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

PurposeAnimal 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.MethodsThree 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.ResultsIntroducing 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.ConclusionGSEM 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.

Great controversy has arisen recently between two differing opinions regarding optimal feeding in the ICU. Traditionally, it has been advocated that patients receive 80% of full calorie and protein (1.2-2.0 g/kg/d) feeds in the first week of ICU to optimize outcomes(1). However, a number of recent trials have advocated for “trophic feeding” or intentional underfeeding in the first ICU week being equally efficacious and perhaps beneficial (2-4). However, it is intuitive to most ICU practitioners that “all ICU patients are not created equal” and undoubtedly “one size does not fit all”. This concept is well described, in the article by Wei et al in this issue of Critical Care Medicine(5). The authors of this manuscript demonstrate that in high-risk ICU patients (mechanically ventilated > 8 days) receiving low nutritional adequacy in the first week of ICU stay ( 80% of calorie needs) after adjusting for key covariates.

Bacterial colonization of the pharynx before and one week after operation, and contamination of the trachea during intubation in 7 patients who underwent operations were investigated. And bacterial colonization of pharynx, tracheas, and mechanical-ventilators in 7 ICU patients was investigated. Flora of palms of 10 ICU personnel was also examined: 1) Oral bacteria began to be found in the trachea several hours after intubation. 2) In oropharyngeal flora, one week after operation, Neisseria and anaerobes which belong to normal flora decreased because of antibiotics, but no new resistant bacteria appeared. 3) Although isolates from pharynx of preoperative patients were normal flora, those of ICU patients were Staphylococcus epidermidis, Enterococcus spp., gram-negative rods such as Pseudomonas aeruginosa, and yeast liked organisms etc, which were resistant to antibiotics. 4) From the trachea of intubated patients in ICU, oral bacteria were isolated. 5) Pseudomonas pickettii was isolated from the expiratory side of ventilator circuits in one patient, but it was not isolated from the patient. 6) From hands of ICU personnel, gram-positive bacteria such as coagulase negative staphylococci, Coryne bacterium spp. and Bacillus spp. were isolated. 7) One patient in ICU, who developed pneumonia due to resistant Bacteroides fragilis following oropharyngeal colonization, was reported. These studies suggested the importance of environmental control, careful selection of antibiotics, and attention to change of flora.

Background VAP is a common complication of ventilator maintenance therapy. The occurrence of VAP is related to many factors such as long duration of breathing, invasive operation, pollution of respiratory tubes and instruments, and low immunity of patients. The prevention of VAP in critically ill patients I the primary problem for clinical medical staff. Avoiding exogenous bacteria invading the respiratory tract and endogenous bacterial infection is the main method. Objective To investigate the value of optimized cluster nursing intervention combined with targeted nursing measures in reducing the incidence of ventilator-associated pneumonia (VAP) in patients with mechanical ventilation in intensive care unit (ICU). Methods 200 patients with mechanical ventilation in ICU of our institute from January 2017 to June 2020 were selected and randomly divided into study group and control group, with 100 cases in each group. The study group was treated with cluster nursing intervention combined with targeted nursing measures optimized by muItL criteria decision analysis method, and the control group was treated with targeted nursing measures. The incidence of VAP, the detection rate of pathogenic bacteria in sputum specimens and the effect of nursing execution were compared between the two groups. 200 patients were divided into VAP group and non-VAP group according to whether VAP occurred. Multivariate Logistic regression model analysis was used to explore the risk factors of VAP in AECOPD patients. Results A total of 4 strains were detected in the study group and 18 strains were detected in the control group. The detection rate of pathogenic bacteria in the study group was higher than that in the control group (y2=10.010, P=0.002<0.05). The incidence of VAP in the study group was 4.00% lower than 17.00% in the control group, and the difference was statistically significant (P<0.05). Compared with VAP group and non-VAP group, the proportion of patients with serum albumin<30g/L, diabetes mellitus rate, APACHE II score>15 points, tracheotomy rate and mechanical ventilation time≥5 days in VAP group were significantly higher than those in non-VAP group, which had statistical significance (P<0.05). The results of logistic regression model snowed that serum albumin ≥30g/L and optimized cluster nursing could effectively reduce the risk of VAP in ICU patients with mechanical ventilation (P<0.05). The risk of VAP in ICU patients with mechanical ventilation was increased by the combination of diabetes rate. APACHE II score≥15 points, tracheotomy and mechanical ventilation time ≥ 5 days (P<0.05). Conclusion The risk of VAP in ICU patients with mechanical ventilation is high, and the optimized cluster nursing intervention combined with targeted nursing measures can effectively reduce the incidence of VAP.

