Selective digestive decontamination, a seemingly effective regimen with individual benefit or a flawed concept with population harm?

Short-duration selective decontamination of the digestive tract infection control does not contribute to increased antimicrobial resistance burden in a pilot cluster randomised trial (the ARCTIC Study)

OBJECTIVE

Selective decontamination of the digestive tract (SDD) is a well-studied but hotly contested medical intervention of enhanced infection control. Here, we aim to characterise the changes to the microbiome and antimicrobial resistance (AMR) gene profiles in critically ill children treated with SDD-enhanced infection control compared with conventional infection control.

DESIGN

We conducted shotgun metagenomic microbiome and resistome analysis on serial oropharyngeal and faecal samples collected from critically ill, mechanically ventilated patients in a pilot multicentre cluster randomised trial of SDD. The microbiome and AMR profiles were compared for longitudinal and intergroup changes. Of consented patients, faecal microbiome baseline samples were obtained in 89 critically ill children. Additionally, samples collected during and after critical illness were collected in 17 children treated with SDD-enhanced infection control and 19 children who received standard care.

RESULTS

SDD affected the alpha and beta diversity of critically ill children to a greater degree than standard care. At cessation of treatment, the microbiome of SDD patients was dominated by Actinomycetota, specifically Bifidobacterium, at the end of mechanical ventilation. Altered gut microbiota was evident in a subset of SDD-treated children who returned late longitudinal samples compared with children receiving standard care. Clinically relevant AMR gene burden was unaffected by the administration of SDD-enhanced infection control compared with standard care. SDD did not affect the composition of the oral microbiome compared with standard treatment.

CONCLUSION

Short interventions of SDD caused a shift in the microbiome but not of the AMR gene pool in critically ill children at the end mechanical ventilation, compared with standard antimicrobial therapy.

Length of intensive care unit stay and the apparent efficacy of antimicrobial-based versus non-antimicrobial-based ventilator pneumonia prevention interventions within the Cochrane review database

BACKGROUND

The risk of acquiring ventilator-associated pneumonia (VAP) increases with intensive care unit (ICU) length of stay (LOS). The objectives here are to estimate, using data derived from randomized concurrent control trials (RCCTs) of non-antimicrobial versus antimicrobial interventions, the relation of LOS with firstly, apparent VAP prevention effect, and secondly, with VAP incidence in control and intervention groups.

METHODS

Control and intervention group data derived from 13 Cochrane reviews of 78 RCCTs of antimicrobial-based interventions versus 111 RCCTs of various non-antimicrobial-based VAP prevention interventions.

RESULTS

In meta-regression models of VAP prevention effect versus group mean LOS, the effect size of non-antimicrobial-based interventions regress towards the null (+0.028; +0.002 to +0.054) whereas antimicrobial-based interventions regress away from the null (-0.043; -0.08 to -0.004). The day 9-10 VAP incidence increase is 1.28 (0.97-1.6) percentage points among the control groups of antimicrobial interventions per day. By contrast, these increases among antimicrobial- (0.45; 0.19-0.71) and non-antimicrobial- (0.58; 0.29-0.87) intervention groups and in control groups of non-antimicrobial- (0.76; 0.46-1.05) interventions are all similar.

CONCLUSIONS

Antimicrobial-based versus non-antimicrobial-based interventions show overall greater apparent VAP prevention which is most apparent with longer group mean LOS. The basis for this surprising relationship with LOS resides, paradoxically, within the control rather than the intervention groups. This discrepancy implicates indirect (spill-over) effects, inapparent within individual antimicrobial-based RCCTs, which could spuriously conflate the appearance of VAP prevention.

Management of pneumonia in the critically ill

Pneumonias continue to be major public health issues and are commonly encountered in the intensive care setting. The most common types of pneumonia leading to critical illness include severe community acquired pneumonia, hospital acquired pneumonia, and ventilator associated pneumonia. Early evaluation, diagnosis, and escalation to appropriate levels of care are imperative to improving survival. Treatment remains challenging with the need to balance antibiotic stewardship and minimizing patient harm. As evidenced in the most recent society guidelines, the identification of risk factors for severe disease and the causative pathogens are crucial in guiding the most appropriate therapy.

