Impact of bronchial colonization with Candida spp. on the risk of bacterial ventilator-associated pneumonia in the ICU: the FUNGIBACT prospective cohort study

Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning

Background

Fungal infections are associated with high morbidity and mortality in the intensive care unit (ICU), but their diagnosis is difficult. In this study, machine learning was applied to design and define the predictive model of ICU-acquired fungi (ICU-AF) in the early stage of fungal infections using Random Forest.

Objectives

This study aimed to provide evidence for the early warning and management of fungal infections.

Methods

We analyzed the data of patients with culture-positive fungi during their admission to seven ICUs of the First Affiliated Hospital of Chongqing Medical University from January 1, 2015, to December 31, 2019. Patients whose first culture was positive for fungi longer than 48 h after ICU admission were included in the ICU-AF cohort. A predictive model of ICU-AF was obtained using the Least Absolute Shrinkage and Selection Operator and machine learning, and the relationship between the features within the model and the disease severity and mortality of patients was analyzed. Finally, the relationships between the ICU-AF model, antifungal therapy and empirical antifungal therapy were analyzed.

Results

A total of 1,434 cases were included finally. We used lasso dimensionality reduction for all features and selected six features with importance ≥0.05 in the optimal model, namely, times of arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation. The area under the curve of the model for predicting ICU-AF was 0.981 in the test set, with a sensitivity of 0.960 and specificity of 0.990. The times of arterial catheter (p = 0.011, OR = 1.057, 95% CI = 1.053-1.104) and invasive mechanical ventilation (p = 0.007, OR = 1.056, 95%CI = 1.015-1.098) were independent risk factors for antifungal therapy in ICU-AF. The times of arterial catheter (p = 0.004, OR = 1.098, 95%CI = 0.855-0.970) were an independent risk factor for empirical antifungal therapy.

Conclusion

The most important risk factors for ICU-AF are the six time-related features of clinical parameters (arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation), which provide early warning for the occurrence of fungal infection. Furthermore, this model can help ICU physicians to assess whether empiric antifungal therapy should be administered to ICU patients who are susceptible to fungal infections.

Rebound Inverts the Staphylococcus aureus Bacteremia Prevention Effect of Antibiotic Based Decontamination Interventions in ICU Cohorts with Prolonged Length of Stay

Could rebound explain the paradoxical lack of prevention effect against Staphylococcus aureus blood stream infections (BSIs) with antibiotic-based decontamination intervention (BDI) methods among studies of ICU patients within the literature? Two meta-regression models were applied, each versus the group mean length of stay (LOS). Firstly, the prevention effects against S. aureus BSI [and S. aureus VAP] among 136 studies of antibiotic-BDI versus other interventions were analyzed. Secondly, the S. aureus BSI [and S. aureus VAP] incidence in 268 control and intervention cohorts from studies of antibiotic-BDI versus that among 165 observational cohorts as a benchmark was modelled. In model one, the meta-regression line versus group mean LOS crossed the null, with the antibiotic-BDI prevention effect against S. aureus BSI at mean LOS day 7 (OR 0.45; 0.30 to 0.68) inverted at mean LOS day 20 (OR 1.7; 1.1 to 2.6). In model two, the meta-regression line versus group mean LOS crossed the benchmark line, and the predicted S. aureus BSI incidence for antibiotic-BDI groups was 0.47; 0.09-0.84 percentage points below versus 3.0; 0.12-5.9 above the benchmark in studies with 7 versus 20 days mean LOS, respectively. Rebound within the intervention groups attenuated and inverted the prevention effect of antibiotic-BDI against S. aureus VAP and BSI, respectively. This explains the paradoxical findings.

Exploring the complex relationship between the lung microbiome and ventilator-associated pneumonia

INTRODUCTION

Understanding the presence and function of a diverse lung microbiome in acute lung infections, particularly ventilator-associated pneumonia (VAP), is still limited, evidencing significant gaps in our knowledge.

AREAS COVERED

In this comprehensive narrative review, we aim to elucidate the contribution of the respiratory microbiome in the development of VAP by examining the current knowledge on the interactions among microorganisms. By exploring these intricate connections, we endeavor to enhance our understanding of the disease's pathophysiology and pave the way for novel ideas and interventions in studying the respiratory tract microbiome.