Nosocomial infections are a significant issue of public health. In Italy, the incidence of nosocomial infections range between 5 and 8% [1]; in Neonatal Intensive Care Unit (NICU) range between 7 and 24.5% [2]. Nosocomial infection in a newborn is defined as an infection arised after 48-72 hours of hospitalization. The extremely low birth weight (ELBW) neonates have an increased risk of developing infections (40%)[2], due to the immaturity of the immune system, the prolonged length of hospitalization and the frequent need for invasive procedures (central venous catheters - CVC, mechanical ventilation, parenteral nutrition, prolonged antibiotic therapies). In NICU, sepsis accounted for 45-55% of cases of nosocomial infections, followed by the lower respiratory tract infections (16-33%), skin and soft tissue infections (26.3%), urinary tract infections (8-19%) and meningitis (9.6%) [2]. The gram-positive bacteria are responsible for 65% of infections (Coagulase-negative Staphylococci - CoNS, Staphylococcus aureus and Enterococcus spp respectively in 50, 35 and 6% of cases), followed by Gram-negative bacteria (Klebsiella, Pseudomonas, E. Coli ) and fungi in 25% of cases each. Candida albicans is involved in 50% of cases of fungal infections. Viruses are accountable for epidemics in the NICU, but the incidence of viral infections is likely to be underestimated. The prevention of nosocomial infections is an essential element for the management of the newborns [3,4] and is based on strategies to reduce the risk factors related to the newborn (immune system, carefull skin care, etc.) and to improve the invasive care procedures (implementation and dissemination of guide lines for accurate and proper hand hygiene [4,5], for prevention of CVC related infections [4,6] and ventilator-associated pneumonia [7], promotion of enteral feeding with breast milk [8]). Not least, the need for accurate diagnostic strategies for early detection of neonatal infections and a rational use of antimicrobial therapies and antibiotic prophylaxis [9,10]. The new strategies of prophylaxis of infections involving the use of bioactive substances with anti-infective properties, such as lactoferrin [11]; the use of probiotics, which have recognized immunomodulatory and anti-infectious activities [12]; the prophylaxis with antifungal drugs [13]. Lastly, NICU should also meet specific criteria of organization, providing to maintain an adequate ratio nurses/beds, avoid overcrowding and understaffing, make easily available devices for hand washing, organize meetings for training/provide to caregivers regular feedback of performance data, plan continuous monitoring and a surveillance system of the rate of nosocomial infections and avoid preventive measures of unproven effectiveness.

5:09 PM, Abstract No. 323 - Predictors of deep vein thrombosis associated with midline venous catheter in hospitalized patients: a single-institute experience

