Analysis of the Risk Factors for Nosocomial Bacterial Infection in Patients with COVID-19 in a Tertiary Hospital

Healthcare-associated infections in Iranian pediatric and adult intensive care units: A comprehensive review of risk factors, etiology, molecular epidemiology, antimicrobial sensitivity, and prevention strategies during the COVID-19 pandemic

The current review article provides a comprehensive analysis of nosocomial infections in pediatric and adult intensive care units (ICUs) in Iran. We examine the risk factors and etiology of nosocomial infections, with a particular focus on molecular epidemiology and antimicrobial sensitivity. In this article, we explore a range of prevention strategies, including hand hygiene, personal protective equipment, environmental cleaning, antibiotic stewardship, education, and training. Moreover, we discuss the impact of the COVID-19 pandemic on infection control measures in ICUs and provide valuable insights for healthcare professionals and policymakers seeking to address this critical public health issue. In conclusion, this review article can serve as a valuable resource for those interested in understanding and improving infection control in ICUs and beyond.

Development and validation of machine learning-based models for predicting healthcare-associated bacterial/fungal infections among COVID-19 inpatients: a retrospective cohort study

BACKGROUND

COVID-19 and bacterial/fungal coinfections have posed significant challenges to human health. However, there is a lack of good tools for predicting coinfection risk to aid clinical work.

OBJECTIVE

We aimed to investigate the risk factors for bacterial/fungal coinfection among COVID-19 patients and to develop machine learning models to estimate the risk of coinfection.

METHODS

In this retrospective cohort study, we enrolled adult inpatients confirmed with COVID-19 in a tertiary hospital between January 1 and July 31, 2023, in China and collected baseline information at admission. All the data were randomly divided into a training set and a testing set at a ratio of 7:3. We developed the generalized linear and random forest models for coinfections in the training set and assessed the performance of the models in the testing set. Decision curve analysis was performed to evaluate the clinical applicability.

RESULTS

A total of 1244 patients were included in the training cohort with 62 healthcare-associated bacterial/fungal infections, while 534 were included in the testing cohort with 22 infections. We found that patients with comorbidities (diabetes, neurological disease) were at greater risk for coinfections than were those without comorbidities (OR = 2.78, 95%CI = 1.61-4.86; OR = 1.93, 95%CI = 1.11-3.35). An indwelling central venous catheter or urinary catheter was also associated with an increased risk (OR = 2.53, 95%CI = 1.39-4.64; OR = 2.28, 95%CI = 1.24-4.27) of coinfections. Patients with PCT > 0.5 ng/ml were 2.03 times (95%CI = 1.41-3.82) more likely to be infected. Interestingly, the risk of coinfection was also greater in patients with an IL-6 concentration < 10 pg/ml (OR = 1.69, 95%CI = 0.97-2.94). Patients with low baseline creatinine levels had a decreased risk of bacterial/fungal coinfections(OR = 0.40, 95%CI = 0.22-0.71). The generalized linear and random forest models demonstrated favorable receiver operating characteristic curves (ROC = 0.87, 95%CI = 0.80-0.94; ROC = 0.88, 95%CI = 0.82-0.93) with high accuracy, sensitivity and specificity of 0.86vs0.75, 0.82vs0.86, 0.87vs0.74, respectively. The corresponding calibration evaluation P statistics were 0.883 and 0.769.

CONCLUSIONS

Our machine learning models achieved strong predictive ability and may be effective clinical decision-support tools for identifying COVID-19 patients at risk for bacterial/fungal coinfection and guiding antibiotic administration. The levels of cytokines, such as IL-6, may affect the status of bacterial/fungal coinfection.

Secondary infections in COVID-19: Antemortem and postmortem culture study

Background

Secondary bacterial infections during COVID-19 hospitalization have been reported in about 6-15% of patients.

Aims

To study the secondary bacterial infections that affected the COVID-19 patients during their hospitalisation and to unearth the bacteriological profile of samples obtained after their demise.

Settings and Design

This prospective study was carried out at a COVID-19 dedicated, apex tertiary care centre in North India from July 2020 to April 2021.

Methods and Materials

Samples of 268 patients were considered for the study. Nasopharyngeal swab specimen, blood, and tissue (lung) were collected from the deceased body as early as possible and processed.

