Time to and differential time to blood culture positivity for assessing catheter-related yeast fungaemia: A longitudinal, 7-year study in a single university hospital

Understanding the diagnosis of catheter-related bloodstream infection: real-time monitoring of biofilm growth dynamics using time-lapse optical microscopy

Background

The differential time to positivity (DTTP) technique is recommended for the conservative diagnosis of catheter-related bloodstream infection (C-RBSI). The technique is based on a 120-minute difference between microbial growth in blood drawn through the catheter and blood drawn through a peripheral vein. However, this cut-off has failed to confirm C-RBSI caused by Candida spp. and Staphylococcus aureus.

Objective

We hypothesized that the biofilm of both microorganisms disperses faster than that of other microorganisms and that microbial load is rapidly equalized between catheter and peripheral blood. Therefore, our aim was to compare the biofilm dynamics of various microorganisms.

Methods

Biofilm of ATCC strains of methicillin-resistant Staphylococcus epidermidis, methicillin-susceptible S. aureus, Enterococcus faecalis, Escherichia coli and Candida albicans was grown on silicon disks and analyzed using time-lapse optical microscopy. The time-lapse images of biofilms were processed using ImageJ2 software. Cell dispersal time and biofilm thickness were calculated.

Results

The mean (standard deviation) dispersal time in C. albicans and S. aureus biofilms was at least nearly 3 hours lower than in biofilm of S. epidermidis, and at least 15 minutes than in E. faecalis and E. coli biofilms.

Conclusion

Our findings could explain why early dissemination of cells in C. albicans and S. aureus prevents us from confirming or ruling out the catheter as the source of the bloodstream infection using the cut-off of 120 minutes in the DTTP technique. In addition, DTTP may not be sufficiently reliable for E. coli since their dispersion time is less than the cut-off of 120 minutes.

Utility of Differential Time to Positivity in Diagnosing Central Line-Associated Bloodstream Infections: A Systematic Review and Meta-Analysis

BACKGROUND

Differential time to positivity (DTP), defined as pathogen growth at least 2 hours earlier from catheter versus paired peripheral blood cultures, is sometimes used to diagnose central line-associated bloodstream infections (CLABSIs). Previous studies assessing DTP, however, have been small, provided conflicting results, and did not assess heterogeneity across important subgroups.

METHODS

We systematically reviewed the diagnostic characteristics of DTP for CLABSI using MEDLINE, Embase, WoS, CINAHL, LILACS, AMED, and the Cochrane database. Studies were included if they reported sensitivities, specificities, predictive values, likelihood ratios, or 2 × 2 tables of DTP for diagnosing CLABSI. Extracted data were analyzed by using forest plots, bivariate model meta-analysis, and QUADAS-2 quality assessment.

RESULTS

We identified 274 records, of which 23 met the criteria for meta-analysis. Among 2526 suspected CLABSIs, DTP demonstrated a summary sensitivity of 81.3% (95% confidence interval [CI]: 72.8%-87.7%), specificity of 91.8% (95% CI: 84.5%-95.8%), positive likelihood ratio of 9.89 (95% CI: 5.14-19.00), and negative likelihood ratio of 0.20 (95% CI: .14-.30). Covariate analysis based on catheter duration, study design, and patient immune status demonstrated no significant differences. However, DTP performed worse for Staphylococcus aureus (low sensitivity but high specificity) and Candida (high sensitivity but low specificity) compared to other organisms.

CONCLUSIONS

DTP performs well in ruling CLABSIs in or out. Obtaining paired catheter and peripheral blood cultures for DTP when the infectious source is unclear may prevent unnecessary line removal and diagnostic tests. However, this must be balanced against higher contamination rates from catheter cultures.

The comparative accuracy of pooled vs. individual blood culture sampling methods for diagnosis of catheter-related bloodstream infection

Background

Catheter-related bloodstream infection (CRBSI) is associated with increased morbidity, mortality, and cost of treatment in critically ill patients. A differential time to positivity (DTP) of 120 min or more between blood cultures obtained through the catheter vs. peripheral vein is an indicator of CRBSI with high sensitivity and specificity. However, it is no clear whether pooled sampling would be as efficient as individual sampling in order to reduce costs, contamination, or anemia.

Methods

This was a prospective diagnostic study conducted at the medical ICU and semi-ICU of Khon Kaen University’s Srinagarind Hospital in Thailand from May 2020 to November 2021. Fifty patients with triple-lumen central venous catheters (CVCs) who were clinically suspected of CRBSI were enrolled. 15 mL of blood was drawn through each catheter lumen, 10 mL of which was inoculated into three blood culture bottles, and the remaining 5 mL was pooled into a single bottle. Sensitivity, specificity, accuracy, and time to positivity of the pooled blood cultures were calculated using individual blood cultures as a reference.

Results

Of the 50 patients enrolled, 14 (28%) were diagnosed with CRBSI, 57.9% of whom were infected with gram-negative bacteria as the causative pathogen (57.9%). Extensively drug-resistant (XDR) Klebsiella pneumoniae was the most common organism. Sensitivity and specificity of the pooled blood sampling method were 69.23% (95% CI [0.44–0.94]) and 97.3% (95% CI [0.92–1.02]), respectively. The area under the ROC curve (AUC) was 0.83 (95% CI [0.68–0.99]). A paired T-Test to compare time to positivity of the pooled blood bottle and the first positive culture from the individual bottles indicated statistical significance (14.9 and 12.4 h, respectively). The mean difference was 2.5 [0.9–4.1] h, with a 95% CI and a p-value of 0.006.