Background: Candida is a significant pathogen among critically ill patients. However, candidiasis among non-trauma emergency surgery (NTES) patients has not been previously investigated. Herein we describe the incidence of both colonization and infection from Candida and risk factors for invasive disease in this population. Methods: For this retrospective single center study we included all NTES patients with ICU stay ≥4 days from May 1st, 2002 to April 30th, 2007. Patients were divided into 3 non-overlapping groups: 1) patients with Candida-infection, 2) patients with Candida colonization and 3) patients with negative Candida cultures. Groups were compared by univariate and multivariate analyses to identify significant risk factors for invasive candidiasis. Results: Of all 289 eligible patients, 63 (21.7%) fulfilled the criteria for Candida infection and 110 (38%) were included in the Candida colonization group. Interestingly, from the 63 patients with invasive candidiasis, 25 (39.7%) were infected by a non-albicans species. Upon multivariate analyses, ventilator-associated pneumonia (VAP) (Odds Ratio [OR]: 2.34; 95%, Confidence Interval [CI]: 1.213 - 4.533, p= 0.0112), bacteremia (OR: 4.778; 95%CI: 1.519 - 15.029, p= 0.0075) and surgical complications (OR: 3.903; 95%CI: 1.335 - 11.412, p= 0.0129) were independent risk factors for the development of Candida infection. Candida infection and colonization were both found to correlate with approximately $40,000 - 100,000 mean additional costs). Interestingly, candidemia was associated with 63% all-cause mortality. For all other forms of candidiasis, mortality was not significantly different among groups. Conclusion: We found thatCandidainfection is alarmingly high among NTES patients with prolonged intensive care unit (ICU) stay. Surgical complications and bacterial infections (VAP and bacteraemia) were significantly correlated with the development of candidiasis. Candidiasis reached a rate of 21.7/100 discharges, which is significantly higher than most established high-risk populations for candidiasis. Future studies should review the need for antifungal prophylaxis on this population.

The Puzzles of Ventilator-Associated Pneumonia and COVID-19: Absolute Knowns and Relative Unknowns.

Effects of Candida colonization on patients with ventilator-associated pneumonia and pathogenic microorganisms: Systematic review and meta-analysis

Mortality and Ventilator-associated Pneumonia: The Best Antibiotics May Be the Least Antibiotics

Pharmacokinetic/pharmacodynamic adequacy of echinocandins against Candida spp. in intensive care unit patients and general patient populations

A point well taken

Background: Ventilator-associated pneumonia (VAP) represents the highest burden among all healthcare-associated infections (HAIs), with a particularly high rate in patients in neurosurgical ICUs. Numerous VAP risk factors have been identified to provide a basis for preventive measures. However, the impact of individual factors on the risk of VAP is unclear. The goal of this study was to evaluate the dynamics of various VAP risk factors given the continuously declining prevalence of VAP in our neurosurgical ICU. Methods: This prospective cohort unit-based study included neurosurgical patients who stayed in the ICU >48 consecutive hours in 2011 through 2018. The infection prevention and control (IPC) program was implemented in 2010 and underwent changes to adopt best practices over time. We used a 2008 CDC definition for VAP. The dynamics of VAP risk factors was considered a time series and was checked for stationarity using theAugmented Dickey-Fuller test (ADF) test. The data were censored when a risk factor was present during and after VAP episodes. Results: In total, 2,957 ICU patients were included in the study, 476 of whom had VAP. Average annual prevalence of VAP decreased from 15.8 per 100 ICU patients in 2011 to 9.5 per 100 ICU patients in 2018 (Welch t test P value = 7.7e-16). The fitted linear model showed negative slope (Fig. 1). During a study period we observed substantial changes in some risk factors and no changes in others. Namely, we detected a decrease in the use of anxiolytics and antibiotics, decreased days on mechanical ventilation, and a lower rate of intestinal dysfunction, all of which were nonstationary processes with a declining trend (ADF testP > .05) (Fig. 2). However, there were no changes over time in such factors as average age, comorbidity index, level of consciousness, gender, and proportion of patients with brain trauma (Fig. 2). Conclusions: Our evidence-based IPC program was effective in lowering the prevalence of VAP and demonstrated which individual measures contributed to this improvement. By following the dynamics of known VAP risk factors over time, we found that their association with declining VAP prevalence varies significantly. Intervention-related factors (ie, use of antibiotics, anxiolytics and mechanical ventilation, and a rate of intestinal dysfunction) demonstrated significant reduction, and patient-related factors (ie, age, sex, comorbidity, etc) remained unchanged. Thus, according to the discriminative model, the intervention-related factors contributed more to the overall risk of VAP than did patient-related factors, and their reduction was associated with a decrease in VAP prevalence in our neurosurgical ICU.Funding: NoneDisclosures: None