Statistical Analysis

Statistical analyses were performed using STATA version 11.1 (Stata Corp., College Station, TX, USA).

Results

A total of 170 samples were received from patients before their death, which included blood, urine, respiratory samples, pus, and cerebrospinal fluid. Forty-four pathogens were isolated, which consisted of Acinetobacter baumannii (43.1%), Klebsiella pneumoniae (36.3%), Escherichia coli (11.3%), and Pseudomonas aeruginosa (4.5%), Enterococcus faecium (4.5%). Two hundred fifty-eight samples were collected from the deceased bodies wherein the nasopharyngeal sample was highest, followed by tissue and blood. A total of 43 pathogens were isolated among them which included A. baumannii (44.1%), followed by K. pneumoniae (25.5%), E. coli (20.9%), P. aeruginosa (6.97%) and Enterobacter cloacae (2.3%). All these isolates were highly resistant to antimicrobials.

Conclusions

In our study, bacterial profiles in antemortem and postmortem samples were found to be similar, suggesting that resistant pathogens may be the cause of mortality in COVID-19 infected hospitalised patients.

Associated Bacterial Coinfections in COVID-19-Positive Patients

Background and Objectives: The aim of this study was to identify specific rhino- and oropharyngeal microbiological pathogens as well as associated comorbidities that favor SARS-CoV-2 infection and corelate them. Materials and Methods: This prospective clinical study enrolled 61 patients (28 COVID-19-positive and 33 controls) who were tested for other comorbidities and co-existence of associated oral pathogenic microbiota. Results: A total of 247 bacterial isolates were identified in the bacterial cultures in both groups. Viral hepatitis type A was more prevalent in the COVID-19-positive group (p = 0.026), as was the presence of oral candidiasis (p = 0.006). In the control group, a moderate direct relationship was observed between the Beta hemolytic streptococcus group G and dermatitis, and strong direct relationships were observed between the Beta hemolytic streptococcus group G and external otitis, Streptococcus pyogenes and dental alveolitis, and Streptococcus pyogenes and chronic lymphocytic leukemia. In the test group, strong direct relationships were observed between Hemophilus influenzae and pulmonary thromboembolism; Staphylococcus aureus and autoimmune thyroiditis; post-viral immunosuppression, chronic coronary syndrome, and hypernatremia; Beta hemolytic streptococcus group C and rheumatoid polyneuropathy; Beta hemolytic streptococcus group G and hyperkalemia, hypothyroidism, secondary anemia, and splenomegaly; and active oral candidiasis and SARS-CoV-2 viral pneumonia. The following relationships were strong, but inverse: Beta hemolytic streptococcus group G and acute respiratory failure, and active oral candidiasis and SARS-CoV-2 viral bronchopneumonia. Conclusions: Briefly, COVID-19-positive patients have the predisposition to build up associated comorbidities and coinfections, which can be the expression of the immune burden that this virus generates to the host.

Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012-2021) Multicenter Retrospective Case-control study

OBJECTIVES

To appraise effective predictors for infection in patients with decompensated cirrhosis (DC) by using XGBoost algorithm in a retrospective case-control study.

METHODS

Clinical data were retrospectively collected from 6,648 patients with DC admitted to five tertiary hospitals. Indicators with significant differences were determined by univariate analysis and least absolute contraction and selection operator (LASSO) regression. Further multi-tree extreme gradient boosting (XGBoost) machine learning-based model was used to rank importance of features selected from LASSO and subsequently constructed infection risk prediction model with simple-tree XGBoost model. Finally, the simple-tree XGBoost model is compared with the traditional logical regression (LR) model. Performances of models were evaluated by area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity.

RESULTS

Six features, including total bilirubin, blood sodium, albumin, prothrombin activity, white blood cell count, and neutrophils to lymphocytes ratio were selected as predictors for infection in patients with DC. Simple-tree XGBoost model conducted by these features can predict infection risk accurately with an AUROC of 0.971, sensitivity of 0.915, and specificity of 0.900 in training set. The performance of simple-tree XGBoost model is better than that of traditional LR model in training set, internal verification set, and external feature set (P < 0.001).

CONCLUSIONS

The simple-tree XGBoost predictive model developed based on a minimal amount of clinical data available to DC patients with restricted medical resources could help primary healthcare practitioners promptly identify potential infection.

