Prevention of Nosocomial Infections in Critically Ill Patients With Lactoferrin: A Randomized, Double-Blind, Placebo-Controlled Study

Assessment of Supplementation with Different Biomolecules in the Prevention and Treatment of COVID-19

Consequences of the disease produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have led to an urgent search for preventive and therapeutic strategies. Besides drug treatments, proposals have been made for supplementation with biomolecules possessing immunomodulatory and antioxidant properties. The objective of this study was to review published evidence on the clinical usefulness of supplementation with vitamin D, antioxidant vitamins (vitamin A, vitamin E, and vitamin C), melatonin, lactoferrin and natural products found in food (curcumin, luteolin, ginger, allicin, magnesium and zinc) as supplements in SARS-CoV-2 infection. In general, supplementation of conventional treatments with these biomolecules has been found to improve the clinical symptoms and severity of the coronavirus disease (COVID-19), with some indications of a preventive effect. In conclusion, these compounds may assist in preventing and/or improving the symptoms of COVID-19. Nevertheless, only limited evidence is available, and findings have been inconsistent. Further investigations are needed to verify the therapeutic potential of these supplements.

Cross-validated risk scores adaptive enrichment (CADEN) design

We propose a Cross-validated ADaptive ENrichment design (CADEN) in which a trial population is enriched with a subpopulation of patients who are predicted to benefit from the treatment more than an average patient (the sensitive group). This subpopulation is found using a risk score constructed from the baseline (potentially high-dimensional) information about patients. The design incorporates an early stopping rule for futility. Simulation studies are used to assess the properties of CADEN against the original (non-enrichment) cross-validated risk scores (CVRS) design which constructs a risk score at the end of the trial. We show that when there exists a sensitive group of patients, CADEN achieves a higher power and a reduction in the expected sample size compared to the CVRS design. We illustrate the application of the design in two real clinical trials. We conclude that the new design offers improved statistical efficiency over the existing non-enrichment method, as well as increased benefit to patients. The method has been implemented in an R package caden.

Colostrum Proteins in Protection against Therapy-Induced Injuries in Cancer Chemo- and Radiotherapy: A Comprehensive Review

In this article, we review the benefits of application of colostrum and colostrum-derived proteins in animal models and clinical trials that include chemotherapy with antimetabolic drugs, radiotherapy and surgical interventions. A majority of the reported investigations was performed with bovine colostrum (BC) and native bovine or recombinant human lactoferrin (LF), applied alone, in nutraceutics or in combination with probiotics. Apart from reducing side effects of the applied therapeutics, radiation and surgical procedures, BC and LF augmented their efficacy and improved the wellness of patients. In conclusion, colostrum and colostrum proteins, preferably administered with probiotic bacteria, are highly recommended for inclusion to therapeutic protocols in cancer chemo- and radiotherapy as well as during the surgical treatment of cancer patients.

Gene Expression Scoring of Immune Activity Levels for Precision Use of Hydrocortisone in Vasodilatory Shock

PURPOSE

Among patients with vasodilatory shock, gene expression scores may identify different immune states. We aimed to test whether such scores are robust in identifying patients' immune state and predicting response to hydrocortisone treatment in vasodilatory shock.

MATERIALS AND METHODS

We selected genes to generate continuous scores to define previously established subclasses of sepsis. We used these scores to identify a patient's immune state. We evaluated the potential for these states to assess the differential effect of hydrocortisone in two randomized clinical trials of hydrocortisone versus placebo in vasodilatory shock.

RESULTS

We initially identified genes associated with immune-adaptive, immune-innate, immune-coagulant functions. From these genes, 15 were most relevant to generate expression scores related to each of the functions. These scores were used to identify patients as immune-adaptive prevalent (IA-P) and immune-innate prevalent (IN-P). In IA-P patients, hydrocortisone therapy increased 28-day mortality in both trials (43.3% vs 14.7%, P = 0.028) and (57.1% vs 0.0%, P = 0.99). In IN-P patients, this effect was numerically reversed.

CONCLUSIONS

Gene expression scores identified the immune state of vasodilatory shock patients, one of which (IA-P) identified those who may be harmed by hydrocortisone. Gene expression scores may help advance the field of personalized medicine.

Two-stage penalized regression screening to detect biomarker-treatment interactions in randomized clinical trials

High-dimensional biomarkers such as genomics are increasingly being measured in randomized clinical trials. Consequently, there is a growing interest in developing methods that improve the power to detect biomarker-treatment interactions. We adapt recently proposed two-stage interaction detecting procedures in the setting of randomized clinical trials. We also propose a new stage 1 multivariate screening strategy using ridge regression to account for correlations among biomarkers. For this multivariate screening, we prove the asymptotic between-stage independence, required for familywise error rate control, under biomarker-treatment independence. Simulation results show that in various scenarios, the ridge regression screening procedure can provide substantially greater power than the traditional one-biomarker-at-a-time screening procedure in highly correlated data. We also exemplify our approach in two real clinical trial data applications.

