The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
Next-generation sequencing diagnostics of bacteremia in septic patients
Open accessAbstract
BACKGROUND: Bloodstream infections remain one of the major challenges in intensive care units, leading to sepsis or even septic shock in many cases. Due to the lack of timely diagnostic approaches with sufficient sensitivity, mortality rates of sepsis are still unacceptably high. However a prompt diagnosis of the causative microorganism is critical to significantly improve outcome of bloodstream infections. Although various targeted molecular tests for blood samples are available, time-consuming blood culture-based approaches still represent the standard of care for the identification of bacteria. METHODS: Here we describe the establishment of a complete diagnostic workflow for the identification of infectious microorganisms from seven septic patients based on unbiased sequence analyses of free circulating DNA from plasma by next-generation sequencing. RESULTS: We found significant levels of DNA fragments derived from pathogenic bacteria in samples from septic patients. Quantitative evaluation of normalized read counts and introduction of a sepsis indicating quantifier (SIQ) score allowed for an unambiguous identification of Gram-positive as well as Gram-negative bacteria that exactly matched with blood cultures from corresponding patient samples. In addition, we also identified species from samples where blood cultures were negative. Reads of non-human origin also comprised fragments derived from antimicrobial resistance genes, showing that, in principle, prediction of specific types of resistance might be possible. CONCLUSIONS: The complete workflow from sample preparation to species identification report could be accomplished in roughly 30 h, thus making this approach a promising diagnostic platform for critically ill patients suffering from bloodstream infections.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Surviving Sepsis Campaign: International Guidelines for Management of Severe Sepsis and Septic Shock
Dellinger, R. P., Levy, M. M., Rhodes, A., Annane, D., Gerlach, H., Opal, S. M., Sevransky, J. E., Sprung, C. L., Douglas, I. S., Jaeschke, R., et al. (2013) · Critical Care Medicine · doi:10.1097/ccm.0b013e31827e83af · Cited by 9,694
The Surviving Sepsis Campaign Guidelines Committee including The Pediatric Subgroup*, Dellinger, R. P., Levy, M. M., Rhodes, A., Annane, D., Gerlach, H., Opal, S. M., Sevransky, J. E., Sprung, C. L., Douglas, I. S., et al. (2013) · Intensive Care Medicine · doi:10.1007/s00134-012-2769-8 · Cited by 7,290
Intravenous Fluids and Acute Kidney Injury
Ding, X., Cheng, Z., & Qian, Q. (2017) · Blood Purification · doi:10.1159/000452702 · Cited by 6,827
2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference
Levy, M. M., Fink, M. P., Marshall, J. C., Abraham, E., Angus, D., Cook, D., Cohen, J., Opal, S. M., Vincent, J.-L., & Ramsay, G. (2003) · Critical Care Medicine · doi:10.1097/01.ccm.0000050454.01978.3b · Cited by 5,995
Reagent and laboratory contamination can critically impact sequence-based microbiome analyses
Salter, S. J., Cox, M. J., Turek, E. M., Calus, S. T., Cookson, W. O., Moffatt, M. F., Turner, P., Parkhill, J., Loman, N. J., & Walker, A. W. (2014) · BMC Biology · doi:10.1186/s12915-014-0087-z · Cited by 3,463
Mayr, F. B., Yende, S., & Angus, D. C. (2014) · Virulence · doi:10.4161/viru.27372 · Cited by 1,208
Actionable Diagnosis of Neuroleptospirosis by Next-Generation Sequencing
Wilson, M. R., Naccache, S. N., Samayoa, E., Biagtan, M., Bashir, H., Yu, G., Salamat, S. M., Somasekar, S., Federman, S., Miller, S., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1401268 · Cited by 977
Calandra, T., & Cohen, J. (2005) · Critical Care Medicine · doi:10.1097/01.ccm.0000168253.91200.83 · Cited by 839
A New Arenavirus in a Cluster of Fatal Transplant-Associated Diseases
Palacios, G., Druce, J., Du, L., Tran, T., Birch, C., Briese, T., Conlan, S., Quan, P.-L., Hui, J., Marshall, J., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa073785 · Cited by 696
Epidemiology of sepsis in Germany: results from a national prospective multicenter study
Engel, C., Brunkhorst, F. M., Bone, H.-G., Brunkhorst, R., Gerlach, H., Grond, S., Gruendling, M., Huhle, G., Jaschinski, U., John, S., et al. (2007) · Intensive Care Medicine · doi:10.1007/s00134-006-0517-7 · Cited by 615
Cited by
Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection
Gu, W., Miller, S., & Chiu, C. Y. (2019) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-012418-012751 · Cited by 1,458
Towards a genomics-informed, real-time, global pathogen surveillance system
Gardy, J. L., & Loman, N. J. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2017.88 · Cited by 771
Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids
Gu, W., Deng, X., Lee, M., Sucu, Y. D., Arevalo, S., Stryke, D., Federman, S., Gopez, A., Reyes, K., Zorn, K., et al. (2021) · Nature Medicine · doi:10.1038/s41591-020-1105-z · Cited by 689
Bloodstream infections in critically ill patients: an expert statement
Timsit, J.-F., Ruppé, E., Barbier, F., Tabah, A., & Bassetti, M. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-05950-6 · Cited by 448
mNGS in clinical microbiology laboratories: on the road to maturity
Han, D., Li, Z., Li, R., Tan, P., Zhang, R., & Li, J. (2019) · Critical Reviews in Microbiology · doi:10.1080/1040841x.2019.1681933 · Cited by 361
Metadata
- Authors
- Grumaz, S., Stevens, P., Grumaz, C., Decker, S. O., Weigand, M. A., Hofer, S., Brenner, T., von Haeseler, A., & Sohn, K.
- Venue
- Genome Medicine
- Published
- 2016-07-01
- Volume
- 8
- Issue
- 1
- Pages
- 73-73
- ISSN
- 1756-994X (ISSN-L)
- OpenAlex
- W2463042271
- Cited by
- 351
- References
- 50
- FWCI
- 20.10
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Next-generation sequencing diagnostics of bacteremia in septic patients. https://app.cochat.ai/papers/10.1186/s13073-016-0326-8
- The paper
- Grumaz, S., Stevens, P., Grumaz, C., Decker, S. O., Weigand, M. A., Hofer, S., Brenner, T., von Haeseler, A., & Sohn, K. (2016). Next-generation sequencing diagnostics of bacteremia in septic patients. Genome Medicine. https://doi.org/10.1186/s13073-016-0326-8
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