A Retrospective Assessment of Sputum Samples and Antimicrobial Resistance in COVID-19 Patients

Data on bacterial or fungal pathogens and their impact on the mortality rates of Western Romanian COVID-19 patients are scarce. As a result, the purpose of this research was to determine the prevalence of bacterial and fungal co- and superinfections in Western Romanian adults with COVID-19, hospitalized in in-ward settings during the second half of the pandemic, and its distribution according to sociodemographic and clinical conditions. The unicentric retrospective observational study was conducted on 407 eligible patients. Expectorate sputum was selected as the sampling technique followed by routine microbiological investigations. A total of 31.5% of samples tested positive for Pseudomonas aeruginosa, followed by 26.2% having co-infections with Klebsiella pneumoniae among patients admitted with COVID-19. The third most common Pathogenic bacteria identified in the sputum samples was Escherichia coli, followed by Acinetobacter baumannii in 9.3% of samples. Commensal human pathogens caused respiratory infections in 67 patients, the most prevalent being Streptococcus penumoniae, followed by methicillin-sensitive and methicillin-resistant Staphylococcus aureus. A total of 53.4% of sputum samples tested positive for Candida spp., followed by 41.1% of samples with Aspergillus spp. growth. The three groups with positive microbial growth on sputum cultures had an equally proportional distribution of patients admitted to the ICU, with an average of 30%, compared with only 17.3% among hospitalized COVID-19 patients with negative sputum cultures (p = 0.003). More than 80% of all positive samples showed multidrug resistance. The high prevalence of bacterial and fungal co-infections and superinfections in COVID-19 patients mandates for strict and effective antimicrobial stewardship and infection control policies.

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.

Immunologic Implications for Stroke Recovery: Unveiling the Role of the Immune System in Pathogenesis, Neurorepair, and Rehabilitation

Stroke is a debilitating neurologic condition characterized by an interruption or complete blockage of blood flow to certain areas of the brain. While the primary injury occurs at the time of the initial ischemic event or hemorrhage, secondary injury mechanisms contribute to neuroinflammation, disruption of the blood-brain barrier (BBB), excitotoxicity, and cerebral edema in the days and hours after stroke. Of these secondary mechanisms of injury, significant dysregulation of various immune populations within the body plays a crucial role in exacerbating brain damage after stroke. Pathological activity of glial cells, infiltrating leukocytes, and the adaptive immune system promote neuroinflammation, BBB damage, and neuronal death. Chronic immune activation can additionally encourage the development of neurologic deficits, immunosuppression, and dysregulation of the gut microbiome. As such, immunotherapy has emerged as a promising strategy for the clinical management of stroke in a highly patient-specific manner. These strategies include regulatory T cells (Tregs), cell adhesion molecules, cytokines, and monoclonal antibodies. However, the use of immunotherapy for stroke remains largely in the early stages, highlighting the need for continued research efforts before widespread clinical use.

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.

Procalcitonin as a Tool to Antimicrobial Stewardship in COVID-19 Patients with Superimposed Bacterial Infections: A Systematic Review

ABSTRACT

Procalcitonin is an inflammatory marker that had shown marked potential as an antimicrobial stewardship tool for administering antibiotics when needed in patients with pneumonia as it raises concurrently with other inflammatory markers, yet no systematic review has assessed its potential in COVID-19 patients. This systematic review aimed to assess the potential appropriateness of procalcitonin as an antimicrobial stewardship tool in COVID-19 patients with superimposed bacterial and non-bacterial infections. All study designs published after 2019 were included in this systematic review. We included all studies that had reported procalcitonin levels in COVID-19 patients with suspected superimposed secondary infection(s). We searched MEDLINE, Scopus, and the Directory for Open Access Journal from April 2022 to May 2022 and retrieved all related articles for screening with no restrictions on language. We conducted risk of bias assessment according to the Critical Appraisal Skills Programme (CASP) criteria for cohort and case-control studies. Results were presented according to procalcitonin cut-off values, gold standard test used to confirm infection, and overall study conclusion(s), among other variables. This systematic review included 18 articles with 7196 patients in 8 countries. Despite different cut-off values of procalcitonin used, thirteen studies had indicated the appropriateness of using procalcitonin as antimicrobial stewardship tool in COVID-19 patients. We urge physicians to take this into account when treating COVID-19 patients suspected of superimposed infections and we look forward to further studies with standardized procalcitonin cut-off values that may provide appropriate quantitative data that can contribute to clinical guidelines.