EXPERT OPINION

The conventional perception of lungs as sterile is deprecated since it is currently recognized the existence of a diverse microbial community within them. However, despite extensive research on the role of the respiratory microbiome in healthy lungs, respiratory chronic diseases and acute lung infections such as pneumonia are not fully understood. It is crucial to investigate further the relationship between the pathophysiology of VAP and the pulmonary microbiome, elucidating the mechanisms underlying the interactions between the microbiome, host immune response and mechanical ventilation for the development of VAP.

Emergence of microbial infections in some hospitals of Cairo, Egypt: studying their corresponding antimicrobial resistance profiles

BACKGROUND

Antimicrobial resistance is one of the ten major public health threats facing humanity, especially in developing countries. Identification of the pathogens responsible for different microbial infections and antimicrobial resistance patterns are important to help clinicians to choose the correct empirical drugs and provide optimal patient care.

METHODS

During the period from November 2020 to January 2021, one hundred microbial isolates were collected randomly from different specimens from some hospitals in Cairo, Egypt. Sputum and chest specimens were from COVID-19 patients. Antimicrobial susceptibility testing was performed according to CLSI guidelines.

RESULTS

Most microbial infections were more common in males and in elderly people over 45 years of age. They were caused by Gram-negative, Gram-positive bacteria, and yeast isolates that represented 69%, 15%, and 16%, respectively. Uropathogenic Escherichia coli (35%) were the most prevalent microbial isolates and showed high resistance rates towards penicillin, ampicillin, and cefixime, followed by Klebsiella spp. (13%) and Candida spp. (16%). Of all microbial isolates, Acinetobacter spp., Serratia spp., Hafnia alvei, and Klebsiella ozaenae were extremely multidrug-resistant (MDR) and have resisted all antibiotic classes used, except for glycylcycline, in varying degrees. Acinetobacter spp., Serratia spp., and Candida spp. were secondary microbial infections in COVID-19 patients, while H. alvei was a bloodstream infection isolate and K. ozaenae was recorded in most infections. Moreover, about half of Staphylococcus aureus strains were MRSA isolates and reported low rates of resistance to glycylcycline and linezolid. In comparison, Candida spp. showed high resistance rates between 77 and 100% to azole drugs and terbinafine, while no resistance rate towards nystatin was reported. Indeed, glycylcycline, linezolid, and nystatin were considered the drugs of choice for the treatment of MDR infections.

CONCLUSION

The prevalence of antimicrobial resistance in some Egyptian hospitals was high among Gram-negative, Gram-positive bacteria, and candida spp. The high resistance pattern -especially in secondary microbial infections in COVID-19 patients- to most antibiotics used is a matter of great concern, portends an inevitable catastrophe, and requires continuous monitoring to avoid the evolution of new generations.

Respiratory Fungal Communities are Associated with Systemic Inflammation and Predict Survival in Patients with Acute Respiratory Failure

Rationale

Disruption of respiratory bacterial communities predicts poor clinical outcomes in critical illness; however, the role of respiratory fungal communities (mycobiome) is poorly understood.

Objectives

We investigated whether mycobiota variation in the respiratory tract is associated with host-response and clinical outcomes in critically ill patients.

Methods

To characterize the upper and lower respiratory tract mycobiota, we performed rRNA gene sequencing (internal transcribed spacer) of oral swabs and endotracheal aspirates (ETA) from 316 mechanically-ventilated patients. We examined associations of mycobiome profiles (diversity and composition) with clinical variables, host-response biomarkers, and outcomes.

Measurements and Main Results

ETA samples with >50% relative abundance for C. albicans (51%) were associated with elevated plasma IL-8 and pentraxin-3 (p=0.05), longer time-to-liberation from mechanical ventilation (p=0.04) and worse 30-day survival (adjusted hazards ratio (adjHR): 1.96 [1.04-3.81], p=0.05). Using unsupervised clustering, we derived two clusters in ETA samples, with Cluster 2 (39%) showing lower alpha diversity (p<0.001) and higher abundance of C. albicans (p<0.001). Cluster 2 was significantly associated with the prognostically adverse hyperinflammatory subphenotype (odds ratio 2.07 [1.03-4.18], p=0.04) and predicted worse survival (adjHR: 1.81 [1.03-3.19], p=0.03). C. albicans abundance in oral swabs was also associated with the hyperinflammatory subphenotype and mortality.

