Bacterial co-infection and secondary infection in patients with COVID-19: a living rapid review and meta-analysis

BackgroundBacterial co-pathogens are commonly identified in viral respiratory infections and are important causes of morbidity and mortality. The prevalence of bacterial infection in patients infected with SARS-CoV-2 is not well understood.AimsTo determine the prevalence of bacterial co-infection (at presentation) and secondary infection (after presentation) in patients with COVID-19.SourcesWe performed a systematic search of MEDLINE, OVID Epub and EMBASE databases for English language literature from 2019 to April 16, 2020. Studies were included if they (a) evaluated patients with confirmed COVID-19 and (b) reported the prevalence of acute bacterial infection.ContentData were extracted by a single reviewer and cross-checked by a second reviewer. The main outcome was the proportion of COVID-19 patients with an acute bacterial infection. Any bacteria detected from non-respiratory-tract or non-bloodstream sources were excluded. Of 1308 studies screened, 24 were eligible and included in the rapid review representing 3338 patients with COVID-19 evaluated for acute bacterial infection. In the meta-analysis, bacterial co-infection (estimated on presentation) was identified in 3.5% of patients (95%CI 0.4–6.7%) and secondary bacterial infection in 14.3% of patients (95%CI 9.6–18.9%). The overall proportion of COVID-19 patients with bacterial infection was 6.9% (95%CI 4.3–9.5%). Bacterial infection was more common in critically ill patients (8.1%, 95%CI 2.3–13.8%). The majority of patients with COVID-19 received antibiotics (71.9%, 95%CI 56.1 to 87.7%).ImplicationsBacterial co-infection is relatively infrequent in hospitalized patients with COVID-19. The majority of these patients may not require empirical antibacterial treatment.     

First COVID-19 mortality case in Taiwan with bacterial co-infection by national surveillance of critically ill patients with influenza-negative pneumonia

A 63-year-old diabetic smoker with alcoholism was the first mortality case of coronavirus disease 2019 (COVID-19) in Taiwan. As concurrently infected with Klebsiella pneumoniae and subsequently with Klebsiella aerogenes, he was exposed by a national survey of patients with critically influenza-negative pneumonia. We recommend COVID-19 screening for patients with severe flu-like syndrome and protecting health-care workers from being infected.     

Bacterial and fungal coinfection among hospitalized patients with COVID-19: a retrospective cohort study in a UK secondary-care setting

ObjectivesTo investigate the incidence of bacterial and fungal coinfection of hospitalized patients with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in this retrospective observational study across two London hospitals during the first UK wave of coronavirus disease 2019 (COVID-19).MethodsA retrospective case series of hospitalized patients with confirmed SARS-CoV-2 by PCR was analysed across two acute NHS hospitals (20 February–20 April 2020; each isolate reviewed independently in parallel). This was contrasted to a control group of influenza-positive patients admitted during the 2019–2020 flu season. Patient demographics, microbiology and clinical outcomes were analysed.ResultsA total of 836 patients with confirmed SARS-CoV-2 were included; 27 (3.2%) of 836 had early confirmed bacterial isolates identified (0–5 days after admission), rising to 51 (6.1%) of 836 throughout admission. Blood cultures, respiratory samples, pneumococcal or Legionella urinary antigens and respiratory viral PCR panels were obtained from 643 (77%), 110 (13%), 249 (30%), 246 (29%) and 250 (30%) COVID-19 patients, respectively. A positive blood culture was identified in 60 patients (7.1%), of which 39 were classified as contaminants. Bacteraemia resulting from respiratory infection was confirmed in two cases (one each community-acquired Klebsiella pneumoniae and ventilator-associated Enterobacter cloacae). Line-related bacteraemia was identified in six patients (three Candida, two Enterococcus spp. and one Pseudomonas aeruginosa). All other community-acquired bacteraemias (n = 16) were attributed to nonrespiratory infection. Zero concomitant pneumococcal, Legionella or influenza infection was detected. A low yield of positive respiratory cultures was identified; Staphylococcus aureus was the most common respiratory pathogen isolated in community-acquired coinfection (4/24; 16.7%), with pseudomonas and yeast identified in late-onset infection. Invasive fungal infections (n = 3) were attributed to line-related infections. Comparable rates of positive coinfection were identified in the control group of confirmed influenza infection; clinically relevant bacteraemias (2/141; 1.4%), respiratory cultures (10/38; 26.3%) and pneumococcal-positive antigens (1/19; 5.3%) were low.ConclusionsWe found a low frequency of bacterial coinfection in early COVID-19 hospital presentation, and no evidence of concomitant fungal infection, at least in the early phase of COVID-19.     