Conclusion

Pooled blood sampling results in a lower sensitivity and longer time to positivity for CRBSI diagnosis in patients with triple-lumen CVCs than individual lumen sampling.

Trial registration Retrospectively registered at Thai Clinical Trials Registry. The study was reviewed and approved on 08/03/2022. TCTR identification number is TCTR20220308002

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07605-x.

Rapid Detection of Bacterial and Fungal Pathogens Using the T2MR versus Blood Culture in Patients with Severe COVID-19

A high rate of bacterial and fungal superinfections was reported in critically ill patients with COVID-19. However, diagnosis can be challenging. The aim of this study is to evaluate the sensitivity and the clinical utility of the point-of-care method T2 magnetic resonance (T2MR) with the gold standard: the blood culture. T2MR can potentially detect five different Candida species and six common bacteria (so-called "ESKAPE" pathogens including Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Acinet`obacter baumanii, Pseudomonas aeruginosa, and Enterococcus faecium). If superinfection was suspected in patients with COVID-19 admitted to the intensive care unit, blood culture and two panels of T2MR were performed. Eighty-five diagnostic bundles were performed in 60 patients in total. T2MR detected an ESKAPE pathogen in 9 out of 85 (10.6%) samples, compared to BC in 3 out of 85 (3.5%). A Candida species was detected in 7 of 85 (8.2%) samples of T2MR compared to 1 out of 85(1.2%) in blood culture. The mean time to positive test result in samples with concordant positive results was 4.5 h with T2MR and 52.5 h with blood culture. The additional use of T2MR enables a highly sensitive and rapid detection of ESKAPE and Candida pathogens. IMPORTANCE Coronavirus disease 2019 (COVID-19) has led to a high number of deaths since the beginning of the pandemic worldwide. One of the reasons is the high number of bacterial and fungal superinfections in patients suffering from critical disease. However, diagnosis is often challenging. In this study we could show that the additional use of the culture-independent method T2MR did not only show a much higher detection rate of bacterial and fungal pathogens but also a significantly shorter time until detection and therapy change compared to the gold standard: the blood culture. The implementation of T2MRin the care of patients with severe course of COVID-19 might lead to an earlier sufficient antimicrobial therapy and as a result lower mortality and less use of broad-spectrum unnecessary therapy reducing the risk of resistance development.

Using Machine Learning Algorithms to Predict Candidaemia in ICU Patients With New-Onset Systemic Inflammatory Response Syndrome

Background: Distinguishing ICU patients with candidaemia can help with the precise prescription of antifungal drugs to create personalized guidelines. Previous prediction models of candidaemia have primarily used traditional logistic models and had some limitations. In this study, we developed a machine learning algorithm trained to predict candidaemia in patients with new-onset systemic inflammatory response syndrome (SIRS).

Methods: This retrospective, observational study used clinical information collected between January 2013 and December 2017 from three hospitals. The ICU patient data were used to train 4 machine learning algorithms–XGBoost, Support Vector Machine (SVM), Random Forest (RF), ExtraTrees (ET)–and a logistic regression (LR) model to predict patients with candidaemia.

Results: Of the 8,002 cases of new-onset SIRS (in 7,932 patients) included in the analysis, 137 new-onset SIRS cases (in 137 patients) were blood culture positive for candidaemia. Risk factors, such as fungal colonization, diabetes, acute kidney injury, the total number of parenteral nutrition days and renal replacement therapy, were important predictors of candidaemia. The XGBoost machine learning model outperformed the other models in distinguishing patients with candidaemia [XGBoost vs. SVM vs. RF vs. ET vs. LR; area under the curve (AUC): 0.92 vs. 0.86 vs. 0.91 vs. 0.90 vs. 0.52, respectively]. The XGBoost model had a sensitivity of 84%, specificity of 89% and negative predictive value of 99.6% at the best cut-off value.

Conclusions: Machine learning algorithms can potentially predict candidaemia in the ICU and have better efficiency than previous models. These prediction models can be used to guide antifungal treatment for ICU patients when SIRS occurs.

Central venous catheter-related infections in hematology and oncology: 2020 updated guidelines on diagnosis, management, and prevention by the Infectious Diseases Working Party (AGIHO) of the German Society of Hematology and Medical Oncology (DGHO)

Cancer patients frequently require central venous catheters for therapy and parenteral nutrition and are at high risk of central venous catheter-related infections (CRIs). Moreover, CRIs prolong hospitalization, cause an excess in resource utilization and treatment cost, often delay anti-cancer treatment, and are associated with a significant increase in mortality in cancer patients. We therefore summoned a panel of experts by the Infectious Diseases Working Party (AGIHO) of the German Society of Hematology and Medical Oncology (DGHO) and updated our previous guideline on CRIs in cancer patients. After conducting systematic literature searches on PubMed, Medline, and Cochrane databases, video- and meeting-based consensus discussions were held. In the presented guideline, we summarize recommendations on definition, diagnosis, management, and prevention of CRIs in cancer patients including the grading of strength of recommendations and the respective levels of evidence. This guideline supports clinicians and researchers alike in the evidence-based decision-making in the management of CRIs in cancer patients.