Conclusions

Variation in respiratory mycobiota was significantly associated with systemic inflammation and clinical outcomes. C. albicans abundance emerged as a negative predictor in both the upper and lower respiratory tract. The lung mycobiome may play an important role in the biological and clinical heterogeneity among critically ill patients and represent a potential therapeutic target for lung injury in critical illness.

Staphylococcus aureus hitchhiking from colonization to bacteremia via Candida within ICU infection prevention studies: a proof of concept modelling

Whether Candida within the patient microbiome drives the pathogenesis of Staphylococcus aureus bacteremia, described as microbial hitchhiking, cannot be directly studied. Group-level observations from studies of various decontamination and non-decontamination-based ICU infection prevention interventions and studies without study interventions (observational groups) collectively enable tests of this interaction within causal models. Candidate models of the propensity for Staphylococcus aureus bacteremia to arise with versus without various antibiotic, anti-septic, and antifungal exposures, each identified as singleton exposures, were tested using generalized structural equation modelling (GSEM) techniques with Candida and Staphylococcus aureus colonization appearing as latent variables within the models. Each model was tested by confrontation against blood and respiratory isolate data, obtained from 467 groups within 284 infection prevention studies. Introducing an interaction term between Candida colonization and Staphylococcus aureus colonization substantially improved GSEM model fit. Model-derived coefficients for singular exposure to anti-septic agents (- 1.28; 95% confidence interval; - 2.05 to - 0.5), amphotericin (- 1.49; - 2.3 to - 0.67), and topical antibiotic prophylaxis (TAP; + 0.93; + 0.15 to + 1.71) as direct effects versus Candida colonization were similar in magnitude but contrary in direction. By contrast, the coefficients for singleton exposure to TAP, as with anti-septic agents, versus Staphylococcus colonization were weaker or non-significant. Topical amphotericin would be predicted to halve both candidemia and Staphylococcus aureus bacteremia incidences versus literature derived benchmarks for absolute differences of < 1 percentage point. Using ICU infection prevention data, GSEM modelling validates the postulated interaction between Candida and Staphylococcus colonization facilitating bacteremia.

Structural equation modelling the impact of antimicrobials on the human microbiome. Colonization resistance versus colonization susceptibility as case studies

The impact of antimicrobials on the human microbiome and its relationship to human health are of great interest. How antimicrobial exposure might drive change within specific constituents of the microbiome to effect clinically relevant endpoints is difficult to study. Clinical investigation of each step within a network of causation would be challenging if done 'step-by-step'. An analytic tool of great potential to clinical microbiome research is structural equation modelling (SEM), which has a long history of applications to research questions arising within subject areas as diverse as psychology and econometrics. SEM enables postulated models based on a network of causation to be tested en bloc by confrontation with data derived from the literature. Case studies for the potential application of SEM techniques are colonization resistance (CR) and its counterpart, colonization susceptibility (CS), wherein specific microbes within the microbiome are postulated to either impede (CR) or facilitate (CS) invasive infection with pathogenic bacteria. These postulated networks have three causation steps: exposure to specific antimicrobials are key drivers, clinically relevant infection endpoints are the measurable observables and the activity of key microbiome constituents mediating CR or CS, which may be unobservable, appear as latent variables in the model. SEM methods have potential application towards evaluating the activity of specific antimicrobial agents within postulated networks of causation using clinically derived data.

Candida and the Gram-positive trio: testing the vibe in the ICU patient microbiome using structural equation modelling of literature derived data

Background

Whether Candida interacts with Gram-positive bacteria, such as Staphylococcus aureus, coagulase negative Staphylococci (CNS) and Enterococci, to enhance their invasive potential from the microbiome of ICU patients remains unclear. Several effective anti-septic, antibiotic, anti-fungal, and non-decontamination based interventions studied for prevention of ventilator associated pneumonia (VAP) and other ICU acquired infections among patients receiving prolonged mechanical ventilation (MV) are known to variably impact Candida colonization. The collective observations within control and intervention groups from numerous ICU infection prevention studies enables tests of these postulated microbial interactions in the clinical context.