COVID-19 associated with pulmonary aspergillosis: A literature review

Bacterial or virus co-infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported in many studies, however, the knowledge on Aspergillus co-infection among patients with coronavirus disease 2019 (COVID-19) was limited. This literature review aims to explore and describe the updated information about COVID-19 associated with pulmonary aspergillosis. We found that Aspergillus spp. can cause co-infections in patients with COVID-19, especially in severe/critical illness. The incidence of IPA in COVID-19 ranged from 19.6% to 33.3%. Acute respiratory distress syndrome requiring mechanical ventilation was the common complications, and the overall mortality was high, which could be up to 64.7% (n = 22) in the pooled analysis of 34 reported cases. The conventional risk factors of invasive aspergillosis were not common among these specific populations. Fungus culture and galactomannan test, especially from respiratory specimens could help early diagnosis. Aspergillus fumigatus was the most common species causing co-infection in COVID-19 patients, followed by Aspergillus flavus. Although voriconazole is the recommended anti-Aspergillus agent and also the most commonly used antifungal agent, aspergillosis caused by azole-resistant Aspergillus is also possible. Additionally, voriconazole should be used carefully in the concern of complicated drug–drug interaction and enhancing cardiovascular toxicity on anti-SARS-CoV-2 agents. Finally, this review suggests that clinicians should keep alerting the possible occurrence of pulmonary aspergillosis in severe/critical COVID-19 patients, and aggressively microbiologic study in addition to SARS-CoV-2 via respiratory specimens should be indicated.     

National surveillance of bacterial and fungal coinfection and secondary infection in COVID-19 patients in England: lessons from the first wave

ObjectivesThe impact of bacterial/fungal infections on the morbidity and mortality of persons with coronavirus disease 2019 (COVID-19) remains unclear. We have investigated the incidence and impact of key bacterial/fungal infections in persons with COVID-19 in England.MethodsWe extracted laboratory-confirmed cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (1st January 2020 to 2nd June 2020) and blood and lower-respiratory specimens positive for 24 genera/species of clinical relevance (1st January 2020 to 30th June 2020) from Public Health England's national laboratory surveillance system. We defined coinfection and secondary infection as a culture-positive key organism isolated within 1 day or 2–27 days, respectively, of the SARS-CoV-2-positive date. We described the incidence and timing of bacterial/fungal infections and compared characteristics of COVID-19 patients with and without bacterial/fungal infection.Results1% of persons with COVID-19 (2279/223413) in England had coinfection/secondary infection, of which >65% were bloodstream infections. The most common causative organisms were Escherichia coli, Staphylococcus aureus and Klebsiella pneumoniae. Cases with coinfection/secondary infections were older than those without (median 70 years (IQR 58–81) versus 55 years (IQR 38–77)), and a higher percentage of cases with secondary infection were of Black or Asian ethnicity than cases without (6.7% versus 4.1%, and 9.9% versus 8.2%, respectively, p < 0.001). Age-sex-adjusted case fatality rates were higher in COVID-19 cases with a coinfection (23.0% (95%CI 18.8–27.6%)) or secondary infection (26.5% (95%CI 14.5–39.4%)) than in those without (7.6% (95%CI 7.5–7.7%)) (p < 0.005).ConclusionsCoinfection/secondary bacterial/fungal infections were rare in non-hospitalized and hospitalized persons with COVID-19, varied by ethnicity and age, and were associated with higher mortality. However, the inclusion of non-hospitalized persons with asymptomatic/mild COVID-19 likely underestimated the rate of secondary bacterial/fungal infections. This should inform diagnostic testing and antibiotic prescribing strategy.     

SARS-CoV-2-induced immunodysregulation and the need for higher clinical suspicion for co-infection and secondary infection in COVID-19 patients

Cases of co-infection and secondary infection emerging during the current Coronavirus Disease-19 (COVID-19) pandemic are a major public health concern. Such cases may result from immunodysregulation induced by the SARS-CoV-2 virus. Pandemic preparedness must include identification of disease natural history and common secondary infections to implement clinical solutions.     