REGISTRATION PROSPERO

CRD42022315013.

Bacterial infections in patients hospitalized with COVID-19

Bacterial infections may complicate the course of COVID-19 patients. The rate and predictors of bacterial infections were examined in patients consecutively admitted with COVID-19 at one tertiary hospital in Madrid between March 1st and April 30th, 2020. Among 1594 hospitalized patients with COVID-19, 135 (8.5%) experienced bacterial infectious events, distributed as follows: urinary tract infections (32.6%), bacteremia (31.9%), pneumonia (31.8%), intra-abdominal infections (6.7%) and skin and soft tissue infections (6.7%). Independent predictors of bacterial infections were older age, neurological disease, prior immunosuppression and ICU admission (p < 0.05). Patients with bacterial infections who more frequently received steroids and tocilizumab, progressed to lower Sap02/FiO2 ratios, and experienced more severe ARDS (p < 0.001). The mortality rate was significantly higher in patients with bacterial infections as compared to the rest (25% vs 6.7%, respectively; p < 0.001). In multivariate analyses, older age, prior neurological or kidney disease, immunosuppression and ARDS severity were associated with an increased mortality (p < 0.05) while bacterial infections were not. Conversely, the use of steroids or steroids plus tocilizumab did not confer a higher risk of bacterial infections and improved survival rates. Bacterial infections occurred in 8.5% of patients hospitalized with COVID-19 during the first wave of the pandemic. They were not independently associated with increased mortality rates. Baseline COVID-19 severity rather than the incidence of bacterial infections seems to contribute to mortality. When indicated, the use of steroids or steroids plus tocilizumab might improve survival in this population.

Co-infections in COVID-19 patients and correlation with mortality rate. Minireview

PURPOSE

The goal of our review was to gather information on the most important community-acquired and hospital-acquired co-infections among coronavirus disease 2019 (COVID-19) patients, and to examine not only the effect of these co-infections on disease outcomes but also to identify the possible risk factors that predispose COVID-19 patients to co-infections.

METHODS

Medline (PubMed) and Google Scholar were searched for relevant articles published between January 1st, 2020, and September 31st, 2021, on the topic of co-infections among COVID-19 patients.

RESULTS

Among community-acquired and hospital-acquired co-infections, bacterial and fungal co-infections are equally frequent, followed by viral co-infections that affected a relatively smaller portion of patients. Overall, co-infections were more frequent in the hospital than at the community level. Risk factors for acquiring co-infections include male gender, longer length of hospital stay, presence of supportive treatment, such as ventilation, the admission to intensive care units, the administration of medications, such as steroids or antibiotics, and certain blood parameters, such as high C-reactive protein or lymphopenia. The presence of co-infections could aggravate the COVID-19 disease severity, prolong the healing time of patients, and lead to worse disease outcomes overall.

CONCLUSION

Co-infections may increase the mortality of COVID-19 patients, especially in the hospital setting. Paying closer attention to hygiene, adhering to diagnostic and therapeutic protocols, implementing antimicrobial stewardship programs could decrease the occurrence of co-infections and lead to improved outcomes for COVID-19 patients.

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

Background

The 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.

Objective

To identify risk factors and microbiology associated with respiratory and bloodstream bacterial infection in patients with COVID-19.

Data sources

We searched MEDLINE, OVID Epub and EMBASE for published literature up to 5 February 2021.

Study eligibility criteria

Studies including at least 50 patients with COVID-19 in any healthcare setting.

Methods

We 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.

Results

Out 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.

Conclusions

While 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.

Bloodstream Infections in Hospitalized Patients with COVID-19: A Systematic Review and Meta-Analysis