Methods

Four candidate generalized structural equation models (GSEM), each with Staphylococcus aureus, CNS and Enterococci colonization, defined as latent variables, were confronted with blood culture and respiratory tract isolate data derived from 460 groups of ICU patients receiving prolonged MV from 283 infection prevention studies.

Results

Introducing interaction terms between Candida colonization and each of S aureus (coefficient + 0.40; 95% confidence interval + 0.24 to + 0.55), CNS (+ 0.68; + 0.34 to + 1.0) and Enterococcal (+ 0.56; + 0.33 to + 0.79) colonization (all as latent variables) improved the fit for each model. The magnitude and significance level of the interaction terms were similar to the positive associations between exposure to topical antibiotic prophylaxis (TAP) on Enterococcal (+ 0.51; + 0.12 to + 0.89) and Candida colonization (+ 0.98; + 0.35 to + 1.61) versus the negative association of TAP with S aureus (− 0.45; − 0.70 to − 0.20) colonization and the negative association of anti-fungal exposure and Candida colonization (− 1.41; − 1.6 to − 0.72).

Conclusions

GSEM modelling of published ICU infection prevention data enables the postulated interactions between Candida and Gram-positive bacteria to be tested using clinically derived data. The optimal model implies interactions occurring in the human microbiome facilitating bacterial invasion and infection. This interaction might also account for the paradoxically high bacteremia incidences among studies of TAP in ICU patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12982-022-00116-9.

GSEM modelling of published ICU infection prevention data from > 250 studies enables a test of and provides support to the interaction between Candida and Gram-positive bacteria.

The various ICU infection prevention interventions may each broadly impact the patient microbiome.

Clinical impact of Candida respiratory tract colonization and acute lung infections in critically ill patients with COVID-19 pneumonia

Coronavirus disease 2019 (COVID-19), which is attributable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been causing a worldwide health issue. Airways colonization by Candida spp. is prevalent among patients on automatic ventilation in intensive care units (ICUs). This research aimed to ascertain the risk factors and roles of Candida spp. respiratory tract colonization, and Candida lung infection during the progression of COVID-19 pneumonia in critically ill patients. In total, Candida spp. were recovered in 69 from 100 immunosuppressed patients with COVID-19. Bronchoscopy was used to collect the Bronchoalveolar lavage (BAL) specimens. For the identification of Candida spp. PCR sequencing was done using the ITS1 and ITS4 primers. The amplification of the HWP1 gene was conducted to identify the Candida albicans complex. The antifungal activities of fluconazole, itraconazole, voriconazole, amphotericin B and caspofungin against Candida spp. were evaluated using the Clinical and Laboratory Standards Institute M60. In 63.77% of the patients, Candida respiratory colonization at D0 and D14 had no impact on the severity of COVID-19. In comparison to C. albicans strains, Candida respiratory disorder with C. glabrata had influenced the severity of COVID-19 for critically ill patients following adjustment for the risk factors of COVID-19 (P < 0.05). Amphotericin B and caspofungin showed superior activity against all Candida spp. All antifungal agents showed 100% sensitivity against the two C. africana strains. Our observation on patients who used automatic ventilation, respiratory colonization by Candida spp. was not seen to influence the infection or death caused by COVID-19. Amphotericin B and caspofungin showed superior activity against all Candida spp. and were recommended for the treatment regime of pulmonary candidiasis associated with COVID-19 infection. Although “Candida pneumonia” is rarely being reported in critically ill patients, Candida airway colonization mainly by Candida albicans is common especially among patients with diabetes, malignancies, and kidney disorders.

Structural equation modelling the relationship between anti-fungal prophylaxis and Pseudomonas bacteremia in ICU patients

Purpose

Animal models implicate candida colonization facilitating invasive bacterial infections. The clinical relevance of this microbial interaction remains undefined and difficult to study directly. Observations from studies of anti-septic, antibiotic, anti-fungal, and non-decontamination-based interventions to prevent ICU acquired infection collectively serve as a natural experiment.

