• Bacterial infections
• Pediatric intensive care units
• Procalcitonin
• Sepsis

• Thermo Fisher Scientific

• Abscess
• CRP
• Cellulitis
• Computed tomography
• Lactate
• Necrotizing infection
• POCUS
• Pneumonia
• Procalcitonin
• SIRS
• SOFA
• Sepsis
• Septic shock
• Ultrasound
• Urinary tract infection
• qSOFA

• Humans
• Shock, Septic/diagnosis
• Shock, Septic/therapy
• Sepsis/diagnosis
• Sepsis/therapy
• Emergency Service, Hospital
• Practice Guidelines as Topic
• Emergency Medicine

• Antibiotic treatment
• Cancer
• Meta-analysis
• Procalcitonin

• Humans
• Neoplasms/drug therapy
• Neoplasms/mortality
• Neoplasms/blood
• Anti-Bacterial Agents/therapeutic use
• Anti-Bacterial Agents/administration & dosage
• Procalcitonin/blood
• Randomized Controlled Trials as Topic
• Sepsis/drug therapy
• Sepsis/mortality
• Sepsis/blood
• Respiratory Tract Infections/drug therapy
• Male
• Female
• Aged
• Middle Aged
• Bacterial Infections/drug therapy
• Bacterial Infections/blood

• Thermo Fisher Scientific
• bioMérieux

• Procalcitonin
• antibiotic cessation
• antibiotic initiation
• antibiotic stewardship
• infection
• sepsis

• meta-analysis
• neutrophil−lymphocyte ratio
• orthopedics
• post-operative infection
• surgery

• Humans
• Neutrophils
• Orthopedic Procedures/adverse effects
• Surgical Wound Infection/diagnosis
• Surgical Wound Infection/blood
• Surgical Wound Infection/epidemiology
• Lymphocytes
• Leukocyte Count
• Sensitivity and Specificity
• Predictive Value of Tests
• ROC Curve

• Sepsis
• antimicrobial
• core measure bundle
• fluid resuscitation
• infection
• screening

• Humans
• Sepsis/therapy
• Sepsis/diagnosis
• Practice Guidelines as Topic
• Patient Care Bundles/standards
• United States
• Shock, Septic/therapy
• Shock, Septic/diagnosis

• Antimicrobial stewardship
• Biomarkers
• Diagnosis
• Risk stratification
• Sepsis
• Transcriptional diagnostics

• Humans
• Sepsis/diagnosis
• Sepsis/blood
• Biomarkers/blood

• Humans
• Sepsis/diagnosis
• Sepsis/microbiology
• Early Diagnosis
• Biomarkers/blood
• Point-of-Care Testing
• Point-of-Care Systems

• Antimicrobial stewardship
• Biomarkers
• C-reactive protein
• Presepsin protein
• Procalcitonin

• Humans
• Anti-Bacterial Agents/therapeutic use
• Antimicrobial Stewardship
• Bacterial Infections/drug therapy
• Bacterial Infections/diagnosis
• Bacterial Infections/blood
• Bacterial Infections/microbiology
• Biomarkers/blood
• C-Reactive Protein/analysis
• COVID-19/blood
• COVID-19/diagnosis
• Predictive Value of Tests
• Procalcitonin/blood

• Humans
• Adult
• Procalcitonin
• Retrospective Studies
• Biomarkers
• Bacterial Infections/diagnosis
• Cardiac Surgical Procedures/adverse effects
• Sensitivity and Specificity

• Adult
• Humans
• Procalcitonin
• Retrospective Studies
• Reproducibility of Results
• Biomarkers
• Sepsis/diagnosis
• Bacteremia/diagnosis
• Hospitals
• Anti-Bacterial Agents

• Antibiotic therapy
• Intensive care
• Procalcitonin
• Sepsis

• Humans
• Procalcitonin
• Critical Illness/therapy
• Coinfection
• Biomarkers
• Sepsis
• Intensive Care Units
• Anti-Bacterial Agents/pharmacology
• Anti-Bacterial Agents/therapeutic use

