The clinical impact of bacterial co-infection among moderate, severe and critically ill COVID-19 patients in the second referral hospital in Surabaya

Characterization of genes related to the efflux pump and porin in multidrug-resistant Escherichia coli strains isolated from patients with COVID-19 after secondary infection

BACKGROUND

Escherichia coli (E. coli) is a multidrug resistant opportunistic pathogen that can cause secondary bacterial infections in patients with COVID-19. This study aimed to determine the antimicrobial resistance profile of E. coli as a secondary bacterial infection in patients with COVID-19 and to assess the prevalence and characterization of genes related to efflux pumps and porin.

METHODS

A total of 50 nonduplicate E. coli isolates were collected as secondary bacterial infections in COVID-19 patients. The isolates were cultured from sputum samples. Confirmation and antibiotic susceptibility testing were conducted by Vitek 2. PCR was used to assess the prevalence of the efflux pump and porin-related genes in the isolates. The phenotypic and genotypic evolution of antibiotic resistance genes related to the efflux pump was evaluated.

RESULTS

The E. coli isolates demonstrated high resistance to ampicillin (100%), cefixime (62%), cefepime (62%), amoxicillin-clavulanic acid (60%), cefuroxime (60%), and ceftriaxone (58%). The susceptibility of E. coli to ertapenem was greatest (92%), followed by imipenem (88%), meropenem (86%), tigecycline (80%), and levofloxacin (76%). Regarding efflux pump gene combinations, there was a significant association between the acrA gene and increased resistance to levofloxacin, between the acrB gene and decreased resistance to meropenem and increased resistance to levofloxacin, and between the ompF and ompC genes and increased resistance to gentamicin.

CONCLUSIONS

The antibiotics ertapenem, imipenem, meropenem, tigecycline, and levofloxacin were effective against E. coli in patients with COVID-19. Genes encoding efflux pumps and porins, such as acrA, acrB, and outer membrane porins, were highly distributed among all the isolates. Efflux pump inhibitors could be alternative antibiotics for restoring tetracycline activity in E. coli isolates.

Hemodynamic, Oxygenation and Lymphocyte Parameters Predict COVID-19 Mortality

The mortality of COVID-19 patients has left the world devastated. Many scoring systems have been developed to predict the mortality of COVID-19 patients, but several scoring components cannot be carried out in limited health facilities. Herein, the authors attempted to create a new and easy scoring system involving mean arterial pressure (MAP), PF Ratio, or SF ratio-respiration rate (SF Ratio-R), and lymphocyte absolute, which were abbreviated as MPL or MSLR functioning, as a predictive scoring system for mortality within 30 days for COVID-19 patients. Of 132 patients with COVID-19 hospitalized between March and November 2021, we followed up on 96 patients. We present bivariate and multivariate analyses as well as the area under the curve (AUC) and Kaplan-Meier charts. From 96 patients, we obtained an MPL score of 3 points: MAP < 75 mmHg, PF Ratio < 200, and lymphocyte absolute < 1500/µL, whereas the MSLR score was 6 points: MAP < 75 mmHg, SF Ratio < 200, lymphocyte absolute < 1500/µL, and respiration rate 24/min. The MPL cut-off point is 2, while the MSLR is 4. MPL and MSLR have the same sensitivity (79.1%) and specificity (75.5%). The AUC value of MPL vs. MSLR was 0.802 vs. 0.807. The MPL ≥ 2 and MSLR ≥ 4 revealed similar predictions for survival within 30 days (p < 0.05). Conclusion: MPL and MSLR scores are potential predictors of mortality in COVID-19 patients within 30 days in a resource-limited country.

Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes

The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in millions of deaths worldwide. The disease presents with various manifestations that can vary in severity and long-term outcomes. Previous efforts have contributed to the development of effective strategies for treatment and prevention by uncovering the mechanism of viral infection. We now know all the direct protein-protein interactions that occur during the lifecycle of SARS-CoV-2 infection, but it is critical to move beyond these known interactions to a comprehensive understanding of the "full interactome" of SARS-CoV-2 infection, which incorporates human microRNAs (miRNAs), additional human protein-coding genes, and exogenous microbes. Potentially, this will help in developing new drugs to treat COVID-19, differentiating the nuances of long COVID, and identifying histopathological signatures in SARS-CoV-2-infected organs. To construct the full interactome, we developed a statistical modeling approach called MLCrosstalk (multiple-layer crosstalk) based on latent Dirichlet allocation. MLCrosstalk integrates data from multiple sources, including microbes, human protein-coding genes, miRNAs, and human protein-protein interactions. It constructs "topics" that group SARS-CoV-2 with genes and microbes based on similar patterns of co-occurrence across patient samples. We use these topics to infer linkages between SARS-CoV-2 and protein-coding genes, miRNAs, and microbes. We then refine these initial linkages using network propagation to contextualize them within a larger framework of network and pathway structures. Using MLCrosstalk, we identified genes in the IL1-processing and VEGFA-VEGFR2 pathways that are linked to SARS-CoV-2. We also found that Rothia mucilaginosa and Prevotella melaninogenica are positively and negatively correlated with SARS-CoV-2 abundance, a finding corroborated by analysis of single-cell sequencing data.

Duration of SARS-CoV-2 RNA Shedding Is Significantly Influenced by Disease Severity, Bilateral Pulmonary Infiltrates, Antibiotic Treatment, and Diabetic Status: Consideration for Isolation Period

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) ribonucleic acid (RNA) shedding is an important parameter for determining the optimal length of isolation period required for coronavirus disease 2019 (COVID-19) patients. However, the clinical (i.e., patient and disease) characteristics that could influence this parameter have yet to be determined. In this study, we aim to explore the potential associations between several clinical features and the duration of SARS-CoV-2 RNA shedding in patients hospitalized with COVID-19. A retrospective cohort study involving 162 patients hospitalized for COVID-19 in a tertiary referral teaching hospital in Indonesia was performed from June to December 2021. Patients were grouped based on the mean duration of viral shedding and were compared based on several clinical characteristics (e.g., age, sex, comorbidities, COVID-19 symptoms, severity, and therapies). Subsequently, clinical factors potentially associated with the duration of SARS-CoV-2 RNA shedding were further assessed using multivariate logistic regression analysis. As a result, the mean duration of SARS-CoV-2 RNA shedding was found to be 13 ± 8.44 days. In patients with diabetes mellitus (without chronic complications) or hypertension, the duration of viral shedding was significantly prolonged (≥13 days; p = 0.001 and p = 0.029, respectively). Furthermore, patients with dyspnea displayed viral shedding for longer durations (p = 0.011). The multivariate logistic regression analysis reveals that independent risk factors associated with the duration of SARS-CoV-2 RNA shedding include disease severity (adjusted odds ratio [aOR] = 2.94; 95% CI = 1.36-6.44), bilateral lung infiltrates (aOR = 2.79; 95% CI = 1.14-6.84), diabetes mellitus (aOR = 2.17; 95% CI = 1.02-4.63), and antibiotic treatment (aOR = 3.66; 95% CI = 1.74-7.71). In summary, several clinical factors are linked with the duration of SARS-CoV-2 RNA shedding. Disease severity is positively associated with the duration of viral shedding, while bilateral lung infiltrates, diabetes mellitus, and antibiotic treatment are negatively linked with the duration of viral shedding. Overall, our findings suggest the need to consider different isolation period estimations for specific clinical characteristics of patients with COVID-19 that affect the duration of SARS-CoV-2 RNA shedding.

Recommendations and guidelines for the diagnosis and management of Coronavirus Disease-19 (COVID-19) associated bacterial and fungal infections in Taiwan

Coronavirus disease-19 (COVID-19) is an emerging infectious disease caused by SARS-CoV-2 that has rapidly evolved into a pandemic to cause over 600 million infections and more than 6.6 million deaths up to Nov 25, 2022. COVID-19 carries a high mortality rate in severe cases. Co-infections and secondary infections with other micro-organisms, such as bacterial and fungus, further increases the mortality and complicates the diagnosis and management of COVID-19. The current guideline provides guidance to physicians for the management and treatment of patients with COVID-19 associated bacterial and fungal infections, including COVID-19 associated bacterial infections (CABI), pulmonary aspergillosis (CAPA), candidiasis (CAC) and mucormycosis (CAM). Recommendations were drafted by the 7th Guidelines Recommendations for Evidence-based Antimicrobial agents use Taiwan (GREAT) working group after review of the current evidence, using the grading of recommendations assessment, development, and evaluation (GRADE) methodology. A nationwide expert panel reviewed the recommendations in March 2022, and the guideline was endorsed by the Infectious Diseases Society of Taiwan (IDST). This guideline includes the epidemiology, diagnostic methods and treatment recommendations for COVID-19 associated infections. The aim of this guideline is to provide guidance to physicians who are involved in the medical care for patients with COVID-19 during the ongoing 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.