Methods

Three candidate generalized structural equation models (GSEM), with Candida and Pseudomonas colonization as latent variables, were confronted with blood culture and respiratory tract isolate data derived from 464 groups from 279 studies including studies of combined antibiotic and antifungal exposures within selective digestive decontamination (SDD) interventions.

Results

Introducing an interaction term between Candida colonization and Pseudomonas colonization substantially improved GSEM model fit. Model derived coefficients for singular exposure to anti-septic agents (− 1.23; − 2.1 to − 0.32), amphotericin (− 1.78; − 2.79 to − 0.78) and topical antibiotic prophylaxis (TAP; + 1.02; + 0.11 to + 1.93) versus Candida colonization were similar in magnitude but contrary in direction. By contrast, the model-derived coefficients for singular exposure to TAP, as with anti-septic agents, versus Pseudomonas colonization were weaker or non-significant. Singular exposure to amphotericin would be predicted to more than halve candidemia and Pseudomonas bacteremia incidences versus literature benchmarks for absolute differences of approximately one percentage point or less.

Conclusion

GSEM modelling of published data supports the postulated interaction between Candida and Pseudomonas colonization towards promoting bacteremia among ICU patients. This would be difficult to detect without GSEM modelling. The model indicates that anti-fungal agents have greater impact in preventing Pseudomonas bacteremia than TAP, which has no impact.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-022-00429-8.

Clinical Implication of Candida Score in Multidrug-Resistant Pneumonia with Airway Candida Colonization

Background

The growth of Candida in respiratory secretions is usually considered colonization, and antifungal therapy is rarely required. The role of Candida colonization in the progression of bacterial pneumonia remains controversial. The aim of this study was to identify the clinical implication of Candida score by analyzinge the relationship with multidrug-resistant (MDR) pneumonia and prognosis in patients with airway Candida colonization.

Materials and Methods

This study was a retrospective review of patients with airway Candida colonization by bronchial washing or bronchoalveolar lavage. The Candida score was calculated according to the four factors (severe sepsis, surgery at baseline, total parenteral nutrition, and multifocal Candida colonization). Pneumonia related mortality or hopeless discharge expecting death was defined as a poor outcome.

Results

A total of 148 patients were enrolled in the study. In a multivariate analysis model, Candida score was identified as an independent predictor of poor outcomes (odds ratio 2.23; 95% confidential interval 1.57 – 3.17; P <0.001) in pneumonia patients with airway Candida colonization. With a Candida score of three or higher compared with low score group, it was associated with bacterial pneumonia, especially methicillin-resistant Staphylococcus aureus (MRSA) infection (0.0% vs. 15.2%, P = 0.004). In addition, patients with a high Candida score had a longer hospital stay (13 vs. 38 days, P <0.001), longer duration of intensive care (7 vs. 18 days, P <0.001), and higher pneumonia-related mortality (0.0% vs. 45.5%, P <0.001) as compared to the low Candida score group. The Candida score showed a positive correlation with other pneumonia severity scales such as CURB-65 (Confusion, Urea, Respiratory rate, Blood pressure, and age ≥65 years) (r = 0.461, P <0.001), Pneumonia Severity Index (r = 0.397, P <0.001), and predisposition, insult, response, and organ dysfunction (PIRO) score (r = 0.425, P <0.001).

Conclusion

This study revealed that Candida is no longer a bystander of airway colonization, and that it affects the progression of bacterial pneumonia, including multidrug-resistant pathogens, particularly MRSA infection. Also Candida score can be used to predict the prognosis of patients with pneumonia.

Impact of Healthcare-Associated Infections Connected to Medical Devices-An Update

Healthcare-associated infections (HAIs) are caused by nosocomial pathogens. HAIs have an immense impact not only on developing countries but also on highly developed parts of world. They are predominantly device-associated infections that are caused by the planktonic form of microorganisms as well as those organized in biofilms. This review elucidates the impact of HAIs, focusing on device-associated infections such as central line-associated bloodstream infection including catheter infection, catheter-associated urinary tract infection, ventilator-associated pneumonia, and surgical site infections. The most relevant microorganisms are mentioned in terms of their frequency of infection on medical devices. Standard care bundles, conventional therapy, and novel approaches against device-associated infections are briefly mentioned as well. This review concisely summarizes relevant and up-to-date information on HAIs and HAI-associated microorganisms and also provides a description of several useful approaches for tackling HAIs.

