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Antimicrobial Stewardship Using Biomarkers: Accumulating Evidence for the Critically Ill.

ABSTRACT: This review aims to summarize current progress in the management of critically ill, using biomarkers as guidance for antimicrobial treatment with a focus on antimicrobial stewardship. Accumulated evidence from randomized clinical trials (RCTs) and observational studies in adults for the biomarker-guided antimicrobial treatment of critically ill (mainly sepsis and COVID-19 patients) has been extensively searched and is provided. Procalcitonin (PCT) is the best studied biomarker; in the majority of randomized clinical trials an algorithm of discontinuation of antibiotics with decreasing PCT over serial measurements has been proven safe and effective to reduce length of antimicrobial treatment, antibiotic-associated adverse events and long-term infectious complications like infections by multidrug-resistant organisms and Clostridioides difficile. Other biomarkers, such as C-reactive protein and presepsin, are already being tested as guidance for shorter antimicrobial treatment, but more research is needed. Current evidence suggests that biomarkers, mainly procalcitonin, should be implemented in antimicrobial stewardship programs even in the COVID-19 era, when, although bacterial coinfection rate is low, antimicrobial overconsumption remains high.

SUBMITTER: Kyriazopoulou E

PROVIDER: S-EPMC8944654 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Antimicrobial Stewardship Using Biomarkers: Accumulating Evidence for the Critically Ill.

Kyriazopoulou Evdoxia E Giamarellos-Bourboulis Evangelos J EJ

Antibiotics (Basel, Switzerland) 20220309 3

This review aims to summarize current progress in the management of critically ill, using biomarkers as guidance for antimicrobial treatment with a focus on antimicrobial stewardship. Accumulated evidence from randomized clinical trials (RCTs) and observational studies in adults for the biomarker-guided antimicrobial treatment of critically ill (mainly sepsis and COVID-19 patients) has been extensively searched and is provided. Procalcitonin (PCT) is the best studied biomarker; in the majority o ...[more]

PMID: 35326830

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Project description:Lower respiratory tract infections (LRTIs) are a major cause of morbidity and death. Because of changes in how LRTIs are defined coupled with the increasing prevalence of drug resistance, there is a gap in knowledge regarding the current burden of antimicrobial use for Centers for Disease Control and Prevention (CDC)-defined LRTIs. We describe the infection characteristics, antibiotic consumption, and clinical and economic outcomes of patients with Gram-negative (GN) LRTIs treated in intensive care units (ICUs).This was a retrospective, observational, cross-sectional study of adult patients treated in ICUs at two large academic medical centers in metropolitan Detroit, Michigan, from October 2013 to October 2015. To meet the inclusion criteria, patients must have had CDC-defined LRTI caused by a GN pathogen during ICU stay. Microbiological assessment of available Pseudomonas aeruginosa isolates included minimum inhibitory concentrations for key antimicrobial agents.Four hundred and seventy-two patients, primarily from the community (346, 73.3%), were treated in medical ICUs (272, 57.6%). Clinically defined pneumonia was common (264, 55.9%). Six hundred and nineteen GN organisms were identified from index respiratory cultures: P. aeruginosa was common (224, 36.2%), with 21.6% of these isolates being multidrug resistant. Cefepime (213, 45.1%) and piperacillin/tazobactam (174, 36.8%) were the most frequent empiric GN therapies. Empiric GN therapy was inappropriate in 44.6% of cases. Lack of in vitro susceptibility (80.1%) was the most common reason for inappropriateness. Patients with inappropriate empiric GN therapy had longer overall stay, which translated to a median total cost of care of $79,800 (interquartile range $48,775 to $129,600) versus $68,000 (interquartile range $38,400 to $116,175), p = 0.013. Clinical failure (31.5% vs 30.0%, p = 0.912) and in-hospital all-cause mortality (26.4% vs 25.9%, p = 0.814) were not different.Drug-resistant pathogens were frequently found and empiric GN therapy was inappropriate in nearly 50% of cases. Inappropriate therapy led to increased lengths of stay and was associated with higher costs of care.

