% CI 38·6-79·3), and the proportion of isolates that were resistant was 37·5% (26·9-49·5). Heterogeneity in the reported prevalence of antimicrobial resistance in organisms was substantial (I2=95%). INTERPRETATION: Although infrequently assessed, antimicrobial resistance is highly prevalent in patients with COVID-19 and bacterial infections. Future research and surveillance assessing the effect of COVID-19 on antimicrobial resistance at the patient and population level are urgently needed. FUNDING: WHO.

An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients.

Background: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. Methods: Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. Results: Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. Conclusions: Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome. Funding: Bronner P. Gonçalves, Peter Horby, Gail Carson, Piero L. Olliaro, Valeria Balan, Barbara Wanjiru Citarella, and research costs were supported by the UK Foreign, Commonwealth and Development Office (FCDO) and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z]; and Janice Caoili and Madiha Hashmi were supported by the UK FCDO and Wellcome [222048/Z/20/Z]. Peter Horby, Gail Carson, Piero L. Olliaro, Kalynn Kennon and Joaquin Baruch were supported by the Bill & Melinda Gates Foundation [OPP1209135]; Laura Merson was supported by University of Oxford's COVID-19 Research Response Fund - with thanks to its donors for their philanthropic support. Matthew Hall was supported by a Li Ka Shing Foundation award to Christophe Fraser. Moritz U.G. Kraemer was supported by the Branco Weiss Fellowship, Google.org, the Oxford Martin School, the Rockefeller Foundation, and the European Union Horizon 2020 project MOOD (#874850). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Contributions from Srinivas Murthy, Asgar Rishu, Rob Fowler, James Joshua Douglas, François Martin Carrier were supported by CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and coordinated out of Sunnybrook Research Institute. Contributions from Evert-Jan Wils and David S.Y. Ong were supported by a grant from foundation Bevordering Onderzoek Franciscus; and Andrea Angheben by the Italian Ministry of Health "Fondi Ricerca corrente-L1P6" to IRCCS Ospedale Sacro Cuore-Don Calabria. The data contributions of J.Kenneth Baillie, Malcolm G. Semple, and Ewen M. Harrison were supported by grants from the National Institute for Health Research (NIHR; award CO-CIN-01), the Medical Research Council (MRC; grant MC_PC_19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE) (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award IS-BRC-1215-20013), and NIHR Clinical Research Network providing infrastructure support. All funders of the ISARIC Clinical Characterisation Group are listed in the appendix.

The First 110,593 COVID-19 Patients Hospitalised in Lombardy: A Regionwide Analysis of Case Characteristics, Risk Factors and Clinical Outcomes.

Objectives: To describe the monthly distribution of COVID-19 hospitalisations, deaths and case-fatality rates (CFR) in Lombardy (Italy) throughout 2020. Methods: We analysed de-identified hospitalisation data comprising all COVID-19-related admissions from 1 February 2020 to 31 December 2020. The overall survival (OS) from time of first hospitalisation was estimated using the Kaplan-Meier method. We estimated monthly CFRs and performed Cox regression models to measure the effects of potential predictors on OS. Results: Hospitalisation and death peaks occurred in March and November 2020. Patients aged ≥70 years had an up to 180 times higher risk of dying compared to younger patients [70-80: HR 58.10 (39.14-86.22); 80-90: 106.68 (71.01-160.27); ≥90: 180.96 (118.80-275.64)]. Risk of death was higher in patients with one or more comorbidities [1: HR 1.27 (95% CI 1.20-1.35); 2: 1.44 (1.33-1.55); ≥3: 1.73 (1.58-1.90)] and in those with specific conditions (hypertension, diabetes). Conclusion: Our data sheds light on the Italian pandemic scenario, uncovering mechanisms and gaps at regional health system level and, on a larger scale, adding to the body of knowledge needed to inform effective health service planning, delivery, and preparedness in times of crisis.

Clinical features of, and risk factors for, severe or fatal COVID-19 among people living with HIV admitted to hospital: analysis of data from the WHO Global Clinical Platform of COVID-19.

BACKGROUND: WHO has established a Global Clinical Platform for the clinical characterisation of COVID-19 among hospitalised individuals. We assessed whether people living with HIV hospitalised with COVID-19 had increased odds of severe presentation and of in-hospital mortality compared with individuals who were HIV-negative and associated risk factors. METHODS: Between Jan 1, 2020, and July 1, 2021, anonymised individual-level data from 338 566 patients in 38 countries were reported to WHO. Using the Platform pooled dataset, we performed descriptive statistics and regression analyses to compare outcomes in the two populations and identify risk factors. FINDINGS: Of 197 479 patients reporting HIV status, 16 955 (8·6%) were people living with HIV. 16 283 (96.0%) of the 16 955 people living with HIV were from Africa; 10 603 (62·9%) were female and 6271 (37·1%) were male; the mean age was 45·5 years (SD 13·7); 6339 (38·3%) were admitted to hospital with severe illness; and 3913 (24·3%) died in hospital. Of the 10 166 people living with HIV with known antiretroviral therapy (ART) status, 9302 (91·5%) were on ART. Compared with individuals without HIV, people living with HIV had 15% increased odds of severe presentation with COVID-19 (aOR 1·15, 95% CI 1·10-1·20) and were 38% more likely to die in hospital (aHR 1·38, 1·34-1·41). Among people living with HIV, male sex, age 45-75 years, and having chronic cardiac disease or hypertension increased the odds of severe COVID-19; male sex, age older than 18 years, having diabetes, hypertension, malignancy, tuberculosis, or chronic kidney disease increased the risk of in-hospital mortality. The use of ART or viral load suppression were associated with a reduced risk of poor outcomes; however, HIV infection remained a risk factor for severity and mortality regardless of ART and viral load suppression status. INTERPRETATION: In this sample of hospitalised people contributing data to the WHO Global Clinical Platform for COVID-19, HIV was an independent risk factor for both severe COVID-19 at admission and in-hospital mortality. These findings have informed WHO immunisation policy that prioritises vaccination for people living with HIV. As the results mostly reflect the data contribution from Africa, this analysis will be updated as more data from other regions become available. FUNDING: None. TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Overview of SARS-CoV-2 infection in adults living with HIV.

Around 2·5 million deaths and more than 110 million COVID-19 cases have been reported globally. Although it initially appeared that HIV infection was not a risk factor for COVID-19 or more severe disease, more recent large studies suggest that people living with HIV (particularly with low CD4 cell counts or untreated HIV infection) might have a more severe clinical course than those who are HIV-negative. Moreover, the COVID-19 pandemic has disrupted HIV prevention and treatment services worldwide, creating huge challenges to the continuity of essential activities. We have reviewed the most relevant features of COVID-19 in people living with HIV and highlighted topics where further research is required.