Comparison of clinical characteristics in patients with coronavirus disease and influenza A in Guangzhou, China

BACKGROUND

This study aims to compare the epidemiological, clinical and laboratory characteristics between patients with coronavirus disease (COVID-19) and influenza A (H1N1), and to develop a differentiating model and a simple scoring system.

METHODS

We retrospectively analyzed the data from patients with COVID-19 and H1N1. The logistic regression model based on clinical and laboratory characteristics was constructed to distinguish COVID-19 from H1N1. Scores were assigned to each of independent discrimination factors based on their odds ratios. The performance of the prediction model and scoring system was assessed.

RESULTS

A total of 236 patients were recruited, including 20 COVID-19 patients and 216 H1N1 patients. Logistic regression revealed that age >34 years, temperature ≤37.5 °C, no sputum or myalgia, lymphocyte ratio ≥20% and creatine kinase-myocardial band isoenzyme (CK-MB) >9.7 U/L were independent differentiating factors for COVID-19. The area under curves (AUCs) of the prediction model and scoring system in differentiating COVID-19 from H1N1 were 0.988 and 0.962, respectively.

CONCLUSIONS

There are certain differences in clinical and laboratory features between patients with COVID-19 and H1N1. The simple scoring system may be a useful tool for the early identification of COVID-19 patients from H1N1 patients.

Strategies for implementation of a multidisciplinary approach to the treatment of nosocomial infections in critically ill patients

INTRODUCTION

Intensive Care Units (ICU) are among the hospital wards exhibiting the highest prevalence of antimicrobial resistance (AMR), and resulting impact on patient outcomes. Antimicrobial resistance surveillance and antimicrobial stewardship (AMS) programs play a pivotal role in promoting interventions tailored to optimize infection diagnosis and treatment in the final attempt to limit unnecessary antimicrobial use and development of resistance.

AREAS COVERED

A narrative review of the literature was carried out to summarize the available evidence and develop a set of actions that should be considered for integration into the ICU stewardship framework. Four questions were addressed: how AMR surveillance can inform antibiotic policy in ICU; whether pharmacokinetic and pharmacodynamic (PK/PD) principles and the use of procalcitonin should be incorporated as a standard practice in ICU AMS programs to optimize antibiotic treatment and to drive antibiotic discontinuation; which criteria should drive treatment duration of ICU-associated infections.

EXPERT OPINION

In this review we aim to highlight that the ICU must be considered in its own right. Each ICU has its own characteristics depending on the country, on the local antibiotic resistance profile, on the patients feature and the severity of infection.

Candida-Acinetobacter-Pseudomonas Interaction Modelled within 286 ICU Infection Prevention Studies

BACKGROUND

Whether Candida interacts to enhance the invasive potential of Acinetobacter and Pseudomonas bacteria cannot be resolved within individual studies. There are several anti-septic, antibiotic, anti-fungal, and non-decontamination-based interventions to prevent ICU acquired infection. These effective prevention interventions would be expected to variably impact Candida colonization. The collective observations within control and intervention groups from numerous ICU infection prevention studies simulates a multi-centre natural experiment with which to evaluate Candida, Acinetobacter and Pseudomonas interaction (CAPI).

METHODS

Eight Candidate-generalized structural equation models (GSEM), with Candida, Pseudomonas and Acinetobacter colonization as latent variables, were confronted with blood culture and respiratory tract isolate data derived from >400 groups derived from 286 infection prevention studies.

RESULTS

Introducing an interaction term between Candida colonization and each of Pseudomonas and Acinetobacter colonization improved model fit in each case. The size of the coefficients (and 95% confidence intervals) for these interaction terms in the optimal Pseudomonas (+0.33; 0.22 to 0.45) and Acinetobacter models (+0.32; 0.01 to 0.5) were similar to each other and similar in magnitude, but contrary in direction, to the coefficient for exposure to topical antibiotic prophylaxis (TAP) on Pseudomonas colonization (-0.45; -0.71 to -0.2). The coefficient for exposure to topical antibiotic prophylaxis on Acinetobacter colonization was not significant.

