| Literature DB >> 30658585 |
Maya Azrad1, Yoram Keness2,3, Orna Nitzan4,5, Nina Pastukh1, Linda Tkhawkho1, Victoria Freidus1, Avi Peretz6,7.
Abstract
BACKGROUND: Rapid and accurate pathogen identification in blood cultures is very important for septic patients and has major consequences on morbidity and mortality rates. In recent years, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)-based technology has become useful for highly specific and sensitive identification of bacteria and yeasts from clinical samples including sterile body fluids. Additional in-house methods enabled direct identification from blood cultures following various preparation protocols.Entities:
Keywords: BACTEC™ FX system; Bacteria; Blood culture; MALDI-TOF MS; SepsiTyper kit
Mesh:
Year: 2019 PMID: 30658585 PMCID: PMC6339441 DOI: 10.1186/s12879-019-3709-9
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Fig. 1Flow diagram of the three methods that were used for the identification of positive blood cultures (routine method, in-house method, and SepsiTyper kit)
Results of MS analysis for microorganisms’ identification in positive blood cultures using SepsiTyper kit and in-house method
| Species (as identified by the routine method) | N | SepsiTyper kit | In-house method | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Sa < 1.7 | 1.7 ≤ S ≤ 1.999 | S ≥ 2.0 | No identification | S < 1.7 | 1.7 ≤ S ≤ 1.999 | S ≥ 2.0 | No identification | ||
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| 6 | 1 | 4 | 1 | 3 | 3 | |||
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| 2 | 2 | 2 | 2 | 2 | ||||
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| 2 | 2 | 1 | 1 | |||||
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| 5 | 1 | 3 | 1 | 3 | 2 | |||
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| 2 | 1 | 1 | 2 | |||||
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| 2 | 1 | 1 | 1 | 1 | ||||
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| 4 | 2 | 2 | 2 | 2 | ||||
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| 2 | 1 | 1 | 1 | 1 | ||||
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| 2 | 2 | 1 | 1 | |||||
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| 1 | 1 | 1 | ||||||
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| 4 | 2 | 2 | 3 | 1 | ||||
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| 4 | 2 | 2 | 1 | 3 | ||||
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| 11 | 2 | 7 | 2 | 6 | 4 | 1 | ||
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| 17 | 6 | 11 | 7 | 8 | 2 | |||
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| 2 | 1 | 1 | 1 | 1 | ||||
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| 3 | 2 | 1 | 3 | |||||
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| 2 | 2 | 2 | ||||||
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| 11 | 6 | 5 | 3 | 8 | ||||
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| 3 | 1 | 2 | 1 | 2 | ||||
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| 2 | 2 | 2 | ||||||
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| 3 | 2 | 1 | 2 | 1 | ||||
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| 4 | 1 | 3 | 3 | 1 | ||||
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| 4 | 4 | 4 | ||||||
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| 4 | 2 | 2 | 1 | 2 | 1 | |||
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| 6 | 2 | 4 | 3 | 3 | ||||
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| 3 | 3 | 3 | ||||||
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| 22 | 9 | 13 | 7 | 11 | 4 | |||
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| 4 | 3 | 1 | 3 | 1 | ||||
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| 16 | 1 | 9 | 6 | 9 | 6 | 1 | ||
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| 3 | 1 | 2 | 2 | 1 | ||||
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| 4 | 1 | 3 | 4 | |||||
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| 3 | 2 | 1 | 1 | 2 | ||||
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| 2 | 2 | 2 | ||||||
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| 2 | 1 | 1 | 1 | 1 | ||||
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| 4 | 1 | 3 | 3 | 1 | ||||
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| 2 | 2 | 2 | ||||||
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| 5 | 1 | 2 | 2 | 2 | 2 | 1 | ||
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| 3 | 1 | 2 | 2 | 1 | ||||
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| 3 | 3 | 2 | 1 | |||||
a S Score
Results of MS analysis for microorganisms’ identification divided to microorganisms’ groups
| Microorganism group | N | SepsiTyper kit | In-house method | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Sa < 1.7 | 1.7 ≤ S ≤ 1.999 | S ≥ 2.0 | No identification | S < 1.7 | 1.7 ≤ S ≤ 1.999 | S ≥ 2.0 | No identification | ||
| Gram negative bacteria | 79 | 5 | 33 | 40 | 1 | 34 | 37 | 4 | 4 |
| Gram positive bacteria | 88 | 9 | 50 | 29 | 0 | 43 | 33 | 5 | 7 |
| Yeasts | 7 | 2 | 4 | 0 | 1 | 3 | 0 | 0 | 4 |
| Anaerobic bacteria | 12 | 4 | 7 | 1 | 0 | 7 | 2 | 0 | 3 |
| Total N (%) | 186 | 20 (11) | 94 (50) | 70 (38) | 2 (1) | 87 (47) | 72 (39) | 9 (5) | 18 (10) |
Correct identification rates by MS analysis using SepsiTyper kit and an in-house method
| Microorganism group (N) | Correct identification rates (%) | ||
|---|---|---|---|
| SepsiTyper kit | In-house method | ||
| Gram negative bacteria (79) | 99 | 95 | < 0.0001 |
| Gram positive bacteria (88) | 100 | 92 | < 0.0001 |
| Yeasts (7) | 86 | 43 | 0.24 |
| Anaerobic bacteria (12) | 100 | 75 | < 0.005 |
| Total (186) | 99 | 90 | < 0.0001 |