Project description:BackgroundDespite the high morbidity and mortality associated with sepsis, the relationship between the plasma proteome and clinical outcome is poorly understood. In this study, we used targeted plasma proteomics to identify novel biomarkers of sepsis in critically ill patients.MethodsBlood was obtained from 15 critically ill patients with suspected/confirmed sepsis (Sepsis-3.0 criteria) on intensive care unit (ICU) Day-1 and Day-3, as well as age- and sex-matched 15 healthy control subjects. A total of 1161 plasma proteins were measured with proximal extension assays. Promising sepsis biomarkers were narrowed with machine learning and then correlated with relevant clinical and laboratory variables.ResultsThe median age for critically ill sepsis patients was 56 (IQR 51-61) years. The median MODS and SOFA values were 7 (IQR 5.0-8.0) and 7 (IQR 5.0-9.0) on ICU Day-1, and 4 (IQR 3.5-7.0) and 6 (IQR 3.5-7.0) on ICU Day-3, respectively. Targeted proteomics, together with feature selection, identified the leading proteins that distinguished sepsis patients from healthy control subjects with ≥ 90% classification accuracy; 25 proteins on ICU Day-1 and 26 proteins on ICU Day-3 (6 proteins overlapped both ICU days; PRTN3, UPAR, GDF8, NTRK3, WFDC2 and CXCL13). Only 7 of the leading proteins changed significantly between ICU Day-1 and Day-3 (IL10, CCL23, TGFα1, ST2, VSIG4, CNTN5, and ITGAV; P < 0.01). Significant correlations were observed between a variety of patient clinical/laboratory variables and the expression of 15 proteins on ICU Day-1 and 14 proteins on ICU Day-3 (P < 0.05).ConclusionsTargeted proteomics with feature selection identified proteins altered in critically ill sepsis patients relative to healthy control subjects. Correlations between protein expression and clinical/laboratory variables were identified, each providing pathophysiological insight. Our exploratory data provide a rationale for further hypothesis-driven sepsis research.

Project description:BackgroundPrior retrospective cross-sectional work has associated antimicrobials with a non-specific phrase: encephalopathy without seizures. The purpose of this study is to determine whether different classes of antimicrobials have differential associations with the daily risk of delirium after critical illness is adjusted for.MethodsOur study was a nested cohort that enrolled non-neurological critically ill adults from a medical or surgical intensive care unit (ICU) with daily follow-up to 30 days. Our independent variable was exposure to previous-day antimicrobial class: beta-lactams (subclasses: penicillins, first- to third-generation cephalosporins, fourth-generation cephalosporins, and carbapenems), macrolides, fluoroquinolones, and other. We adjusted for baseline covariates (age, comorbidities, cognition scores, sepsis, and mechanical ventilation), previous-day covariates (delirium, doses of analgesics/sedatives, and antipsychotic use), and same-day covariates (illness severity). Our primary outcome of delirium was measured by using the Confusion Assessment Method for the ICU. A daily delirium logistic regression model was used with an ICU time-restricted sensitivity analysis including daily adjustment for sepsis and mechanical ventilation.ResultsOf 418 ICU patients, delirium occurred in 308 (74%) with a median of 3 days (interquartile range 2-6) among those affected and 318 (76%) were exposed to antimicrobials. When covariates and ICU type were adjusted for, only first- to third-generation cephalosporins were associated with delirium (logistic regression model odds ratio (OR) = 2.2, 95% confidence interval (CI) 1.28-3.79, P = 0.004; sensitivity analysis OR = 2.13, 95% CI 1.10-4.10, P = 0.024).ConclusionsFirst-, second-, and third-generation cephalosporins doubled the odds of delirium after baseline co-morbidities, ICU type, the course of critical care, and other competing antimicrobial and psychotropic medication risks were adjusted for. We did not find an association between delirium and cefepime, penicillins, carbapenems, fluoroquinolones, or macrolides.

Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyteÂ® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyteÂ® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyteÂ® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyteÂ® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyteÂ® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyteÂ® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator

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Antimicrobial Stewardship Using Biomarkers: Accumulating Evidence for the Critically Ill.

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Antimicrobial Stewardship Using Biomarkers: Accumulating Evidence for the Critically Ill.

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