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Rapid identification of pathogens in positive blood culture of patients with sepsis: review and meta-analysis of the performance of the sepsityper kit.

ABSTRACT: Sepsis is one of the leading causes of deaths, and rapid identification (ID) of blood stream infection is mandatory to perform adequate antibiotic therapy. The advent of MALDI-TOF Mass Spectrometry for the rapid ID of pathogens was a major breakthrough in microbiology. Recently, this method was combined with extraction methods for pathogens directly from positive blood cultures. This review summarizes the results obtained so far with the commercial Sepsityper sample preparation kit, which is now approved for in vitro diagnostic use. Summarizing data from 21 reports, the Sepsityper kit allowed a reliable ID on the species level of 80% of 3320 positive blood culture bottles. Gram negative bacteria resulted consistently in higher ID rates (90%) compared to Gram positive bacteria (76%) or yeast (66%). No relevant misidentifications on the genus level were reported at a log(score)cut-off of 1.6. The Sepsityper kit is a simple and reproducible method which extends the MALDI-TOF technology to positive blood culture specimens and shortens the time to result by several hours or even days. In combination with antibiotic stewardship programs, this rapid ID allows a much faster optimization of antibiotic therapy in patients with sepsis compared to conventional workflows.

SUBMITTER: Morgenthaler NG

PROVIDER: S-EPMC4426779 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Rapid identification of pathogens in positive blood culture of patients with sepsis: review and meta-analysis of the performance of the sepsityper kit.

Morgenthaler Nils G NG Kostrzewa Markus M

International journal of microbiology 20150427

Sepsis is one of the leading causes of deaths, and rapid identification (ID) of blood stream infection is mandatory to perform adequate antibiotic therapy. The advent of MALDI-TOF Mass Spectrometry for the rapid ID of pathogens was a major breakthrough in microbiology. Recently, this method was combined with extraction methods for pathogens directly from positive blood cultures. This review summarizes the results obtained so far with the commercial Sepsityper sample preparation kit, which is now ...[more]

PMID: 26000017

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Project description:Rapid identification from positive blood cultures is standard of care (SOC) in many clinical microbiology laboratories. The GenMark Dx ePlex Blood Culture Identification Gram-Positive (BCID-GP) Panel is a multiplex nucleic acid amplification assay based on competitive DNA hybridization and electrochemical detection using eSensor technology. This multicenter study compared the investigational-use-only (IUO) BCID-GP Panel to other methods of identification of 20 Gram-positive bacteria, four antimicrobial resistance genes, and both Pan Candida and Pan Gram-Negative targets that are unique to the BCID-GP Panel. Ten microbiology laboratories throughout the United States collected residual, deidentified positive blood culture samples for analysis. Five laboratories tested both clinical and contrived samples with the BCID-GP Panel. Comparator identification methods included each laboratory's SOC, which included matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and automated identification systems as well as targeted PCR/analytically validated real-time PCR (qPCR) with bidirectional sequencing. A total of 2,342 evaluable samples (1,777 clinical and 565 contrived) were tested with the BCID-GP Panel. The overall sample accuracy for on-panel organisms was 89% before resolution of discordant results. For pathogenic Gram-positive targets (Bacillus cereus group, Enterococcus spp., Enterococcus faecalis, Enterococcus faecium, Staphylococcus spp., Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus lugdunensis, Listeria spp., Listeria monocytogenes, Streptococcus spp., Streptococcus agalactiae, Streptococcus anginosus group, Streptococcus pneumoniae, and Streptococcus pyogenes), positive percent agreement (PPA) and negative percent agreement (NPA) ranged from 93.1% to 100% and 98.8% to 100%, respectively. For contamination rule-out targets (Bacillus subtilis group, Corynebacterium, Cutibacterium acnes, Lactobacillus, and Micrococcus), PPA and NPA ranged from 84.5% to 100% and 99.9% to 100%, respectively. Positive percent agreement and NPA for the Pan Candida and Pan Gram-Negative targets were 92.4% and 95.7% for the former and 99.9% and 99.6% for the latter. The PPAs for resistance markers were as follows: mecA, 97.2%; mecC, 100%; vanA, 96.8%; and vanB, 100%. Negative percent agreement ranged from 96.6% to 100%. In conclusion, the ePlex BCID-GP Panel compares favorably to SOC and targeted molecular methods for the identification of 20 Gram-positive pathogens and four antimicrobial resistance genes in positive blood culture bottles. This panel detects a broad range of pathogens and mixed infections with yeast and Gram-negative organisms from the same positive blood culture bottle.

Project description:BACKGROUND:The primary objective of this study was to compare the characteristics of culture-positive and culture-negative status in septic patients. We also determined whether culture status is associated with mortality and whether unique variables are associated with mortality in culture-positive and culture-negative patients separately. METHODS:Utilizing patient records from intensive care units, emergency department, and general care wards in a large academic medical center, we identified adult patients with suspected infection and ≥2 systemic inflammatory response syndrome criteria between January 1, 2007, and May 31, 2014. We compared the characteristics between culture-positive and culture-negative patients and used binary logistic regression to identify variables independently associated with culture status and mortality. We also did sensitivity analyses using patients with Sequential Organ Failure Assessment and quick Sequential Organ Failure Assessment criteria for sepsis. RESULTS:The study population included 9288 culture-negative patients (89%) and 1105 culture-positive patients (11%). Culture-negative patients received more antibiotics during the 48 hours preceding diagnosis but otherwise demonstrated similar characteristics as culture-positive patients. After adjusting for illness severity, a positive culture was not independently associated with mortality (odds ratio = 1.01 [95% CI, 0.81-1.26]; P = .945). The models predicting mortality separately in culture-negative and culture-positive patients demonstrated very good and excellent discrimination (C-statistic ± SD, 0.87 ± 0.01 and 0.92 ± 0.01), respectively. In the sensitivity analyses using patients with sepsis by Sequential Organ Failure Assessment and quick Sequential Organ Failure Assessment criteria, after adjustments for illness severity, positive cultures were still not associated with mortality (odds ratio = 1.13 [95% CI, 0.86-1.43]; P = .303; and odds ratio = 1.05 [95% CI, 0.83-1.33]; P = .665), respectively. In all models, physiological derangements were associated with mortality. CONCLUSIONS:While culture status is important for tailoring antibiotics, culture-negative and culture-positive patients with sepsis demonstrate similar characteristics and, after adjusting for severity of illness, similar mortality. The most important factor associated with negative cultures is receipt of antibiotics during the preceding 48 hours. The risk of death in patients suspected of having an infection is most associated with severity of illness. This is aligned with the Sepsis-3 definition using Sequential Organ Failure Assessment score to better identify those suspected of infection at highest risk of a poor outcome.

Dataset Information

Rapid identification of pathogens in positive blood culture of patients with sepsis: review and meta-analysis of the performance of the sepsityper kit.

Publications

Rapid identification of pathogens in positive blood culture of patients with sepsis: review and meta-analysis of the performance of the sepsityper kit.

Similar Datasets

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