Bacterial co-infection and antibiotic stewardship in patients with COVID-19: a systematic review and meta-analysis

INTRODUCTION

Understanding the proportion of patients with COVID-19 who have respiratory bacterial co-infections and the responsible pathogens is important for managing COVID-19 effectively while ensuring responsible antibiotic use.

OBJECTIVE

To estimate the frequency of bacterial co-infection in COVID-19 hospitalized patients and of antibiotic prescribing during the early pandemic period and to appraise the use of antibiotic stewardship criteria.

METHODS

Systematic review and meta-analysis was performed using major databases up to May 5, 2021. We included studies that reported proportion/prevalence of bacterial co-infection in hospitalized COVID-19 patients and use of antibiotics. Where available, data on duration and type of antibiotics, adverse events, and any information about antibiotic stewardship policies were also collected.

RESULTS

We retrieved 6,798 studies and included 85 studies with data from more than 30,000 patients. The overall prevalence of bacterial co-infection was 11% (95% CI 8% to 16%; 70 studies). When only confirmed bacterial co-infections were included the prevalence was 4% (95% CI 3% to 6%; 20 studies). Overall antibiotic use was 60% (95% CI 52% to 68%; 52 studies). Empirical antibiotic use rate was 62% (95% CI 55% to 69%; 11 studies). Few studies described criteria for stopping antibiotics.

CONCLUSION

There is currently insufficient evidence to support widespread empirical use of antibiotics in most hospitalised patients with COVID-19, as the overall proportion of bacterial co-infection is low. Furthermore, as the use of antibiotics during the study period appears to have been largely empirical, clinical guidelines to promote and support more targeted administration of antibiotics in patients admitted to hospital with COVID-19 are required.

Coronavirus disease 2019 (COVID-19) associated bacterial coinfection: Incidence, diagnosis and treatment

Coronavirus disease 2019 (COVID-19) emerged as a pandemic that spread rapidly around the world, causing nearly 500 billion infections and more than 6 million deaths to date. During the first wave of the pandemic, empirical antibiotics was prescribed in over 70% of hospitalized COVID-19 patients. However, research now shows a low incidence rate of bacterial coinfection in hospitalized COVID-19 patients, between 2.5% and 5.1%. The rate of secondary infections was 3.7% in overall, but can be as high as 41.9% in the intensive care units. Over-prescription of antibiotics to treat COVID-19 patients fueled the ongoing antimicrobial resistance globally. Diagnosis of bacterial coinfection is challenging due to indistinguishable clinical presentations with overlapping lower respiratory tract symptoms such as fever, cough and dyspnea. Other diagnostic methods include conventional culture, diagnostic syndromic testing, serology test and biomarkers. COVID-19 patients with bacterial coinfection or secondary infection have a higher in-hospital mortality and longer length of stay, timely and appropriate antibiotic use aided by accurate diagnosis is crucial to improve patient outcome and prevent antimicrobial resistance.

Occurrence and distribution of azithromycin in wastewater treatment plants, seawater, and sediments of the northern part of the Persian Gulf around Bushehr port: A comparison with Pre-COVID 19 pandemic

One of the environmental effects of COVID 19 is the contamination of ecosystems with antibiotics due to their high consumption to treat this disease. Many years ago, the distribution of antibiotics including azithromycin (Azi) in wastewater treatment plants in Bushehr city, seawater, and sediment of the Persian Gulf has been investigated. As Azi has been prescribed to COVID 19 patients, contamination of the environment with this drug can also be assumed. Thus, we decided to examine this hypothesis by repeating our previous study during COVID 19 period. We collected wastewater samples from influent, effluent, and different units of three wastewater treatment plants (WWTPs) including one municipal WWTP (Plant A) and two hospital-WWTPs (Plant B and C). Seawater and adjusted sediments were gathered from 8 stations located in the Persian Gulf in two seasons to evaluate the special and temporal variation. The results showed a huge growth of Azi pollution in all studied matrixes. The mean Azi values in the influent of Plant A, B, and C were 145 ng/L, 110 ng/L, and 896 ng/L, which represented an 9, 6, and 48-time increase compared with those obtained in 2017 (before COVID 19). The Azi removal efficiency had a different behavior compared to before COVID 19. The mean concentration of Azi in seawater and sediment samples was 9 ng/L and 6 ng/g, which was 3 and 4-fold higher than the previous study. Opposed to our former study, the Azi amount in the aqueous phase was less subjected to temporal seasonal variations. Our observations indicated the wide distribution of Azi in the environment and a future threat of intense growth of antibiotic resistance in ecosystems.