Lactoferrin reduces the risk of respiratory tract infections: A meta-analysis of randomized controlled trials

BACKGROUND

Lactoferrin (Lf) is one of the key immunomodulatory substances found naturally in various body fluids, such as saliva, tears, and breast milk, and forms a vital part of the innate defense against invading pathogens. Various studies have demonstrated antibacterial, antifungal, and antiviral properties of Lf and its protective role against respiratory tract infections (RTIs). The present meta-analysis aims to elucidate the association of Lf administration in reducing the risk of RTIs by systematically reviewing the data from randomized controlled trials (RCTs).

METHODS

We systematically searched PubMed, Cochrane Library, Medline & CINAHL, Turning Research into Practice (TRIP), ProQuest Theses & Dissertations Databases, and China National Knowledge Infrastructure (CNKI) from inception till March 15, 2021. The primary outcome measure was a reduction in respiratory illness; decrease in frequency, symptoms, and duration. Random-effects model was used to estimate the odds ratio (OR) and 95% confidence interval (CI). We used Cochrane's RoB-2 to appraise the risk of bias of included RCTs.

RESULTS

A total of nine RCTs were eligible for this review, of which six were included in the meta-analysis. Overall, two studies demonstrated a high risk of bias. The meta-analysis revealed a significantly reduced odds of developing respiratory infections with the use of Lf relative to the control (pooled odds ratio = 0.57; 95% confidence interval 0.44 to 0.74, n = 1,194), with sufficient evidence against the hypothesis of 'no significant difference' at the current sample size.

CONCLUSIONS

The administration of Lf shows promising efficacy in reducing the risk of RTIs. Current evidence also favours Lf fortification of infant formula. Lf may also have a beneficial role in managing symptoms and recovery of patients suffering from RTIs and may have potential for use as an adjunct in COVID-19, however this warrants further evidence from a large well-designed RCT.

The relationship between immune status as measured by stimulated ex-vivo tumour necrosis factor alpha levels and the acquisition of nosocomial infections in critically ill mechanically ventilated patients

Introduction

Immunological dysfunction is common in critically ill patients but its clinical significance and the optimal method to measure it are unknown. The level of tumor necrosis factor alpha (TNF-α) after ex-vivo whole blood stimulation with lipopolysaccharide (LPS) has been proposed as a possible method to quantify immunological function. We hypothesized that in a cohort of critically ill patients, those with a lower post-stimulation TNF-α level would have increased rates of nosocomial infections (NIs) and worse clinical outcomes.

Methods

A secondary analysis of a phase 2 randomized, multi-centre, double-blinded placebo-controlled trial. As there was no difference between treatment and control arms in outcomes and NI rate, all the patients were analyzed as one cohort. On enrolment, day 4, 7, and weekly until day 28, whole blood was incubated with LPS ex-vivo and subsequent TNF-α level was measured. Patients were grouped in tertiles according to delta and peak TNF-α level. The primary outcome was the association between NIs and tertiles of TNF-α level post LPS stimulation; secondary outcomes included ICU and 90-day mortality, and ICU and hospital length of stay.

Results

Data was available for 201 patients. Neither the post LPS stimulation delta TNF-α group nor the peak TNF-α post-stimulation group were associated with the development of NIs or clinical outcomes. Patients in the highest tertile for post LPS stimulation delta TNF-α compared to the lowest tertile were younger [61.1 years ± 15.7 vs. 68.6 years ± 12.8 standard deviations (SD) in the lowest tertile], had lower acuity of illness (APACHE II 25.0 ± 9.7 vs. 26.7 ± 6.1) and had lower baseline TNF-α (9.9 pg/mL ± 19.0 vs. 31.0 pg/mL ± 68.5). When grouped according to peak post-stimulation TNF-α levels, patients in the highest tertile had higher serum TNF-α at baseline (21.3 pg/mL ± 66.7 compared to 6.5 pg/mL ± 9.0 in the lowest tertile).

Conclusion

In this prospective multicenter study, ex-vivo stimulated TNF-α level was not associated with the occurrence of NIs or clinical outcomes. Further study is required to better ascertain whether TNF levels and ex-vivo stimulation can be used to characterize immune function in critical illness and if other assays might be better suited to this task.

