Non-culture based diagnostics for intravascular catheter related bloodstream infections

Early warning of bloodstream infection in elderly patients with circulating microparticles

Background

The difficulty of early diagnosis of bloodstream infection in the elderly patients leads to high mortality. Therefore, it is essential to determine some new methods of early warning of bloodstream infection in the elderly patients for timely adjustment of treatment and improvement of prognosis.

Methods

Patients aged over 65 years with suspected bloodstream infections were included and divided into bloodstream infection (BSI) and non-bloodstream infection (non-BSI) groups based on blood culture results. The morphology of microparticles (MPs) was observed by using transmission electron microscopy, and the number of MPs was dynamically monitored by flow cytometry.

Results

A total of 140 patients were included in the study: 54 in the BSI group and 86 in the non-BSI group. Total MPs (T-MPs) ≥ 6000 events/µL (OR, 7.693; 95% CI 2.944–20.103, P < 0.0001), neutrophil-derived MPs (NMPs) ≥ 500 events/µL (OR, 12.049; 95% CI 3.574–40.623, P < 0.0001), and monocyte counts ≤ 0.4 × 10⁹/L (OR, 3.637; 95% CI 1.415–9.348, P = 0.007) within 6 h of fever were independently associated with bloodstream infection in the elderly patients. We also developed an early warning model for bloodstream infection in the elderly patients with an area under the curve of 0.884 (95% CI 0.826–0.942, P < 0.0001), sensitivity of 86.8%, specificity of 76.5%, positive predictive value of 70.8%, and negative predictive value of 89.8%.

Conclusion

The early warning model of bloodstream infection based on circulating T-MPs, NMPs, and monocyte counts within 6 h of fever in the elderly patients was helpful in early detection of bloodstream infection and therefore promptly adjustment of treatment plan.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00901-w.

NGS plus bacterial culture: A more accurate method for diagnosing forensic-related nosocomial infections

Traditional autopsy and microscopic examination of pathological sections are the "gold standard" for the cause of death diagnosis. However, in some special cases, such as the deaths caused by bacterial infections, pathological sections are not always sufficient to provide convincing evidences for determining the causes of death. In recent years, with the development of Next Generation Sequencing (NGS), clinical medicine has already introduced it into the diagnosis of difficult diseases, which is rare in forensic pathological diagnoses. Here, we applied an NGS-based method combined with bacterial culture to examine a special case in which the deceased was suspected of having suffered from nosocomial infections. Results of the NGS and bacterial culture showed that Enterococcus and Acinetobacter baumannii, which are the most common bacteria causing nosocomial infections, were abundant in blood and hydropericardium of the deceased. Combining medical records and the results of the dissections, we proved that the death was actually caused by MODS which was the adverse consequence of nosocomial infections. In this case, the combination of NGS and bacterial culture was used to identify the pathogen which had caused the death. The results of NGS not only shorten the period of diagnosis, but also greatly increase the credibility of traditional anatomy and results of bacterial culture, which is expected to be further applied for forensic practices in the near future.

Rapid Detection of Aspergillus fumigatus Using Multiple Cross Displacement Amplification Combined With Nanoparticles-Based Lateral Flow

Aspergillus fumigatus is an opportunistic, ubiquitous, saprophytic mold which can cause infection in the lungs, nose, eyes, brain, and bones in humans, especially in immunocompromised patients. However, it is difficult to diagnose A. fumigatus infection quickly. Here, we introduce a new detection method, namely multiple cross displacement amplification (MCDA) combined with nanoparticle-based lateral flow biosensor (LFB) (MCDA-LFB), which was proved to be fast, reliable, and simple for detecting A. fumigatus. We designed a set of 10 primers targeting the gene annexin ANXC4 of A. fumigatus. The best MCDA condition is 66 °C for 35 min. The minimum concentration that can be detected by this method was 10 fg. In the case of 100 sputum samples, 20 (20%) and 15 (15%) samples were positive by MCDA-LFB and PCR method, respectively. MCDA-LFB and traditional culture method showed the same results. Compared with the culture method, the diagnostic accuracy of MCDA-LFB can reach 100%. It showed that the MCDA-LFB method has better detection ability than the PCR method. We found that the whole process could be controlled within 60 min including the preparation of DNA (20 min), MCDA reaction (35 min) and results reporting (2 min). These results show that this assay is suitable for the rapid, sensitive and specific detection of A. fumigatus in clinical samples.

The clinical value of IL-3, IL-4, IL-12p70, IL17A, IFN-γ, MIP-1β, NLR, P-selectin, and TNF-α in differentiating bloodstream infections caused by gram-negative, gram-positive bacteria and fungi in hospitalized patients: An Observational Study

Early differential diagnosis of bloodstream infections (BSIs) caused by different sources and species of bacteria in hospitalized patients is crucial for the timely targeted interventions including appropriate use of antibiotics. The aim of this study was to identify 9 biomarkers for the early differentiation of gram-negative-bloodstream infection (GN-BSI), gram-positive (GP)-BSI, and fungal-BSI.A prospective study was conducted for a total of 390 inpatients who underwent blood culture in the Chinese PLA General Hospital from September 2015 to March 2018. Patients with positive culture of a single pathogen were divided into GN-BSI, GP-BSI, and Fungal-BSI groups, and a culture-negative disease control group was also established. The serum levels of macrophage inflammatory protein 1β (MIP-1β), tumor necrosis factor α (TNF-α), interleukin (IL)-3, interferon (IFN)-γ, IL-17A, IL-4, IL-12p70, and P-selectin were detected and the NLR was calculated from routine blood test. Receiver-operating characteristic analysis was used to determine the efficacy of various indicators in the differential diagnosis of BSIs. Prediction and validation experiments on clinical patient samples (263 cases) were also performed.The level of IL-3 in the GP-BSI group was significantly higher than those in the other 3 groups. The level of IFN-γ in the fungal-BSI group was significantly higher than those in the other 3 groups. NLR, MIP-1β, TNF-α, IL-17A, and IL3 exhibited some efficacy when distinguishing between GN-BSI and GP-BSI and NLR had the largest area under curve (AUC) (0.728), followed by MIP-1β with an AUC of 0.679. IFN-γ and IL-3 exhibited some value in differential diagnosis between GN-BSI and Fungal-BSI. IL-3, MIP-1β, TNF-α, IFN-γ, NLR, IL-17A, and IL-4 exhibited some value in distinguishing fungal-BSI and GP-BSI, with IL-3 had the largest AUC (0.722), followed by MIP-1β with an AUC of 0.703.NLR and MIP-1β may be valuable in differentiating GN-BSI from GP-BSI in hospitalized patients. IFN-γ and IL-3 may be helpful in differential diagnosis GN-BSI and fungal-BSI. IL-3 and MIP-1β exhibited some diagnostic efficacy in distinguishing fungal-BSI and GP-BSI. Additionally, IL-3 with high serum level may be a marker for GP-BSI and IFN-γ with high serum level may be a valuable marker for the prediction of Fungal-BSI. The utility of these biomarkers to predict BSIs owing to different pathogens in hospitalized patients needs to be assessed in further studies.