Background: Little is known about the occurrence of bloodstream infections in hospitalized patients with COVID-19 and the related clinical consequences. The aim of this systematic review and meta-analysis was to estimate the pooled occurrence of BSIs among hospitalized patients with COVID-19 and mortality of this patient population. Methods: A systematic search was performed on PubMed, EMBASE, and Web of Science from inception to 19 April 2021. The primary outcome was the occurrence of BSIs among hospitalized patients with COVID-19. The secondary outcome was mortality at the longest available follow-up. Results: Forty-six studies met the inclusion criteria, with a total of 42,694 patients evaluated. The estimated occurrence of BSIs was 7.3% (95% CI 4.7–1.1%) among hospitalized patients with COVID-19, with a mortality rate of 41% (95% CI 30%–52.8%). The subgroup analysis conducted on patients admitted to ICU provided an estimated occurrence of 29.6% (95% CI 21.7%–38.8%). A higher occurrence of BSI was observed in patients with COVID-19, in comparison with patients without COVID-19 (OR 2.77; 95% CI 1.53–5.02; p < 0.001). Conclusions: Our analysis estimated the occurrence of BSIs among hospitalized patients with COVID-19 at around 7%. A four-times higher occurrence was estimated among patients admitted to ICU.

Risk factors for nosocomial bloodstream infections in COVID-19 affected patients: protocol for a case-control study

BACKGROUND

Nosocomial bloodstream infection (nBSI) is an important clinical concern among COVID-19 hospitalised patients. It can cause sepsis and septic shock leading to high morbidity, mortality, and the emergence of antibiotic resistance. The aim of this case-control study is to identify the risk factors associated with the nBSI development in COVID-19 hospitalised patients and its incidence.

METHODS AND ANALYSIS

A retrospective case-control study will be performed. Cases will include nBSI episodes of adult patients (≥18 years) admitted to Hospital Universitari Germans Trias i Pujol, Barcelona, Spain, from April to December 2020 with a diagnosis of SARS-CoV-2 pneumonia. Patients transferred from other hospitals will be excluded. Controls will include hospitalisation episodes of COVID-19 patients without nBSI. We will recruit a minimum of 74 nBSI episodes (cases) and 74 controls (according to sample size calculation). We will collect data on sociodemographics, clinical status at admission, hospital admission, in-hospital mortality, and exposure data (use of antivirals, glucocorticoids or immunomodulatory agents, length of hospitalisation, and use of medical devices such as intravenous catheters). A bivariate and a subsequent multivariate regression analysis will be performed to assess the independent effect of the associated risk factors after adjusting for confounders. The nBSI incidence rate will be estimated according to the number of nBSI episodes in admitted COVID-19 patients among the total person-month of follow-up.

ETHICS AND DISSEMINATION

The protocol of this study was approved by the Ethical Committee for Drug Investigation of the Hospital Universitari Germans Trias i Pujol. The results of this case-control study will be published in a peer reviewed journal.

Characterization of Secondary Bacterial Infections and Antibiotic Use in Mechanically Ventilated Patients With COVID-19 Induced Acute Respiratory Distress Syndrome

Background:

COVID-19 has a widely variable clinical syndrome that is difficult to distinguish from bacterial sepsis, leading to high rates of antibiotic use. Early studies indicate low rates of secondary bacterial infections (SBIs) but have included heterogeneous patient populations. Here, we catalogue all SBIs and antibiotic prescription practices in a population of mechanically ventilated patients with COVID-19 induced acute respiratory distress syndrome (ARDS).

Methods:

This was a retrospective cohort study of all patients with COVID-19 ARDS requiring mechanical ventilation from 3 Seattle, Washington hospitals in 2020. Data were obtained via electronic and manual review of the electronic medical record. We report the incidence and site of SBIs, mortality, and antibiotics per day using descriptive statistics.

Results:

We identified 126 patients with COVID-19 induced ARDS during the study period. Of these patients, 61% developed clinical infection confirmed by bacterial culture. Ventilator associated pneumonia was confirmed in 55% of patients, bacteremia in 20%, and urinary tract infection (UTI) in 17%. Staphylococcus aureus was the most commonly isolated bacterial species. A total of 97% of patients received antibiotics during their hospitalization, and patients received nearly one antibiotic per day during their hospital stay.

Conclusions:

Mechanically ventilated patients with COVID-19 induced ARDS are at high risk for secondary bacterial infections and have extensive antibiotic exposure.

C-reactive protein and procalcitonin for antimicrobial stewardship in COVID-19

Purpose

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory coronavirus 2 (SARS-CoV-2) has spread around the world. Differentiation between pure viral COVID-19 pneumonia and secondary infection can be challenging. In patients with elevated C-reactive protein (CRP) on admission physicians often decide to prescribe antibiotic therapy. However, overuse of anti-infective therapy in the pandemic should be avoided to prevent increasing antimicrobial resistance. Procalcitonin (PCT) and CRP have proven useful in other lower respiratory tract infections and might help to differentiate between pure viral or secondary infection.

