The Clinician and the Microbiology Laboratory

Enhancing antibiotic therapy through comprehensive pharmacokinetic/pharmacodynamic principles

Antibiotic therapy relies on understanding both pharmacokinetics (PK) and pharmacodynamics (PD), which respectively address drug absorption, distribution, and elimination, and the relationship between drug concentration and antimicrobial efficacy. This review synthesizes decades of research, drawing from in-vitro studies, in-vivo models, and clinical observations, to elucidate the temporal dynamics of antibiotic activity. We explore how these dynamics, including concentration-effect relationships and post antibiotic effects, inform the classification of antibiotics based on their PD profiles. Additionally, we discuss the pivotal role of PK/PD principles in determining optimal dosage regimens. By providing a comprehensive overview of PK/PD principles in antibiotic therapy, this review aims to enhance understanding and improve treatment outcomes in clinical practice.

Proof of concept study on early forecasting of antimicrobial resistance in hospitalized patients using machine learning and simple bacterial ecology data

Antibiotic resistance in bacterial pathogens is a major threat to global health, exacerbated by the misuse of antibiotics. In hospital practice, results of bacterial cultures and antibiograms can take several days. Meanwhile, prescribing an empirical antimicrobial treatment is challenging, as clinicians must balance the antibiotic spectrum against the expected probability of susceptibility. We present here a proof of concept study of a machine learning-based system that predicts the probability of antimicrobial susceptibility and explains the contribution of the different cofactors in hospitalized patients, at four different stages prior to the antibiogram (sampling, direct examination, positive culture, and species identification), using only historical bacterial ecology data that can be easily collected from any laboratory information system (LIS) without GDPR restrictions once the data have been anonymised. A comparative analysis of different state-of-the-art machine learning and probabilistic methods was performed using 44,026 instances over 7 years from the Hôpital Européen Marseille, France. Our results show that multilayer dense neural networks and Bayesian models are suitable for early prediction of antibiotic susceptibility, with AUROCs reaching 0.88 at the positive culture stage and 0.92 at the species identification stage, and even 0.82 and 0.92, respectively, for the least frequent situations. Perspectives and potential clinical applications of the system are discussed.

Clinicians' Intention to Submit Microbiological Pathogenic Test Before Antibiotics Use and Its Influencing Factors: New Evidence from the Perspective of Hospital Management

Purpose

Antimicrobial resistance (AR) is a global public health problem, improving clinicians’ intention to submit microbiological pathogenic test (submission intention) can effectively increase the value for rational use antibiotics to curb AR. However, there are few studies on the factors influencing improvement of the submission intention, especially from the perspective of hospital management. This study will fill the gap and provide evidence that can continuously support improvement of antibiotics prescribing rationally.

Patients and Methods

A cross-sectional survey of clinicians was conducted in all public hospitals in Hubei, China. Dependent variables were submission intention of non-restricted-use, restricted-use and special-use antibiotics which were measured submission, not sure submission, no submission. Independent variables were frequency of training and publicity on submission, and hospital with or without submission performance assessment, guideline, information decision system and laboratory items, including bacterial culture item, fungal culture item and so on. Clinicians’ demographics were applied as control variables. Multinomial logistic regression was performed to model independent variables influencing submission intention.

Results

For non-restricted-use antibiotics, guideline (OR = 0.263; 95% CI = [0.188, 0.369]) (OR = 0.526; 95% CI = [0.375, 0.738]) and bacterial culture item (OR = 0.141; 95% CI = [0.074, 0.268]) (OR = 0.520; 95% CI = [0.292, 0.927]) are key factors that positively affect clinicians’ intention on submission and not sure submission; For restricted-use and special-use antibiotics, training frequency and bacterial culture item (OR = 0.155; 95% CI = [0.076, 0.315]) (OR = 0.092; 95% CI = [0.036, 0.232]) (OR = 0.106; 95% CI = [0.046, 0.248]) (OR = 0.027; 95% CI = [0.006, 0.117]) are key factors that positively affect clinicians’ intention on submission and not sure submission.

Conclusion

This study found that bacterial culture item, guideline, and training frequency are key factors that affect clinicians’ intention on submission and not sure submission, but various factors exist different effects level on different types of antibiotics. Consequently, a focus should be placed on the construction and implementation of management factors, as well as reformation of antimicrobial stewardship in hospitals according to the types of antibiotics.

Contamination rates of different methods of urine culture collection in children: A retrospective cohort study

AIM

Urinary tract infection is a common cause of paediatric morbidity. However, there is no consensus on the default method for urine culture collection in children. This study aimed to examine the contamination rates of different urine collection methods.

METHODS

This was a retrospective cohort study in a paediatric emergency department. Data were collected from electronic health records on all children whose urine culture samples were obtained in the paediatric emergency department between March 2018 and March 2019. Different methods of urine collection included the midstream (MS) method, clean catch (CC), transurethral bladder catheterisation and suprapubic aspiration. Contamination rates and positive urine culture rates were calculated and compared for sex, age, and collection method.

RESULTS

Urine culture samples were collected from 1507 children. There were 284 (18.8%) cultures that were positive with significant growth and 52 (3.5%) that were defined as 'contaminated'. The contamination rates for the midstream method in toilet-trained children were 1.6% (10/609), 4.9% (17/348) for CC in pre-continent children, 4.9% (25/515) for transurethral bladder catheterisation and 0% (0/35) (P = 0.006) for suprapubic aspiration. There was no significant difference in contamination rates of urine cultures collected by CC and catheterisation in the compared groups. The rates of positive cultures in the subgroup of children with high suspicion for Urinary tract infection were also found to be similar.

CONCLUSIONS

Our study shows that CC is non-inferior to catheterisation for collecting urine cultures in young children.

The dormant blood microbiome in chronic, inflammatory diseases

Blood in healthy organisms is seen as a ‘sterile’ environment: it lacks proliferating microbes. Dormant or not-immediately-culturable forms are not absent, however, as intracellular dormancy is well established. We highlight here that a great many pathogens can survive in blood and inside erythrocytes. ‘Non-culturability’, reflected by discrepancies between plate counts and total counts, is commonplace in environmental microbiology. It is overcome by improved culturing methods, and we asked how common this would be in blood. A number of recent, sequence-based and ultramicroscopic studies have uncovered an authentic blood microbiome in a number of non-communicable diseases. The chief origin of these microbes is the gut microbiome (especially when it shifts composition to a pathogenic state, known as ‘dysbiosis’). Another source is microbes translocated from the oral cavity. ‘Dysbiosis’ is also used to describe translocation of cells into blood or other tissues. To avoid ambiguity, we here use the term ‘atopobiosis’ for microbes that appear in places other than their normal location. Atopobiosis may contribute to the dynamics of a variety of inflammatory diseases. Overall, it seems that many more chronic, non-communicable, inflammatory diseases may have a microbial component than are presently considered, and may be treatable using bactericidal antibiotics or vaccines.

Atopobiosis of microbes (the term describing microbes that appear in places other than where they should be), as well as the products of their metabolism, seems to correlate with, and may contribute to, the dynamics of a variety of inflammatory diseases.