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Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies
Published on: November 19, 2020
CEREBRAL OXIMETRY AS A PREDICTOR OF THE OUTCOME OF THE DISEASE IN PATIENTS WITH SECONDARY BRAIN LESIONS
Zh Sarkulova1, A Tokshilykova1, M Sarkulov1
1West Kazakhstan Medical University named after Marat Ospanov, Kazakhstan.
Cerebral oximetry, specifically rSO2<45%, is a significant predictor of mortality in brain injury patients. This finding aids in forecasting outcomes for acute cerebral pathology.
Area of Science:
- Neuroscience
- Critical Care Medicine
- Biomedical Engineering
Background:
- Brain injuries, including vascular and traumatic types, pose significant mortality risks.
- Accurate prognostic indicators are crucial for managing patients in intensive care.
- Cerebral oximetry offers a non-invasive method to assess brain oxygenation.
Purpose of the Study:
- To investigate the prognostic value of cerebral oximetry indicators in predicting mortality.
- To determine the role of cerebral oxygenation in vascular and traumatic brain injuries.
- To establish cut-off values for cerebral oximetry as risk factors for unfavorable outcomes.
Main Methods:
- A prospective cohort study of 129 patients with acute cerebral pathology.
- Monitoring of cerebral gas exchange, oxygenation (rSO2), arteriovenous difference, and neuron-specific markers (S100ß, NSE).
- Analysis of acid-base status and arterial blood gas composition at multiple time points.
Main Results:
- A reduced regional cerebral oxygen saturation (rSO2) below 45% was identified as a significant risk factor for mortality.
- Direct correlations were found between rSO2<45% and elevated S100ß, pneumonia, and specific diagnoses.
- A predictive model demonstrated strong performance (AuROC 0.846) for patient outcomes.
Conclusions:
- Cerebral oximetry, particularly rSO2 levels, serves as a valuable prognostic tool in critical care settings.
- The findings support the use of cerebral oximetry in predicting mortality in patients with vascular and traumatic brain injuries.
- The developed model can assist clinicians in forecasting outcomes for patients with acute cerebral conditions.
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