Insights Into a "Negative" ICU Trial Derived From Gene Expression Profiling

OBJECTIVES

Randomized controlled trials in the ICU often fail to show differences in endpoints between groups. We sought to explore reasons for this at a molecular level by analyzing transcriptomic data from a recent negative trial. Our objectives were to determine if randomization successfully balanced transcriptomic features between groups, to assess transcriptomic heterogeneity among the study subjects included, and to determine if the study drug had any effect at the gene expression level.

DESIGN

Bioinformatics analysis of transcriptomic and clinical data collected in the course of a randomized controlled trial.

SETTING

Tertiary academic mixed medical-surgical ICU.

PATIENTS

Adult, critically ill patients expected to require invasive mechanical ventilation more than 48 hours.

INTERVENTIONS

Lactoferrin or placebo delivered enterally and via an oral swab for up to 28 days.

MEASUREMENTS AND MAIN RESULTS

We found no major imbalances in transcriptomic features between groups. Unsupervised analysis did not reveal distinct clusters among patients at the time of enrollment. There were marked differences in gene expression between early and later time points. Patients in the lactoferrin group showed changes in the expression of genes associated with immune pathways known to be associated with lactoferrin.

CONCLUSIONS

In this clinical trial, transcriptomic data provided a useful complement to clinical data, suggesting that the reasons for the negative result were less likely related to the biological efficacy of the study drug, and may instead have been related to poor sensitivity of the clinical outcomes. In larger studies, transcriptomics may also prove useful in predicting response to treatment.

Fully moderated t-statistic in linear modeling of mixed effects for differential expression analysis

BACKGROUND

Gene expression profiling experiments with few replicates lead to great variability in the estimates of gene variances. Toward this end, several moderated t-test methods have been developed to reduce this variability and to increase power for testing differential expression. Most of these moderated methods are based on linear models with fixed effects where residual variances are smoothed under a hierarchical Bayes framework. However, they are inadequate for designs with complex correlation structures, therefore application of moderated methods to linear models with mixed effects are needed for differential expression analysis.

RESULTS

We demonstrated the implementation of the fully moderated t-statistic method for linear models with mixed effects, where both residual variances and variance estimates of random effects are smoothed under a hierarchical Bayes framework. We compared the proposed method with two current moderated methods and show that the proposed method can control the expected number of false positives at the nominal level, while the two current moderated methods fail.

CONCLUSIONS

We proposed an approach for testing differential expression under complex correlation structures while providing variance shrinkage. The proposed method is able to improve power by moderation and controls the expected number of false positives properly at the nominal level.

A test for treatment effects in randomized controlled trials, harnessing the power of ultrahigh dimensional big data

BACKGROUND

The randomized controlled trial (RCT) is the gold-standard research design in biomedicine. However, practical concerns often limit the sample size, n, the number of patients in a RCT. We aim to show that the power of a RCT can be increased by increasing p, the number of baseline covariates (sex, age, socio-demographic, genomic, and clinical profiles et al, of the patients) collected in the RCT (referred to as the 'dimension').

METHODS

The conventional test for treatment effects is based on testing the 'crude null' that the outcomes of the subjects are of no difference between the two arms of a RCT. We propose a 'high-dimensional test' which is based on testing the 'sharp null' that the experimental intervention has no treatment effect whatsoever, for patients of any covariate profile.

RESULTS

Using computer simulations, we show that the high-dimensional test can become very powerful in detecting treatment effects for very large p, but not so for small or moderate p. Using a real dataset, we demonstrate that the P value of the high-dimensional test decreases as the number of baseline covariates increases, though it is still not significant.

CONCLUSION

In this big-data era, pushing p of a RCT to the millions, billions, or even trillions may someday become feasible. And the high-dimensional test proposed in this study can become very powerful in detecting treatment effects.

Healthcare-Associated Infections in the Neurocritical Care Unit

PURPOSE OF REVIEW

This article summarizes updated data and knowledge on healthcare-associated infections in the neurocritical care unit, with a focus on central nervous system infections and systemic infectious complications in patients with acute brain disease. It also reviews the concept of brain injury-induced immune modulation, an underlying mechanism to explain why the neuro-ICU population is particularly susceptible to infections.

RECENT FINDINGS

Healthcare-associated infections in the neuro-ICU are common: up to 40 % of meningitides in the developed world are now healthcare-associated. The number of gram-negative infections is rising. New diagnostic approaches attempt to aid in the diagnosis of healthcare-associated meningitis and ventriculitis. Healthcare-associated infections in the neurocritical care unit remain a challenge for diagnosis, treatment, and prevention. Gaining a better understanding of at-risk patients and development of preventative strategies will be the goal for future investigation.

Iron Metabolism: An Emerging Therapeutic Target in Critical Illness

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2019. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2019. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.