• K 138816 Hungarian National Research, Development and Innovation Office
• Semmelweis University

• Flow cytometry
• HLA-DR
• Injury
• L-selectin
• Monocytes
• Sepsis

• Humans
• Shock, Septic
• HLA-DR Antigens/genetics
• HLA-DR Antigens/metabolism
• Pilot Projects
• Prospective Studies
• Flow Cytometry
• Critical Illness
• Sepsis/diagnosis
• Monocytes

• C-reactive protein
• critical illness
• pneumonia
• procalcitonin
• sepsis

• Humans
• C-Reactive Protein/analysis
• Procalcitonin
• Duration of Therapy
• Calcitonin
• Calcitonin Gene-Related Peptide
• Critical Illness
• Protein Precursors
• Biomarkers
• Critical Care
• Anti-Infective Agents/therapeutic use

• compliance
• intensive care
• pneumonia
• procalcitonin

• Lower respiratory tract infections
• antibiotic stewardship
• antimicrobial pressure
• critical care
• procalcitonin
• sepsis
• ventilator-associated pneumonia

• Humans
• Procalcitonin
• Calcitonin
• Calcitonin Gene-Related Peptide
• Protein Precursors
• Respiratory Tract Infections/diagnosis
• Respiratory Tract Infections/drug therapy
• Respiratory Tract Infections/chemically induced
• Anti-Bacterial Agents/therapeutic use
• Biomarkers

• Antimicrobial stewardship
• Carbapenem-sparing agents
• De-escalation
• Intensive care unit

• Antibiotic Stewardship
• Infectious Disease
• Respiratory Infections
• Sepsis

• emergency department
• in-hospital mortality
• management
• sepsis
• septic shock

• antibiotic dose adjustment
• antimicrobial prescription optimization
• appropriate antibiotic
• critically ill patients
• immunocompromised patients

• Antibiotic stewardship
• Elderly
• Geriatrics
• Infection
• Procalcitonin

• Antibiotic stewardship
• Biomarkers
• Diagnosis
• Intensive care unit
• Sepsis

• Humans
• Sepsis/diagnosis
• Biomarkers/metabolism
• Procalcitonin
• Prognosis
• C-Reactive Protein
• Anti-Bacterial Agents/therapeutic use

• MR/V006118/1 Medical Research Council

• CD3 + CD8 + CD69+T cell
• ICU discharge
• gram negative (G -) bacteria
• gram positive (G +) bacteria
• sepsis

• Antibiotic stewardship
• Biomarker
• C-reactive protein
• Procalcitonin

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.

Antimicrobial stewardship interventions (ASIs) aim to reduce the emergence of antimicrobial resistance. We sought to systematically evaluate how microbiological outcomes have been handled and analysed in randomized controlled trials (RCTs) evaluating ASIs.

We searched PubMed and Embase from 2011–21. Studies were selected if they were RCTs evaluating ASIs. A narrative synthesis approach was taken, identifying whether the study reported any microbiological data (bacterial genus/species; bacterial colony counts; prevalence of bacterial, microbiologically defined infections; and antibiotic susceptibility, measured pre-randomization or post-randomization in one arm only) or outcomes (post-randomization data compared between arms). Studies with or without microbiological data/outcomes were summarized in terms of study characteristics, methods of reporting and analysis of these outcomes.

We identified 117 studies, with 34 (29.1%) collecting microbiological data and 18 (15.4%) reporting microbiological outcomes. Most studies with microbiological outcomes were conducted in secondary care (12/18, 66.7%) and targeted adult populations (14/18, 77.8%), and the intervention involved biomarker-guided rapid diagnostic testing (7/18, 38.9%). The overall quality of reporting and analysing microbiological outcomes was low and inconsistent. The selected study population in analyses and methods of handling missing data were unclear.

This review demonstrates that the quality of handling and reporting microbiological outcomes in RCTs of ASIs was low. The lack of consistency and clarity made it difficult to compare the findings across studies, limiting policy- and clinical decision-making. Therefore, there is a clear need for the development of guidance for handling microbiological outcomes in RCTs and adopting appropriate methods to evaluate these data carefully.