Prevalence of bacterial coinfection and patterns of antibiotics prescribing in patients with COVID-19: A systematic review and meta-analysis

Background

Evidence around prevalence of bacterial coinfection and pattern of antibiotic use in COVID-19 is controversial although high prevalence rates of bacterial coinfection have been reported in previous similar global viral respiratory pandemics. Early data on the prevalence of antibiotic prescribing in COVID-19 indicates conflicting low and high prevalence of antibiotic prescribing which challenges antimicrobial stewardship programmes and increases risk of antimicrobial resistance (AMR).

Aim

To determine current prevalence of bacterial coinfection and antibiotic prescribing in COVID-19 patients.

Data source

OVID MEDLINE, OVID EMBASE, Cochrane and MedRxiv between January 2020 and June 2021.

Study eligibility

English language studies of laboratory-confirmed COVID-19 patients which reported (a) prevalence of bacterial coinfection and/or (b) prevalence of antibiotic prescribing with no restrictions to study designs or healthcare setting.

Participants

Adults (aged ≥ 18 years) with RT-PCR confirmed diagnosis of COVID-19, regardless of study setting.

Methods

Systematic review and meta-analysis. Proportion (prevalence) data was pooled using random effects meta-analysis approach; and stratified based on region and study design.

Results

A total of 1058 studies were screened, of which 22, hospital-based studies were eligible, compromising 76,176 of COVID-19 patients. Pooled estimates for the prevalence of bacterial co-infection and antibiotic use were 5.62% (95% CI 2.26–10.31) and 61.77% (CI 50.95–70.90), respectively. Sub-group analysis by region demonstrated that bacterial co-infection was more prevalent in North American studies (7.89%, 95% CI 3.30–14.18).

Conclusion

Prevalence of bacterial coinfection in COVID-19 is low, yet prevalence of antibiotic prescribing is high, indicating the need for targeted COVID-19 antimicrobial stewardship initiatives to reduce the global threat of AMR.

Negative predictive value of procalcitonin to rule out bacterial respiratory co-infection in critical covid-19 patients

Background

: Procalcitonin (PCT) and C-Reactive Protein (CRP) are useful biomarkers to differentiate bacterial from viral or fungal infections, although the association between them and co-infection or mortality in COVID-19 remains unclear.

Methods

: The study represents a retrospective cohort study of patients admitted for COVID-19 pneumonia to 84 ICUs from ten countries between (March 2020-January 2021). Primary outcome was to determine whether PCT or CRP at admission could predict community-acquired bacterial respiratory co-infection (BC) and its added clinical value by determining the best discriminating cut-off values. Secondary outcome was to investigate its association with mortality. To evaluate the main outcome, a binary logistic regression was performed. The area under the curve evaluated diagnostic performance for BC prediction.

Results

: 4635 patients were included, 7.6% fulfilled BC diagnosis. PCT (0.25[IQR 0.1-0.7] versus 0.20[IQR 0.1-0.5]ng/mL, p<0.001) and CRP (14.8[IQR 8.2-23.8] versus 13.3 [7-21.7]mg/dL, p=0.01) were higher in BC group. Neither PCT nor CRP were independently associated with BC and both had a poor ability to predict BC (AUC for PCT 0.56, for CRP 0.54). Baseline values of PCT<0.3ng/mL, could be helpful to rule out BC (negative predictive value 91.1%) and PCT≥0.50ng/mL was associated with ICU mortality (OR 1.5,p<0.001).

Conclusions

: These biomarkers at ICU admission led to a poor ability to predict BC among patients with COVID-19 pneumonia. Baseline values of PCT<0.3ng/mL may be useful to rule out BC, providing clinicians a valuable tool to guide antibiotic stewardship and allowing the unjustified overuse of antibiotics observed during the pandemic, additionally PCT≥0.50ng/mL might predict worsening outcomes.