Predictors and microbiology of respiratory and bloodstream bacterial infection in patients with COVID-19: living rapid review update and meta-regression

BackgroundThe prevalence of bacterial infection in patients with COVID-19 is low, however, empiric antibiotic use is high. Risk stratification may be needed to minimize unnecessary empiric antibiotic use.ObjectiveTo identify risk factors and microbiology associated with respiratory and bloodstream bacterial infection in patients with COVID-19.Data sourcesWe searched MEDLINE, OVID Epub and EMBASE for published literature up to 5 February 2021.Study eligibility criteriaStudies including at least 50 patients with COVID-19 in any healthcare setting.MethodsWe used a validated ten-item risk of bias tool for disease prevalence. The main outcome of interest was the proportion of COVID-19 patients with bloodstream and/or respiratory bacterial co-infection and secondary infection. We performed meta-regression to identify study population factors associated with bacterial infection including healthcare setting, age, comorbidities and COVID-19 medication.ResultsOut of 33 345 studies screened, 171 were included in the final analysis. Bacterial infection data were available from 171 262 patients. The prevalence of co-infection was 5.1% (95% CI 3.6–7.1%) and secondary infection was 13.1% (95% CI 9.8–17.2%). There was a higher odds of bacterial infection in studies with a higher proportion of patients in the intensive care unit (ICU) (adjusted OR 18.8, 95% CI 6.5–54.8). Female sex was associated with a lower odds of secondary infection (adjusted OR 0.73, 95% CI 0.55–0.97) but not co-infection (adjusted OR 1.05, 95% CI 0.80–1.37). The most common organisms isolated included Staphylococcus aureus, coagulase-negative staphylococci and Klebsiella species.ConclusionsWhile the odds of respiratory and bloodstream bacterial infection are low in patients with COVID-19, meta-regression revealed potential risk factors for infection, including ICU setting and mechanical ventilation. The risk for secondary infection is substantially greater than the risk for co-infection in patients with COVID-19. Understanding predictors of co-infection and secondary infection may help to support improved antibiotic stewardship in patients with COVID-19.     

Respiratory viral co-infections in patients with COVID-19 and associated outcomes: A systematic review and meta-analysis

The aim of this systematic review and meta-analysis was to critically assess the published literature related to community-acquired viral co-infections and COVID-19 and to evaluate the prevalence, most identified co-pathogens, and relevant risk factors. Furthermore, we aimed to examine the clinical features and outcomes of co-infected compared to mono-infected COVID-19 patients. We systematically searched PubMed, Web of Science, Embase, Scopus, and The Cochrane Library for studies published from 1 November 2019 to 13 August 2021. We included patients of all ages and any COVID-19 severity who were screened for respiratory viral co-infection within 48 h of COVID-19 diagnosis. The main outcome was the proportion of patients with a respiratory viral co-infection. The systematic review was registered to PROSPERO (CRD42021272235). Out of 6053 initially retrieved studies, 59 studies with a total of 16,643 SARS-CoV-2 positive patients were included. The global pooled prevalence was 5.01% (95% CI 3.34%–7.27%; I² = 95%) based on a random-effects model, with Influenza Viruses (1.54%) and Enteroviruses (1.32%) being the most prevalent pathogens. Subgroup analyses showed that co-infection was significantly higher in paediatric (9.39%) than adult (3.51%) patients (p-value = 0.02). Furthermore, co-infected patients were more likely to be dyspnoeic and the odds of fatality (OR = 1.66) were increased. Although a relatively low proportion of COVID-19 patients have a respiratory viral co-infection, our findings show that multiplex viral panel testing may be advisable in patients with compatible symptoms. Indeed, respiratory virus co-infections may be associated with adverse clinical outcomes and therefore have therapeutic and prognostic implications.     

Secondary infections in patients hospitalized with COVID-19: incidence and predictive factors

ObjectivesThe aim of our study was to describe the incidence and predictive factors of secondary infections in patients with coronavirus disease 2019 (COVID-19).MethodsThis was a cohort study of patients hospitalized with COVID-19 at IRCCS San Raffaele Hospital between 25th February and 6th April 2020 (NCT04318366). We considered secondary bloodstream infections (BSIs) or possible lower respiratory tract infections (pLRTIs) occurring 48 hours after hospital admission until death or discharge. We calculated multivariable Fine–Gray models to assess factors associated with risk of secondary infections.ResultsAmong 731 patients, a secondary infection was diagnosed in 68 patients (9.3%); 58/731 patients (7.9%) had at least one BSI and 22/731 patients (3.0%) at least one pLRTI. The overall 28-day cumulative incidence was 16.4% (95%CI 12.4–21.0%). Most of the BSIs were due to Gram-positive pathogens (76/106 isolates, 71.7%), specifically coagulase-negative staphylococci (53/76, 69.7%), while among Gram-negatives (23/106, 21.7%) Acinetobacter baumanii (7/23, 30.4%) and Escherichia coli (5/23, 21.7%) predominated. pLRTIs were caused mainly by Gram-negative pathogens (14/26, 53.8%). Eleven patients were diagnosed with putative invasive aspergillosis. At multivariable analysis, factors associated with secondary infections were low baseline lymphocyte count (≤0.7 versus >0.7 per 10⁹/L, subdistribution hazard ratios (sdHRs) 1.93, 95%CI 1.11–3.35), baseline PaO₂/FiO₂ (per 100 points lower: sdHRs 1.56, 95%CI 1.21–2.04), and intensive-care unit (ICU) admission in the first 48 hours (sdHR 2.51, 95%CI 1.04–6.05).ConclusionsPatients hospitalized with COVID-19 had a high incidence of secondary infections. At multivariable analysis, early need for ICU, respiratory failure, and severe lymphopenia were identified as risk factors for secondary infections.     