The early identification of bacteremia is critical for ensuring appropriate treatment of nosocomial infections in intensive care unit (ICU) patients. The aim of this study was to use flow cytometric data of myeloid cells as a biomarker of bloodstream infection (BSI). An eight-color antibody panel was used to identify seven monocyte and two dendritic cell subsets. In the learning cohort, immunophenotyping was applied to (1) control subjects, (2) postoperative heart surgery patients, as a model of noninfectious inflammatory responses, and (3) blood culture-positive patients. Of the complex changes in the myeloid cell phenotype, a decrease in myeloid and plasmacytoid dendritic cell numbers, increase in CD14⁺CD16⁺ inflammatory monocyte numbers, and upregulation of neutrophils CD64 and CD123 expression were prominent in BSI patients. An extreme gradient boosting (XGBoost) algorithm called the “infection detection and ranging score” (iDAR), ranging from 0 to 100, was developed to identify infection-specific changes in 101 phenotypic variables related to neutrophils, monocytes and dendritic cells. The tenfold cross-validation achieved an area under the receiver operating characteristic (AUROC) of 0.988 (95% CI 0.985–1) for the detection of bacteremic patients. In an out-of-sample, in-house validation, iDAR achieved an AUROC of 0.85 (95% CI 0.71–0.98) in differentiating localized from bloodstream infection and 0.95 (95% CI 0.89–1) in discriminating infected from noninfected ICU patients. In conclusion, a machine learning approach was used to translate the changes in myeloid cell phenotype in response to infection into a score that could identify bacteremia with high specificity in ICU patients.

• Adults
• Evidence based medicine
• Guidelines
• Sepsis
• Septic shock

Older patients have a less pronounced immune response to infection, which may also influence infection biomarkers. There is currently insufficient data regarding clinical effects of procalcitonin (PCT) to guide antibiotic treatment in older patients.

We performed an individual patient data meta-analysis to investigate the association of age on effects of PCT-guided antibiotic stewardship regarding antibiotic use and outcome.

We had access to 9,421 individual infection patients from 28 randomized controlled trials comparing PCT-guided antibiotic therapy (intervention group) or standard care. We stratified patients according to age in four groups (<75 years [n = 7,079], 75–80 years [n = 1,034], 81–85 years [n = 803] and >85 years [n = 505]). The primary endpoint was the duration of antibiotic treatment and the secondary endpoints were 30-day mortality and length of stay.

Compared to control patients, mean duration of antibiotic therapy in PCT-guided patients was significantly reduced by 24, 22, 26 and 24% in the four age groups corresponding to adjusted differences in antibiotic days of −1.99 (95% confidence interval [CI] −2.36 to −1.62), −1.98 (95% CI −2.94 to −1.02), −2.20 (95% CI −3.15 to −1.25) and − 2.10 (95% CI −3.29 to −0.91) with no differences among age groups. There was no increase in the risk for mortality in any of the age groups. Effects were similar in subgroups by infection type, blood culture result and clinical setting (P interaction >0.05).

This large individual patient data meta-analysis confirms that, similar to younger patients, PCT-guided antibiotic treatment in older patients is associated with significantly reduced antibiotic exposures and no increase in mortality.

• age
• antibiotic stewardship
• older patients
• procalcitonin

• Biomarker
• Critical illness
• Pneumonia
• Procalcitonin
• Sepsis

• Adult
• Aged
• Aged, 80 and over
• Croatia/epidemiology
• Humans
• Intensive Care Units
• Middle Aged
• Procalcitonin
• Prognosis
• ROC Curve
• Sepsis

Reducing unnecessary antibiotic exposure is a key strategy in reducing the development and selection of antibiotic-resistant bacteria. Hospital antimicrobial stewardship (AMS) interventions are inherently complex, often requiring multiple healthcare professionals to change multiple behaviours at multiple timepoints along the care pathway. Inaction can arise when roles and responsibilities are unclear. A behavioural perspective can offer insights to maximize the chances of successful implementation.

