Rapid Sepsis Diagnosis in Critically Ill Adults with Remoscope Label-Free Whole-Blood Imaging

Abstract

Sepsis is life-threatening, yet diagnosis remains a major global challenge because existing approaches lack speed and accuracy. Here we show that label-free imaging cytometry of 10 {micro}L whole-blood samples by Remoscope rapidly distinguishes patients with sepsis from those with non-infectious critical illness and healthy controls. In a prospective study of 29 critically ill adults, multi-physician adjudication identified sepsis (n=13), non-infectious critical illness (n=12), and indeterminate status (n=4); these patients were compared to healthy controls (n=22). A multiple instance learning (MIL) model pooled unbiased features from thousands of blood images per patient. Optimized for rule-out, the three-class model detected sepsis with 100% sensitivity and 85.3% specificity. Class activation heatmaps, unsupervised single cell embeddings, and morphometrics converged on abnormal leukocyte and erythrocyte morphology, including immature neutrophil-like cells. Label-free whole-blood imaging with MIL detects sepsis-associated hematologic signatures without stains or cold chain, establishing a foundation for rapid critical care diagnostics.

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Cite

BibTeX RIS

BibTeX

@misc{bratvold2026rapid,
  title = {{Rapid Sepsis Diagnosis in Critically Ill Adults with Remoscope Label-Free Whole-Blood Imaging}},
  author = {N. Bratvold and I. Jeyakumar and M. Khoo and G. Suematsu and O. Chao and T. Shwartzman and A. Willmore and J. Hutchinson and C. Calfee and M. Matthay and N. Spottiswoode and C. Langelier and P. Lebel},
  howpublished = {medRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.08.26364716},
  url = {https://www.medrxiv.org/content/10.64898/2026.10.08.26364716v1},
  note = {CC BY-NC-ND},
}

RIS

TY  - UNPB
TI  - Rapid Sepsis Diagnosis in Critically Ill Adults with Remoscope Label-Free Whole-Blood Imaging
AU  - N. Bratvold
AU  - I. Jeyakumar
AU  - M. Khoo
AU  - G. Suematsu
AU  - O. Chao
AU  - T. Shwartzman
AU  - A. Willmore
AU  - J. Hutchinson
AU  - C. Calfee
AU  - M. Matthay
AU  - N. Spottiswoode
AU  - C. Langelier
AU  - P. Lebel
PY  - 2026
DA  - 2026/10/08
PB  - medRxiv
DO  - 10.64898/2026.10.08.26364716
UR  - https://www.medrxiv.org/content/10.64898/2026.10.08.26364716v1
AB  - Sepsis is life-threatening, yet diagnosis remains a major global challenge because existing approaches lack speed and accuracy. Here we show that label-free imaging cytometry of 10 {micro}L whole-blood samples by Remoscope rapidly distinguishes patients with sepsis from those with non-infectious critical illness and healthy controls. In a prospective study of 29 critically ill adults, multi-physician adjudication identified sepsis (n=13), non-infectious critical illness (n=12), and indeterminate status (n=4); these patients were compared to healthy controls (n=22). A multiple instance learning (MIL) model pooled unbiased features from thousands of blood images per patient. Optimized for rule-out, the three-class model detected sepsis with 100% sensitivity and 85.3% specificity. Class activation heatmaps, unsupervised single cell embeddings, and morphometrics converged on abnormal leukocyte and erythrocyte morphology, including immature neutrophil-like cells. Label-free whole-blood imaging with MIL detects sepsis-associated hematologic signatures without stains or cold chain, establishing a foundation for rapid critical care diagnostics.
ER  -

Abstract

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