CONCLUSIONS

GSEM modelling of published ICU infection prevention data supports the CAPI concept. The CAPI model could account for some paradoxically high Acinetobacter and Pseudomonas infection incidences, most apparent among the concurrent control groups of TAP studies.

Changes in immune indicators and bacteriologic profile were associated with patients with ventilator-associated pneumonia

The aim of this study is to explore and identify ventilator-associated pneumonia (VAP)-related prognostic immune factors and further detect the drug-resistant pathogens to establish the theoretical guidance for clinical prevention and treatment strategies of VAP. A total of 478 patients using ventilator who were hospitalized in July 2014 to November 2016 in our hospital were enrolled in this study. About 103 patients with VAP (21.5%, 103/478) among 478 cases of patients using ventilator. Among the 103 patients with VAP, the distribution of pathogenic bacteria and drug resistance in patients with VAP were detected and analyzed. In the VAP group, 35 patients died and 43 patients had simultaneous sepsis. Compared with those of non-VAP group, the proportion of CD3 (P = .012), CD3CD4 (P = .024) and CD8CD28 ( P = .017) T cells in VAP group increased significantly, which indicated more severe immune response. Multivariate regression model analysis revealed that tracheotomy of mechanical ventilation (P = .013), mechanical ventilation time ≥7 days (P = .02) and aspiration and reflux (P = .011) were independent risk factors associated with VAP. According to the results of bacterial culture and drug sensitivity test, rational selection of antibiotics and monitoring of patients within intensive care unit can effectively control the incidence of VAP and improve the prognosis of patients.

Ventilator-associated pneumonia in adults: a narrative review

Ventilator-associated pneumonia (VAP) is one of the most frequent ICU-acquired infections. Reported incidences vary widely from 5 to 40% depending on the setting and diagnostic criteria. VAP is associated with prolonged duration of mechanical ventilation and ICU stay. The estimated attributable mortality of VAP is around 10%, with higher mortality rates in surgical ICU patients and in patients with mid-range severity scores at admission. Microbiological confirmation of infection is strongly encouraged. Which sampling method to use is still a matter of controversy. Emerging microbiological tools will likely modify our routine approach to diagnosing and treating VAP in the next future. Prevention of VAP is based on minimizing the exposure to mechanical ventilation and encouraging early liberation. Bundles that combine multiple prevention strategies may improve outcomes, but large randomized trials are needed to confirm this. Treatment should be limited to 7 days in the vast majority of the cases. Patients should be reassessed daily to confirm ongoing suspicion of disease, antibiotics should be narrowed as soon as antibiotic susceptibility results are available, and clinicians should consider stopping antibiotics if cultures are negative.

Biomarker-guided antibiotic stewardship in suspected ventilator-associated pneumonia (VAPrapid2): a randomised controlled trial and process evaluation

BACKGROUND

Ventilator-associated pneumonia is the most common intensive care unit (ICU)-acquired infection, yet accurate diagnosis remains difficult, leading to overuse of antibiotics. Low concentrations of IL-1β and IL-8 in bronchoalveolar lavage fluid have been validated as effective markers for exclusion of ventilator-associated pneumonia. The VAPrapid2 trial aimed to determine whether measurement of bronchoalveolar lavage fluid IL-1β and IL-8 could effectively and safely improve antibiotic stewardship in patients with clinically suspected ventilator-associated pneumonia.