Methods

We performed a retrospective study of patients admitted with COVID-19 between 6th March and 30th October 2020. Patient background, clinical course, laboratory findings with focus on PCT and CRP levels and microbiology results were evaluated. Patients with and without secondary bacterial infection in relation to PCT and CRP were compared. Using receiver operating characteristic (ROC) analysis, the best discriminating cut-off value of PCT and CRP with the corresponding sensitivity and specificity was calculated.

Results

Out of 99 inpatients (52 ICU, 47 Non-ICU) with COVID-19, 32 (32%) presented with secondary bacterial infection during hospitalization. Patients with secondary bacterial infection had higher PCT (0.4 versus 0.1 ng/mL; p = 0.016) and CRP (131 versus 73 mg/L; p = 0.001) levels at admission and during the hospital stay (2.9 versus 0.1 ng/mL; p < 0.001 resp. 293 versus 94 mg/L; p < 0.001). The majority of patients on general ward had no secondary bacterial infection (93%). More than half of patients admitted to the ICU developed secondary bacterial infection (56%). ROC analysis of highest PCT resp. CRP and secondary infection yielded AUCs of 0.88 (p < 0.001) resp. 0.86 (p < 0.001) for the entire cohort. With a PCT cut-off value at 0.55 ng/mL, the sensitivity was 91% with a specificity of 81%; a CRP cut-off value at 172 mg/L yielded a sensitivity of 81% with a specificity of 76%.

Conclusion

PCT and CRP measurement on admission and during the course of the disease in patients with COVID-19 may be helpful in identifying secondary bacterial infections and guiding the use of antibiotic therapy.

Inappropriate antibiotic use in the COVID-19 era: Factors associated with inappropriate prescribing and secondary complications. Analysis of the registry SEMI-COVID

BACKGROUND

Most patients with COVID-19 receive antibiotics despite the fact that bacterial co-infections are rare. This can lead to increased complications, including antibacterial resistance. We aim to analyze risk factors for inappropriate antibiotic prescription in these patients and describe possible complications arising from their use.

METHODS

The SEMI-COVID-19 Registry is a multicenter, retrospective patient cohort. Patients with antibiotic were divided into two groups according to appropriate or inappropriate prescription, depending on whether the patient fulfill any criteria for its use. Comparison was made by means of multilevel logistic regression analysis. Possible complications of antibiotic use were also identified.

RESULTS

Out of 13,932 patients, 3047 (21.6%) were prescribed no antibiotics, 6116 (43.9%) were appropriately prescribed antibiotics, and 4769 (34.2%) were inappropriately prescribed antibiotics. The following were independent factors of inappropriate prescription: February-March 2020 admission (OR 1.54, 95%CI 1.18-2.00), age (OR 0.98, 95%CI 0.97-0.99), absence of comorbidity (OR 1.43, 95%CI 1.05-1.94), dry cough (OR 2.51, 95%CI 1.94-3.26), fever (OR 1.33, 95%CI 1.13-1.56), dyspnea (OR 1.31, 95%CI 1.04-1.69), flu-like symptoms (OR 2.70, 95%CI 1.75-4.17), and elevated C-reactive protein levels (OR 1.01 for each mg/L increase, 95% CI 1.00-1.01). Adverse drug reactions were more frequent in patients who received ANTIBIOTIC (4.9% vs 2.7%, p < .001).

CONCLUSION

The inappropriate use of antibiotics was very frequent in COVID-19 patients and entailed an increased risk of adverse reactions. It is crucial to define criteria for their use in these patients. Knowledge of the factors associated with inappropriate prescribing can be helpful.

Prevalence and outcomes of co-infection and superinfection with SARS-CoV-2 and other pathogens: A systematic review and meta-analysis

INTRODUCTION

The recovery of other pathogens in patients with SARS-CoV-2 infection has been reported, either at the time of a SARS-CoV-2 infection diagnosis (co-infection) or subsequently (superinfection). However, data on the prevalence, microbiology, and outcomes of co-infection and superinfection are limited. The purpose of this study was to examine the occurrence of co-infections and superinfections and their outcomes among patients with SARS-CoV-2 infection.

