Critical factors in the recovery of pathogenic microorganisms in blood

Detection value of third-generation sequencing to identify the pathogenic organisms in prosthetic joint infection

To compare the detection value of third-generation sequencing (TGS) with pathogenic microbial culture in prosthetic joint infection (PJI). Arthrocentesis was performed on 29 patients who underwent hip and knee revision surgeries. In the PJI group, TGS detected 85.71 % of positive cases, while pathogenic microbial culture detected only 42.85 %. TGS identified 17 different pathogenic microorganisms, including Staphylococcus epidermidis, Staphylococcus aureus, Streptococcus lactis, and Mycobacterium tuberculosis complex. In the loosening group, TGS was positive in one patient, while microbial culture was negative in all cases. TGS showed higher sensitivity (85.71 % vs. 42.85 %), comparable specificity (93.33 % vs. 100 %), and similar positive predictive value (92.31 % vs. 100 %) compared to culture.However, TGS had a higher negative predictive value (87.5 % vs. 65.22 %).Additionally, TGS provided faster results (mean time 23.8±3.6 h) compared to microbial culture (mean time 108.0±9.4 h).These findings suggest that TGS holds promise for detecting pathogenic microorganisms in PJI and has potential for clinical application.

A multi-pronged approach to improve blood culture diagnostics in different clinical departments: a single-centre experience

PURPOSE

Blood culture (BC) diagnostics are influenced by many factors. We performed a targeted interdisciplinary analysis to analyse effects of various measures on BC diagnostics performance.

METHODS

A diagnostic stewardship initiative was conducted at two intervention and two control wards in a German tertiary level hospital. The initiative comprised staff training on the correct indications and sampling for BC, implementation of information cards, labels to identify the collection site, regular BC bottle feedback including the number of bottles, filling volumes and identified pathogens; and the use of a specific sampling device (BD Vacutainer®). Before and after the interventions, two three-month measurement periods were performed, as well as a one-month follow-up period to assess the sustainability of the conducted measures.

RESULTS

In total, 9362 BC bottles from 787 patients were included in the analysis. The number of BCs obtained from peripheral venous puncture could be increased at both intervention wards (44.0 vs. 22.2%, 58.3 vs. 34.4%), while arterial sampling could be reduced (30.6 vs. 4.9%). A total of 134 staff members were fully trained. The intervention led to a considerable increase in BC knowledge (from 62.4 to 79.8% correct answers) with differences between the individual professional groups. Relevant reduced contamination rates could be detected at both intervention wards.

CONCLUSIONS

As knowledge on the correct BC sampling and strategies to reduce contamination varies considerably between clinical departments and healthcare professionals, a targeted training should be adapted to the specific needs of the individual professional groups. An additional filling device is not necessary.

Enzyme-Activated, Chemiluminescent Siderophore-Dioxetane Probes Enable the Selective and Highly Sensitive Detection of Bacterial Pathogens

The sensitive detection of bacterial infections is a prerequisite for their successful treatment. The use of a chemiluminescent readout was so far hampered by an insufficient probe enrichment at the pathogens. We coupled siderophore moieties, that harness the unique iron transport system of bacteria, with enzyme‐activatable dioxetanes and obtained seven trifunctional probes with high signal‐to‐background ratios (S/B=426‐859). Conjugates with efficient iron transport capability into bacteria were identified through a growth recovery assay. All ESKAPE pathogens were labelled brightly by desferrioxamine conjugates, while catechols were weaker due to self‐quenching. Bacteria could also be detected inside lung epithelial cells. The best probe 8 detected 9.1×10³ CFU mL⁻¹ of S. aureus and 5.0×10⁴ CFU mL⁻¹ of P. aeruginosa, while the analogous fluorescent probe 10 was 205–305fold less sensitive. This qualifies siderophore dioxetane probes for the selective and sensitive detection of bacteria.

Diagnosing hospital bacteraemia in the framework of predictive, preventive and personalised medicine using electronic health records and machine learning classifiers

Background

The bacteraemia prediction is relevant because sepsis is one of the most important causes of morbidity and mortality. Bacteraemia prognosis primarily depends on a rapid diagnosis. The bacteraemia prediction would shorten up to 6 days the diagnosis, and, in conjunction with individual patient variables, should be considered to start the early administration of personalised antibiotic treatment and medical services, the election of specific diagnostic techniques and the determination of additional treatments, such as surgery, that would prevent subsequent complications. Machine learning techniques could help physicians make these informed decisions by predicting bacteraemia using the data already available in electronic hospital records.

Objective

This study presents the application of machine learning techniques to these records to predict the blood culture's outcome, which would reduce the lag in starting a personalised antibiotic treatment and the medical costs associated with erroneous treatments due to conservative assumptions about blood culture outcomes.

Methods

Six supervised classifiers were created using three machine learning techniques, Support Vector Machine, Random Forest and K-Nearest Neighbours, on the electronic health records of hospital patients. The best approach to handle missing data was chosen and, for each machine learning technique, two classification models were created: the first uses the features known at the time of blood extraction, whereas the second uses four extra features revealed during the blood culture.

Results

The six classifiers were trained and tested using a dataset of 4357 patients with 117 features per patient. The models obtain predictions that, for the best case, are up to a state-of-the-art accuracy of 85.9%, a sensitivity of 87.4% and an AUC of 0.93.

Conclusions

Our results provide cutting-edge metrics of interest in predictive medical models with values that exceed the medical practice threshold and previous results in the literature using classical modelling techniques in specific types of bacteraemia. Additionally, the consistency of results is reasserted because the three classifiers' importance ranking shows similar features that coincide with those that physicians use in their manual heuristics. Therefore, the efficacy of these machine learning techniques confirms their viability to assist in the aims of predictive and personalised medicine once the disease presents bacteraemia-compatible symptoms and to assist in improving the healthcare economy.

Simulated Pediatric Blood Cultures to Assess the Inactivation of Clinically Relevant Antimicrobial Drug Concentrations in Resin-Containing Bottles

The bacteremia level as well as the administration of antibiotics before blood collection may significantly affect the recovery of bacterial pathogens from pediatric blood cultures in BacT/Alert Virtuo or Bactec FX BC systems, which remain the common techniques to diagnose bacteremia in pediatric patients. We simulated pediatric blood cultures with low or intermediate bacteremia level to evaluate BacT/Alert PF Plus and Bactec Peds Plus blood culture bottles for resin-based inactivation of 16 antibiotic-bacterium combinations. Overall, 105/192 (54.7%) of BacT/Alert PF Plus bottles and 69/192 (36.0%) of Bactec Peds Plus bottles allowed organisms to grow when exposed to antibiotics. In particular, both BacT/Alert PF Plus and Bactec Peds Plus bottles proved to be effective with piperacillin/tazobactam and Pseudomonas aeruginosa or with oxacillin and methicillin-susceptible Staphylococcus aureus (100% growth), whereas no effectiveness was apparent with ceftriaxone and Escherichia coli, Streptococcus agalactiae, or Streptococcus pneumoniae or with cefepime and E. coli (0% growth). In some relevant instances (e.g., with vancomycin and methicillin-resistant S. aureus or Streptococcus pneumoniae), BacT/Alert PF Plus bottles were superior to Bactec Peds Plus bottles. Together, these findings underscore the potentiality of resin-containing bottles to enhance diagnosis of bacteremia in pediatric patients on antimicrobial therapy. This is particularly true with one of the evaluated BC systems and with simulated intermediate bacteremia level only.