METHODS

VAPrapid2 was a multicentre, randomised controlled trial in patients admitted to 24 ICUs from 17 National Health Service hospital trusts across England, Scotland, and Northern Ireland. Patients were screened for eligibility and included if they were 18 years or older, intubated and mechanically ventilated for at least 48 h, and had suspected ventilator-associated pneumonia. Patients were randomly assigned (1:1) to biomarker-guided recommendation on antibiotics (intervention group) or routine use of antibiotics (control group) using a web-based randomisation service hosted by Newcastle Clinical Trials Unit. Patients were randomised using randomly permuted blocks of size four and six and stratified by site, with allocation concealment. Clinicians were masked to patient assignment for an initial period until biomarker results were reported. Bronchoalveolar lavage was done in all patients, with concentrations of IL-1β and IL-8 rapidly determined in bronchoalveolar lavage fluid from patients randomised to the biomarker-based antibiotic recommendation group. If concentrations were below a previously validated cutoff, clinicians were advised that ventilator-associated pneumonia was unlikely and to consider discontinuing antibiotics. Patients in the routine use of antibiotics group received antibiotics according to usual practice at sites. Microbiology was done on bronchoalveolar lavage fluid from all patients and ventilator-associated pneumonia was confirmed by at least 104 colony forming units per mL of bronchoalveolar lavage fluid. The primary outcome was the distribution of antibiotic-free days in the 7 days following bronchoalveolar lavage. Data were analysed on an intention-to-treat basis, with an additional per-protocol analysis that excluded patients randomly assigned to the intervention group who defaulted to routine use of antibiotics because of failure to return an adequate biomarker result. An embedded process evaluation assessed factors influencing trial adoption, recruitment, and decision making. This study is registered with ISRCTN, ISRCTN65937227, and ClinicalTrials.gov, NCT01972425.

FINDINGS

Between Nov 6, 2013, and Sept 13, 2016, 360 patients were screened for inclusion in the study. 146 patients were ineligible, leaving 214 who were recruited to the study. Four patients were excluded before randomisation, meaning that 210 patients were randomly assigned to biomarker-guided recommendation on antibiotics (n=104) or routine use of antibiotics (n=106). One patient in the biomarker-guided recommendation group was withdrawn by the clinical team before bronchoscopy and so was excluded from the intention-to-treat analysis. We found no significant difference in the primary outcome of the distribution of antibiotic-free days in the 7 days following bronchoalveolar lavage in the intention-to-treat analysis (p=0·58). Bronchoalveolar lavage was associated with a small and transient increase in oxygen requirements. Established prescribing practices, reluctance for bronchoalveolar lavage, and dependence on a chain of trial-related procedures emerged as factors that impaired trial processes.

INTERPRETATION

Antibiotic use remains high in patients with suspected ventilator-associated pneumonia. Antibiotic stewardship was not improved by a rapid, highly sensitive rule-out test. Prescribing culture, rather than poor test performance, might explain this absence of effect.

FUNDING

UK Department of Health and the Wellcome Trust.

Effect of Candida albicans bronchial colonization on hospital-acquired bacterial pneumonia in patients with systemic lupus erythematosus

Background

To investigate the effect of Candida albicans airway colonization on hospital-acquired bacterial pneumonia (HABP) in patients with systemic lupus erythematosus (SLE).

Methods

SLE patients with HAP were enrolled in this retrospective cohort study from January 2015 to December 2018. According to the culture results of respiratory tract secretions and antifungal treatment, patients were divided into non-C. albicans colonization group (NCG), C. albicans colonization with antifungal treatment group (CTG) and C. albicans colonization without antifungal treatment group (CNTG). Twenty-eight days of all-cause mortality after the onset of HABP of each group was assessed, total duration of antibiotic treatment, changes of inflammatory cytokines and markers of immune status were documented.

Results

A total of 269 SLE patients with HABP were finally included in the study. Among them, 69.1% (186/269) were found C. albicans airway colonization, and 36.1% (97/269) received antifungal treatment. No difference of 28 days of all-cause mortality after HABP onset was found among the three groups (10.8% vs. 13.4% vs. 15.7%, P>0.05). Duration of antibiotic treatment of HABP due to Acinetobacter baumannii was shorter in CTG (11.21±2.45 days) than that in CNTG (12.89±3.87 days) as well as HABP due to Pseudomonas aeruginosa (10.57±2.66 vs. 12.56±3.04 days) (P<0.05, respectively). Antifungal treatment could decrease the level of interleukin-1β, interleukin-6, tumor necrosis factor-α and interferon-γ in CTG than in CNTG (P<0.05, respectively). In addition, it could regulate immune function by decrease the concentration of interleukin-17 and elevate the counts of CD4+Th lymphocyte as well (P<0.05, respectively).

Conclusions

C. albicans airway colonization was not associated with HABP mortality in SLE patients. Antifungal therapy in these patients might shorten the duration of antibiotics in treating HABP due to A. baumannii and P. aeruginosa.