Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Diagnosis of sepsis from a drop of blood by measurement of spontaneous neutrophil motility in a microfluidic assay

Abstract

Current methods for the diagnosis of sepsis have insufficient precision, causing regular misdiagnoses. Microbiological tests can help to diagnose sepsis, but are usually too slow to have an impact on timely clinical decision-making. Neutrophils have a high sensitivity to infections, yet measurements of neutrophil surface markers, genomic changes and phenotype alterations have had only a marginal effect on sepsis diagnosis. Here, we report a microfluidic assay that measures, from one droplet of diluted blood, the spontaneous motility of neutrophils in the presence of plasma. We measured the performance of the assay in two independent cohorts of critically ill patients suspected of sepsis. Using data from a first cohort, we developed a machine-learning-based scoring system (sepsis score) that segregated patients with sepsis from those without sepsis. We then validated the sepsis score in a double-blind, prospective case–control study. For the 42 patients across the two cohorts, the assay identified sepsis patients with 97% sensitivity and 98% specificity. The neutrophil assay could potentially be used to accurately diagnose and monitor sepsis in larger populations of at-risk patients.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: A microfluidic device to assay spontaneous neutrophil motility from a droplet of diluted blood.
Fig. 2: Neutrophil spontaneous migration patterns that are specific to sepsis.
Fig. 3: Whole blood quality controls.
Fig. 4: Comparison of neutrophil behaviour in diluted whole-blood and isolated neutrophil assays.
Fig. 5: Whole-blood assays provide higher accuracy by retaining plasma factors.
Fig. 6: Segregation of clinical conditions using the sepsis score in the derivation and validation cohorts.

Similar content being viewed by others

References

  1. Vincent, J. L. et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Med. 22, 707–710 (1996).

    Article  CAS  PubMed  Google Scholar 

  2. Singer, M. et al. The third international consensus definitions for sepsis and septic shock (sepsis-3)J. Am. Med. Assoc. 315, 801–810 (2016).

    Article  CAS  Google Scholar 

  3. Sharma, S. & Kumar, A. Antimicrobial management of sepsis and septic shock. Clin. Chest Med. 29, 677–687 (2008).

    Article  PubMed  Google Scholar 

  4. Kumar, A. et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit. Care Med. 34, 1589–1596 (2006).

    Article  PubMed  Google Scholar 

  5. Pierrakos, C. & Vincent, J.-L. Sepsis biomarkers: a review. Crit. Care 14, R15 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Liu, Y. et al. Biomarkers for diagnosis of sepsis in patients with systemic inflammatory response syndrome: a systematic review and meta-analysis. SpringerPlus 5, 2091 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Hsu, K. H., Chan, M. C., Wang, J. M., Lin, L. Y. & Wu, C. L. Comparison of Fcγ receptor expression on neutrophils with procalcitonin for the diagnosis of sepsis in critically ill patients. Respirology 16, 152–160 (2011).

    Article  PubMed  Google Scholar 

  8. Hassan, U. et al. A point-of-care microfluidic biochip for quantification of CD64 expression from whole blood for sepsis stratification. Nat. Commun. 8, 15949 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Stubljar, D. & Skvarc, M. Effective strategies for diagnosis of systemic inflammatory response syndrome (SIRS) due to bacterial infection in surgical patients. Infect. Disord. Drug Targets 15, 53–56 (2015).

    Article  CAS  PubMed  Google Scholar 

  10. Bone, R. C. et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. Chest 101, 1644–1655 (1992).

    Article  CAS  PubMed  Google Scholar 

  11. Brown, K. A. et al. Neutrophils in development of multiple organ failure in sepsis. Lancet 368, 157–169 (2006).

    Article  CAS  PubMed  Google Scholar 

  12. Fazal, N. et al. CINC blockade prevents neutrophil Ca2+ signaling upregulation and gut bacterial translocation in thermal injury. Biochim. Biophys. Acta 1535, 50–59 (2000).

    Article  CAS  PubMed  Google Scholar 

  13. Weiss, S. J. Tissue destruction by neutrophils. N. Engl. J. Med. 320, 365–376 (1989).

    Article  CAS  PubMed  Google Scholar 

  14. Butler, K. L. et al. Burn injury reduces neutrophil directional migration speed in microfluidic devices. PloS ONE 5, e11921 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Jones, C. N. et al. Spontaneous neutrophil migration patterns during sepsis after major burns. PloS ONE 9, e114509 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Solomkin, J. S. Neutrophil disorders in burn injury: complement, cytokines, and organ injury. J. Trauma 30, S80–S85 (1990).

    Article  CAS  PubMed  Google Scholar 

  17. Kurihara, T. et al. Resolvin D2 restores neutrophil directionality and improves survival after burns. FASEB J. 27, 2270–2281 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Hoang, A. N. et al Measuring neutrophil speed and directionality during chemotaxis, directly from a droplet of whole blood. Technology (Singap. World Sci.) 1, 49 (2013).

    Google Scholar 

  19. Simpson, S. Q. Diagnosing sepsis: a step forward, and possibly a step back. Ann. Transl. Med. 5, 55 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Pepe, M. C. in The Statistical Evaluation of Medical Tests for Classification and Prediction 218–228 (Oxford Univ. Press, Oxford, 2004).