Introduction The lung microbiota of patients with inhalation injury (INHI) may be distinct from those who do not have INHI. Furthermore, the lung trauma from mechanical ventilation or INHI can increase the risk of ventilator-associated pneumonia (VAP), a leading cause of death in hospital acquired infections. The purpose of this study was to identify the main pathogens isolated from mechanically ventilated patients, with and without INHI, including those that develop VAP to test the hypothesis that INHI itself influences the bacterial present in airways. Methods Data was collected via a single institution retrospective review using the Burn Registry and adjacent health records from 1/1/2019 to 12/31/2021. VAP was defined as a hospital-acquired pneumonia that developed ≥ 48 hours of mechanical ventilation and positive culture was growth of any microorganism. Data were examined for the 3 most common pathogens cultured from respiratory samples obtained via bronchoalveolar lavage (BAL), mini-BAL, or sputum induction. Results The 3 most common pathogens cultured from respiratory samples are presented as the percentage of the cohort in which each pathogen was identified. In all mechanically ventilated patients (n=213), Staphylococcus aureus (15.9%), Pseudomonas aeruginosa (9.9%), and Diphtheroid (9.9%) were most commonly isolated. In all patients with INHI (n=78), S. aureus (21.3%), Diphtheroid (13.3%), and gamma hemolytic Streptococcus (10.7%) were the most common. In all patients with no INHI (n=135), S. aureus (14.1%), P. aeruginosa (10.9%) and Diphtheroid (7.0%) were the most common. In those with INHI and with VAP (n=3), S. aureus (100%) was present in addition to P. aeruginosa, Klebsiella pneumoniae, Acinetobacter baumannii, and Klebsiella aerogenes which were each in 33% of patients. In those with INHI and without VAP (n=75), S. aureus (17.3%), Diphtheroid (13.3%), and gamma hemolytic Strep. (10.7%) were the most cultured. P. aeruginosa was in 8% of patients. In those with no INHI and with VAP (n=7), the most common bacteria were S. aureus (57.1%) followed by Enterobacter cloacae, P. aeruginosa, gamma hemolytic Strep., Diphtheroid, E. coli, A. baumanii, and S. pneumoniae which were each in 28.6% of patients. In those with no INHI and no VAP (n=128), S. aureus (10.9%), P. aeruginosa (9.4%) were found and alpha hemolytic Strep., Diphtheroid, K. pneumoniae and coagulase negative Staph. were each in 7% of patients. Conclusions All VAP patients had polymicrobial infections. Differences in the most common pathogens of ventilated patients with INHI versus those without INHI were seen. P. aeruginosa was not one of the top 3 pathogens in patients with INHI and MRSA was not one of the top 3 pathogens for either group. Follow up studies with a larger VAP sample size are needed to evaluate whether these trends are significant and generalizable. Applicability of Research to Practice Understanding the microbiology of patients with and without INHI can guide targeted antibiotic treatment.

Whether exposing the microbiome to antibiotics decreases or increases the risk of blood stream infection with Pseudomonas aeruginosa, Staphylococcus aureus, Acinetobacter, and Candida among ICU patients, and how this altered risk might be mediated, are critical research questions. Addressing these questions through the direct study of specific constituents within the microbiome would be difficult. An alternative tool for addressing these research questions is structural equation modelling (SEM). SEM enables competing theoretical causation networks to be tested 'en bloc' by confrontation with data derived from the literature. These causation models have three conceptual steps: exposure to specific antimicrobials are the key drivers, clinically relevant infection end points are the measurable observables, and the activity of key microbiome constituents on microbial invasion serve as mediators. These mediators, whether serving to promote, to impede, or neither, are typically unobservable and appear as latent variables in each model. SEM methods enable comparisons through confronting the three competing models, each versus clinically derived data with the various exposures, such as topical or parenteral antibiotic prophylaxis, factorized in each model. Candida colonization, represented as a latent variable, and concurrency are consistent promoters of all types of blood stream infection, and emerge as harmful mediators.