PATIENTS AND METHODS

We searched literature databases for studies published from October 1, 2019, through February 8, 2021. We included studies that reported clinical features and outcomes of co-infection or superinfection of SARS-CoV-2 and other pathogens in hospitalized and non-hospitalized patients. We followed PRISMA guidelines, and we registered the protocol with PROSPERO as: CRD42020189763.

RESULTS

Of 6639 articles screened, 118 were included in the random effects meta-analysis. The pooled prevalence of co-infection was 19% (95% confidence interval [CI]: 14%-25%, I2 = 98%) and that of superinfection was 24% (95% CI: 19%-30%). Pooled prevalence of pathogen type stratified by co- or superinfection were: viral co-infections, 10% (95% CI: 6%-14%); viral superinfections, 4% (95% CI: 0%-10%); bacterial co-infections, 8% (95% CI: 5%-11%); bacterial superinfections, 20% (95% CI: 13%-28%); fungal co-infections, 4% (95% CI: 2%-7%); and fungal superinfections, 8% (95% CI: 4%-13%). Patients with a co-infection or superinfection had higher odds of dying than those who only had SARS-CoV-2 infection (odds ratio = 3.31, 95% CI: 1.82-5.99). Compared to those with co-infections, patients with superinfections had a higher prevalence of mechanical ventilation (45% [95% CI: 33%-58%] vs. 10% [95% CI: 5%-16%]), but patients with co-infections had a greater average length of hospital stay than those with superinfections (mean = 29.0 days, standard deviation [SD] = 6.7 vs. mean = 16 days, SD = 6.2, respectively).

CONCLUSIONS

Our study showed that as many as 19% of patients with COVID-19 have co-infections and 24% have superinfections. The presence of either co-infection or superinfection was associated with poor outcomes, including increased mortality. Our findings support the need for diagnostic testing to identify and treat co-occurring respiratory infections among patients with SARS-CoV-2 infection.

Bacterial coinfections in coronavirus disease 2019

Bacterial coinfections increase the severity of respiratory viral infections and were frequent causes of mortality in influenza pandemics but have not been well characterized in patients with coronavirus disease 2019 (COVID-19). The aim of this review was to identify the frequency and microbial etiologies of bacterial coinfections that are present upon admission to the hospital and that occur during hospitalization for COVID-19. We found that bacterial coinfections were present in <4% of patients upon admission and the yield of routine diagnostic tests for pneumonia was low. When bacterial coinfections did occur, Staphylococcus aureus, Streptococcus pneumoniae, and Haemophilus influenzae were the most common pathogens and atypical bacteria were rare. Although uncommon upon admission, bacterial infections frequently occurred in patients with prolonged hospitalization, and Pseudomonas aeruginosa, Klebsiella spp., and S. aureus were common pathogens. Antibacterial therapy and diagnostic testing for bacterial infections are unnecessary upon admission in most patients hospitalized with COVID-19, but clinicians should be vigilant for nosocomial bacterial infections.

Ventilator-associated pneumonia in critically ill patients with COVID-19

BACKGROUND

Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP).

OBJECTIVES

To study the incidence of VAP and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients.

METHODS

In this retrospective observational study, we compared the incidence of VAP and secondary infections using a combination of microbial culture and a TaqMan multi-pathogen array. In addition, we determined the lung microbiome composition using 16S RNA analysis in a subset of samples. The study involved 81 COVID-19 and 144 non-COVID-19 patients receiving invasive ventilation in a single University teaching hospital between March 15th 2020 and August 30th 2020.

RESULTS

COVID-19 patients were significantly more likely to develop VAP than patients without COVID (Cox proportional hazard ratio 2.01 95% CI 1.14-3.54, p = 0.0015) with an incidence density of 28/1000 ventilator days versus 13/1000 for patients without COVID (p = 0.009). Although the distribution of organisms causing VAP was similar between the two groups, and the pulmonary microbiome was similar, we identified 3 cases of invasive aspergillosis amongst the patients with COVID-19 but none in the non-COVID-19 cohort. Herpesvirade activation was also numerically more frequent amongst patients with COVID-19.

CONCLUSION

COVID-19 is associated with an increased risk of VAP, which is not fully explained by the prolonged duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the causative organisms of secondary pneumonia observed are similar to that seen in critically ill patients ventilated for other reasons.