Antibiotics in Chronic Liver Disease and Their Effects on Gut Microbiota

Impairments in liver function lead to different complications. As chronic liver disease progresses (CLD), hypoalbuminemia and alterations in bile acid compositions lead to changes in gut microbiota and, therefore, in the host-microbiome interaction, leading to a proinflammatory state. Alterations in gut microbiota composition and permeability, known as gut dysbiosis, have important implications in CLD; alterations in the gut-liver axis are a consequence of liver disease, but also a cause of CLD. Furthermore, gut dysbiosis plays an important role in the progression of liver cirrhosis and decompensation, particularly with complications such as hepatic encephalopathy and spontaneous bacterial peritonitis. In relation to this, antibiotics play an important role in treating CLD. While certain antibiotics have specific indications, others have been subjected to continued study to determine whether or not they have a modulatory effect on gut microbiota. In contrast, the rational use of antibiotics is important, not only because of their disrupting effects on gut microbiota, but also in the context of multidrug-resistant organisms. The aim of this review is to illustrate the role of gut microbiota alterations in CLD, the use and impact of antibiotics in liver cirrhosis, and their harmful and beneficial effects.

Trends in ICU mortality and underlying risk over three decades among mechanically ventilated patients. A group level analysis of cohorts from infection prevention studies

BACKGROUND

Has either the underlying risk or the mortality incidence among ICU patients receiving mechanical ventilation (MV) in the literature changed in recent decades? Interpreting ICU mortality trends requires an adjusted analysis accounting for changes in underlying patient risk.

METHODS

Control and intervention groups from 147 randomized concurrent control trials (RCCT) of various VAP prevention interventions, as listed primarily within 13 Cochrane reviews and 63 observational studies listed primarily within four systematic reviews. Eligible studies were those including ICU patients with > 50% of patients receiving > 24 h of MV with mortality data available. ICU mortality (censored day 21 or before) or late (after day 21) mortality together with group-mean age, and group-mean APACHE II scores were extracted from all groups. These incidences were summarized in five meta-regression models versus publication year being variously adjusted for age, APACHE II scores, type of study intervention and other group level parameters.

RESULTS

Among 210 studies published between 1985 and 2021, 169 being found in systematic reviews, the increase per decade in mean mortality incidence, group-mean APACHE II scores, and group-mean age, were < 1 percentage point (p = 0.43), 1.83 (95% CI; 0.51-3.15) points, and 3.9 (95% CI; 1.1-6.7) years, respectively. Only in the model with risk adjustment for both group-mean age and group-mean APACHE II score was a significant decline in mortality apparent. In all models, the mortality incidence among concurrent control groups of decontamination studies was paradoxically five percentage points higher than benchmark and showed greater dispersion.

CONCLUSION

Mortality incidence has changed little over 35 years among ICU infection prevention studies whilst the patient age and underlying disease severity, measured as APACHE II, have both increased. The paradoxically high mortality among concurrent control groups within studies of decontamination methods of infection prevention remains unaccounted for.

Establishing the safety of selective digestive decontamination within the ICU population: a bridge too far?

BACKGROUND

Infection prevention interventions within the intensive care unit (ICU) setting, whether studied within quality improvement projects or cluster randomized trials (CRT), are seen as low risk and grounded in an ethical imperative. Selective digestive decontamination (SDD) appears highly effective at preventing ICU infections within randomized concurrent control trials (RCCTs) prompting mega-CRTs with mortality as the primary endpoint.

FINDINGS

Surprisingly, the summary results of RCCTs versus CRTs differ strikingly, being respectively, a 15-percentage-point versus a zero-percentage-point ICU mortality difference between control versus SDD intervention groups. Multiple other discrepancies are equally puzzling and contrary to both prior expectations and the experience within population-based studies of infection prevention interventions using vaccines. Could spillover effects from SDD conflate the RCCT control group event rate differences and represent population harm? Evidence that SDD is fundamentally safe to concurrent non-recipients in ICU populations is absent. A postulated CRT to realize this, the SDD Herd Effects Estimation Trial (SHEET), would require > 100 ICUs to achieve sufficient statistical power to find a two-percentage-point mortality spillover effect. Moreover, as a potentially harmful population-based intervention, SHEET would pose novel and insurmountable ethical issues including who is the research subject; whether informed consent is required and from whom; whether there is equipoise; the benefit versus the risk; considerations of vulnerable groups; and who should be the gatekeeper?

CONCLUSION

The basis for the mortality difference between control and intervention groups of SDD studies remains unclear. Several paradoxical results are consistent with a spillover effect that would conflate the inference of benefit originating from RCCTs. Moreover, this spillover effect would constitute to herd peril.

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.

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.