Quantitative Assessment of Chest CT Patterns in COVID-19 and Bacterial Pneumonia Patients: a Deep Learning Perspective

BackgroundIt is difficult to distinguish subtle differences shown in computed tomography (CT) images of coronavirus disease 2019 (COVID-19) and bacterial pneumonia patients, which often leads to an inaccurate diagnosis. It is desirable to design and evaluate interpretable feature extraction techniques to describe the patient''s condition.MethodsThis is a retrospective cohort study of 170 confirmed patients with COVID-19 or bacterial pneumonia acquired at Yeungnam University Hospital in Daegu, Korea. The Lung and lesion regions were segmented to crop the lesion into 2D patches to train a classifier model that could differentiate between COVID-19 and bacterial pneumonia. The K-means algorithm was used to cluster deep features extracted by the trained model into 20 groups. Each lesion patch cluster was described by a characteristic imaging term for comparison. For each CT image containing multiple lesions, a histogram of lesion types was constructed using the cluster information. Finally, a Support Vector Machine classifier was trained with the histogram and radiomics features to distinguish diseases and severity.ResultsThe 20 clusters constructed from 170 patients were reviewed based on common radiographic appearance types. Two clusters showed typical findings of COVID-19, with two other clusters showing typical findings related to bacterial pneumonia. Notably, there is one cluster that showed bilateral diffuse ground-glass opacities (GGOs) in the central and peripheral lungs and was considered to be a key factor for severity classification. The proposed method achieved an accuracy of 91.2% for classifying COVID-19 and bacterial pneumonia patients with 95% reported for severity classification. The CT quantitative parameters represented by the values of cluster 8 were correlated with existing laboratory data and clinical parameters.ConclusionDeep chest CT analysis with constructed lesion clusters revealed well-known COVID-19 CT manifestations comparable to manual CT analysis. The constructed histogram features improved accuracy for both diseases and severity classification, and showed correlations with laboratory data and clinical parameters. The constructed histogram features can provide guidance for improved analysis and treatment of COVID-19.     

Management of SARS-CoV-2 infection is a major challenge in patients with lymphoid malignancies: Warrants a clear therapeutic strategy

Patients with lymphoid malignancies are at a higher risk of coronavirus disease 2019 (COVID-19) infection due to their immunocompromised state and results in higher mortality rates in these patients. Anti-CD 20 therapy is one of the leading causes of immunosuppression that worsens in COVID-19 cases. COVID-19 vaccines, on the other hand, appear to be less beneficial to these patients. App-ropriate treatment and recommendations are required for these COVID-19 patients with lymphoid malignancies.     

Role of high dose vitamin C in management of hospitalised COVID-19 patients: A minireview

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as one of the most dreadful viruses the mankind has witnessed. It has caused world-wide havoc and wrecked human life. In our quest to find therapeutic options to counter this threat, several drugs have been tried, with varying success. Certain agents like corticosteroids, some anti-virals and immunosuppressive drugs have been found useful in improving clinical outcomes. Vitamin C, a water-soluble vitamin with good safety profile, has been tried to reduce progression and im-prove outcomes of patients with coronavirus disease 2019 (COVID-19). Because of its anti-oxidant and immunomodulatory properties, the role of vitamin C has expanded well beyond the management of scurvy and it is increasingly been employed in the treatment of critically ill patients with sepsis, septic shock, acute pancreatitis and even cancer. However, in spite of many case series, observational studies and even randomised control trials, the role of vitamin C remains ambiguous. In this review, we will be discussing the scientific rationale and the current clinical evidence for using high dose vitamin C in the management of COVID-19 patients.     

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.     

Antibody responses in COVID-19 patients

Measuring virus-specific antibody responses to emerging pathogens is a well-established and highly useful tool to diagnose such infections, understand interactions between the immune system and pathogens, and provide potential clues for the development of vaccines or therapeutic agents against such pathogens. Since the beginning of 2020, the discovery of SARS-CoV-2 as the emerging virus responsible for the COVID-19 pandemic has provided new insight into the complexity of antibody responses to this dangerous virus. The current review aims to sort out diverse and sometimes seemingly confusing findings to put together a cohesive understanding on the profile of antibody responses elicited in COVID-19 patients.