To apply a behavioural framework [the Target Action Context Timing Actors (TACTA) framework] to existing evidence about hospital AMS interventions to specify which key behavioural aspects of interventions are detailed.

Randomized controlled trials (RCTs) and interrupted time series (ITS) studies with a focus on reducing unnecessary exposure to antibiotics were identified from the most recent Cochrane review of interventions to improve hospital AMS. The TACTA framework was applied to published intervention reports to assess the extent to which key details were reported about what behaviour should be performed, who is responsible for doing it and when, where, how often and with whom it should be performed.

The included studies (n = 45; 31 RCTs and 14 ITS studies with 49 outcome measures) reported what should be done, where and to whom. However, key details were missing about who should act (45%) and when (22%). Specification of who should act was missing in 79% of 15 interventions to reduce duration of treatment in continuing-care wards.

The lack of precise specification within AMS interventions limits the generalizability and reproducibility of evidence, hampering efforts to implement AMS interventions in practice.

• Antibacterial
• ICU
• PCT-based
• mortality
• sepsis

To assess the ability of procalcitonin (PCT) to distinguish between bacterial and nonbacterial causes of patients with severe acute exacerbation of COPD (AECOPD) admitted to the ICU, we conducted a retrospective analysis of two prospective studies including 375 patients with severe AECOPD with suspected lower respiratory tract infections. PCT levels were sequentially assessed at the time of inclusion, 6 h after and at day 1, using a sensitive immunoassay. The patients were classified according to the presence of a documented bacterial infection (including bacterial and viral coinfection) (BAC + group), or the absence of a documented bacterial infection (i.e., a documented viral infection alone or absence of a documented pathogen) (BAC- group). The accuracy of PCT levels in predicting bacterial infection (BAC + group) vs no bacterial infection (BAC- group) at different time points was evaluated by receiver operating characteristic (ROC) analysis.

Regarding the entire cohort (n = 375), at any time, the PCT levels significantly differed between groups (Kruskal–Wallis test, p < 0.001). A pairwise comparison showed that PCT levels were significantly higher in patients with bacterial infection (n = 94) than in patients without documented pathogens (n = 218) (p < 0.001). No significant difference was observed between patients with bacterial and viral infection (n = 63). For example, the median PCT-H₀ levels were 0.64 ng/ml [0.22–0.87] in the bacterial group vs 0.24 ng/ml [0.15–0.37] in the viral group and 0.16 ng/mL [0.11–0.22] in the group without documented pathogens. With a c-index of 0.64 (95% CI; 0.58–0.71) at H₀, 0.64 [95% CI 0.57–0.70] at H₆ and 0.63 (95% CI; 0.56–0.69) at H₂₄, PCT had a low accuracy for predicting bacterial infection (BAC + group).

Despite higher PCT levels in severe AECOPD caused by bacterial infection, PCT had a poor accuracy to distinguish between bacterial and nonbacterial infection. Procalcitonin might not be sufficient as a standalone marker for initiating antibiotic treatment in this setting.

• Antibiotic stewardship
• Chronic obstructive pulmonary disease
• Community-acquired pneumonia
• Procalcitonin
• Respiratory tract infection
• Viral infection

• Antimicrobial stewardship
• Biomarkers
• De-escalation
• Pharmacodynamics
• Pharmacokinetics

• Anti-Bacterial Agents/therapeutic use
• Antimicrobial Stewardship
• Biomarkers
• Critical Illness
• Humans
• Intensive Care Units

• ICU
• arylesterase activity
• dyslipideamia
• high density lipoprotein (HDL)
• paraoxonase (PON)
• paraoxonase (PON1)
• sepsis

• DOC 31 Austrian Science Fund FWF

• Antimicrobial resistance
• Antimicrobial stewardship
• Healthcare-associated infections
• Infection control
• Multidrug-resistant organisms
• Preoperative antibiotic prophylaxis
• Surgical site infections

• Anti-Bacterial Agents/therapeutic use
• Antimicrobial Stewardship
• Humans
• Infection Control/standards
• Surgical Wound Infection/prevention & control