The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
How to use biomarkers of infection or sepsis at the bedside: guide to clinicians
Open accessAbstract
Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. In this context, biomarkers could be considered as indicators of either infection or dysregulated host response or response to treatment and/or aid clinicians to prognosticate patient risk. More than 250 biomarkers have been identified and evaluated over the last few decades, but no biomarker accurately differentiates between sepsis and sepsis-like syndrome. Published data support the use of biomarkers for pathogen identification, clinical diagnosis, and optimization of antibiotic treatment. In this narrative review, we highlight how clinicians could improve the use of pathogen-specific and of the most used host-response biomarkers, procalcitonin and C-reactive protein, to improve the clinical care of patients with sepsis. Biomarker kinetics are more useful than single values in predicting sepsis, when making the diagnosis and assessing the response to antibiotic therapy. Finally, integrated biomarker-guided algorithms may hold promise to improve both the diagnosis and prognosis of sepsis. Herein, we provide current data on the clinical utility of pathogen-specific and host-response biomarkers, offer guidance on how to optimize their use, and propose the needs for future research.
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Cites
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Self-citationSurviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021
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Self-citationKalil, A. C., Metersky, M. L., Klompas, M., Muscedere, J., Sweeney, D. A., Palmer, L. B., Napolitano, L. M., O'Grady, N. P., Bartlett, J. G., Carratalà, J., et al. (2016) · Clinical Infectious Diseases · doi:10.1093/cid/ciw353 · Cited by 3,892
Self-citationSimon, L., Gauvin, F., Amre, D. K., Saint-Louis, P., & Lacroix, J. (2004) · Clinical Infectious Diseases · doi:10.1086/421997 · Cited by 1,787
Torres, A., Niederman, M. S., Chastre, J., Ewig, S., Fernandez-Vandellos, P., Hanberger, H., Kollef, M., Li Bassi, G., Luna, C. M., Martin-Loeches, I., et al. (2017) · European Respiratory Journal · doi:10.1183/13993003.00582-2017 · Cited by 1,387
Self-citationProcalcitonin as a diagnostic marker for sepsis: A systematic review and meta-analysis.
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Prevalence and outcomes of infection among patients in intensive care units in 2017.
Vincent, J.-L., Sakr, Y., Singer, M., Martin-Loeches, I., Machado, F. R., Marshall, J. C., Finfer, S., Pelosi, P., Brazzi, L., Aditianingsih, D., et al. (2020) · JAMA · doi:10.1001/jama.2020.2717 · Cited by 1,011
Self-citationde Jong, E., van Oers, J. A., Beishuizen, A., Vos, P., Vermeijden, W. J., Haas, L. E., Loef, B. G., Dormans, T., van Melsen, G. C., Kluiters, Y. C., et al. (2016) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(16)00053-0 · Cited by 836
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Metadata
- Authors
- Póvoa, P., Coelho, L., Dal-Pizzol, F., Ferrer, R., Huttner, A., Conway Morris, A., Nobre, V., Ramirez, P., Rouze, A., Salluh, J., Singer, M., Sweeney, D. A., Torres, A., Waterer, G., & Kalil, A. C.
- Venue
- Intensive Care Medicine
- Published
- 2023-01-02
- Volume
- 49
- Issue
- 2
- Pages
- 142-153
- ISSN
- 0342-4642 (ISSN-L)
- 1432-1238
- OpenAlex
- W4313424514
- Cited by
- 292
- References
- 75
- FWCI
- 48.84
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: How to use biomarkers of infection or sepsis at the bedside: guide to clinicians. https://app.cochat.ai/papers/10.1007/s00134-022-06956-y
- The paper
- Póvoa, P., Coelho, L., Dal-Pizzol, F., Ferrer, R., Huttner, A., Conway Morris, A., Nobre, V., Ramirez, P., Rouze, A., Salluh, J., Singer, M., Sweeney, D. A., Torres, A., Waterer, G., & Kalil, A. C. (2023). How to use biomarkers of infection or sepsis at the bedside: guide to clinicians. Intensive Care Medicine. https://doi.org/10.1007/s00134-022-06956-y
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.
