Frontiers in Medical Technology (Apr 2024)

OxyHbMeter—a novel bedside medical device for monitoring cell-free hemoglobin in the cerebrospinal fluid—proof of principle

  • Nikolaos Tachatos,
  • Jan Folkard Willms,
  • Michael Sebastian Gerlt,
  • Kiran Kuruvithadam,
  • Michael Hugelshofer,
  • Kevin Akeret,
  • Jeremy Deuel,
  • Emanuela Keller,
  • Marianne Schmid Daners

DOI
https://doi.org/10.3389/fmedt.2024.1274058
Journal volume & issue
Vol. 6

Abstract

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Delayed cerebral ischemia (DCI) occurs in up to one third of patients suffering from aneurysmal subarachnoid hemorrhage (aSAH). Untreated, it leads to secondary cerebral infarctions and is frequently associated with death or severe disability. After aneurysm rupture, erythrocytes in the subarachnoid space lyse and liberate free hemoglobin (Hb), a key driver for the development of DCI. Hemoglobin in the cerebrospinal fluid (CSF-Hb) can be analyzed through a two-step procedure of centrifugation to exclude intact erythrocytes and subsequent spectrophotometric quantification. This analysis can only be done in specialized laboratories but not at the bedside in the intensive care unit. This limits the number of tests done, increases the variability of the results and restricts accuracy. Bedside measurements of CSF-Hb as a biomarker with a point of care diagnostic test system would allow for a continuous monitoring for the risk of DCI in the individual patient. In this study, a microfluidic chip was explored that allows to continuously separate blood particles from CSF or plasma based on acoustophoresis. An in vitro test bench was developed to test in-line measurements with the developed microfluidic chip and a spectrometer. The proof of principle for a continuous particle separation device has been established with diluted blood and CSF samples from animals and aSAH patients, respectively. Processing 1 mL of blood in our microfluidic device was achieved within around 70 min demonstrating only minor deviations from the gold standard centrifugation (7% average error of patient samples), while saving several hours of processing time and additionally the reduction of deviations in the results due to manual labor.

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