  21. Ambravaneswaran, V., Wong, I. Y., Aranyosi, A. J., Toner, M. & Irimia, D. Directional decisions during neutrophil chemotaxis inside bifurcating channels. Integr. Biol. 2, 639–647 (2010).

    Article  CAS  Google Scholar 

  22. Akhundov, A. G. On the problem of toxic granulation of the neutrophils in acute suppurative diseases and sepsis. Klin. Med. (Mosk.) 39, 84–89 (1961).

    CAS  Google Scholar 

  23. Povoa, P. C-reactive protein: a valuable marker of sepsis. Intensive Care Med. 28, 235–243 (2002).

    Article  PubMed  Google Scholar 

  24. Weng, X., Cloutier, G., Beaulieu, R. & Roederer, G. O. Influence of acute-phase proteins on erythrocyte aggregation. Am. J. Physiol. 271, H2346–H2352 (1996).

    CAS  PubMed  Google Scholar 

  25. Gawaz, M., Fateh-Moghadam, S., Pilz, G., Gurland, H. J. & Werdan, K. Platelet activation and interaction with leucocytes in patients with sepsis or multiple organ failure. Eur. J. Clin. Investig. 25, 843–851 (1995).

    Article  CAS  Google Scholar 

  26. Mavrommatis, A. C. et al. Coagulation system and platelets are fully activated in uncomplicated sepsis. Crit. Care Med. 28, 451–457 (2000).

    Article  CAS  PubMed  Google Scholar 

  27. Ogura, H. et al. Activated platelets enhance microparticle formation and platelet–leukocyte interaction in severe trauma and sepsis. J. Trauma 50, 801–809 (2001).

    Article  CAS  PubMed  Google Scholar 

  28. Engelmann, B. & Massberg, S. Thrombosis as an intravascular effector of innate immunity. Nat. Rev. Immunol. 13, 34–45 (2013).

    Article  CAS  PubMed  Google Scholar 

  29. Frydman, G. H. et al. Technical advance: changes in neutrophil migration patterns upon contact with platelets in a microfluidic assay. J. Leukoc. Biol. 101, 797–806 (2017).

  30. Jones, C. N. et al. Microfluidic platform for measuring neutrophil chemotaxis from unprocessed whole blood. J. Vis. Exp. 88, e51215 (2014).

  31. Furey, T. S. et al. Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 16, 906–914 (2000).

    Article  CAS  PubMed  Google Scholar 

  32. Suykens, J. A. K. & Vandewalle, J. Least squares support vector machine classifiers. Neural Process. Lett. 9, 293–300 (1999).

    Article  Google Scholar 

  33. Vapnik, V. N. Statistical Learning Theory (ed Haykin, S.) (Wiley, New York, 1998).

  34. Vapnik, V. in Nonlinear Modeling (eds Suykens, J. A. K. & Vandewalle, J.) 55–85 (Springer, Boston, 1998)..

  35. Fan, J., Guo, S. & Hao, N. Variance estimation using refitted cross-validation in ultrahigh dimensional regression. J. R. Stat. Soc. Ser. B, Stat. Methodol. 74, 37–65 (2012).

    Article  Google Scholar 

  36. Varma, S. & Simon, R. Bias in error estimation when using cross-validation for model selection. BMC Bioinformatics 7, 91 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Van Der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).

    Google Scholar 

Download references

Acknowledgements

We thank C. Holland and K. Brait for assistance in recruiting patients; M. Toner, H. S. Warren and M. Filbin for thoughtful discussions and advice; and D. Hayden for biostatistics assistance.This project was supported by funding from the National Institutes of Health, National Institute of General Medical Sciences (grant GM092804) and National Institute of Allergy and Infectious Diseases (grant AI113937), and Shriners Hospitals for Children. Biostatistics work was conducted in part with assistance from the Harvard Catalyst program, supported by a grant from the National Center for Advancing Translational Sciences (grant UL1 TR001102). Microfluidic devices were manufactured at the BioMEMS Resource Center at Massachusetts General Hospital, supported by a grant from the National Institute of Biomedical Imaging and Bioengineering (grant EB002503). F.E. was supported by a fellowship from Shriners Hospitals for Children.

Author information

Authors and Affiliations

Authors

Contributions

F.E. designed the study, designed and fabricated the microfluidic device, performed experiments, analysed the data and wrote the manuscript. J.J. performed experiments and cell tracking, analysed the data and applied machine-learning approaches to derive the sepsis score. J.J. and A.L.M. performed blood-spiking experiments. M.M.M., Y.M.L. and K.L.B. coordinated collection of patient samples for the first, derivation cohort and provided advice on the study design and manuscript. V.S. and J.L. coordinated collection of samples for the validation cohort and provided advice on the study design and wrote the manuscript. D.I. conceived, designed and supervised the study and wrote the manuscript.

Corresponding author

Correspondence to Daniel Irimia.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary figures, tables and video caption.

Life Sciences Reporting Summary

Supplementary Video 1

Spontaneous motility of neutrophils in the microfluidic device.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ellett, F., Jorgensen, J., Marand, A.L. et al. Diagnosis of sepsis from a drop of blood by measurement of spontaneous neutrophil motility in a microfluidic assay. Nat Biomed Eng 2, 207–214 (2018). https://doi.org/10.1038/s41551-018-0208-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41551-018-0208-z

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing